diff --git a/src/backend/base/langflow/base/models/model.py b/src/backend/base/langflow/base/models/model.py index d0a25fb35..ad24f7c25 100644 --- a/src/backend/base/langflow/base/models/model.py +++ b/src/backend/base/langflow/base/models/model.py @@ -30,9 +30,9 @@ class LCModelComponent(Component): name="system_message", display_name="System Message", info="System message to pass to the model.", - advanced=True, + advanced=False, ), - BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True), + BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=False), ] outputs = [ diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json new file mode 100644 index 000000000..f6a91504f --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json @@ -0,0 +1,2185 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-jhEkE", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-FlJ4C", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-jhEkE{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-jhEkEœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-FlJ4C{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-FlJ4Cœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "OpenAIModel-jhEkE", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-jhEkEœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-FlJ4C", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-FlJ4Cœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-Lmlx2", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_message", + "id": "OpenAIModel-cn7cK", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-Lmlx2{œdataTypeœ:œPromptœ,œidœ:œPrompt-Lmlx2œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-cn7cK{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-cn7cKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-Lmlx2", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-Lmlx2œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-cn7cK", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-cn7cKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-MbPd9", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-cn7cK", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-MbPd9{œdataTypeœ:œChatInputœ,œidœ:œChatInput-MbPd9œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-cn7cK{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-cn7cKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-MbPd9", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-MbPd9œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-cn7cK", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-cn7cKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-TbFnC", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_message", + "id": "OpenAIModel-xWhtK", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-TbFnC{œdataTypeœ:œPromptœ,œidœ:œPrompt-TbFnCœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-xWhtK{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-xWhtKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-TbFnC", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-TbFnCœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-xWhtK", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-xWhtKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-cn7cK", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-xWhtK", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-cn7cK{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-cn7cKœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-xWhtK{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-xWhtKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-cn7cK", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-cn7cKœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-xWhtK", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-xWhtKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-3CcjN", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_message", + "id": "OpenAIModel-jhEkE", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-3CcjN{œdataTypeœ:œPromptœ,œidœ:œPrompt-3CcjNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-jhEkE{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-jhEkEœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-3CcjN", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-3CcjNœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-jhEkE", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-jhEkEœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-xWhtK", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-jhEkE", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-xWhtK{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-xWhtKœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-jhEkE{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-jhEkEœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-xWhtK", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-xWhtKœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-jhEkE", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-jhEkEœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-TbFnC", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "You are a seasoned business analyst with a strong background in tech product development and market research. Your analytical skills are unparalleled, allowing you to dissect product concepts and evaluate their market viability with precision. You have a keen eye for identifying potential challenges and opportunities that others might overlook. Your insights have been crucial in shaping successful product strategies for numerous tech companies.\n\nYour task is to:\n\n1. Evaluate the concept in terms of market potential and technical feasibility\n2. Identify two potential challenges for developing this product\n3. Suggest one improvement or expansion to the concept\n\n\nPlease structure your response as follows:\n\nConcept Evaluation:\n[concept_evaluation]\n\nPotential Challenges:\n1. [challenge_1]\n2. [challenge_2]\n...\n\nImprovement Suggestion:\n[improvement_suggestion]\n\nProvide an objective and well-founded analysis, considering market and technological factors in your evaluation.\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-TbFnC", + "position": { + "x": 1921.9168573384, + "y": 1162.4082184281983 + }, + "positionAbsolute": { + "x": 1921.9168573384, + "y": 1162.4082184281983 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "ChatInput-MbPd9", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "category": "inputs", + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "key": "ChatInput", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "The growing demand for personalized, AI-driven mental health support tools that can provide real-time interventions and track long-term emotional well-being." + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-MbPd9", + "position": { + "x": 1178.0239685549568, + "y": 879.9087836229152 + }, + "positionAbsolute": { + "x": 1178.0239685549568, + "y": 879.9087836229152 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-FlJ4C", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-FlJ4C", + "position": { + "x": 3363.868906129255, + "y": 1189.5351768654318 + }, + "positionAbsolute": { + "x": 3363.868906129255, + "y": 1189.5351768654318 + }, + "selected": true, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-3CcjN", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "You are an accomplished product manager with a track record of bringing innovative tech products from concept to market. Your strategic thinking and ability to balance technical feasibility with market demands have resulted in several successful product launches. You excel at distilling complex ideas into clear, actionable plans and have a talent for identifying the most critical features that will drive product adoption and success.\n\nBased on the analysis of the innovative product, create a simplified development plan that includes:\n\n1. Product overview (1-2 sentences)\n2. Three main features to be developed\n3. A basic market launch strategy\n\n\nPlease structure your plan as follows:\n\nProduct Overview:\n[product_overview]\n\nMain Features:\n1. [feature_1]\n2. [feature_2]\n3. [feature_3]\n...\n\nLaunch Strategy:\n[launch_strategy]\n\nYour plan should be concise, realistic, and aligned with the information provided in the previous steps.\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-3CcjN", + "position": { + "x": 2647.8305106628454, + "y": 1161.2328062686402 + }, + "positionAbsolute": { + "x": 2647.8305106628454, + "y": 1161.2328062686402 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-cn7cK", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-cn7cK", + "position": { + "x": 1561.5122766985614, + "y": 805.4323582784689 + }, + "positionAbsolute": { + "x": 1561.5122766985614, + "y": 805.4323582784689 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-jhEkE", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-jhEkE", + "position": { + "x": 3013.354174710099, + "y": 800.0470124871745 + }, + "positionAbsolute": { + "x": 3013.354174710099, + "y": 800.0470124871745 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-Lmlx2", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "You are a visionary product innovator at a cutting-edge tech startup. Your expertise lies in identifying emerging market trends and translating them into groundbreaking product concepts. Your creative thinking and deep understanding of technology allow you to envision products that not only meet current needs but also anticipate future demands. Your ideas often challenge conventional thinking and push the boundaries of what's possible with current technology.\n\nPlease create a product concept, providing:\n\n1. Product name\n2. Brief description (2-3 sentences)\n3. Main innovative feature\n4. Target audience\n\nStructure your response like this:\n\nProduct Name: [product_name]\n\nDescription: [product_description]\n\nMain Innovation: [main_innovation]\n\nTarget Audience: [target_audience]\n\nBe creative and bold in your idea, but keep it realistic and aligned with the provided market trend." + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-Lmlx2", + "position": { + "x": 1178.7099500302636, + "y": 1167.8586867404465 + }, + "positionAbsolute": { + "x": 1178.7099500302636, + "y": 1167.8586867404465 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-tSZsX", + "node": { + "description": "### Input Examples\n1.\n \"The growing demand for personalized, AI-driven mental health support tools that can provide real-time interventions and track long-term emotional well-being.\"\n\n\n2. \n \"The increasing need for secure and user-friendly decentralized finance (DeFi) platforms that make cryptocurrency investments accessible to non-tech-savvy users.\"\n \n\n3. \n \"The rising popularity of immersive, augmented reality (AR) experiences for remote collaboration and virtual team-building in distributed workforces.\"\n\n\n4. \n \"The expanding market for smart, IoT-enabled urban farming solutions that allow city dwellers to grow their own food efficiently in small spaces.\"\n\n\n5. \n \"The emerging demand for AI-powered personal styling and shopping assistants that consider sustainability, body positivity, and individual style preferences.\"\n\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "emerald" + } + }, + "type": "note" + }, + "dragging": false, + "height": 430, + "id": "note-tSZsX", + "position": { + "x": 528.0392006831054, + "y": 973.781986567496 + }, + "positionAbsolute": { + "x": 528.0392006831054, + "y": 973.781986567496 + }, + "resizing": false, + "selected": false, + "style": { + "height": 430, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "id": "note-FCbTW", + "node": { + "description": "### Prompt Chaining\n\nThis flow demonstrates fundamental prompt chaining principles:\n\n1. **Chain Structure**\n • User input → First Prompt → LLM\n • First output → Second Prompt → LLM\n • Second output → Final Prompt → LLM\n • Final output\n\n2. **Key Technique Elements**\n • Each prompt is specifically designed to process previous output\n • Output formatting ensures clean handoff between stages\n • Context flows naturally through the chain\n • Each LLM call builds upon previous results\n\n3. **Technical Implementation**\n • Multiple prompt templates working in sequence\n • Strategic input/output connections\n • Consistent message handling between stages\n • Progressive refinement through the chain\n\nThis pattern can be adapted for any use case by modifying the prompt templates while keeping the same chaining structure.", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 451, + "id": "note-FCbTW", + "position": { + "x": 892.4280059782889, + "y": 406.2411111617474 + }, + "positionAbsolute": { + "x": 892.4280059782889, + "y": 406.2411111617474 + }, + "resizing": false, + "selected": false, + "style": { + "height": 451, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-xWhtK", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-xWhtK", + "position": { + "x": 2294.5699142425065, + "y": 796.3787911368381 + }, + "positionAbsolute": { + "x": 2294.5699142425065, + "y": 796.3787911368381 + }, + "selected": false, + "type": "genericNode", + "width": 320 + } + ], + "viewport": { + "x": -648.2477908002534, + "y": -146.07166399594246, + "zoom": 0.5557618545546786 + } + }, + "description": "Connect multiple prompts in sequence where each output becomes the next stage's input, enabling step-by-step text processing.", + "endpoint_name": null, + "icon": "Link", + "id": "b5b0c252-95ae-4b07-8211-67c8b12ea60e", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "Prompt Chaining", + "tags": [ + "chatbots" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json similarity index 87% rename from src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json rename to src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json index f147a545e..b6ecc8382 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json @@ -2,64 +2,65 @@ "data": { "edges": [ { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-AwB1F", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "user_input", - "id": "Prompt-bHLxK", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-AwB1F{œdataTypeœ:œChatInputœ,œidœ:œChatInput-AwB1Fœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-bHLxK{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-bHLxKœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-AwB1F", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-AwB1Fœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-bHLxK", - "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-bHLxKœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-bHLxK", + "id": "Prompt-euzzD", "name": "prompt", "output_types": [ "Message" ] }, "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-tnzXU", + "fieldName": "system_message", + "id": "OpenAIModel-mMCO4", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-bHLxK{œdataTypeœ:œPromptœ,œidœ:œPrompt-bHLxKœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-tnzXU{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-tnzXUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-bHLxK", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-bHLxKœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-tnzXU", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-tnzXUœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-euzzD{œdataTypeœ:œPromptœ,œidœ:œPrompt-euzzDœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-mMCO4{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-mMCO4œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-euzzD", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-euzzDœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-mMCO4", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-mMCO4œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-M2ktx", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-mMCO4", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-M2ktx{œdataTypeœ:œChatInputœ,œidœ:œChatInput-M2ktxœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-mMCO4{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-mMCO4œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-M2ktx", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-M2ktxœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-mMCO4", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-mMCO4œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-tnzXU", + "id": "OpenAIModel-mMCO4", "name": "text_output", "output_types": [ "Message" @@ -67,18 +68,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-wbcyd", + "id": "ChatOutput-1s4P8", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-tnzXU{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-tnzXUœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-wbcyd{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-wbcydœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-tnzXU", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-tnzXUœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-wbcyd", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-wbcydœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-mMCO4{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-mMCO4œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-1s4P8{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1s4P8œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-mMCO4", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-mMCO4œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-1s4P8", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-1s4P8œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -86,7 +87,7 @@ "data": { "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", - "id": "ChatInput-AwB1F", + "id": "ChatInput-M2ktx", "node": { "base_classes": [ "Message" @@ -109,6 +110,7 @@ "frozen": false, "icon": "MessagesSquare", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -247,7 +249,7 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "" + "value": "Hello" }, "sender": { "advanced": true, @@ -349,25 +351,25 @@ "type": "ChatInput" }, "dragging": false, - "height": 297, - "id": "ChatInput-AwB1F", + "height": 234, + "id": "ChatInput-M2ktx", "position": { - "x": 54.0197580905824, - "y": 777.1114693911709 + "x": 689.5720422421635, + "y": 765.155834131403 }, "positionAbsolute": { - "x": 54.0197580905824, - "y": 777.1114693911709 + "x": 689.5720422421635, + "y": 765.155834131403 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "Create a prompt template with dynamic variables. If using an OutputParser, you must include {format_instructions} as an additional variable.", + "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-bHLxK", + "id": "Prompt-euzzD", "node": { "base_classes": [ "Message" @@ -375,9 +377,7 @@ "beta": false, "conditional_paths": [], "custom_fields": { - "template": [ - "user_input" - ] + "template": [] }, "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", @@ -426,6 +426,7 @@ "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { + "_input_type": "PromptInput", "advanced": false, "display_name": "Template", "dynamic": false, @@ -437,317 +438,68 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "type": "prompt", - "value": "Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: " - }, - "user_input": { - "advanced": false, - "display_name": "user_input", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_input", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" + "value": "Answer the user as if you were a pirate." } - } + }, + "tool_mode": false }, "type": "Prompt" }, "dragging": false, - "height": 411, - "id": "Prompt-bHLxK", + "height": 260, + "id": "Prompt-euzzD", "position": { - "x": 577.3727711743836, - "y": 853.9773971889889 + "x": 690.2015147036818, + "y": 1018.5443911764344 }, "positionAbsolute": { - "x": 577.3727711743836, - "y": 853.9773971889889 + "x": 690.2015147036818, + "y": 1018.5443911764344 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "Display a chat message in the Playground.\n\n💡 Click the ▶️ to run the flow.", - "display_name": "Chat Output", - "id": "ChatOutput-wbcyd", + "id": "undefined-emdQy", "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.\n\n💡 Click the ▶️ to run the flow.", - "display_name": "Chat Output", + "description": "### ✅ Basic System Prompting README\n\nExperiment with AI behavior control using system prompts. \n\n#### Component Overview\n- **Chat Input:** User message entry point\n- **System Message:** Sets AI personality/behavior\n- **OpenAI Model:** Processes both prompts and generates responses\n- **Chat Output:** Displays the AI response in the Playground\n\n#### Quick Start\n- Add your **OpenAI API key** to the **OpenAI Model**\n- Modify the **System Prompt** template to change AI behavior\n- Use the **Playground** to start chatting\n\nThe default prompt makes the AI respond like a pirate! Try changing it to create different AI personalities.\n\nFor more details, check the [system prompting guide](https://docs.langflow.org/guides/system-prompting).", + "display_name": "Read Me", "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "store_message", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } + "backgroundColor": "blue" } - }, - "type": "ChatOutput" + } }, "dragging": false, - "height": 297, - "id": "ChatOutput-wbcyd", + "height": 561, + "id": "undefined-emdQy", "position": { - "x": 1760.7152955011902, - "y": 903.6717604714486 + "x": 66.38770028934243, + "y": 749.744424427066 }, "positionAbsolute": { - "x": 1760.7152955011902, - "y": 903.6717604714486 + "x": 66.38770028934243, + "y": 749.744424427066 }, - "selected": false, - "type": "genericNode", - "width": 384 + "resizing": false, + "selected": true, + "style": { + "height": 561, + "width": 600 + }, + "type": "noteNode", + "width": 600 }, { "data": { - "description": "Generates text using OpenAI LLMs.\n\n💡 Be sure to add your **OpenAI API Key**", + "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", - "id": "OpenAIModel-tnzXU", + "id": "OpenAIModel-mMCO4", "node": { "base_classes": [ "LanguageModel", @@ -756,23 +508,24 @@ "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.\n\n💡 Be sure to add your **OpenAI API Key**", + "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "documentation": "", "edited": false, "field_order": [ "input_value", + "system_message", + "stream", "max_tokens", "model_kwargs", "json_mode", "output_schema", "model_name", "openai_api_base", - "openai_api_key", + "api_key", "temperature", - "stream", - "system_message", - "seed" + "seed", + "output_parser" ], "frozen": false, "icon": "OpenAI", @@ -846,6 +599,7 @@ "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { + "_input_type": "MessageInput", "advanced": false, "display_name": "Input", "dynamic": false, @@ -866,6 +620,7 @@ "value": "" }, "json_mode": { + "_input_type": "BoolInput", "advanced": true, "display_name": "JSON Mode", "dynamic": false, @@ -881,6 +636,7 @@ "value": false }, "max_tokens": { + "_input_type": "IntInput", "advanced": true, "display_name": "Max Tokens", "dynamic": false, @@ -888,6 +644,12 @@ "list": false, "name": "max_tokens", "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, "required": false, "show": true, "title_case": false, @@ -896,6 +658,7 @@ "value": "" }, "model_kwargs": { + "_input_type": "DictInput", "advanced": true, "display_name": "Model Kwargs", "dynamic": false, @@ -911,7 +674,9 @@ "value": {} }, "model_name": { + "_input_type": "DropdownInput", "advanced": false, + "combobox": false, "display_name": "Model Name", "dynamic": false, "info": "", @@ -929,11 +694,13 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", - "value": "gpt-4o" + "value": "gpt-4o-mini" }, "openai_api_base": { + "_input_type": "StrInput", "advanced": true, "display_name": "OpenAI API Base", "dynamic": false, @@ -969,6 +736,7 @@ "value": "" }, "output_schema": { + "_input_type": "DictInput", "advanced": true, "display_name": "Schema", "dynamic": false, @@ -984,6 +752,7 @@ "value": {} }, "seed": { + "_input_type": "IntInput", "advanced": true, "display_name": "Seed", "dynamic": false, @@ -999,7 +768,8 @@ "value": 1 }, "stream": { - "advanced": true, + "_input_type": "BoolInput", + "advanced": false, "display_name": "Stream", "dynamic": false, "info": "Stream the response from the model. Streaming works only in Chat.", @@ -1014,10 +784,14 @@ "value": false }, "system_message": { - "advanced": true, + "_input_type": "MessageTextInput", + "advanced": false, "display_name": "System Message", "dynamic": false, "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], "list": false, "load_from_db": false, "name": "system_message", @@ -1025,11 +799,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, + "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "temperature": { + "_input_type": "FloatInput", "advanced": false, "display_name": "Temperature", "dynamic": false, @@ -1044,74 +821,315 @@ "type": "float", "value": 0.1 } - } + }, + "tool_mode": false }, "type": "OpenAIModel" }, "dragging": false, - "height": 595, - "id": "OpenAIModel-tnzXU", + "height": 630, + "id": "OpenAIModel-mMCO4", "position": { - "x": 1165.97061248482, - "y": 768.6307079517978 + "x": 1081.0157946607428, + "y": 707.3740542546418 }, "positionAbsolute": { - "x": 1165.97061248482, - "y": 768.6307079517978 + "x": 1081.0157946607428, + "y": 707.3740542546418 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "id": "undefined-XuFCr", + "id": "ChatOutput-1s4P8", "node": { - "description": "### ✅ Basic Prompting (Hello, World) README\n\nPerform basic prompting with an OpenAI model. *Psst: look out for the* '💡' *emoji for tips in components.*\n\n#### Extra notes on these Components\n- **Chat Input:** Sends natural language instructions to the OpenAI model.\n- **OpenAI Model:** Processes the prompt and generates a response.\n- **Chat Output:** Processes the prompt and generates a response.\n#### Get started\n- Input your **OpenAI API key** to the **OpenAI Model component**\n- Select the **Playground** to interact with the chatbot.\n\nFor more details, see the [flow overview doc](https://docs.langflow.org/starter-projects-basic-prompting).", - "display_name": "Read Me", + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, "template": { - "backgroundColor": "indigo" - } - } + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" }, "dragging": false, - "height": 800, - "id": "undefined-XuFCr", + "height": 234, + "id": "ChatOutput-1s4P8", "position": { - "x": -580.3704460174015, - "y": 498.2202393425737 + "x": 1444.936881624563, + "y": 872.7273956769025 }, "positionAbsolute": { - "x": -580.3704460174015, - "y": 498.2202393425737 + "x": 1444.936881624563, + "y": 872.7273956769025 }, - "resizing": false, "selected": false, - "style": { - "height": 800, - "width": 532 - }, - "type": "noteNode", - "width": 532 + "type": "genericNode", + "width": 320 } ], "viewport": { - "x": 208.20796881231723, - "y": -76.87392199339831, - "zoom": 0.4810857801741779 + "x": -21.631817700819965, + "y": -334.5576887147924, + "zoom": 0.7749929474098888 } }, - "description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ", + "description": "Basic prompt engineering flow - customize AI responses by changing the system prompt template to create different personalities.", "endpoint_name": null, - "gradient": "oaidfnoaienfwpiawjde", - "icon": "BotMessageSquare", - "id": "fd36e130-512d-48e6-96cc-f1e03c5d3a18", + "icon": "Braces", + "id": "1511c230-d446-43a7-bfc3-539e69ce05b8", "is_component": false, - "last_tested_version": "1.0.18", - "name": "Basic Prompting (Hello, World)", + "last_tested_version": "1.0.19.post2", + "name": "Basic Prompting", "tags": [ - "chatbots", - "openai" + "chatbots" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json index 75c37849c..9dc213928 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json @@ -2,11 +2,12 @@ "data": { "edges": [ { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "URL", - "id": "URL-v3FkJ", + "id": "URL-ewId1", "name": "data", "output_types": [ "Data" @@ -14,25 +15,26 @@ }, "targetHandle": { "fieldName": "data", - "id": "ParseData-qffHj", + "id": "ParseData-Zwm0z", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-URL-v3FkJ{œdataTypeœ:œURLœ,œidœ:œURL-v3FkJœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-qffHj{œfieldNameœ:œdataœ,œidœ:œParseData-qffHjœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "URL-v3FkJ", - "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-v3FkJœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-qffHj", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-qffHjœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-URL-ewId1{œdataTypeœ:œURLœ,œidœ:œURL-ewId1œ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-Zwm0z{œfieldNameœ:œdataœ,œidœ:œParseData-Zwm0zœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "URL-ewId1", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-ewId1œ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-Zwm0z", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-Zwm0zœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "ParseData", - "id": "ParseData-qffHj", + "id": "ParseData-Zwm0z", "name": "text", "output_types": [ "Message" @@ -40,7 +42,7 @@ }, "targetHandle": { "fieldName": "references", - "id": "Prompt-ztjwI", + "id": "Prompt-WTVXx", "inputTypes": [ "Message", "Text" @@ -48,18 +50,19 @@ "type": "str" } }, - "id": "reactflow__edge-ParseData-qffHj{œdataTypeœ:œParseDataœ,œidœ:œParseData-qffHjœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-ztjwI{œfieldNameœ:œreferencesœ,œidœ:œPrompt-ztjwIœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ParseData-qffHj", - "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-qffHjœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-ztjwI", - "targetHandle": "{œfieldNameœ: œreferencesœ, œidœ: œPrompt-ztjwIœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ParseData-Zwm0z{œdataTypeœ:œParseDataœ,œidœ:œParseData-Zwm0zœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-WTVXx{œfieldNameœ:œreferencesœ,œidœ:œPrompt-WTVXxœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-Zwm0z", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-Zwm0zœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-WTVXx", + "targetHandle": "{œfieldNameœ: œreferencesœ, œidœ: œPrompt-WTVXxœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "TextInput", - "id": "TextInput-A7goL", + "id": "TextInput-PAceh", "name": "text", "output_types": [ "Message" @@ -67,7 +70,7 @@ }, "targetHandle": { "fieldName": "instructions", - "id": "Prompt-ztjwI", + "id": "Prompt-WTVXx", "inputTypes": [ "Message", "Text" @@ -75,18 +78,19 @@ "type": "str" } }, - "id": "reactflow__edge-TextInput-A7goL{œdataTypeœ:œTextInputœ,œidœ:œTextInput-A7goLœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-ztjwI{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-ztjwIœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "TextInput-A7goL", - "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-A7goLœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-ztjwI", - "targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-ztjwIœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-TextInput-PAceh{œdataTypeœ:œTextInputœ,œidœ:œTextInput-PAcehœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-WTVXx{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-WTVXxœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "TextInput-PAceh", + "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-PAcehœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-WTVXx", + "targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-WTVXxœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-ztjwI", + "id": "Prompt-WTVXx", "name": "prompt", "output_types": [ "Message" @@ -94,25 +98,26 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-Y3GUP", + "id": "OpenAIModel-s4uQ3", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-ztjwI{œdataTypeœ:œPromptœ,œidœ:œPrompt-ztjwIœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-Y3GUP{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Y3GUPœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-ztjwI", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-ztjwIœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-Y3GUP", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-Y3GUPœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-WTVXx{œdataTypeœ:œPromptœ,œidœ:œPrompt-WTVXxœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-s4uQ3{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-s4uQ3œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-WTVXx", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-WTVXxœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-s4uQ3", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-s4uQ3œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-Y3GUP", + "id": "OpenAIModel-s4uQ3", "name": "text_output", "output_types": [ "Message" @@ -120,18 +125,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-Y7FC3", + "id": "ChatOutput-uL64L", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-Y3GUP{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Y3GUPœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-Y7FC3{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Y7FC3œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-Y3GUP", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-Y3GUPœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-Y7FC3", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-Y7FC3œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-s4uQ3{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-s4uQ3œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-uL64L{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-uL64Lœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-s4uQ3", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-s4uQ3œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-uL64L", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-uL64Lœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -139,7 +144,7 @@ "data": { "description": "Fetch content from one or more URLs.", "display_name": "URL", - "id": "URL-v3FkJ", + "id": "URL-ewId1", "node": { "base_classes": [ "Data" @@ -157,6 +162,7 @@ "frozen": false, "icon": "layout-template", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -243,8 +249,8 @@ "trace_as_metadata": true, "type": "str", "value": [ - "langflow.org/", - "docs.langflow.org/" + "https://langflow.org/", + "https://docs.langflow.org/" ] } } @@ -252,25 +258,25 @@ "type": "URL" }, "dragging": false, - "height": 465, - "id": "URL-v3FkJ", + "height": 418, + "id": "URL-ewId1", "position": { - "x": 220.79156431407534, - "y": 498.8186168722667 + "x": 544.3302626182673, + "y": 495.2237424466647 }, "positionAbsolute": { - "x": 220.79156431407534, - "y": 498.8186168722667 + "x": 544.3302626182673, + "y": 495.2237424466647 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Convert Data into plain text following a specified template.", "display_name": "Parse Data", - "id": "ParseData-qffHj", + "id": "ParseData-Zwm0z", "node": { "base_classes": [ "Message" @@ -290,6 +296,7 @@ "frozen": false, "icon": "braces", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -387,25 +394,25 @@ "type": "ParseData" }, "dragging": false, - "height": 353, - "id": "ParseData-qffHj", + "height": 302, + "id": "ParseData-Zwm0z", "position": { - "x": 754.3607306709101, - "y": 736.8516961537598 + "x": 955.6736985046297, + "y": 702.7003891105396 }, "positionAbsolute": { - "x": 754.3607306709101, - "y": 736.8516961537598 + "x": 955.6736985046297, + "y": 702.7003891105396 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-ztjwI", + "id": "Prompt-WTVXx", "node": { "base_classes": [ "Message" @@ -428,6 +435,7 @@ "frozen": false, "icon": "prompts", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -533,25 +541,25 @@ "type": "Prompt" }, "dragging": false, - "height": 477, - "id": "Prompt-ztjwI", + "height": 433, + "id": "Prompt-WTVXx", "position": { - "x": 1368.0633591447076, - "y": 467.19448061224284 + "x": 1341.1018009526915, + "y": 456.4098573354365 }, "positionAbsolute": { - "x": 1368.0633591447076, - "y": 467.19448061224284 + "x": 1341.1018009526915, + "y": 456.4098573354365 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Get text inputs from the Playground.", "display_name": "Instructions", - "id": "TextInput-A7goL", + "id": "TextInput-PAceh", "node": { "base_classes": [ "Message" @@ -568,6 +576,7 @@ ], "frozen": false, "icon": "type", + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -631,25 +640,25 @@ "type": "TextInput" }, "dragging": false, - "height": 289, - "id": "TextInput-A7goL", + "height": 234, + "id": "TextInput-PAceh", "position": { - "x": 743.7338453293725, - "y": 301.58775454952183 + "x": 955.8314364398983, + "y": 402.24423846638155 }, "positionAbsolute": { - "x": 743.7338453293725, - "y": 301.58775454952183 + "x": 955.8314364398983, + "y": 402.24423846638155 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Display a chat message in the Playground.", "display_name": "Chat Output", - "id": "ChatOutput-Y7FC3", + "id": "ChatOutput-uL64L", "node": { "base_classes": [ "Message" @@ -672,6 +681,7 @@ "frozen": false, "icon": "MessagesSquare", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -890,25 +900,25 @@ "type": "ChatOutput" }, "dragging": false, - "height": 289, - "id": "ChatOutput-Y7FC3", + "height": 234, + "id": "ChatOutput-uL64L", "position": { - "x": 2449.3489426461606, - "y": 571.2449700910389 + "x": 2113.228183852361, + "y": 594.6116538574528 }, "positionAbsolute": { - "x": 2449.3489426461606, - "y": 571.2449700910389 + "x": 2113.228183852361, + "y": 594.6116538574528 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", - "id": "OpenAIModel-Y3GUP", + "id": "OpenAIModel-s4uQ3", "node": { "base_classes": [ "LanguageModel", @@ -938,6 +948,7 @@ "frozen": false, "icon": "OpenAI", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -1160,7 +1171,7 @@ "value": 1 }, "stream": { - "advanced": true, + "advanced": false, "display_name": "Stream", "dynamic": false, "info": "Stream the response from the model. Streaming works only in Chat.", @@ -1175,7 +1186,7 @@ "value": false }, "system_message": { - "advanced": true, + "advanced": false, "display_name": "System Message", "dynamic": false, "info": "System message to pass to the model.", @@ -1210,35 +1221,133 @@ "type": "OpenAIModel" }, "dragging": false, - "height": 587, - "id": "OpenAIModel-Y3GUP", + "height": 495, + "id": "OpenAIModel-s4uQ3", "position": { - "x": 1950.3830456413473, - "y": 380.8161704718418 + "x": 1713.1213335516065, + "y": 456.3085334094866 }, "positionAbsolute": { - "x": 1950.3830456413473, - "y": 380.8161704718418 + "x": 1713.1213335516065, + "y": 456.3085334094866 }, - "selected": true, + "selected": false, "type": "genericNode", - "width": 384 + "width": 320 + }, + { + "data": { + "id": "note-5zVjK", + "node": { + "description": "## URL Component Setup\n\n**Purpose:**\nFetch and process content from the web to use as reference material for creating a blog post.\n\n**Instructions:**\n1. **Input URLs**: List the URLs of web pages whose content you want to fetch. Ensure the URLs start with `http://` or `https://`.\n2. **Select Output Format**:\n - **Text**: To extract plain text from the pages.\n - **Raw HTML**: To retrieve the raw HTML content for advanced uses.\n\n**Tips**:\n- Double-check URL formats to prevent any data fetching errors.\n- Use the '+' button to add multiple URLs as needed for comprehensive references.\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 329, + "id": "note-5zVjK", + "position": { + "x": 484.73635938598477, + "y": 153.29803159918163 + }, + "positionAbsolute": { + "x": 484.73635938598477, + "y": 153.29803159918163 + }, + "resizing": false, + "selected": false, + "style": { + "height": 329, + "width": 414 + }, + "type": "noteNode", + "width": 414 + }, + { + "data": { + "id": "note-TrHJa", + "node": { + "description": "# Blog Writing Flow Overview\n\n**Workflow Description:**\nThis flow assists in creating a blog post by using content fetched from URLs and user-provided instructions. It combines external references and user inputs to generate coherent and context-rich text.\n\n**Components**:\n1. **URL Component**: Fetches reference content from specified web pages.\n2. **Parse Data**: Converts the fetched content into a text format.\n3. **Text Input**: Accepts user-specific instructions for the blog post.\n4. **Prompt with Variables**: Merges references and instructions into a dynamic writing prompt.\n5. **OpenAI Model**: Generates the blog post using an AI language model.\n6. **Chat Output**: Displays the final blog text for user review and further refinement.\n\n**Steps to Execute**:\n1. Enter the relevant URLs and specify the output format in the **URL Component**.\n2. Provide detailed writing **Instructions** for AI to follow.\n3. Run the flow to generate the blog and view the result in **Chat Output**.\n\n**Benefits**:\n- Simplifies blog creation by using AI to structure and write content.\n- Incorporates comprehensive reference material to enhance post depth and accuracy.", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 509, + "id": "note-TrHJa", + "position": { + "x": -78.41970365609802, + "y": 405.04114164010207 + }, + "positionAbsolute": { + "x": -78.41970365609802, + "y": 405.04114164010207 + }, + "resizing": false, + "selected": false, + "style": { + "height": 509, + "width": 562 + }, + "type": "noteNode", + "width": 562 + }, + { + "data": { + "id": "note-b1YaN", + "node": { + "description": "## Get Your OpenAI API Key\n**Steps**:\n1. **Visit** [OpenAI's API Key Page](https://platform.openai.com/api-keys).\n\n2. **Log In/Sign Up**:\n - Log in or create a new OpenAI account.\n\n3. **Generate API Key**:\n - Click \"Create New Secret Key\" to obtain your key.\n\n4. **Store Your Key Securely**:\n - Note it down as it will only display once.\n\n5. **Enter API Key**:\n - Input your key in the OpenAI API Key field within the component setup.\n\nKeep your key safe and manage it responsibly!", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "rose" + } + }, + "type": "note" + }, + "dragging": false, + "height": 324, + "id": "note-b1YaN", + "position": { + "x": 1703.974189852056, + "y": 125.15366878585462 + }, + "positionAbsolute": { + "x": 1703.974189852056, + "y": 125.15366878585462 + }, + "resizing": false, + "selected": false, + "style": { + "height": 324, + "width": 343 + }, + "type": "noteNode", + "width": 343 } ], "viewport": { - "x": -46.935859383438924, - "y": 110.83424076132906, - "zoom": 0.5205627295612754 + "x": 94.80835919355627, + "y": 105.45081997045315, + "zoom": 0.5284811262210728 } }, - "description": "This flow can be used to create a blog post following instructions from the user, using two other blogs as reference.", + "description": "Auto-generate a customized blog post from instructions and referenced articles.", "endpoint_name": null, - "icon": "FileText", - "id": "5e9b5662-0985-4d40-8ffe-b7f42fa86421", + "icon": "NotebookPen", + "id": "8b12aa0f-8b59-4806-a01f-5e545b5b1688", "is_component": false, - "last_tested_version": "1.0.19.post1", + "last_tested_version": "1.0.19.post2", "name": "Blog Writer", "tags": [ - "chatbots" + "chatbots", + "content-generation" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Complex Agent.json b/src/backend/base/langflow/initial_setup/starter_projects/Complex Agent.json deleted file mode 100644 index ccac3d66c..000000000 --- a/src/backend/base/langflow/initial_setup/starter_projects/Complex Agent.json +++ /dev/null @@ -1,4526 +0,0 @@ -{ - "data": { - "edges": [ - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "HierarchicalCrewComponent", - "id": "HierarchicalCrewComponent-3JGY1", - "name": "output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-8FKry", - 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"target": "CrewAIAgentComponent-ViX9d", - "targetHandle": "{œfieldNameœ: œtoolsœ, œidœ: œCrewAIAgentComponent-ViX9dœ, œinputTypesœ: [œToolœ], œtypeœ: œotherœ}" - } - ], - "nodes": [ - { - "data": { - "description": "Represents a group of agents, defining how they should collaborate and the tasks they should perform.", - "display_name": "Hierarchical Crew", - "id": "HierarchicalCrewComponent-3JGY1", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Represents a group of agents, defining how they should collaborate and the tasks they should perform.", - "display_name": "Hierarchical Crew", - "documentation": "", - "edited": false, - "field_order": [ - "verbose", - "memory", - "use_cache", - "max_rpm", - "share_crew", - "function_calling_llm", - "agents", - "tasks", - "manager_llm", - "manager_agent" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Output", - "method": "build_output", - "name": "output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "agents": { - "advanced": false, - "display_name": "Agents", - "dynamic": false, - "info": "", - "input_types": [ - "Agent" - ], - "list": true, - "name": "agents", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import os\n\nfrom crewai import Crew, Process\n\nfrom langflow.base.agents.crewai.crew import BaseCrewComponent\nfrom langflow.io import HandleInput, SecretStrInput\n\n\nclass HierarchicalCrewComponent(BaseCrewComponent):\n display_name: str = \"Hierarchical Crew\"\n description: str = (\n \"Represents a group of agents, defining how they should collaborate and the tasks they should perform.\"\n )\n documentation: str = \"https://docs.crewai.com/how-to/Hierarchical/\"\n icon = \"CrewAI\"\n\n inputs = [\n *BaseCrewComponent._base_inputs,\n HandleInput(name=\"agents\", display_name=\"Agents\", input_types=[\"Agent\"], is_list=True),\n HandleInput(name=\"tasks\", display_name=\"Tasks\", input_types=[\"HierarchicalTask\"], is_list=True),\n HandleInput(name=\"manager_llm\", display_name=\"Manager LLM\", input_types=[\"LanguageModel\"], required=False),\n HandleInput(name=\"manager_agent\", display_name=\"Manager Agent\", input_types=[\"Agent\"], required=False),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n value=\"OPENAI_API_KEY\",\n ),\n ]\n\n def build_crew(self) -> Crew:\n tasks, agents = self.get_tasks_and_agents()\n\n # Set the OpenAI API Key\n if self.openai_api_key:\n os.environ[\"OPENAI_API_KEY\"] = self.openai_api_key\n\n return Crew(\n agents=agents,\n tasks=tasks,\n process=Process.hierarchical,\n verbose=self.verbose,\n memory=self.memory,\n cache=self.use_cache,\n max_rpm=self.max_rpm,\n share_crew=self.share_crew,\n function_calling_llm=self.function_calling_llm,\n manager_agent=self.manager_agent,\n manager_llm=self.manager_llm,\n step_callback=self.get_step_callback(),\n task_callback=self.get_task_callback(),\n )\n" - }, - "function_calling_llm": { - "advanced": true, - "display_name": "Function Calling LLM", - "dynamic": false, - "info": "Turns the ReAct CrewAI agent into a function-calling agent", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "function_calling_llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "manager_agent": { - "advanced": false, - "display_name": "Manager Agent", - "dynamic": false, - "info": "", - "input_types": [ - "Agent" - ], - "list": false, - "name": "manager_agent", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "manager_llm": { - "advanced": false, - "display_name": "Manager LLM", - "dynamic": false, - "info": "", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "manager_llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "max_rpm": { - "advanced": true, - "display_name": "Max RPM", - "dynamic": false, - "info": "", - "list": false, - "name": "max_rpm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 100 - }, - "memory": { - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "openai_api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "share_crew": { - "advanced": true, - "display_name": "Share Crew", - "dynamic": false, - "info": "", - "list": false, - "name": "share_crew", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "tasks": { - "advanced": false, - "display_name": "Tasks", - "dynamic": false, - "info": "", - "input_types": [ - "HierarchicalTask" - ], - "list": true, - "name": "tasks", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "use_cache": { - "advanced": true, - "display_name": "Cache", - "dynamic": false, - "info": "", - "list": false, - "name": "use_cache", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 0 - } - } - }, - "type": "HierarchicalCrewComponent" - }, - "height": 460, - "id": "HierarchicalCrewComponent-3JGY1", - "position": { - "x": 2444.845721347115, - "y": 1410.1850661630874 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-ucjrK", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 605, - "id": "OpenAIModel-ucjrK", - "position": { - "x": 993.5222179419411, - "y": 2121.1120144471624 - }, - "positionAbsolute": { - "x": 993.5222179419411, - "y": 2121.1120144471624 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "id": "ChatOutput-8FKry", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "should_store_message", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "height": 302, - "id": "ChatOutput-8FKry", - "position": { - "x": 2947.7605810360546, - "y": 1557.6959660020289 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Each task must have a description, an expected output and an agent responsible for execution.", - "display_name": "Hierarchical Task", - "id": "HierarchicalTaskComponent-GuXH7", - "node": { - "base_classes": [ - "HierarchicalTask" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Each task must have a description, an expected output and an agent responsible for execution.", - "display_name": "Hierarchical Task", - "documentation": "", - "edited": false, - "field_order": [ - "task_description", - "expected_output", - "tools" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Task", - "method": "build_task", - "name": "task_output", - "selected": "HierarchicalTask", - "types": [ - "HierarchicalTask" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.agents.crewai.tasks import HierarchicalTask\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, MultilineInput, Output\n\n\nclass HierarchicalTaskComponent(Component):\n display_name: str = \"Hierarchical Task\"\n description: str = \"Each task must have a description, an expected output and an agent responsible for execution.\"\n icon = \"CrewAI\"\n inputs = [\n MultilineInput(\n name=\"task_description\",\n display_name=\"Description\",\n info=\"Descriptive text detailing task's purpose and execution.\",\n ),\n MultilineInput(\n name=\"expected_output\",\n display_name=\"Expected Output\",\n info=\"Clear definition of expected task outcome.\",\n ),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"List of tools/resources limited for task execution. Uses the Agent tools by default.\",\n required=False,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Task\", name=\"task_output\", method=\"build_task\"),\n ]\n\n def build_task(self) -> HierarchicalTask:\n task = HierarchicalTask(\n description=self.task_description,\n expected_output=self.expected_output,\n tools=self.tools or [],\n )\n self.status = task\n return task\n" - }, - "expected_output": { - "advanced": false, - "display_name": "Expected Output", - "dynamic": false, - "info": "Clear definition of expected task outcome.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "expected_output", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Succinct response that answers the User's query." - }, - "task_description": { - "advanced": false, - "display_name": "Description", - "dynamic": false, - "info": "Descriptive text detailing task's purpose and execution.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "task_description", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "tools": { - "advanced": true, - "display_name": "Tools", - "dynamic": false, - "info": "List of tools/resources limited for task execution. Uses the Agent tools by default.", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - } - } - }, - "type": "HierarchicalTaskComponent" - }, - "height": 440, - "id": "HierarchicalTaskComponent-GuXH7", - "position": { - "x": 1940.5188074417165, - "y": 682.2998623189735 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "id": "CrewAIAgentComponent-ViX9d", - "node": { - "base_classes": [ - "Agent" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "kwargs" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Agent", - "method": "build_output", - "name": "output", - "selected": "Agent", - "types": [ - "Agent" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "allow_code_execution": { - "advanced": true, - "display_name": "Allow Code Execution", - "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "advanced": false, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "backstory": { - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "backstory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent\n\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass CrewAIAgentComponent(Component):\n display_name = \"CrewAI Agent\"\n description = \"Represents an agent of CrewAI.\"\n documentation: str = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(name=\"backstory\", display_name=\"Backstory\", info=\"The backstory of the agent.\"),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agents disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=False,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"kwargs\",\n display_name=\"kwargs\",\n info=\"kwargs of agent.\",\n is_list=True,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Agent\", name=\"output\", method=\"build_output\"),\n ]\n\n def build_output(self) -> Agent:\n kwargs = self.kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **kwargs,\n )\n self.status = repr(agent)\n return agent\n" - }, - "goal": { - "advanced": false, - "display_name": "Goal", - "dynamic": false, - "info": "The objective of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "kwargs": { - "advanced": true, - "display_name": "kwargs", - "dynamic": false, - "info": "kwargs of agent.", - "list": true, - "name": "kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "llm": { - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "memory": { - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "Whether the agent should have memory or not", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "role": { - "advanced": false, - "display_name": "Role", - "dynamic": false, - "info": "The role of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "tools": { - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "Tools at agents disposal", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": [] - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - } - } - }, - "type": "CrewAIAgentComponent" - }, - "dragging": false, - "height": 638, - "id": "CrewAIAgentComponent-ViX9d", - "position": { - "x": 1397.4912377259789, - "y": 1242.739374306084 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "id": "CrewAIAgentComponent-aCLi7", - "node": { - "base_classes": [ - "Agent" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "kwargs" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Agent", - "method": "build_output", - "name": "output", - "selected": "Agent", - "types": [ - "Agent" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "allow_code_execution": { - "advanced": true, - "display_name": "Allow Code Execution", - "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "advanced": false, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "backstory": { - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "backstory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You are polite and helpful. You've always been a beacon of politeness." - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent\n\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass CrewAIAgentComponent(Component):\n display_name = \"CrewAI Agent\"\n description = \"Represents an agent of CrewAI.\"\n documentation: str = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(name=\"backstory\", display_name=\"Backstory\", info=\"The backstory of the agent.\"),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agents disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=False,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"kwargs\",\n display_name=\"kwargs\",\n info=\"kwargs of agent.\",\n is_list=True,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Agent\", name=\"output\", method=\"build_output\"),\n ]\n\n def build_output(self) -> Agent:\n kwargs = self.kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **kwargs,\n )\n self.status = repr(agent)\n return agent\n" - }, - "goal": { - "advanced": false, - "display_name": "Goal", - "dynamic": false, - "info": "The objective of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You can answer general questions from the User and may call others for help if needed." - }, - "kwargs": { - "advanced": true, - "display_name": "kwargs", - "dynamic": false, - "info": "kwargs of agent.", - "list": true, - "name": "kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "llm": { - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "memory": { - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "Whether the agent should have memory or not", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "role": { - "advanced": false, - "display_name": "Role", - "dynamic": false, - "info": "The role of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Manager" - }, - "tools": { - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "Tools at agents disposal", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": [] - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - } - } - }, - "type": "CrewAIAgentComponent" - }, - "dragging": false, - "height": 638, - "id": "CrewAIAgentComponent-aCLi7", - "position": { - "x": 1897.563645835175, - "y": 2043.8342912334688 - }, - "positionAbsolute": { - "x": 1897.563645835175, - "y": 2043.8342912334688 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-wMVJn", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 605, - "id": "OpenAIModel-wMVJn", - "position": { - "x": 1689.7403176652529, - "y": 2778.554803586579 - }, - "positionAbsolute": { - "x": 1689.7403176652529, - "y": 2778.554803586579 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-gbnQU", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "query" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "edited": false, - "error": null, - "field_order": [ - "template" - ], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "legacy": false, - "metadata": {}, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" - }, - "query": { - "advanced": false, - "display_name": "query", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "query", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "User's query:\n{query}\n\nRespond to the user with as much as information as you can about the topic. Delete if needed. If it is just a general query (e.g a greeting) you can respond them directly." - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 416, - "id": "Prompt-gbnQU", - "position": { - "x": 1314.943965489173, - "y": 624.296875 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ChatInput-1Gki8", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "should_store_message", - "sender", - "sender_name", - "session_id", - "files" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "files": { - "advanced": true, - "display_name": "Files", - "dynamic": false, - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx", - "jpg", - "jpeg", - "png", - "bmp", - "image" - ], - "file_path": "", - "info": "Files to be sent with the message.", - "list": true, - "name": "files", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "file", - "value": "" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as input.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Could you search info about AAPL?" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatInput" - }, - "dragging": false, - "height": 302, - "id": "ChatInput-1Gki8", - "position": { - "x": -812.219234501281, - "y": 283.9527676042414 - }, - "positionAbsolute": { - "x": -812.219234501281, - "y": 283.9527676042414 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Tool for interacting with Yahoo Finance News.", - "display_name": "Yahoo Finance News Tool", - "id": "YFinanceTool-gzeyq", - "node": { - "base_classes": [ - "Tool" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Tool for interacting with Yahoo Finance News.", - "display_name": "Yahoo Finance News Tool", - "documentation": "", - "edited": false, - "field_order": [], - "frozen": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "run_model", - "name": "api_run_model", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Tool", - "method": "build_tool", - "name": "tool", - "selected": "Tool", - "types": [ - "Tool" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import cast\n\nfrom langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Data, Tool\nfrom langflow.inputs.inputs import MessageTextInput\nfrom langflow.template.field.base import Output\n\n\nclass YfinanceToolComponent(LCToolComponent):\n display_name = \"Yahoo Finance News Tool\"\n description = \"Tool for interacting with Yahoo Finance News.\"\n name = \"YFinanceTool\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Query\",\n info=\"Input should be a company ticker. For example, AAPL for Apple, MSFT for Microsoft.\",\n )\n ]\n\n outputs = [\n Output(name=\"api_run_model\", display_name=\"Data\", method=\"run_model\"),\n # Keep this for backwards compatibility\n Output(name=\"tool\", display_name=\"Tool\", method=\"build_tool\"),\n ]\n\n def build_tool(self) -> Tool:\n return cast(Tool, YahooFinanceNewsTool())\n\n def run_model(self) -> Data:\n tool = self.build_tool()\n return tool.run(self.input_value)\n" - }, - "input_value": { - "_input_type": "MessageTextInput", - "advanced": false, - "display_name": "Query", - "dynamic": false, - "info": "Input should be a company ticker. For example, AAPL for Apple, MSFT for Microsoft.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "YFinanceTool" - }, - "dragging": false, - "height": 347, - "id": "YFinanceTool-gzeyq", - "position": { - "x": 339.85802955438953, - "y": 941.0061737791777 - }, - "positionAbsolute": { - "x": 339.85802955438953, - "y": 941.0061737791777 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-KnjCY", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 605, - "id": "OpenAIModel-KnjCY", - "position": { - "x": -1421.3072930401338, - "y": 944.2116827656167 - }, - "positionAbsolute": { - "x": -1421.3072930401338, - "y": 944.2116827656167 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Role Prompt", - "id": "Prompt-qCC5T", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "query" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Role Prompt", - "documentation": "", - "edited": false, - "field_order": [ - "template" - ], - "frozen": false, - "icon": "prompts", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" - }, - "query": { - "advanced": false, - "display_name": "query", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "query", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "_input_type": "PromptInput", - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "Define a Role that could execute or answer well the user's query.\n\nUser's query: {query}\n\nRole should be two words max. Something like \"Researcher\" or \"Software Developer\".\n" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 416, - "id": "Prompt-qCC5T", - "position": { - "x": -2011.857599027479, - "y": 811.2903194233206 - }, - "positionAbsolute": { - "x": -2011.857599027479, - "y": 811.2903194233206 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-wOSDH", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 605, - "id": "OpenAIModel-wOSDH", - "position": { - "x": -652.5526340446298, - "y": 2170.3301251807097 - }, - "positionAbsolute": { - "x": -652.5526340446298, - "y": 2170.3301251807097 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Goal Prompt", - "id": "Prompt-5wrVb", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "query", - "role" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Goal Prompt", - "documentation": "", - "edited": false, - "field_order": [ - "template" - ], - "frozen": false, - "icon": "prompts", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" - }, - "query": { - "advanced": false, - "display_name": "query", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "query", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "role": { - "advanced": false, - "display_name": "role", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "_input_type": "PromptInput", - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "Define the Goal of this Role, given the User's Query. \nUser's query: {query}\n\nRole: {role}\n\nThe goal should be concise and specific.\nGoal: \n" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 502, - "id": "Prompt-5wrVb", - "position": { - "x": -1127.1897676702288, - "y": 1693.922415635935 - }, - "positionAbsolute": { - "x": -1127.1897676702288, - "y": 1693.922415635935 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-lajm6", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 605, - "id": "OpenAIModel-lajm6", - "position": { - "x": -173.231944282948, - "y": 3277.114857802737 - }, - "positionAbsolute": { - "x": -173.231944282948, - "y": 3277.114857802737 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-g5dyc", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "query", - "role", - "goal" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "edited": false, - "error": null, - "field_order": [ - "template" - ], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "legacy": false, - "metadata": {}, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" - }, - "goal": { - "advanced": false, - "display_name": "goal", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "query": { - "advanced": false, - "display_name": "query", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "query", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "role": { - "advanced": false, - "display_name": "role", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "Define a Backstory of this Role and Goal, given the User's Query. \nUser's query: {query}\n\nRole: {role}\nGoal: {goal}\n\nThe backstory should be specific and well aligned with the rest of the information.\nBackstory:" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 588, - "id": "Prompt-g5dyc", - "position": { - "x": -559.9999554636487, - "y": 2893.2894056013133 - }, - "positionAbsolute": { - "x": -559.9999554636487, - "y": 2893.2894056013133 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Call the searchapi.io API", - "display_name": "Search API", - "id": "SearchAPI-1mPpu", - "node": { - "base_classes": [ - "Data", - "Tool" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Call the searchapi.io API with result limiting", - "display_name": "Search API", - "documentation": "https://www.searchapi.io/docs/google", - "edited": false, - "field_order": [ - "engine", - "api_key", - "input_value", - "search_params" - ], - "frozen": false, - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "run_model", - "name": "api_run_model", - "required_inputs": [ - "api_key" - ], - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Tool", - "method": "build_tool", - "name": "api_build_tool", - "required_inputs": [ - "api_key" - ], - "selected": "Tool", - "types": [ - "Tool" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "advanced": false, - "display_name": "SearchAPI API Key", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import Any\n\nfrom langchain.tools import StructuredTool\nfrom langchain_community.utilities.searchapi import SearchApiAPIWrapper\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import DictInput, IntInput, MessageTextInput, MultilineInput, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass SearchAPIComponent(LCToolComponent):\n display_name: str = \"Search API\"\n description: str = \"Call the searchapi.io API with result limiting\"\n name = \"SearchAPI\"\n documentation: str = \"https://www.searchapi.io/docs/google\"\n\n inputs = [\n MessageTextInput(name=\"engine\", display_name=\"Engine\", value=\"google\"),\n SecretStrInput(name=\"api_key\", display_name=\"SearchAPI API Key\", required=True),\n MultilineInput(\n name=\"input_value\",\n display_name=\"Input\",\n ),\n DictInput(name=\"search_params\", display_name=\"Search parameters\", advanced=True, is_list=True),\n IntInput(name=\"max_results\", display_name=\"Max Results\", value=5, advanced=True),\n IntInput(name=\"max_snippet_length\", display_name=\"Max Snippet Length\", value=100, advanced=True),\n ]\n\n class SearchAPISchema(BaseModel):\n query: str = Field(..., description=\"The search query\")\n params: dict[str, Any] = Field(default_factory=dict, description=\"Additional search parameters\")\n max_results: int = Field(5, description=\"Maximum number of results to return\")\n max_snippet_length: int = Field(100, description=\"Maximum length of each result snippet\")\n\n def _build_wrapper(self):\n return SearchApiAPIWrapper(engine=self.engine, searchapi_api_key=self.api_key)\n\n def build_tool(self) -> Tool:\n wrapper = self._build_wrapper()\n\n def search_func(\n query: str, params: dict[str, Any] | None = None, max_results: int = 5, max_snippet_length: int = 100\n ) -> list[dict[str, Any]]:\n params = params or {}\n full_results = wrapper.results(query=query, **params)\n organic_results = full_results.get(\"organic_results\", [])[:max_results]\n\n limited_results = []\n for result in organic_results:\n limited_result = {\n \"title\": result.get(\"title\", \"\")[:max_snippet_length],\n \"link\": result.get(\"link\", \"\"),\n \"snippet\": result.get(\"snippet\", \"\")[:max_snippet_length],\n }\n limited_results.append(limited_result)\n\n return limited_results\n\n tool = StructuredTool.from_function(\n name=\"search_api\",\n description=\"Search for recent results using searchapi.io with result limiting\",\n func=search_func,\n args_schema=self.SearchAPISchema,\n )\n\n self.status = f\"Search API Tool created with engine: {self.engine}\"\n return tool\n\n def run_model(self) -> list[Data]:\n tool = self.build_tool()\n results = tool.run(\n {\n \"query\": self.input_value,\n \"params\": self.search_params or {},\n \"max_results\": self.max_results,\n \"max_snippet_length\": self.max_snippet_length,\n }\n )\n\n data_list = [Data(data=result, text=result.get(\"snippet\", \"\")) for result in results]\n\n self.status = data_list\n return data_list\n" - }, - "engine": { - "advanced": false, - "display_name": "Engine", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "engine", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "google" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "max_results": { - "_input_type": "IntInput", - "advanced": true, - "display_name": "Max Results", - "dynamic": false, - "info": "", - "list": false, - "name": "max_results", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 5 - }, - "max_snippet_length": { - "_input_type": "IntInput", - "advanced": true, - "display_name": "Max Snippet Length", - "dynamic": false, - "info": "", - "list": false, - "name": "max_snippet_length", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 100 - }, - "search_params": { - "advanced": true, - "display_name": "Search parameters", - "dynamic": false, - "info": "", - "list": true, - "name": "search_params", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - } - } - }, - "type": "SearchAPI" - }, - "dragging": false, - "height": 519, - "id": "SearchAPI-1mPpu", - "position": { - "x": 333.3937684700711, - "y": 310.93183831810336 - }, - "positionAbsolute": { - "x": 333.3937684700711, - "y": 310.93183831810336 - }, - "selected": false, - "type": "genericNode", - "width": 384 - } - ], - "viewport": { - "x": 514.3183520357233, - "y": 43.747988301750695, - "zoom": 0.4190366645156897 - } - }, - "description": "This Agent is created on the fly based on what the user asks and a Manager Agent calls it if needed.", - "endpoint_name": null, - "icon": "Users", - "id": "93709197-049c-41fa-ab4d-f871c20e83eb", - "is_component": false, - "last_tested_version": "1.0.17", - "name": "Dynamic Agent", - "tags": [ - "agents", - "openai", - "chatbots" - ] -} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json b/src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json new file mode 100644 index 000000000..bffc330de --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json @@ -0,0 +1,2014 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Memory", + "id": "Memory-tBe70", + "name": "messages_text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "CHAT_HISTORY", + "id": "Prompt-WSv03", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Memory-tBe70{œdataTypeœ:œMemoryœ,œidœ:œMemory-tBe70œ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-WSv03{œfieldNameœ:œCHAT_HISTORYœ,œidœ:œPrompt-WSv03œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "selected": false, + "source": "Memory-tBe70", + "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-tBe70œ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-WSv03", + "targetHandle": "{œfieldNameœ: œCHAT_HISTORYœ, œidœ: œPrompt-WSv03œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-VUqPC", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "USER_INPUT", + "id": "Prompt-WSv03", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-VUqPC{œdataTypeœ:œChatInputœ,œidœ:œChatInput-VUqPCœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-WSv03{œfieldNameœ:œUSER_INPUTœ,œidœ:œPrompt-WSv03œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "selected": false, + "source": "ChatInput-VUqPC", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-VUqPCœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-WSv03", + "targetHandle": "{œfieldNameœ: œUSER_INPUTœ, œidœ: œPrompt-WSv03œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-WSv03", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "AnthropicModel-laWKJ", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-WSv03{œdataTypeœ:œPromptœ,œidœ:œPrompt-WSv03œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-AnthropicModel-laWKJ{œfieldNameœ:œinput_valueœ,œidœ:œAnthropicModel-laWKJœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-WSv03", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-WSv03œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "AnthropicModel-laWKJ", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œAnthropicModel-laWKJœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "AnthropicModel", + "id": "AnthropicModel-laWKJ", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-XNaWv", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-AnthropicModel-laWKJ{œdataTypeœ:œAnthropicModelœ,œidœ:œAnthropicModel-laWKJœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-XNaWv{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-XNaWvœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "AnthropicModel-laWKJ", + "sourceHandle": "{œdataTypeœ: œAnthropicModelœ, œidœ: œAnthropicModel-laWKJœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-XNaWv", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-XNaWvœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "URL", + "id": "URL-9b1oo", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "EXAMPLE_COMPONENTS", + "id": "Prompt-WSv03", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-URL-9b1oo{œdataTypeœ:œURLœ,œidœ:œURL-9b1ooœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-WSv03{œfieldNameœ:œEXAMPLE_COMPONENTSœ,œidœ:œPrompt-WSv03œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "URL-9b1oo", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-9b1ooœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-WSv03", + "targetHandle": "{œfieldNameœ: œEXAMPLE_COMPONENTSœ, œidœ: œPrompt-WSv03œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "URL", + "id": "URL-HTi1a", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "BASE_COMPONENT_CODE", + "id": "Prompt-WSv03", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-URL-HTi1a{œdataTypeœ:œURLœ,œidœ:œURL-HTi1aœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-WSv03{œfieldNameœ:œBASE_COMPONENT_CODEœ,œidœ:œPrompt-WSv03œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "URL-HTi1a", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-HTi1aœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-WSv03", + "targetHandle": "{œfieldNameœ: œBASE_COMPONENT_CODEœ, œidœ: œPrompt-WSv03œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "URL", + "id": "URL-bqkBy", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "CUSTOM_COMPONENT_CODE", + "id": "Prompt-WSv03", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-URL-bqkBy{œdataTypeœ:œURLœ,œidœ:œURL-bqkByœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-WSv03{œfieldNameœ:œCUSTOM_COMPONENT_CODEœ,œidœ:œPrompt-WSv03œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "URL-bqkBy", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-bqkByœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-WSv03", + "targetHandle": "{œfieldNameœ: œCUSTOM_COMPONENT_CODEœ, œidœ: œPrompt-WSv03œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "id": "ChatInput-VUqPC", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Failed to get YouTube transcripts: 1 validation error for Data\ndata\n Input should be a valid dictionary [type=dict_type, input_value=Document(metadata={'sourc...adding the API key and\"), input_type=Document]\n For further information visit https://errors.pydantic.dev/2.9/v/dict_type\n\n\nAlso, adapt the \"text\" bc it returns this \"Document(metadata={'source': 'UkV79sJAvz8'}, page_content=\"assembly AI is one of the leaders in transcription services so you can convert speech into text and they have many different products available on their platform and we can use assembly within langlow and the way we can get started is to First make an account with assembly Ai and once you get started you will be provided with an API key this is something we're going to need in langlow now back in link flow there are a few different components available and in this example we are using the start transcript component within this component we can provide a file and what I did is I uploaded a 1-hour talk by Andre karpati and this is intro to the large language models and this is an MP3 file so after adding the API key and then the audio file we can select a model that we want to use for the transcription there are two different options available here best and Nano now after you select the model you can either have the language detection on or leave defaults so I left everything in default and then I started the task and once we run the flow we get a transcript ID and attaching this component with the assembly AI pole transcript component we can now get the results and if we were to look at the results available able from this component there are quite a lot of fields that we can see as a result of this component and some of the most important ones you can see is the text from the transcript as you can see it's quite a large file and all of that was converted from speech to text easily by assembly AI it just took a few seconds and then we can see Word level timestamps if needed as what was spoken at what time the starting and end time for that and also the confidence if there are multiple speakers then it also identifies the speakers for us and then we can also see the utterances at different times so there's also word there's a full text and there's some additional information available here now we can use this data for many different things one is we can parse the transcript so we can just look at the full transcript that was available from this video or in this case this MP3 file and then we can also run to get subtitles and this could be used for any Services where we want to add subtitles in different formats so there is the SRT and the VT format available and the way this looks so I ran it for SRT We have basically the time stamps as well as the sentences those were converted from those time stamps and we can see that it goes on for the full length of the audio file and then if needed we can also convert that to vtt last thing is that if you have credits available in your assembly AI account you can also perform a summary of the audio or you could perhaps do some additional task so for example in our case we could say that create a summary of the transcript we could also say that create a blog post from the transcript or perhaps an essay from the transcript so we can get creative with the available information since the transcript of the file is now available and we can utilize that text for many different purposes the flow and the components should be available in the store be sure to add your API key in all of these components wherever it says to add the API key if not it might throw some errors and there are also some additional components available you can check those out based on your use cases as well give it a try and let us know if you found it helpful\")\" \n\nwe only want the page_content " + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-VUqPC", + "position": { + "x": 1436.7228707197569, + "y": 1045.2749109595 + }, + "positionAbsolute": { + "x": 1436.7228707197569, + "y": 1045.2749109595 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Retrieves stored chat messages from Langflow tables or an external memory.", + "display_name": "Chat Memory", + "id": "Memory-tBe70", + "node": { + "base_classes": [ + "Data", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Retrieves stored chat messages from Langflow tables or an external memory.", + "display_name": "Chat Memory", + "documentation": "", + "edited": false, + "field_order": [ + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template" + ], + "frozen": false, + "icon": "message-square-more", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "retrieve_messages", + "name": "messages", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "retrieve_messages_as_text", + "name": "messages_text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain.memory import ConversationBufferMemory\n\nfrom langflow.custom import Component\nfrom langflow.field_typing import BaseChatMemory\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import LCBuiltinChatMemory, get_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n icon = \"message-square-more\"\n name = \"Memory\"\n\n inputs = [\n HandleInput(\n name=\"memory\",\n display_name=\"External Memory\",\n input_types=[\"BaseChatMessageHistory\"],\n info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Filter by sender type.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Filter by sender name.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. \"\n \"It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Text\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n if self.memory:\n # override session_id\n self.memory.session_id = session_id\n\n stored = self.memory.messages\n # langchain memories are supposed to return messages in ascending order\n if order == \"DESC\":\n stored = stored[::-1]\n if n_messages:\n stored = stored[:n_messages]\n stored = [Message.from_lc_message(m) for m in stored]\n if sender:\n expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n stored = [m for m in stored if m.type == expected_type]\n else:\n stored = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = stored\n return stored\n\n def retrieve_messages_as_text(self) -> Message:\n stored_text = data_to_text(self.template, self.retrieve_messages())\n self.status = stored_text\n return Message(text=stored_text)\n\n def build_lc_memory(self) -> BaseChatMemory:\n chat_memory = self.memory or LCBuiltinChatMemory(flow_id=self.flow_id, session_id=self.session_id)\n return ConversationBufferMemory(chat_memory=chat_memory)\n" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + } + }, + "tool_mode": false + }, + "type": "Memory" + }, + "dragging": false, + "height": 264, + "id": "Memory-tBe70", + "position": { + "x": 1830.6888981898887, + "y": 946.1205963195098 + }, + "positionAbsolute": { + "x": 1830.6888981898887, + "y": 946.1205963195098 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-WSv03", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "BASE_COMPONENT_CODE", + "CUSTOM_COMPONENT_CODE", + "EXAMPLE_COMPONENTS", + "CHAT_HISTORY", + "USER_INPUT" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "BASE_COMPONENT_CODE": { + "advanced": false, + "display_name": "BASE_COMPONENT_CODE", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "BASE_COMPONENT_CODE", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "CHAT_HISTORY": { + "advanced": false, + "display_name": "CHAT_HISTORY", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "CHAT_HISTORY", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "CUSTOM_COMPONENT_CODE": { + "advanced": false, + "display_name": "CUSTOM_COMPONENT_CODE", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "CUSTOM_COMPONENT_CODE", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "EXAMPLE_COMPONENTS": { + "advanced": false, + "display_name": "EXAMPLE_COMPONENTS", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "EXAMPLE_COMPONENTS", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "USER_INPUT": { + "advanced": false, + "display_name": "USER_INPUT", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "USER_INPUT", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "\nYou are an AI assistant specialized in creating Langflow components based on user requirements. Your task is to generate the code for a custom Langflow component according to the user's specifications.\n\nFirst, review the following code snippets for reference:\n\n\n{BASE_COMPONENT_CODE}\n\n\n\n{CUSTOM_COMPONENT_CODE}\n\n\n\n{EXAMPLE_COMPONENTS}\n\n\nNow, follow these steps to create a custom Langflow component:\n\n1. Analyze the user's input to determine the requirements for the component.\n2. Use an section to plan out the component structure and features based on the user's requirements.\n3. Generate the code for the custom component, using the provided code snippets as reference and inspiration.\n4. Provide a brief explanation of the component's functionality and how to use it.\n\nHere's the chat history and user input:\n\n\n{CHAT_HISTORY}\n\n\n\n{USER_INPUT}\n\n\nBased on the user's input, create a custom Langflow component that meets their requirements. Your response should include:\n\n1. \n Use this section to analyze the user's requirements and plan the component structure.\n\n\n2. \n Generate the complete code for the custom Langflow component here.\n\n\n3. \n Provide a brief explanation of the component's functionality and how to use it.\n\n\nRemember to:\n- Use the provided code snippets as a reference, but create a unique component tailored to the user's needs.\n- Include all necessary imports and class definitions.\n- Implement the required inputs, outputs, and any additional features specified by the user.\n- Use clear and descriptive variable names and comments to enhance code readability.\n- Ensure that the component follows Langflow best practices and conventions.\n\nIf the user's input is unclear or lacks specific details, make reasonable assumptions based on the context and explain these assumptions in your response.\n\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 693, + "id": "Prompt-WSv03", + "position": { + "x": 2219.5265974825707, + "y": 521.6320563271215 + }, + "positionAbsolute": { + "x": 2219.5265974825707, + "y": 521.6320563271215 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-XNaWv", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-XNaWv", + "position": { + "x": 2947.267779013826, + "y": 891.8123698756774 + }, + "positionAbsolute": { + "x": 2947.267779013826, + "y": 891.8123698756774 + }, + "selected": true, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-ybslb", + "node": { + "description": "# Fetch Components code \n\nUsing the URL component we are extracting from Github, the code from a few classes to provide as example to the LLM. \n\nThis ensures we are always up to date with recent information from the codebase.", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-ybslb", + "position": { + "x": 1430.2014058924922, + "y": -19.30392196909918 + }, + "positionAbsolute": { + "x": 1430.2014058924922, + "y": -19.30392196909918 + }, + "selected": false, + "type": "noteNode", + "width": 325 + }, + { + "data": { + "id": "note-7Judu", + "node": { + "description": "# 🛠️ Custom Component Generator 🚀\n\nHi! I'm here to help you create custom components for Langflow. Think of me as your technical partner who can help turn your ideas into working components! \n\n## 🎯 How to Work With Me\n\n### 1. 💭 Tell Me What You Want to Build\nSimply describe what you want your component to do in plain English. For example:\n- \"I need a component that sends Slack messages\"\n- \"I want to create a tool that can process CSV files\"\n- \"I need something that can translate text\"\n\n### 2. 📚 Share Any Relevant Information\nIf you're working with a specific:\n- 🔑 API or service (just share the documentation link or main endpoints)\n- 📄 File format\n- 🔄 Data structure\n- 🔧 Existing component you want to modify\n\n### 3. 🎨 Let Me Help Design It\nI'll help by:\n- 📊 Breaking down complex requirements into manageable pieces\n- 💡 Suggesting the best way to structure inputs and outputs\n- ⚙️ Creating the component code\n- 📝 Explaining how to use it\n\n### 4. 🔄 Iterative Refinement\nWe can then:\n- ✅ Test and refine the component\n- ⭐ Add features\n- 🔧 Modify behavior\n- 🛡️ Improve error handling\n- 📖 Add documentation\n\n## 🚀 What I Can Help With\n\nI can help create components that:\n- 📊 Process different file types (CSV, JSON, Excel, etc.)\n- 🔌 Integrate with external APIs\n- 🔄 Transform data\n- 🔀 Route messages\n- 🌐 Handle web requests\n- 🎯 Parse structured data\n- ✨ And much more!\n\n## 💡 Tips for Best Results\n\n1. **Be Specific** 🎯: The more details you provide about what you want to accomplish, the better I can help.\n\n2. **Share Examples** 📋: If you have example data or specific use cases, share them.\n\n3. **Ask Questions** ❓: Don't hesitate to ask for clarification or modifications.\n\nJust start by telling me what kind of component you'd like to create, and I'll guide you through the process! \n\nReady to build something awesome? 🚀 Let's get started!", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 573, + "id": "note-7Judu", + "position": { + "x": 807.6293964045135, + "y": 605.6504562080672 + }, + "positionAbsolute": { + "x": 807.6293964045135, + "y": 605.6504562080672 + }, + "resizing": false, + "selected": false, + "style": { + "height": 573, + "width": 564 + }, + "type": "noteNode", + "width": 564 + }, + { + "data": { + "id": "AnthropicModel-laWKJ", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generate text using Anthropic Chat&Completion LLMs with prefill support.", + "display_name": "Anthropic", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model", + "anthropic_api_key", + "temperature", + "anthropic_api_url", + "prefill", + "output_parser" + ], + "frozen": false, + "icon": "Anthropic", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "anthropic_api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "Anthropic API Key", + "dynamic": false, + "info": "Your Anthropic API key.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "anthropic_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "ANTHROPIC_API_KEY" + }, + "anthropic_api_url": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Anthropic API URL", + "dynamic": false, + "info": "Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "anthropic_api_url", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs.inputs import HandleInput\nfrom langflow.io import DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass AnthropicModelComponent(LCModelComponent):\n display_name = \"Anthropic\"\n description = \"Generate text using Anthropic Chat&Completion LLMs with prefill support.\"\n icon = \"Anthropic\"\n name = \"AnthropicModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n value=4096,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DropdownInput(\n name=\"model\",\n display_name=\"Model Name\",\n options=[\n \"claude-3-5-sonnet-20240620\",\n \"claude-3-opus-20240229\",\n \"claude-3-sonnet-20240229\",\n \"claude-3-haiku-20240307\",\n ],\n info=\"https://python.langchain.com/docs/integrations/chat/anthropic\",\n value=\"claude-3-5-sonnet-20240620\",\n ),\n SecretStrInput(name=\"anthropic_api_key\", display_name=\"Anthropic API Key\", info=\"Your Anthropic API key.\"),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n MessageTextInput(\n name=\"anthropic_api_url\",\n display_name=\"Anthropic API URL\",\n advanced=True,\n info=\"Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.\",\n ),\n MessageTextInput(\n name=\"prefill\", display_name=\"Prefill\", info=\"Prefill text to guide the model's response.\", advanced=True\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n try:\n from langchain_anthropic.chat_models import ChatAnthropic\n except ImportError as e:\n msg = \"langchain_anthropic is not installed. Please install it with `pip install langchain_anthropic`.\"\n raise ImportError(msg) from e\n model = self.model\n anthropic_api_key = self.anthropic_api_key\n max_tokens = self.max_tokens\n temperature = self.temperature\n anthropic_api_url = self.anthropic_api_url or \"https://api.anthropic.com\"\n\n try:\n output = ChatAnthropic(\n model=model,\n anthropic_api_key=(SecretStr(anthropic_api_key).get_secret_value() if anthropic_api_key else None),\n max_tokens_to_sample=max_tokens,\n temperature=temperature,\n anthropic_api_url=anthropic_api_url,\n streaming=self.stream,\n )\n except Exception as e:\n msg = \"Could not connect to Anthropic API.\"\n raise ValueError(msg) from e\n\n return output\n\n def _get_exception_message(self, exception: Exception) -> str | None:\n \"\"\"Get a message from an Anthropic exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from anthropic import BadRequestError\n except ImportError:\n return None\n if isinstance(exception, BadRequestError):\n message = exception.body.get(\"error\", {}).get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 4096 + }, + "model": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "https://python.langchain.com/docs/integrations/chat/anthropic", + "name": "model", + "options": [ + "claude-3-5-sonnet-20240620", + "claude-3-opus-20240229", + "claude-3-sonnet-20240229", + "claude-3-haiku-20240307" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "claude-3-5-sonnet-20240620" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "prefill": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Prefill", + "dynamic": false, + "info": "Prefill text to guide the model's response.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "prefill", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + } + }, + "type": "AnthropicModel" + }, + "dragging": false, + "height": 515, + "id": "AnthropicModel-laWKJ", + "position": { + "x": 2587.564685535714, + "y": 646.2448246136587 + }, + "positionAbsolute": { + "x": 2587.564685535714, + "y": 646.2448246136587 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "URL-HTi1a", + "node": { + "base_classes": [ + "Data", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Fetch content from one or more URLs.", + "display_name": "URL", + "documentation": "", + "edited": false, + "field_order": [ + "urls", + "format" + ], + "frozen": false, + "icon": "layout-template", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "fetch_content", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "fetch_content_text", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import re\n\nfrom langchain_community.document_loaders import AsyncHtmlLoader, WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n name = \"URL\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, by clicking the '+' button.\",\n is_list=True,\n tool_mode=True,\n ),\n DropdownInput(\n name=\"format\",\n display_name=\"Output format\",\n info=\"Output format. Use 'Text' to extract the text from the HTML or 'Raw HTML' for the raw HTML content.\",\n options=[\"Text\", \"Raw HTML\"],\n value=\"Text\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n Output(display_name=\"Text\", name=\"text\", method=\"fetch_content_text\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(https?:\\/\\/)?\" # optional protocol\n r\"(www\\.)?\" # optional www\n r\"([a-zA-Z0-9.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,})?\" # top-level domain\n r\"(:\\d+)?\" # optional port\n r\"(\\/[^\\s]*)?$\", # optional path\n re.IGNORECASE,\n )\n\n if not url_regex.match(string):\n msg = f\"Invalid URL: {string}\"\n raise ValueError(msg)\n\n return string\n\n def fetch_content(self) -> list[Data]:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n if self.format == \"Raw HTML\":\n loader = AsyncHtmlLoader(web_path=urls, encoding=\"utf-8\")\n else:\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(text=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n\n def fetch_content_text(self) -> Message:\n data = self.fetch_content()\n\n result_string = data_to_text(\"{text}\", data)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "format": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Output format", + "dynamic": false, + "info": "Output format. Use 'Text' to extract the text from the HTML or 'Raw HTML' for the raw HTML content.", + "name": "format", + "options": [ + "Text", + "Raw HTML" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Text" + }, + "urls": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "URLs", + "dynamic": false, + "info": "Enter one or more URLs, by clicking the '+' button.", + "input_types": [ + "Message" + ], + "list": true, + "load_from_db": false, + "name": "urls", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": [ + "https://raw.githubusercontent.com/langflow-ai/langflow/refs/heads/main/src/backend/base/langflow/custom/custom_component/component.py" + ] + } + }, + "tool_mode": false + }, + "type": "URL" + }, + "dragging": false, + "height": 368, + "id": "URL-HTi1a", + "position": { + "x": 1436.3617127766433, + "y": 264.218898085405 + }, + "positionAbsolute": { + "x": 1436.3617127766433, + "y": 264.218898085405 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "URL-9b1oo", + "node": { + "base_classes": [ + "Data", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Fetch content from one or more URLs.", + "display_name": "URL", + "documentation": "", + "edited": false, + "field_order": [ + "urls", + "format" + ], + "frozen": false, + "icon": "layout-template", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "fetch_content", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "fetch_content_text", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import re\n\nfrom langchain_community.document_loaders import AsyncHtmlLoader, WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n name = \"URL\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, by clicking the '+' button.\",\n is_list=True,\n tool_mode=True,\n ),\n DropdownInput(\n name=\"format\",\n display_name=\"Output format\",\n info=\"Output format. Use 'Text' to extract the text from the HTML or 'Raw HTML' for the raw HTML content.\",\n options=[\"Text\", \"Raw HTML\"],\n value=\"Text\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n Output(display_name=\"Text\", name=\"text\", method=\"fetch_content_text\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(https?:\\/\\/)?\" # optional protocol\n r\"(www\\.)?\" # optional www\n r\"([a-zA-Z0-9.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,})?\" # top-level domain\n r\"(:\\d+)?\" # optional port\n r\"(\\/[^\\s]*)?$\", # optional path\n re.IGNORECASE,\n )\n\n if not url_regex.match(string):\n msg = f\"Invalid URL: {string}\"\n raise ValueError(msg)\n\n return string\n\n def fetch_content(self) -> list[Data]:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n if self.format == \"Raw HTML\":\n loader = AsyncHtmlLoader(web_path=urls, encoding=\"utf-8\")\n else:\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(text=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n\n def fetch_content_text(self) -> Message:\n data = self.fetch_content()\n\n result_string = data_to_text(\"{text}\", data)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "format": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Output format", + "dynamic": false, + "info": "Output format. Use 'Text' to extract the text from the HTML or 'Raw HTML' for the raw HTML content.", + "name": "format", + "options": [ + "Text", + "Raw HTML" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Text" + }, + "urls": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "URLs", + "dynamic": false, + "info": "Enter one or more URLs, by clicking the '+' button.", + "input_types": [ + "Message" + ], + "list": true, + "load_from_db": false, + "name": "urls", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": [ + "https://raw.githubusercontent.com/langflow-ai/langflow/refs/heads/main/src/backend/base/langflow/components/helpers/extract_key.py", + "https://raw.githubusercontent.com/langflow-ai/langflow/refs/heads/main/src/backend/base/langflow/components/helpers/data_conditional_router.py", + "https://raw.githubusercontent.com/langflow-ai/langflow/refs/heads/main/src/backend/base/langflow/components/tools/calculator.py", + "https://raw.githubusercontent.com/langflow-ai/langflow/refs/heads/main/src/backend/base/langflow/components/tools/tavily_search.py", + "https://raw.githubusercontent.com/langflow-ai/langflow/refs/heads/main/src/backend/base/langflow/components/models/ollama.py" + ] + } + }, + "tool_mode": false + }, + "type": "URL" + }, + "dragging": false, + "height": 568, + "id": "URL-9b1oo", + "position": { + "x": 1837.4098708175009, + "y": 323.6213535047409 + }, + "positionAbsolute": { + "x": 1837.4098708175009, + "y": 323.6213535047409 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "URL-bqkBy", + "node": { + "base_classes": [ + "Data", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Fetch content from one or more URLs.", + "display_name": "URL", + "documentation": "", + "edited": false, + "field_order": [ + "urls", + "format" + ], + "frozen": false, + "icon": "layout-template", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "fetch_content", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "fetch_content_text", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import re\n\nfrom langchain_community.document_loaders import AsyncHtmlLoader, WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n name = \"URL\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, by clicking the '+' button.\",\n is_list=True,\n tool_mode=True,\n ),\n DropdownInput(\n name=\"format\",\n display_name=\"Output format\",\n info=\"Output format. Use 'Text' to extract the text from the HTML or 'Raw HTML' for the raw HTML content.\",\n options=[\"Text\", \"Raw HTML\"],\n value=\"Text\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n Output(display_name=\"Text\", name=\"text\", method=\"fetch_content_text\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(https?:\\/\\/)?\" # optional protocol\n r\"(www\\.)?\" # optional www\n r\"([a-zA-Z0-9.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,})?\" # top-level domain\n r\"(:\\d+)?\" # optional port\n r\"(\\/[^\\s]*)?$\", # optional path\n re.IGNORECASE,\n )\n\n if not url_regex.match(string):\n msg = f\"Invalid URL: {string}\"\n raise ValueError(msg)\n\n return string\n\n def fetch_content(self) -> list[Data]:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n if self.format == \"Raw HTML\":\n loader = AsyncHtmlLoader(web_path=urls, encoding=\"utf-8\")\n else:\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(text=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n\n def fetch_content_text(self) -> Message:\n data = self.fetch_content()\n\n result_string = data_to_text(\"{text}\", data)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "format": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Output format", + "dynamic": false, + "info": "Output format. Use 'Text' to extract the text from the HTML or 'Raw HTML' for the raw HTML content.", + "name": "format", + "options": [ + "Text", + "Raw HTML" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Text" + }, + "urls": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "URLs", + "dynamic": false, + "info": "Enter one or more URLs, by clicking the '+' button.", + "input_types": [ + "Message" + ], + "list": true, + "load_from_db": false, + "name": "urls", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": [ + "https://raw.githubusercontent.com/langflow-ai/langflow/refs/heads/main/src/backend/base/langflow/components/custom_component/custom_component.py" + ] + } + }, + "tool_mode": false + }, + "type": "URL" + }, + "dragging": false, + "height": 368, + "id": "URL-bqkBy", + "position": { + "x": 1436.982480021523, + "y": 651.1409296825055 + }, + "positionAbsolute": { + "x": 1436.982480021523, + "y": 651.1409296825055 + }, + "selected": false, + "type": "genericNode", + "width": 320 + } + ], + "viewport": { + "x": -776.9383804523111, + "y": -4.900459222819279, + "zoom": 0.5322184854204348 + } + }, + "description": "Generates well-structured code for custom components following Langflow's specifications.", + "endpoint_name": null, + "icon": "SquareCode", + "id": "aabe02e5-255f-447a-8ec2-be6f43955a43", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "Custom Component Generator", + "tags": [ + "coding", + "web-scraping" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json b/src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json similarity index 86% rename from src/backend/base/langflow/initial_setup/starter_projects/Document QA.json rename to src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json index 2f76e096c..4c42cf6cf 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json @@ -2,64 +2,39 @@ "data": { "edges": [ { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-Emi4q", + "id": "ChatInput-1lWBj", "name": "message", "output_types": [ "Message" ] }, - "targetHandle": { - "fieldName": "Question", - "id": "Prompt-n8yRL", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-Emi4q{œdataTypeœ:œChatInputœ,œidœ:œChatInput-Emi4qœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-n8yRL{œfieldNameœ:œQuestionœ,œidœ:œPrompt-n8yRLœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-Emi4q", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-Emi4qœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-n8yRL", - "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-n8yRLœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-n8yRL", - "name": "prompt", - "output_types": [ - "Message" - ] - }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-1hwZ2", + "id": "OpenAIModel-HIx8w", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-n8yRL{œdataTypeœ:œPromptœ,œidœ:œPrompt-n8yRLœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-1hwZ2{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-1hwZ2œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-n8yRL", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-n8yRLœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-1hwZ2", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-1hwZ2œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-1lWBj{œdataTypeœ:œChatInputœ,œidœ:œChatInput-1lWBjœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-HIx8w{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-HIx8wœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-1lWBj", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-1lWBjœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-HIx8w", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-HIx8wœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-1hwZ2", + "id": "OpenAIModel-HIx8w", "name": "text_output", "output_types": [ "Message" @@ -67,52 +42,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-sD0lp", + "id": "ChatOutput-hKFON", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-1hwZ2{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-1hwZ2œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-sD0lp{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-sD0lpœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-1hwZ2", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-1hwZ2œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-sD0lp", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-sD0lpœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ParseData", - "id": "ParseData-qYLes", - "name": "text", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "Document", - "id": "Prompt-n8yRL", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ParseData-qYLes{œdataTypeœ:œParseDataœ,œidœ:œParseData-qYLesœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-n8yRL{œfieldNameœ:œDocumentœ,œidœ:œPrompt-n8yRLœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ParseData-qYLes", - "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-qYLesœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-n8yRL", - "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-n8yRLœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-HIx8w{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-HIx8wœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-hKFON{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-hKFONœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-HIx8w", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-HIx8wœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-hKFON", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-hKFONœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "File", - "id": "File-0oa6O", + "id": "File-dlDLp", "name": "data", "output_types": [ "Data" @@ -120,172 +68,77 @@ }, "targetHandle": { "fieldName": "data", - "id": "ParseData-qYLes", + "id": "ParseData-mIiSz", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-File-0oa6O{œdataTypeœ:œFileœ,œidœ:œFile-0oa6Oœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-qYLes{œfieldNameœ:œdataœ,œidœ:œParseData-qYLesœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "File-0oa6O", - "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-0oa6Oœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-qYLes", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-qYLesœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-File-dlDLp{œdataTypeœ:œFileœ,œidœ:œFile-dlDLpœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-mIiSz{œfieldNameœ:œdataœ,œidœ:œParseData-mIiSzœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "File-dlDLp", + "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-dlDLpœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-mIiSz", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-mIiSzœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + }, + { + "data": { + "sourceHandle": { + "dataType": "ParseData", + "id": "ParseData-mIiSz", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "Document", + "id": "Prompt-L5CiD", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ParseData-mIiSz{œdataTypeœ:œParseDataœ,œidœ:œParseData-mIiSzœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-L5CiD{œfieldNameœ:œDocumentœ,œidœ:œPrompt-L5CiDœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-mIiSz", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-mIiSzœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-L5CiD", + "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-L5CiDœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-L5CiD", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_message", + "id": "OpenAIModel-HIx8w", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-L5CiD{œdataTypeœ:œPromptœ,œidœ:œPrompt-L5CiDœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-HIx8w{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-HIx8wœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-L5CiD", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-L5CiDœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-HIx8w", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-HIx8wœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-n8yRL", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "Document", - "Question" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "edited": false, - "field_order": [ - "template" - ], - "frozen": false, - "icon": "prompts", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "Document": { - "advanced": false, - "display_name": "Document", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "Document", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "Question": { - "advanced": false, - "display_name": "Question", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "Question", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "Answer user's questions based on the document below:\n\n---\n\n{Document}\n\n---\n\nQuestion:\n{Question}\n\nAnswer:\n" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 517, - "id": "Prompt-n8yRL", - "position": { - "x": 637.3518652087848, - "y": 47.191730368560215 - }, - "positionAbsolute": { - "x": 637.3518652087848, - "y": 47.191730368560215 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, { "data": { "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", - "id": "ChatInput-Emi4q", + "id": "ChatInput-1lWBj", "node": { "base_classes": [ "Message" @@ -308,6 +161,7 @@ "frozen": false, "icon": "MessagesSquare", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -446,7 +300,7 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "" + "value": "What is this document is about?" }, "sender": { "advanced": true, @@ -548,25 +402,25 @@ "type": "ChatInput" }, "dragging": false, - "height": 309, - "id": "ChatInput-Emi4q", + "height": 234, + "id": "ChatInput-1lWBj", "position": { - "x": 50.08709924122684, - "y": 320.88186720121615 + "x": 516.7529480335185, + "y": 237.04967879541528 }, "positionAbsolute": { - "x": 50.08709924122684, - "y": 320.88186720121615 + "x": 516.7529480335185, + "y": 237.04967879541528 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Display a chat message in the Playground.", "display_name": "Chat Output", - "id": "ChatOutput-sD0lp", + "id": "ChatOutput-hKFON", "node": { "base_classes": [ "Message" @@ -580,15 +434,19 @@ "edited": false, "field_order": [ "input_value", - "store_message", + "should_store_message", "sender", "sender_name", "session_id", - "data_template" + "data_template", + "background_color", + "chat_icon", + "text_color" ], "frozen": false, "icon": "MessagesSquare", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -623,6 +481,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -644,6 +503,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -668,6 +528,7 @@ "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" }, "data_template": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Data Template", "dynamic": false, @@ -682,12 +543,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "{text}" }, "input_value": { + "_input_type": "MessageInput", "advanced": false, "display_name": "Text", "dynamic": false, @@ -708,7 +571,9 @@ "value": "" }, "sender": { + "_input_type": "DropdownInput", "advanced": true, + "combobox": false, "display_name": "Sender Type", "dynamic": false, "info": "Type of sender.", @@ -721,11 +586,13 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "Machine" }, "sender_name": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Sender Name", "dynamic": false, @@ -740,12 +607,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "AI" }, "session_id": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Session ID", "dynamic": false, @@ -760,6 +629,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -797,355 +667,37 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" } - } + }, + "tool_mode": false }, "type": "ChatOutput" }, "dragging": false, - "height": 309, - "id": "ChatOutput-sD0lp", + "height": 234, + "id": "ChatOutput-hKFON", "position": { - "x": 1831.1359796346408, - "y": 139.5174517327903 + "x": 1631.3766926569258, + "y": 136.66509468115308 }, "positionAbsolute": { - "x": 1831.1359796346408, - "y": 139.5174517327903 + "x": 1631.3766926569258, + "y": 136.66509468115308 }, "selected": false, "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "id": "OpenAIModel-1hwZ2", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 623, - "id": "OpenAIModel-1hwZ2", - "position": { - "x": 1264.0039093582332, - "y": -67.93731748926709 - }, - "positionAbsolute": { - "x": 1264.0039093582332, - "y": -67.93731748926709 - }, - "selected": false, - "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Convert Data into plain text following a specified template.", "display_name": "Parse Data", - "id": "ParseData-qYLes", + "id": "ParseData-mIiSz", "node": { "base_classes": [ "Message" @@ -1165,6 +717,7 @@ "frozen": false, "icon": "braces", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -1262,25 +815,427 @@ "type": "ParseData" }, "dragging": false, - "height": 385, - "id": "ParseData-qYLes", + "height": 302, + "id": "ParseData-mIiSz", "position": { - "x": 87.26129917199853, - "y": -181.46350622708565 + "x": 514.8054600415829, + "y": -117.1921617826383 }, "positionAbsolute": { - "x": 87.26129917199853, - "y": -181.46350622708565 + "x": 514.8054600415829, + "y": -117.1921617826383 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "A generic file loader.", - "display_name": "File", - "id": "File-0oa6O", + "id": "note-Tz3ZY", + "node": { + "description": "## Get Your OpenAI API Key\n\n**Steps**:\n\n1. **Visit** [OpenAI's API Key Page](https://platform.openai.com/api-keys).\n\n2. **Log In/Sign Up**:\n - Log in or create a new OpenAI account.\n\n3. **Generate API Key**:\n - Click \"Create New Secret Key\" to obtain your key.\n\n4. **Store Your Key Securely**:\n - Note it down as it will only display once.\n\n5. **Enter API Key**:\n - Input your key in the OpenAI API Key field within the component setup.\n\nKeep your key safe and manage it responsibly!", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "rose" + } + }, + "type": "note" + }, + "dragging": true, + "height": 325, + "id": "note-Tz3ZY", + "position": { + "x": 1253.2038187140245, + "y": -421.5721019678553 + }, + "positionAbsolute": { + "x": 1253.2038187140245, + "y": -421.5721019678553 + }, + "selected": false, + "type": "noteNode", + "width": 325 + }, + { + "data": { + "id": "OpenAIModel-HIx8w", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-HIx8w", + "position": { + "x": 1259.2100978002586, + "y": -88.15692253090975 + }, + "positionAbsolute": { + "x": 1259.2100978002586, + "y": -88.15692253090975 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-XGIUa", + "node": { + "description": "# Document Q&A\n\n**Purpose:**\nThis flow leverages a language model to answer questions based on content from a loaded document. It's ideal for obtaining quick insights from PDFs or other text files by asking direct questions.\n\n**Components**:\n1. **File Component**: Loads and processes your document in supported formats.\n2. **Parse Data**: Converts the loaded document into text using a specified template for consistent processing.\n3. **Prompt Component**: Forms a structured query by combining the parsed document content with user questions.\n4. **OpenAI Model**: Engages OpenAI's language model to generate responses to queries based on the document context.\n5. **Chat Input/Output**: Facilitates user queries and displays AI-generated answers seamlessly.\n\n**Steps to Use**:\n1. **Upload Document**: Use the \"File\" component to upload a document or text file you want to query.\n2. **Enter Question**: Through the \"Chat Input\" field, type your question related to the document content.\n3. **Run the Flow**: Activate the flow to process the input and generate an answer using the OpenAI model.\n4. **View Response**: Read the generated answer in the \"Chat Output\" field for immediate insights.\n\n**Benefits**:\n- Simplifies the process of extracting information from documents.\n- Provides a user-friendly interface for interactive document exploration using AI.\n", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 452, + "id": "note-XGIUa", + "position": { + "x": -338.7070086205371, + "y": -177.11912020709357 + }, + "positionAbsolute": { + "x": -338.7070086205371, + "y": -177.11912020709357 + }, + "resizing": false, + "selected": false, + "style": { + "height": 452, + "width": 469 + }, + "type": "noteNode", + "width": 469 + }, + { + "data": { + "id": "File-dlDLp", "node": { "base_classes": [ "Data" @@ -1288,13 +1243,15 @@ "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "A generic file loader.", + "description": "Load a file to be used in your project.", "display_name": "File", "documentation": "", "edited": false, "field_order": [ "path", - "silent_errors" + "silent_errors", + "use_multithreading", + "concurrency_multithreading" ], "frozen": false, "icon": "file-text", @@ -1352,6 +1309,7 @@ "value": 4 }, "path": { + "_input_type": "FileInput", "advanced": false, "display_name": "Path", "dynamic": false, @@ -1376,7 +1334,7 @@ "tsx", "zip" ], - "file_path": "049e2133-b45d-44a3-906a-1e8be93d9d7b/Prompt Engineering Guide 3ff66c517bff423c863bbb1c0eb21be8.md", + "file_path": "", "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx, zip", "list": false, "name": "path", @@ -1389,6 +1347,7 @@ "value": "" }, "silent_errors": { + "_input_type": "BoolInput", "advanced": true, "display_name": "Silent Errors", "dynamic": false, @@ -1419,41 +1378,171 @@ "type": "bool", "value": false } - } + }, + "tool_mode": false }, "type": "File" }, "dragging": false, - "height": 301, - "id": "File-0oa6O", + "height": 232, + "id": "File-dlDLp", "position": { - "x": -462.90407701896845, - "y": -316.82165433756165 + "x": 155.39382083637838, + "y": -82.32805525710685 }, "positionAbsolute": { - "x": -462.90407701896845, - "y": -316.82165433756165 + "x": 155.39382083637838, + "y": -82.32805525710685 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-L5CiD", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "Document" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "Document": { + "advanced": false, + "display_name": "Document", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "Document", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "Answer user's questions based on the document below:\n\n---\n\n{Document}\n\n---\n\nQuestion:" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 347, + "id": "Prompt-L5CiD", + "position": { + "x": 895.1947781377585, + "y": -59.89409263992732 + }, + "positionAbsolute": { + "x": 895.1947781377585, + "y": -59.89409263992732 + }, + "selected": false, + "type": "genericNode", + "width": 320 } ], "viewport": { - "x": 338.5057346133326, - "y": 271.3577975536086, - "zoom": 0.36856730432277524 + "x": 262.21464656923195, + "y": 450.3754323717522, + "zoom": 0.5739369419687381 } }, - "description": "This flow integrates PDF reading with a language model to answer document-specific questions. Ideal for small-scale texts, it facilitates direct queries with immediate insights.", + "description": "Integrates PDF reading with a language model to answer document-specific questions. Ideal for small-scale texts, it facilitates direct queries with immediate insights.", "endpoint_name": null, - "icon": "FileText", - "id": "6fb449a7-563c-446e-82d2-36f3defb9a48", + "icon": "FileQuestion", + "id": "febba2f9-69b3-484b-8aef-65626810ec8a", "is_component": false, - "last_tested_version": "1.0.9", - "name": "Document QA", + "last_tested_version": "1.0.19.post2", + "name": "Document Q&A", "tags": [ - "chatbots", + "rag", + "q-a", "openai" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json b/src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json new file mode 100644 index 000000000..7a0fa2299 --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json @@ -0,0 +1,1605 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "StructuredOutputComponent", + "id": "StructuredOutputComponent-2koen", + "name": "structured_output", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "data", + "id": "ParseData-qwHwN", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-StructuredOutputComponent-2koen{œdataTypeœ:œStructuredOutputComponentœ,œidœ:œStructuredOutputComponent-2koenœ,œnameœ:œstructured_outputœ,œoutput_typesœ:[œDataœ]}-ParseData-qwHwN{œfieldNameœ:œdataœ,œidœ:œParseData-qwHwNœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "StructuredOutputComponent-2koen", + "sourceHandle": "{œdataTypeœ: œStructuredOutputComponentœ, œidœ: œStructuredOutputComponent-2koenœ, œnameœ: œstructured_outputœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-qwHwN", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-qwHwNœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ParseData", + "id": "ParseData-qwHwN", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-pZKpN", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ParseData-qwHwN{œdataTypeœ:œParseDataœ,œidœ:œParseData-qwHwNœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-pZKpN{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-pZKpNœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ParseData-qwHwN", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-qwHwNœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-pZKpN", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-pZKpNœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-9oYd2", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "StructuredOutputComponent-2koen", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-9oYd2{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-9oYd2œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-StructuredOutputComponent-2koen{œfieldNameœ:œinput_valueœ,œidœ:œStructuredOutputComponent-2koenœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-9oYd2", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-9oYd2œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "StructuredOutputComponent-2koen", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œStructuredOutputComponent-2koenœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-9oYd2", + "name": "model_output", + "output_types": [ + "LanguageModel" + ] + }, + "targetHandle": { + "fieldName": "llm", + "id": "StructuredOutputComponent-2koen", + "inputTypes": [ + "LanguageModel" + ], + "type": "other" + } + }, + "id": "reactflow__edge-OpenAIModel-9oYd2{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-9oYd2œ,œnameœ:œmodel_outputœ,œoutput_typesœ:[œLanguageModelœ]}-StructuredOutputComponent-2koen{œfieldNameœ:œllmœ,œidœ:œStructuredOutputComponent-2koenœ,œinputTypesœ:[œLanguageModelœ],œtypeœ:œotherœ}", + "source": "OpenAIModel-9oYd2", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-9oYd2œ, œnameœ: œmodel_outputœ, œoutput_typesœ: [œLanguageModelœ]}", + "target": "StructuredOutputComponent-2koen", + "targetHandle": "{œfieldNameœ: œllmœ, œidœ: œStructuredOutputComponent-2koenœ, œinputTypesœ: [œLanguageModelœ], œtypeœ: œotherœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-G7si2", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-9oYd2", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-G7si2{œdataTypeœ:œChatInputœ,œidœ:œChatInput-G7si2œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-9oYd2{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-9oYd2œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-G7si2", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-G7si2œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-9oYd2", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-9oYd2œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-ySGe4", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_message", + "id": "OpenAIModel-9oYd2", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-ySGe4{œdataTypeœ:œPromptœ,œidœ:œPrompt-ySGe4œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-9oYd2{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-9oYd2œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-ySGe4", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-ySGe4œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-9oYd2", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-9oYd2œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "id": "ChatInput-G7si2", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-G7si2", + "position": { + "x": 1258.8272095125978, + "y": 367.0048451335054 + }, + "positionAbsolute": { + "x": 1258.8272095125978, + "y": 367.0048451335054 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-pZKpN", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-pZKpN", + "position": { + "x": 2742.72534045604, + "y": 681.9098282545469 + }, + "positionAbsolute": { + "x": 2742.72534045604, + "y": 681.9098282545469 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-pSMKi", + "node": { + "description": "# Image Sentiment Analysis\nWelcome to the Image Sentiment Classifier - an AI tool for quick image sentiment analysis!\n\n## Instructions\n\n1. **Prepare Your Image**\n - Image should be clear and visible\n\n2. **Upload Options**\n - Open the Playground\n - Click file attachment icon\n - Or drag and drop into playground\n\n3. **Wait for Analysis**\n - System will process the image\n - Uses zero-shot learning\n - Classification happens automatically\n\n4. **Review Results**\n - Get classification: Positive/Negative/Neutral\n - Review confidence level\n - Check reasoning if provided\n\n5. **Expected Classifications**\n - Positive: Happy scenes, smiles, celebrations\n - Negative: Sad scenes, problems, conflicts\n - Neutral: Objects, landscapes, neutral scenes\n\nRemember: The clearer the image, the more accurate the classification! 📸✨", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 583, + "id": "note-pSMKi", + "position": { + "x": 791.7294511578832, + "y": 340.1333942936967 + }, + "positionAbsolute": { + "x": 791.7294511578832, + "y": 340.1333942936967 + }, + "resizing": false, + "selected": false, + "style": { + "height": 583, + "width": 436 + }, + "type": "noteNode", + "width": 436 + }, + { + "data": { + "description": "Transforms LLM responses into **structured data formats**. Ideal for extracting specific information or creating consistent outputs.", + "display_name": "Structured Output", + "id": "StructuredOutputComponent-2koen", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Transforms LLM responses into **structured data formats**. Ideal for extracting specific information or creating consistent outputs.", + "display_name": "Structured Output", + "documentation": "", + "edited": false, + "field_order": [ + "llm", + "input_value", + "schema_name", + "output_schema", + "multiple" + ], + "frozen": false, + "icon": "braces", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Structured Output", + "method": "build_structured_output", + "name": "structured_output", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from typing import cast\n\nfrom pydantic import BaseModel, Field, create_model\n\nfrom langflow.base.models.chat_result import get_chat_result\nfrom langflow.custom import Component\nfrom langflow.field_typing.constants import LanguageModel\nfrom langflow.helpers.base_model import build_model_from_schema\nfrom langflow.io import BoolInput, HandleInput, MessageTextInput, Output, StrInput, TableInput\nfrom langflow.schema.data import Data\n\n\nclass StructuredOutputComponent(Component):\n display_name = \"Structured Output\"\n description = (\n \"Transforms LLM responses into **structured data formats**. Ideal for extracting specific information \"\n \"or creating consistent outputs.\"\n )\n icon = \"braces\"\n\n inputs = [\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"The language model to use to generate the structured output.\",\n input_types=[\"LanguageModel\"],\n ),\n MessageTextInput(name=\"input_value\", display_name=\"Input message\"),\n StrInput(\n name=\"schema_name\",\n display_name=\"Schema Name\",\n info=\"Provide a name for the output data schema.\",\n ),\n TableInput(\n name=\"output_schema\",\n display_name=\"Output Schema\",\n info=\"Define the structure and data types for the model's output.\",\n table_schema=[\n {\n \"name\": \"name\",\n \"display_name\": \"Name\",\n \"type\": \"str\",\n \"description\": \"Specify the name of the output field.\",\n },\n {\n \"name\": \"description\",\n \"display_name\": \"Description\",\n \"type\": \"str\",\n \"description\": \"Describe the purpose of the output field.\",\n },\n {\n \"name\": \"type\",\n \"display_name\": \"Type\",\n \"type\": \"str\",\n \"description\": (\n \"Indicate the data type of the output field \" \"(e.g., str, int, float, bool, list, dict).\"\n ),\n \"default\": \"text\",\n },\n {\n \"name\": \"multiple\",\n \"display_name\": \"Multiple\",\n \"type\": \"boolean\",\n \"description\": \"Set to True if this output field should be a list of the specified type.\",\n \"default\": \"False\",\n },\n ],\n ),\n BoolInput(\n name=\"multiple\",\n display_name=\"Generate Multiple\",\n info=\"Set to True if the model should generate a list of outputs instead of a single output.\",\n ),\n ]\n\n outputs = [\n Output(name=\"structured_output\", display_name=\"Structured Output\", method=\"build_structured_output\"),\n ]\n\n def build_structured_output(self) -> Data:\n if not hasattr(self.llm, \"with_structured_output\"):\n msg = \"Language model does not support structured output.\"\n raise TypeError(msg)\n if not self.output_schema:\n msg = \"Output schema cannot be empty\"\n raise ValueError(msg)\n\n _output_model = build_model_from_schema(self.output_schema)\n if self.multiple:\n output_model = create_model(\n self.schema_name,\n objects=(list[_output_model], Field(description=f\"A list of {self.schema_name}.\")), # type: ignore[valid-type]\n )\n else:\n output_model = _output_model\n try:\n llm_with_structured_output = cast(LanguageModel, self.llm).with_structured_output(schema=output_model) # type: ignore[valid-type, attr-defined]\n\n except NotImplementedError as exc:\n msg = f\"{self.llm.__class__.__name__} does not support structured output.\"\n raise TypeError(msg) from exc\n config_dict = {\n \"run_name\": self.display_name,\n \"project_name\": self.get_project_name(),\n \"callbacks\": self.get_langchain_callbacks(),\n }\n output = get_chat_result(runnable=llm_with_structured_output, input_value=self.input_value, config=config_dict)\n if isinstance(output, BaseModel):\n output_dict = output.model_dump()\n else:\n msg = f\"Output should be a Pydantic BaseModel, got {type(output)} ({output})\"\n raise TypeError(msg)\n return Data(data=output_dict)\n" + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input message", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "llm": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Language Model", + "dynamic": false, + "info": "The language model to use to generate the structured output.", + "input_types": [ + "LanguageModel" + ], + "list": false, + "name": "llm", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "multiple": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Generate Multiple", + "dynamic": false, + "info": "Set to True if the model should generate a list of outputs instead of a single output.", + "list": false, + "name": "multiple", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "output_schema": { + "_input_type": "TableInput", + "advanced": false, + "display_name": "Output Schema", + "dynamic": false, + "info": "Define the structure and data types for the model's output.", + "is_list": true, + "load_from_db": false, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "table_schema": { + "columns": [ + { + "description": "Specify the name of the output field.", + "display_name": "Name", + "filterable": true, + "formatter": "text", + "name": "name", + "sortable": true, + "type": "text" + }, + { + "description": "Describe the purpose of the output field.", + "display_name": "Description", + "filterable": true, + "formatter": "text", + "name": "description", + "sortable": true, + "type": "text" + }, + { + "default": "text", + "description": "Indicate the data type of the output field (e.g., str, int, float, bool, list, dict).", + "display_name": "Type", + "filterable": true, + "formatter": "text", + "name": "type", + "sortable": true, + "type": "text" + }, + { + "default": "False", + "description": "Set to True if this output field should be a list of the specified type.", + "display_name": "Multiple", + "filterable": true, + "formatter": "text", + "name": "multiple", + "sortable": true, + "type": "boolean" + } + ] + }, + "title_case": false, + "trace_as_metadata": true, + "type": "table", + "value": [ + { + "description": "A Positive|Negative value that represents the image.", + "multiple": "False", + "name": "sentiment", + "type": "text" + }, + { + "description": "Brief Description of the image", + "multiple": "False", + "name": "description", + "type": "text" + } + ] + }, + "schema_name": { + "_input_type": "StrInput", + "advanced": false, + "display_name": "Schema Name", + "dynamic": false, + "info": "Provide a name for the output data schema.", + "list": false, + "load_from_db": false, + "name": "schema_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "image_classification" + } + }, + "tool_mode": false + }, + "type": "StructuredOutputComponent" + }, + "dragging": false, + "height": 541, + "id": "StructuredOutputComponent-2koen", + "position": { + "x": 2029.441019694193, + "y": 414.7974622616549 + }, + "positionAbsolute": { + "x": 2029.441019694193, + "y": 414.7974622616549 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "ParseData-qwHwN", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Convert Data into plain text following a specified template.", + "display_name": "Parse Data", + "documentation": "", + "edited": false, + "field_order": [ + "data", + "template", + "sep" + ], + "frozen": false, + "icon": "braces", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "parse_data", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n name = \"ParseData\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. \"\n \"It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "data": { + "_input_type": "DataInput", + "advanced": false, + "display_name": "Data", + "dynamic": false, + "info": "The data to convert to text.", + "input_types": [ + "Data" + ], + "list": false, + "name": "data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "sep": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Separator", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "sep", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "\n" + }, + "template": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Sentiment: {sentiment} \n\nDescription: {description} " + } + }, + "tool_mode": false + }, + "type": "ParseData" + }, + "dragging": false, + "height": 302, + "id": "ParseData-qwHwN", + "position": { + "x": 2389.490977317181, + "y": 646.9530981549555 + }, + "positionAbsolute": { + "x": 2389.490977317181, + "y": 646.9530981549555 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-9oYd2", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-9oYd2", + "position": { + "x": 1644.460882817477, + "y": 381.35290572159937 + }, + "positionAbsolute": { + "x": 1644.460882817477, + "y": 381.35290572159937 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-ySGe4", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "Classify the image into neutral, negative or positive. " + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-ySGe4", + "position": { + "x": 1262.0179832573751, + "y": 632.1360181124842 + }, + "positionAbsolute": { + "x": 1262.0179832573751, + "y": 632.1360181124842 + }, + "selected": false, + "type": "genericNode", + "width": 320 + } + ], + "viewport": { + "x": -767.6296307973882, + "y": -46.714664128928234, + "zoom": 0.798427315747602 + } + }, + "description": "Analyzes images and categorizes them as positive, negative, or neutral using zero-shot learning.", + "endpoint_name": null, + "icon": "Image", + "id": "0caf0da8-c233-4fc5-9df3-41bb58403885", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "Image Sentiment Analysis", + "tags": [ + "classification" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Sequential Agent.json b/src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json similarity index 52% rename from src/backend/base/langflow/initial_setup/starter_projects/Sequential Agent.json rename to src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json index bd1da7877..ffadf173c 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Sequential Agent.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json @@ -2,371 +2,288 @@ "data": { "edges": [ { + "animated": false, "className": "", "data": { "sourceHandle": { - "dataType": "SequentialCrewComponent", - "id": "SequentialCrewComponent-3dbbB", - "name": "output", + "dataType": "TextInput", + "id": "TextInput-VURDN", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "guidelines", + "id": "Prompt-vFWlB", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-TextInput-VURDN{œdataTypeœ:œTextInputœ,œidœ:œTextInput-VURDNœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-vFWlB{œfieldNameœ:œguidelinesœ,œidœ:œPrompt-vFWlBœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "TextInput-VURDN", + "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-VURDNœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-vFWlB", + "targetHandle": "{œfieldNameœ: œguidelinesœ, œidœ: œPrompt-vFWlBœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-e0DLW", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "post", + "id": "Prompt-0R6oq", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-e0DLW{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-e0DLWœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-Prompt-0R6oq{œfieldNameœ:œpostœ,œidœ:œPrompt-0R6oqœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-e0DLW", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-e0DLWœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-0R6oq", + "targetHandle": "{œfieldNameœ: œpostœ, œidœ: œPrompt-0R6oqœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-vFWlB", + "name": "prompt", "output_types": [ "Message" ] }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-nwCjg", + "id": "OpenAIModel-e0DLW", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-SequentialCrewComponent-3dbbB{œdataTypeœ:œSequentialCrewComponentœ,œidœ:œSequentialCrewComponent-3dbbBœ,œnameœ:œoutputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-nwCjg{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-nwCjgœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "SequentialCrewComponent-3dbbB", - "sourceHandle": "{œdataTypeœ: œSequentialCrewComponentœ, œidœ: œSequentialCrewComponent-3dbbBœ, œnameœ: œoutputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-nwCjg", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-nwCjgœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-vFWlB{œdataTypeœ:œPromptœ,œidœ:œPrompt-vFWlBœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-e0DLW{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-e0DLWœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-vFWlB", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-vFWlBœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": 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"reactflow__edge-OpenAIModel-XHfFc{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-XHfFcœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-Prompt-Z1RBN{œfieldNameœ:œimage_descriptionœ,œidœ:œPrompt-Z1RBNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-XHfFc", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-XHfFcœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-Z1RBN", + "targetHandle": "{œfieldNameœ: œimage_descriptionœ, œidœ: œPrompt-Z1RBNœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-Z1RBN", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-1gPMj", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-Z1RBN{œdataTypeœ:œPromptœ,œidœ:œPrompt-Z1RBNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-1gPMj{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1gPMjœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-Z1RBN", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-Z1RBNœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-1gPMj", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-1gPMjœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ { "data": { - "description": "Represents a group of agents, defining how they should collaborate and the tasks they should perform.", - "display_name": "Sequential Crew", - "id": "SequentialCrewComponent-3dbbB", + "id": "ChatInput-RN2Gt", "node": { "base_classes": [ "Message" @@ -374,523 +291,8 @@ "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "Represents a group of agents with tasks that are executed sequentially.", - "display_name": "Sequential Crew", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "verbose", - "memory", - "use_cache", - "max_rpm", - "share_crew", - "function_calling_llm", - "tasks" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "lf_version": "1.0.15", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Output", - "method": "build_output", - "name": "output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent, Crew, Process, Task\n\nfrom langflow.base.agents.crewai.crew import BaseCrewComponent\nfrom langflow.io import HandleInput\nfrom langflow.schema.message import Message\n\n\nclass SequentialCrewComponent(BaseCrewComponent):\n display_name: str = \"Sequential Crew\"\n description: str = \"Represents a group of agents with tasks that are executed sequentially.\"\n documentation: str = \"https://docs.crewai.com/how-to/Sequential/\"\n icon = \"CrewAI\"\n\n inputs = [\n *BaseCrewComponent._base_inputs,\n HandleInput(name=\"tasks\", display_name=\"Tasks\", input_types=[\"SequentialTask\"], is_list=True),\n ]\n\n def get_tasks_and_agents(self) -> tuple[list[Task], list[Agent]]:\n return self.tasks, [task.agent for task in self.tasks]\n\n def build_crew(self) -> Message:\n tasks, agents = self.get_tasks_and_agents()\n return Crew(\n agents=agents,\n tasks=tasks,\n process=Process.sequential,\n verbose=self.verbose,\n memory=self.memory,\n cache=self.use_cache,\n max_rpm=self.max_rpm,\n share_crew=self.share_crew,\n function_calling_llm=self.function_calling_llm,\n step_callback=self.get_step_callback(),\n task_callback=self.get_task_callback(),\n )\n" - }, - "function_calling_llm": { - "advanced": true, - "display_name": "Function Calling LLM", - "dynamic": false, - "info": "Turns the ReAct CrewAI agent into a function-calling agent", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "function_calling_llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "max_rpm": { - "advanced": true, - "display_name": "Max RPM", - "dynamic": false, - "info": "", - "list": false, - "name": "max_rpm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 100 - }, - "memory": { - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "share_crew": { - "advanced": true, - "display_name": "Share Crew", - "dynamic": false, - "info": "", - "list": false, - "name": "share_crew", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "tasks": { - "advanced": false, - "display_name": "Tasks", - "dynamic": false, - "info": "", - "input_types": [ - "SequentialTask" - ], - "list": true, - "name": "tasks", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "use_cache": { - "advanced": true, - "display_name": "Cache", - "dynamic": false, - "info": "", - "list": false, - "name": "use_cache", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 0 - } - } - }, - "type": "SequentialCrewComponent" - }, - "dragging": false, - "height": 284, - "id": "SequentialCrewComponent-3dbbB", - "position": { - "x": 1452.9740869513873, - "y": 217.5447804074488 - }, - "positionAbsolute": { - "x": 1452.9740869513873, - "y": 217.5447804074488 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-lQ5HF", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "lf_version": "1.0.15", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 601, - "id": "OpenAIModel-lQ5HF", - "position": { - "x": -2046.2369515771168, - "y": -396.97559934517443 - }, - "positionAbsolute": { - "x": -2046.2369515771168, - "y": -396.97559934517443 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "id": "ChatOutput-nwCjg", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", "documentation": "", "edited": false, "field_order": [ @@ -899,12 +301,15 @@ "sender", "sender_name", "session_id", - "data_template" + "files", + "background_color", + "chat_icon", + "text_color" ], "frozen": false, "icon": "MessagesSquare", "legacy": false, - "lf_version": "1.0.15", + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -981,38 +386,62 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" }, - "data_template": { + "files": { + "_input_type": "FileInput", "advanced": true, - "display_name": "Data Template", + "display_name": "Files", "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" ], - "list": false, - "load_from_db": false, - "name": "data_template", + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", "placeholder": "", "required": false, "show": true, "title_case": false, - "trace_as_input": true, "trace_as_metadata": true, - "type": "str", - "value": "{text}" + "type": "file", + "value": "" }, "input_value": { + "_input_type": "MultilineInput", "advanced": false, "display_name": "Text", "dynamic": false, - "info": "Message to be passed as output.", + "info": "Message to be passed as input.", "input_types": [ "Message" ], "list": false, "load_from_db": false, + "multiline": true, "name": "input_value", "placeholder": "", "required": false, @@ -1021,10 +450,12 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "" + "value": "Create a Langflow post" }, "sender": { + "_input_type": "DropdownInput", "advanced": true, + "combobox": false, "display_name": "Sender Type", "dynamic": false, "info": "Type of sender.", @@ -1039,9 +470,10 @@ "title_case": false, "trace_as_metadata": true, "type": "str", - "value": "Machine" + "value": "User" }, "sender_name": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Sender Name", "dynamic": false, @@ -1059,9 +491,10 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "AI" + "value": "User" }, "session_id": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Session ID", "dynamic": false, @@ -1082,6 +515,7 @@ "value": "" }, "should_store_message": { + "_input_type": "BoolInput", "advanced": true, "display_name": "Store Messages", "dynamic": false, @@ -1119,22 +553,174 @@ } } }, - "type": "ChatOutput" + "type": "ChatInput" }, "dragging": false, - "height": 298, - "id": "ChatOutput-nwCjg", + "height": 234, + "id": "ChatInput-RN2Gt", "position": { - "x": 1938.1856451557874, - "y": 227.4117341237682 + "x": 5183.264962599111, + "y": 3024.7129453201533 + }, + "positionAbsolute": { + "x": 5183.264962599111, + "y": 3024.7129453201533 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "id": "TextInput-6QUGr", + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-vFWlB", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "context", + "guidelines" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "context": { + "advanced": false, + "display_name": "context", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "context", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "guidelines": { + "advanced": false, + "display_name": "guidelines", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "guidelines", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "Based on the following context: \n\n{context} \n\n\nFollow these guidelines: \n\n{guidelines}" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 433, + "id": "Prompt-vFWlB", + "position": { + "x": 6013.179772864059, + "y": 2937.851014457363 + }, + "positionAbsolute": { + "x": 6013.179772864059, + "y": 2937.851014457363 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "TextInput-VURDN", "node": { "base_classes": [ "Message" @@ -1143,7 +729,7 @@ "conditional_paths": [], "custom_fields": {}, "description": "Get text inputs from the Playground.", - "display_name": "Topic", + "display_name": "Text Input", "documentation": "", "edited": false, "field_order": [ @@ -1151,7 +737,9 @@ ], "frozen": false, "icon": "type", - "lf_version": "1.0.15", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, "output_types": [], "outputs": [ { @@ -1185,9 +773,10 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n message = Message(\n text=self.input_value,\n )\n return message\n" + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n return Message(\n text=self.input_value,\n )\n" }, "input_value": { + "_input_type": "MultilineInput", "advanced": false, "display_name": "Text", "dynamic": false, @@ -1197,6 +786,151 @@ ], "list": false, "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Build a post for Instagram:\n\n1. **Opening Line**: Start with a powerful, intriguing question or statement to grab attention. Example: \"Ever wondered what it feels like to fly?\"\n\n2. **Main Content**: \n - Briefly share a personal story or insight related to the opening line. Keep it engaging and relatable.\n - Include valuable information or a lesson learned that your audience can benefit from.\n\n3. **Emojis**: Integrate emojis naturally within your text to emphasize key points and add a playful tone.\n\n4. **Call to Action (CTA)**: End with a clear CTA. Encourage your audience to share their thoughts, experiences, or to take a specific action. Example: \"Share your dream adventure in the comments! 🌍✈️\"\n\n5. **Hashtags**: Conclude with a selection of relevant hashtags. Place them at the end of your post to maintain focus on your message." + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 234, + "id": "TextInput-VURDN", + "position": { + "x": 5671.190001393486, + "y": 3422.371192525402 + }, + "positionAbsolute": { + "x": 5671.190001393486, + "y": 3422.371192525402 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-e0DLW", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, "name": "input_value", "placeholder": "", "required": false, @@ -1205,32 +939,235 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "Agile" + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 } - } + }, + "tool_mode": false }, - "type": "TextInput" + "type": "OpenAIModel" }, "dragging": false, - "height": 298, - "id": "TextInput-6QUGr", + "height": 543, + "id": "OpenAIModel-e0DLW", "position": { - "x": -2044.1039646921665, - "y": 291.77565151149054 + "x": 6427.182886017446, + "y": 2891.554378731566 }, "positionAbsolute": { - "x": -2044.1039646921665, - "y": 291.77565151149054 + "x": 6427.182886017446, + "y": 2891.554378731566 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-GOdlL", + "id": "Prompt-0R6oq", "node": { "base_classes": [ "Message" @@ -1239,7 +1176,7 @@ "conditional_paths": [], "custom_fields": { "template": [ - "topic" + "post" ] }, "description": "Create a prompt template with dynamic variables.", @@ -1252,7 +1189,7 @@ "frozen": false, "icon": "prompts", "legacy": false, - "lf_version": "1.0.15", + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -1289,25 +1226,9 @@ "type": "code", "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, - "template": { + "post": { "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "Topic: {topic}\n\nBuild a document about this document." - }, - "topic": { - "advanced": false, - "display_name": "topic", + "display_name": "post", "dynamic": false, "field_type": "str", "fileTypes": [], @@ -1320,69 +1241,90 @@ "list": false, "load_from_db": false, "multiline": true, - "name": "topic", - "password": false, + "name": "post", "placeholder": "", "required": false, "show": true, "title_case": false, "type": "str", "value": "" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "Based on the following post: \n\n{post} \n\nCraft a compelling prompt for image generator involving a blend of specificity, creativity, and clarity. Begin with a clear, concise description of the subject or scene you envision, incorporating specific details such as the setting, mood, and any key elements that are crucial to your vision. It's important to use descriptive language that conveys not just the visual aspects but also the emotional tone or atmosphere you wish to capture. Modifiers that specify the style, technique, or artistic influences can greatly enhance the prompt, guiding the AI to produce results that align closely with your expectations. Additionally, consider including any particular textures, lighting styles, or perspectives that will help refine the image to your liking. The goal is to provide Leonardo AI with a well-rounded, detailed description that leaves little room for ambiguity, enabling it to generate an image that closely matches your request.\n\nA good prompt should read like a brief to an artist, containing all the necessary information but leaving enough creative freedom for the AI to work effectively. It's a delicate balance between being overly prescriptive and too vague. The inclusion of what to avoid, using negative prompts, can also be helpful in steering the AI away from undesired outcomes. Remember, the effectiveness of a prompt often improves with experimentation and iteration, refining your approach based on the results you receive.\n\nExample 1: \"Create a digital painting of a serene lakeside at dusk, reflecting the vibrant hues of the sunset. The scene should be framed by weeping willows, with a lone wooden rowboat gently bobbing on the water's surface. Aim for a realistic style with a touch of impressionism, focusing on the interplay of light and shadow.\"\n\nExample 2: \"Illustrate a bustling medieval marketplace scene, vibrant and full of life, set within a walled city. Include diverse merchants, from a blacksmith to a spice trader, and townsfolk in period attire. The artwork should capture the dynamic energy of the market, with attention to historical accuracy and rich, earthy colors. Opt for a detailed, digital illustration style that brings out the textures of fabrics, metals, and natural elements.\"" } - } + }, + "tool_mode": false }, "type": "Prompt" }, "dragging": false, - "height": 412, - "id": "Prompt-GOdlL", + "height": 347, + "id": "Prompt-0R6oq", "position": { - "x": -1154.4124217561132, - "y": 813.2475923059123 + "x": 6786.650693383261, + "y": 3042.4668667721307 }, "positionAbsolute": { - "x": -1154.4124217561132, - "y": 813.2475923059123 + "x": 6786.650693383261, + "y": 3042.4668667721307 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-824D7", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-1gPMj", "node": { "base_classes": [ "Message" ], "beta": false, "conditional_paths": [], - "custom_fields": { - "template": [ - "topic" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", "documentation": "", "edited": false, "field_order": [ - "template" + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" ], "frozen": false, - "icon": "prompts", + "icon": "MessagesSquare", "legacy": false, - "lf_version": "1.0.15", "metadata": {}, "output_types": [], "outputs": [ { "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", + "display_name": "Message", + "method": "message_response", + "name": "message", "selected": "Message", "types": [ "Message" @@ -1393,6 +1335,50 @@ "pinned": false, "template": { "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, "code": { "advanced": true, "dynamic": true, @@ -1409,102 +1395,229 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" }, - "template": { - "advanced": false, - "display_name": "Template", + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", "dynamic": false, - "info": "", + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], "list": false, "load_from_db": false, - "name": "template", + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_input": true, - "type": "prompt", - "value": "Topic: {topic}\n\nRevise this document." + "trace_as_metadata": true, + "type": "str", + "value": "" }, - "topic": { - "advanced": false, - "display_name": "topic", + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "topic", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" } - } + }, + "tool_mode": false }, - "type": "Prompt" + "type": "ChatOutput" }, "dragging": false, - "height": 412, - "id": "Prompt-824D7", + "height": 234, + "id": "ChatOutput-1gPMj", "position": { - "x": -369.56336473301, - "y": 790.2887357303061 + "x": 7980.617825443558, + "y": 3377.2219674389726 }, "positionAbsolute": { - "x": -369.56336473301, - "y": 790.2887357303061 + "x": 7980.617825443558, + "y": 3377.2219674389726 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-0vHob", + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "id": "Agent-9Wf58", "node": { "base_classes": [ "Message" ], "beta": false, "conditional_paths": [], - "custom_fields": { - "template": [ - "topic" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", "documentation": "", "edited": false, "field_order": [ - "template" + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" ], "frozen": false, - "icon": "prompts", + "icon": "bot", "legacy": false, - "lf_version": "1.0.15", "metadata": {}, "output_types": [], "outputs": [ { "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", + "display_name": "Response", + "method": "message_response", + "name": "response", "selected": "Message", "types": [ "Message" @@ -1515,6 +1628,92 @@ "pinned": false, "template": { "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Amazon Bedrock", + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, "code": { "advanced": true, "dynamic": true, @@ -1531,373 +1730,404 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix), display_name\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" }, - "template": { + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", "advanced": false, - "display_name": "Template", + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are a helpful AI assistant. Use the following information from a web search to answer the user's question. If the search results don't contain relevant information, say so and offer to help with something else.\n\n{input}" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", "dynamic": false, "info": "", "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, "load_from_db": false, + "multiline": true, "name": "template", "placeholder": "", "required": false, "show": true, "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "Topic: {topic}\n\nBuild a fun blog post about this topic." - }, - "topic": { - "advanced": false, - "display_name": "topic", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "topic", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 412, - "id": "Prompt-0vHob", - "position": { - "x": 383.48176594858205, - "y": 804.7835051646966 - }, - "positionAbsolute": { - "x": 383.48176594858205, - "y": 804.7835051646966 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "SequentialTaskAgentComponent-GWMA1", - "node": { - "base_classes": [ - "SequentialTask" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Creates a CrewAI Task and its associated Agent.", - "display_name": "Sequential Task Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "agent_kwargs", - "task_description", - "expected_output", - "async_execution", - "previous_task" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "lf_version": "1.0.15", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Sequential Task", - "method": "build_agent_and_task", - "name": "task_output", - "selected": "SequentialTask", - "types": [ - "SequentialTask" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "agent_kwargs": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Agent kwargs", - "dynamic": false, - "info": "Additional kwargs for the agent.", - "list": true, - "name": "agent_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "allow_code_execution": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Allow Code Execution", - "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "async_execution": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Async Execution", - "dynamic": false, - "info": "Boolean flag indicating asynchronous task execution.", - "list": false, - "name": "async_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "backstory": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "backstory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "Research has always been your thing. You can quickly find things on the web because of your skills." - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent, Task\n\nfrom langflow.base.agents.crewai.tasks import SequentialTask\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass SequentialTaskAgentComponent(Component):\n display_name = \"Sequential Task Agent\"\n description = \"Creates a CrewAI Task and its associated Agent.\"\n documentation = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n # Agent inputs\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(\n name=\"backstory\",\n display_name=\"Backstory\",\n info=\"The backstory of the agent.\",\n ),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agent's disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=False,\n advanced=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"agent_kwargs\",\n display_name=\"Agent kwargs\",\n info=\"Additional kwargs for the agent.\",\n is_list=True,\n advanced=True,\n ),\n # Task inputs\n MultilineInput(\n name=\"task_description\",\n display_name=\"Task Description\",\n info=\"Descriptive text detailing task's purpose and execution.\",\n ),\n MultilineInput(\n name=\"expected_output\",\n display_name=\"Expected Task Output\",\n info=\"Clear definition of expected task outcome.\",\n ),\n BoolInput(\n name=\"async_execution\",\n display_name=\"Async Execution\",\n value=False,\n advanced=True,\n info=\"Boolean flag indicating asynchronous task execution.\",\n ),\n # Chaining input\n HandleInput(\n name=\"previous_task\",\n display_name=\"Previous Task\",\n input_types=[\"SequentialTask\"],\n info=\"The previous task in the sequence (for chaining).\",\n required=False,\n ),\n ]\n\n outputs = [\n Output(\n display_name=\"Sequential Task\",\n name=\"task_output\",\n method=\"build_agent_and_task\",\n ),\n ]\n\n def build_agent_and_task(self) -> list[SequentialTask]:\n # Build the agent\n agent_kwargs = self.agent_kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **agent_kwargs,\n )\n\n # Build the task\n task = Task(\n description=self.task_description,\n expected_output=self.expected_output,\n agent=agent,\n async_execution=self.async_execution,\n )\n\n # If there's a previous task, create a list of tasks\n if self.previous_task:\n tasks = [*self.previous_task, task] if isinstance(self.previous_task, list) else [self.previous_task, task]\n else:\n tasks = [task]\n\n self.status = f\"Agent: {agent!r}\\nTask: {task!r}\"\n return tasks\n" - }, - "expected_output": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Expected Task Output", - "dynamic": false, - "info": "Clear definition of expected task outcome.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "expected_output", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Bullet points and small phrases about the research topic." - }, - "goal": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Goal", - "dynamic": false, - "info": "The objective of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Search Google to find information to complete the task." - }, - "llm": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "memory": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "Whether the agent should have memory or not", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "previous_task": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Previous Task", - "dynamic": false, - "info": "The previous task in the sequence (for chaining).", - "input_types": [ - "SequentialTask" - ], - "list": false, - "name": "previous_task", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "role": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Role", - "dynamic": false, - "info": "The role of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Researcher" - }, - "task_description": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Task Description", - "dynamic": false, - "info": "Descriptive text detailing task's purpose and execution.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "task_description", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" + "value": "{sender_name}: {text}" }, "tools": { "_input_type": "HandleInput", "advanced": false, "display_name": "Tools", "dynamic": false, - "info": "Tools at agent's disposal", + "info": "These are the tools that the agent can use to help with tasks.", "input_types": [ - "Tool" + "Tool", + "BaseTool", + "StructuredTool" ], "list": true, "name": "tools", @@ -1907,7 +2137,7 @@ "title_case": false, "trace_as_metadata": true, "type": "other", - "value": [] + "value": "" }, "verbose": { "_input_type": "BoolInput", @@ -1925,746 +2155,56 @@ "type": "bool", "value": true } - } + }, + "tool_mode": false }, - "type": "SequentialTaskAgentComponent" + "type": "Agent" }, "dragging": false, - "height": 810, - "id": "SequentialTaskAgentComponent-GWMA1", + "height": 650, + "id": "Agent-9Wf58", "position": { - "x": -742.6676461208307, - "y": -336.7987303380612 + "x": 5665.465212822881, + "y": 2760.0819124193113 }, "positionAbsolute": { - "x": -742.6676461208307, - "y": -336.7987303380612 + "x": 5665.465212822881, + "y": 2760.0819124193113 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "id": "SequentialTaskAgentComponent-5i4Wg", - "node": { - "base_classes": [ - "SequentialTask" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Creates a CrewAI Task and its associated Agent.", - "display_name": "Sequential Task Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "agent_kwargs", - "task_description", - "expected_output", - "async_execution", - "previous_task" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "lf_version": "1.0.15", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Sequential Task", - "method": "build_agent_and_task", - "name": "task_output", - "selected": "SequentialTask", - "types": [ - "SequentialTask" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "agent_kwargs": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Agent kwargs", - "dynamic": false, - "info": "Additional kwargs for the agent.", - "list": true, - "name": "agent_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "allow_code_execution": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Allow Code Execution", - "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "async_execution": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Async Execution", - "dynamic": false, - "info": "Boolean flag indicating asynchronous task execution.", - "list": false, - "name": "async_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "backstory": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "backstory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You are the editor of the most reputable journal in the world." - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent, Task\n\nfrom langflow.base.agents.crewai.tasks import SequentialTask\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass SequentialTaskAgentComponent(Component):\n display_name = \"Sequential Task Agent\"\n description = \"Creates a CrewAI Task and its associated Agent.\"\n documentation = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n # Agent inputs\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(\n name=\"backstory\",\n display_name=\"Backstory\",\n info=\"The backstory of the agent.\",\n ),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agent's disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=False,\n advanced=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"agent_kwargs\",\n display_name=\"Agent kwargs\",\n info=\"Additional kwargs for the agent.\",\n is_list=True,\n advanced=True,\n ),\n # Task inputs\n MultilineInput(\n name=\"task_description\",\n display_name=\"Task Description\",\n info=\"Descriptive text detailing task's purpose and execution.\",\n ),\n MultilineInput(\n name=\"expected_output\",\n display_name=\"Expected Task Output\",\n info=\"Clear definition of expected task outcome.\",\n ),\n BoolInput(\n name=\"async_execution\",\n display_name=\"Async Execution\",\n value=False,\n advanced=True,\n info=\"Boolean flag indicating asynchronous task execution.\",\n ),\n # Chaining input\n HandleInput(\n name=\"previous_task\",\n display_name=\"Previous Task\",\n input_types=[\"SequentialTask\"],\n info=\"The previous task in the sequence (for chaining).\",\n required=False,\n ),\n ]\n\n outputs = [\n Output(\n display_name=\"Sequential Task\",\n name=\"task_output\",\n method=\"build_agent_and_task\",\n ),\n ]\n\n def build_agent_and_task(self) -> list[SequentialTask]:\n # Build the agent\n agent_kwargs = self.agent_kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **agent_kwargs,\n )\n\n # Build the task\n task = Task(\n description=self.task_description,\n expected_output=self.expected_output,\n agent=agent,\n async_execution=self.async_execution,\n )\n\n # If there's a previous task, create a list of tasks\n if self.previous_task:\n tasks = [*self.previous_task, task] if isinstance(self.previous_task, list) else [self.previous_task, task]\n else:\n tasks = [task]\n\n self.status = f\"Agent: {agent!r}\\nTask: {task!r}\"\n return tasks\n" - }, - "expected_output": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Expected Task Output", - "dynamic": false, - "info": "Clear definition of expected task outcome.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "expected_output", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Small paragraphs and bullet points with the corrected content." - }, - "goal": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Goal", - "dynamic": false, - "info": "The objective of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You should edit the Information provided by the Researcher to make it more palatable and to not contain misleading information." - }, - "llm": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "memory": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "Whether the agent should have memory or not", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "previous_task": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Previous Task", - "dynamic": false, - "info": "The previous task in the sequence (for chaining).", - "input_types": [ - "SequentialTask" - ], - "list": false, - "name": "previous_task", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "role": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Role", - "dynamic": false, - "info": "The role of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Editor" - }, - "task_description": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Task Description", - "dynamic": false, - "info": "Descriptive text detailing task's purpose and execution.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "task_description", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "tools": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "Tools at agent's disposal", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": [] - }, - "verbose": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - } - } - }, - "type": "SequentialTaskAgentComponent" - }, - "dragging": false, - "height": 810, - "id": "SequentialTaskAgentComponent-5i4Wg", - "position": { - "x": 62.10105154443647, - "y": -336.82282969954827 - }, - "positionAbsolute": { - "x": 62.10105154443647, - "y": -336.82282969954827 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "SequentialTaskAgentComponent-TPEWE", - "node": { - "base_classes": [ - "SequentialTask" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Creates a CrewAI Task and its associated Agent.", - "display_name": "Sequential Task Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "agent_kwargs", - "task_description", - "expected_output", - "async_execution", - "previous_task" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "lf_version": "1.0.15", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Sequential Task", - "method": "build_agent_and_task", - "name": "task_output", - "selected": "SequentialTask", - "types": [ - "SequentialTask" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "agent_kwargs": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Agent kwargs", - "dynamic": false, - "info": "Additional kwargs for the agent.", - "list": true, - "name": "agent_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "allow_code_execution": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Allow Code Execution", - "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "async_execution": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Async Execution", - "dynamic": false, - "info": "Boolean flag indicating asynchronous task execution.", - "list": false, - "name": "async_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "backstory": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "backstory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Your formal occupation is Comedian-in-Chief. You write jokes, do standup comedy and write funny articles." - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent, Task\n\nfrom langflow.base.agents.crewai.tasks import SequentialTask\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass SequentialTaskAgentComponent(Component):\n display_name = \"Sequential Task Agent\"\n description = \"Creates a CrewAI Task and its associated Agent.\"\n documentation = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n # Agent inputs\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(\n name=\"backstory\",\n display_name=\"Backstory\",\n info=\"The backstory of the agent.\",\n ),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agent's disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=False,\n advanced=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"agent_kwargs\",\n display_name=\"Agent kwargs\",\n info=\"Additional kwargs for the agent.\",\n is_list=True,\n advanced=True,\n ),\n # Task inputs\n MultilineInput(\n name=\"task_description\",\n display_name=\"Task Description\",\n info=\"Descriptive text detailing task's purpose and execution.\",\n ),\n MultilineInput(\n name=\"expected_output\",\n display_name=\"Expected Task Output\",\n info=\"Clear definition of expected task outcome.\",\n ),\n BoolInput(\n name=\"async_execution\",\n display_name=\"Async Execution\",\n value=False,\n advanced=True,\n info=\"Boolean flag indicating asynchronous task execution.\",\n ),\n # Chaining input\n HandleInput(\n name=\"previous_task\",\n display_name=\"Previous Task\",\n input_types=[\"SequentialTask\"],\n info=\"The previous task in the sequence (for chaining).\",\n required=False,\n ),\n ]\n\n outputs = [\n Output(\n display_name=\"Sequential Task\",\n name=\"task_output\",\n method=\"build_agent_and_task\",\n ),\n ]\n\n def build_agent_and_task(self) -> list[SequentialTask]:\n # Build the agent\n agent_kwargs = self.agent_kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **agent_kwargs,\n )\n\n # Build the task\n task = Task(\n description=self.task_description,\n expected_output=self.expected_output,\n agent=agent,\n async_execution=self.async_execution,\n )\n\n # If there's a previous task, create a list of tasks\n if self.previous_task:\n tasks = [*self.previous_task, task] if isinstance(self.previous_task, list) else [self.previous_task, task]\n else:\n tasks = [task]\n\n self.status = f\"Agent: {agent!r}\\nTask: {task!r}\"\n return tasks\n" - }, - "expected_output": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Expected Task Output", - "dynamic": false, - "info": "Clear definition of expected task outcome.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "expected_output", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "A small blog about the topic." - }, - "goal": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Goal", - "dynamic": false, - "info": "The objective of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You write comedic content based on the information provided by the editor." - }, - "llm": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "memory": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "Whether the agent should have memory or not", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "previous_task": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Previous Task", - "dynamic": false, - "info": "The previous task in the sequence (for chaining).", - "input_types": [ - "SequentialTask" - ], - "list": false, - "name": "previous_task", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "role": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Role", - "dynamic": false, - "info": "The role of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Comedian" - }, - "task_description": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Task Description", - "dynamic": false, - "info": "Descriptive text detailing task's purpose and execution.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "task_description", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "tools": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "Tools at agent's disposal", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": [] - }, - "verbose": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - } - } - }, - "type": "SequentialTaskAgentComponent" - }, - "dragging": false, - "height": 810, - "id": "SequentialTaskAgentComponent-TPEWE", - "position": { - "x": 800.6536575540351, - "y": -345.48877618011403 - }, - "positionAbsolute": { - "x": 800.6536575540351, - "y": -345.48877618011403 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "YFinanceTool-Asoka", + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "id": "TavilyAISearch-AN1Hv", "node": { "base_classes": [ + "Data", "Tool" ], "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "Tool for interacting with Yahoo Finance News.", - "display_name": "Yahoo Finance News Tool", - "documentation": "", + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "documentation": "https://docs.tavily.com/", "edited": false, - "field_order": [], + "field_order": [ + "api_key", + "query", + "search_depth", + "topic", + "max_results", + "include_images", + "include_answer" + ], "frozen": false, - "lf_version": "1.0.15", + "icon": "TavilyIcon", + "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -2673,6 +2213,9 @@ "display_name": "Data", "method": "run_model", "name": "api_run_model", + "required_inputs": [ + "api_key" + ], "selected": "Data", "types": [ "Data" @@ -2683,7 +2226,10 @@ "cache": true, "display_name": "Tool", "method": "build_tool", - "name": "tool", + "name": "api_build_tool", + "required_inputs": [ + "api_key" + ], "selected": "Tool", "types": [ "Tool" @@ -2692,6 +2238,570 @@ } ], "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "Tavily API Key", + "dynamic": false, + "info": "Your Tavily API Key.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from enum import Enum\n\nimport httpx\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass TavilySearchDepth(Enum):\n BASIC = \"basic\"\n ADVANCED = \"advanced\"\n\n\nclass TavilySearchTopic(Enum):\n GENERAL = \"general\"\n NEWS = \"news\"\n\n\nclass TavilySearchSchema(BaseModel):\n query: str = Field(..., description=\"The search query you want to execute with Tavily.\")\n search_depth: TavilySearchDepth = Field(TavilySearchDepth.BASIC, description=\"The depth of the search.\")\n topic: TavilySearchTopic = Field(TavilySearchTopic.GENERAL, description=\"The category of the search.\")\n max_results: int = Field(5, description=\"The maximum number of search results to return.\")\n include_images: bool = Field(default=False, description=\"Include a list of query-related images in the response.\")\n include_answer: bool = Field(default=False, description=\"Include a short answer to original query.\")\n\n\nclass TavilySearchToolComponent(LCToolComponent):\n display_name = \"Tavily AI Search\"\n description = \"\"\"**Tavily AI** is a search engine optimized for LLMs and RAG, \\\n aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n\"\"\"\n icon = \"TavilyIcon\"\n name = \"TavilyAISearch\"\n documentation = \"https://docs.tavily.com/\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Tavily API Key\",\n required=True,\n info=\"Your Tavily API Key.\",\n ),\n MessageTextInput(\n name=\"query\",\n display_name=\"Search Query\",\n info=\"The search query you want to execute with Tavily.\",\n ),\n DropdownInput(\n name=\"search_depth\",\n display_name=\"Search Depth\",\n info=\"The depth of the search.\",\n options=list(TavilySearchDepth),\n value=TavilySearchDepth.ADVANCED,\n advanced=True,\n ),\n DropdownInput(\n name=\"topic\",\n display_name=\"Search Topic\",\n info=\"The category of the search.\",\n options=list(TavilySearchTopic),\n value=TavilySearchTopic.GENERAL,\n advanced=True,\n ),\n IntInput(\n name=\"max_results\",\n display_name=\"Max Results\",\n info=\"The maximum number of search results to return.\",\n value=5,\n advanced=True,\n ),\n BoolInput(\n name=\"include_images\",\n display_name=\"Include Images\",\n info=\"Include a list of query-related images in the response.\",\n value=True,\n advanced=True,\n ),\n BoolInput(\n name=\"include_answer\",\n display_name=\"Include Answer\",\n info=\"Include a short answer to original query.\",\n value=True,\n advanced=True,\n ),\n ]\n\n def run_model(self) -> list[Data]:\n # Convert string values to enum instances with validation\n try:\n search_depth_enum = (\n self.search_depth\n if isinstance(self.search_depth, TavilySearchDepth)\n else TavilySearchDepth(str(self.search_depth).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid search depth value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n try:\n topic_enum = (\n self.topic if isinstance(self.topic, TavilySearchTopic) else TavilySearchTopic(str(self.topic).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid topic value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n return self._tavily_search(\n self.query,\n search_depth=search_depth_enum,\n topic=topic_enum,\n max_results=self.max_results,\n include_images=self.include_images,\n include_answer=self.include_answer,\n )\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"tavily_search\",\n description=\"Perform a web search using the Tavily API.\",\n func=self._tavily_search,\n args_schema=TavilySearchSchema,\n )\n\n def _tavily_search(\n self,\n query: str,\n *,\n search_depth: TavilySearchDepth = TavilySearchDepth.BASIC,\n topic: TavilySearchTopic = TavilySearchTopic.GENERAL,\n max_results: int = 5,\n include_images: bool = False,\n include_answer: bool = False,\n ) -> list[Data]:\n # Validate enum values\n if not isinstance(search_depth, TavilySearchDepth):\n msg = f\"Invalid search_depth value: {search_depth}\"\n raise TypeError(msg)\n if not isinstance(topic, TavilySearchTopic):\n msg = f\"Invalid topic value: {topic}\"\n raise TypeError(msg)\n\n try:\n url = \"https://api.tavily.com/search\"\n headers = {\n \"content-type\": \"application/json\",\n \"accept\": \"application/json\",\n }\n payload = {\n \"api_key\": self.api_key,\n \"query\": query,\n \"search_depth\": search_depth.value,\n \"topic\": topic.value,\n \"max_results\": max_results,\n \"include_images\": include_images,\n \"include_answer\": include_answer,\n }\n\n with httpx.Client() as client:\n response = client.post(url, json=payload, headers=headers)\n\n response.raise_for_status()\n search_results = response.json()\n\n data_results = [\n Data(\n data={\n \"title\": result.get(\"title\"),\n \"url\": result.get(\"url\"),\n \"content\": result.get(\"content\"),\n \"score\": result.get(\"score\"),\n }\n )\n for result in search_results.get(\"results\", [])\n ]\n\n if include_answer and search_results.get(\"answer\"):\n data_results.insert(0, Data(data={\"answer\": search_results[\"answer\"]}))\n\n if include_images and search_results.get(\"images\"):\n data_results.append(Data(data={\"images\": search_results[\"images\"]}))\n\n self.status = data_results # type: ignore[assignment]\n\n except httpx.HTTPStatusError as e:\n error_message = f\"HTTP error: {e.response.status_code} - {e.response.text}\"\n logger.debug(error_message)\n self.status = error_message\n raise ToolException(error_message) from e\n except Exception as e:\n error_message = f\"Unexpected error: {e}\"\n logger.opt(exception=True).debug(\"Error running Tavily Search\")\n self.status = error_message\n raise ToolException(error_message) from e\n return data_results\n" + }, + "include_answer": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Answer", + "dynamic": false, + "info": "Include a short answer to original query.", + "list": false, + "name": "include_answer", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "include_images": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Images", + "dynamic": false, + "info": "Include a list of query-related images in the response.", + "list": false, + "name": "include_images", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "max_results": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Results", + "dynamic": false, + "info": "The maximum number of search results to return.", + "list": false, + "name": "max_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 5 + }, + "query": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Search Query", + "dynamic": false, + "info": "The search query you want to execute with Tavily.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "search_depth": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Depth", + "dynamic": false, + "info": "The depth of the search.", + "load_from_db": false, + "name": "search_depth", + "options": [ + "basic", + "advanced" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "advanced" + }, + "topic": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Topic", + "dynamic": false, + "info": "The category of the search.", + "load_from_db": false, + "name": "topic", + "options": [ + "general", + "news" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "general" + } + }, + "tool_mode": false + }, + "type": "TavilyAISearch" + }, + "dragging": false, + "height": 481, + "id": "TavilyAISearch-AN1Hv", + "position": { + "x": 5178.005987190226, + "y": 3496.7214582697484 + }, + "positionAbsolute": { + "x": 5178.005987190226, + "y": 3496.7214582697484 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-XHfFc", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 543, + "id": "OpenAIModel-XHfFc", + "position": { + "x": 7211.829041441037, + "y": 2938.1023670807563 + }, + "positionAbsolute": { + "x": 7211.829041441037, + "y": 2938.1023670807563 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-Z1RBN", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "post", + "image_description" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, "template": { "_type": "Component", "code": { @@ -2710,65 +2820,255 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import cast\n\nfrom langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Data, Tool\nfrom langflow.inputs.inputs import MessageTextInput\nfrom langflow.template.field.base import Output\n\n\nclass YfinanceToolComponent(LCToolComponent):\n display_name = \"Yahoo Finance News Tool\"\n description = \"Tool for interacting with Yahoo Finance News.\"\n name = \"YFinanceTool\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Query\",\n info=\"Input should be a company ticker. For example, AAPL for Apple, MSFT for Microsoft.\",\n )\n ]\n\n outputs = [\n Output(name=\"api_run_model\", display_name=\"Data\", method=\"run_model\"),\n # Keep this for backwards compatibility\n Output(name=\"tool\", display_name=\"Tool\", method=\"build_tool\"),\n ]\n\n def build_tool(self) -> Tool:\n return cast(Tool, YahooFinanceNewsTool())\n\n def run_model(self) -> Data:\n tool = self.build_tool()\n return tool.run(self.input_value)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, - "input_value": { - "_input_type": "MessageTextInput", + "image_description": { "advanced": false, - "display_name": "Query", + "display_name": "image_description", "dynamic": false, - "info": "Input should be a company ticker. For example, AAPL for Apple, MSFT for Microsoft.", + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", "input_types": [ - "Message" + "Message", + "Text" ], "list": false, "load_from_db": false, - "name": "input_value", + "multiline": true, + "name": "image_description", "placeholder": "", "required": false, "show": true, "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, "type": "str", "value": "" + }, + "post": { + "advanced": false, + "display_name": "post", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "post", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "{post}\n \n\n{image_description} " } - } + }, + "tool_mode": false }, - "type": "YFinanceTool" + "type": "Prompt" }, "dragging": false, - "height": 216, - "id": "YFinanceTool-Asoka", + "height": 433, + "id": "Prompt-Z1RBN", "position": { - "x": -1395.322640611045, - "y": -397.3732940326163 + "x": 7613.837241084599, + "y": 3139.8282595890087 }, "positionAbsolute": { - "x": -1395.322640611045, - "y": -397.3732940326163 + "x": 7613.837241084599, + "y": 3139.8282595890087 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 + }, + { + "data": { + "id": "note-Jr7lC", + "node": { + "description": "# Instagram Copywriter \n\nWelcome to the Instagram Copywriter! This flow helps you create compelling Instagram posts with AI-generated content and image prompts.\n\n## Instructions\n1. Enter Your Topic\n - In the Chat Input, enter a brief description of the topic you want to post about.\n - Example: \"Create a post about meditation and its benefits\"\n\n2. Review the Generated Content\n - The flow will use AI to research your topic and generate a formatted Instagram post.\n - The post will include an opening line, main content, emojis, a call-to-action, and hashtags.\n\n3. Check the Image Prompt\n - The flow will also generate a detailed image prompt based on your post content.\n - This prompt can be used with image generation tools to create a matching visual.\n\n4. Copy the Final Output\n - The Chat Output will display the complete Instagram post text followed by the image generation prompt.\n - Copy this output to use in your Instagram content creation process.\n\n5. Refine if Needed\n - If you're not satisfied with the result, you can adjust the input or modify the OpenAI model settings for different outputs.\n\nRemember: Keep your initial topic input clear and concise for best results! 🎨✨", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "amber" + } + }, + "type": "note" + }, + "dragging": false, + "height": 648, + "id": "note-Jr7lC", + "position": { + "x": 4492.051129290571, + "y": 2746.336592524463 + }, + "positionAbsolute": { + "x": 4560.051129290571, + "y": 2746.336592524463 + }, + "resizing": false, + "selected": false, + "style": { + "height": 648, + "width": 554 + }, + "type": "noteNode", + "width": 554 + }, + { + "data": { + "id": "note-tWoba", + "node": { + "description": "**Text Input (Guidelines Prompt)**\n - NOTE: \"Contains Instagram post formatting rules. Don't modify this component as it maintains format consistency.\"\n - Maintains fixed guidelines for:\n * Opening structure\n * Main content\n * Emoji usage\n * Call to Action (CTA)\n * Hashtags\n\n4. **First Prompt + OpenAI Sequence**\n - NOTE: \"Generates initial post content following Instagram guidelines\"\n - Settings:\n * Temperature: 0.7 (good balance between creativity and consistency)\n * Input: Receives research context\n * Output: Generates formatted post text\n\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-tWoba", + "position": { + "x": 5667.476249937603, + "y": 3644.9055828357396 + }, + "positionAbsolute": { + "x": 5667.476249937603, + "y": 3644.9055828357396 + }, + "resizing": false, + "selected": false, + "type": "noteNode", + "width": 325 + }, + { + "data": { + "id": "note-9ABdX", + "node": { + "description": "**Second Prompt + OpenAI Sequence**\n - NOTE: \"Transforms the generated post into a prompt for image generation\"\n - Settings:\n * Temperature: 0.7\n * Input: Receives generated post\n * Output: Creates detailed description for image generation\n\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-9ABdX", + "position": { + "x": 6786.375917286389, + "y": 3393.8522072000146 + }, + "positionAbsolute": { + "x": 6786.375917286389, + "y": 3393.8522072000146 + }, + "selected": false, + "type": "noteNode", + "width": 325 + }, + { + "data": { + "id": "note-aplGD", + "node": { + "description": "**Final Prompt**\n - NOTE: \"Combines Instagram post with image prompt in a final format\"\n - Structure:\n * First part: Complete Instagram post\n * Second part: Image generation prompt\n * Separator: Uses \"**Prompt:**\" to divide sections\n\n7. **Chat Output (Final Output)**\n - NOTE: \"Presents the combined final result that can be copied and used directly\"\n\nGENERAL USAGE TIPS:\n- Keep initial inputs clear and specific\n- Don't modify pre-defined Instagram guidelines\n- If style adjustments are needed, only modify the OpenAI models' temperature\n- Verify all connections are correct before running\n- Final result will always have two parts: post + image prompt\n\nFLOW CONSIDERATIONS:\n- All tools connect only to the Tool Calling Agent\n- The flow is unidirectional (no loops)\n- Each prompt template maintains specific formatting\n- Temperatures are set for optimal creativity/consistency balance\n\nTROUBLESHOOTING NOTES:\n- If output is too creative: Lower temperature", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-aplGD", + "position": { + "x": 7606.419013912975, + "y": 3612.8149429707646 + }, + "positionAbsolute": { + "x": 7606.419013912975, + "y": 3612.8149429707646 + }, + "selected": false, + "type": "noteNode", + "width": 325 + }, + { + "data": { + "id": "note-AKIwx", + "node": { + "description": "# 🔑 Tavily AI Search Needs API Key\n\nYou can get 1000 searches/month free [here](https://tavily.com/) ", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "lime" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-AKIwx", + "position": { + "x": 5174.678177457385, + "y": 3339.6628854203204 + }, + "positionAbsolute": { + "x": 5174.678177457385, + "y": 3339.6628854203204 + }, + "selected": false, + "type": "noteNode", + "width": 325 } ], "viewport": { - "x": 573.0114453101413, - "y": 469.2263376930288, - "zoom": 0.29771421234125156 + "x": -1826.8109854875006, + "y": -1023.2049813606079, + "zoom": 0.4417458816510278 } }, - "description": "This Agent runs tasks in a predefined sequence.", + "description": " Create engaging Instagram posts with AI-generated content and image prompts, streamlining social media content creation.", "endpoint_name": null, - "icon": "ListOrdered", - "id": "c2e3229c-813e-43eb-9041-cdfcfab90e08", + "icon": "InstagramIcon", + "id": "4bb309e6-42b4-4565-b960-8bd0f7e431f2", "is_component": false, - "last_tested_version": "1.0.15", - "name": "Sequential Tasks Agent", + "last_tested_version": "1.0.19.post2", + "name": "Instagram Copywriter", "tags": [ - "agents", - "openai", - "chatbots" + "content-generation", + "chatbots", + "agents" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Market Research.json b/src/backend/base/langflow/initial_setup/starter_projects/Market Research.json new file mode 100644 index 000000000..323aaefa5 --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Market Research.json @@ -0,0 +1,2497 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": 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"str" + } + }, + "id": "reactflow__edge-Agent-QSS16{œdataTypeœ:œAgentœ,œidœ:œAgent-QSS16œ,œnameœ:œresponseœ,œoutput_typesœ:[œMessageœ]}-StructuredOutputComponent-421WY{œfieldNameœ:œinput_valueœ,œidœ:œStructuredOutputComponent-421WYœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "Agent-QSS16", + "sourceHandle": "{œdataTypeœ: œAgentœ, œidœ: œAgent-QSS16œ, œnameœ: œresponseœ, œoutput_typesœ: [œMessageœ]}", + "target": "StructuredOutputComponent-421WY", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œStructuredOutputComponent-421WYœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "id": "ChatInput-1iaFN", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Amazon" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-1iaFN", + "position": { + "x": 472.38251755471583, + "y": 889.8398446936101 + }, + "positionAbsolute": { + "x": 472.38251755471583, + "y": 889.8398446936101 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-hBRXA", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-hBRXA", + "position": { + "x": 2518.282039019285, + "y": 855.3686932779933 + }, + "positionAbsolute": { + "x": 2518.282039019285, + "y": 855.3686932779933 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "id": "TavilyAISearch-ghguc", + "node": { + "base_classes": [ + "Data", + "Tool" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "documentation": "https://docs.tavily.com/", + "edited": false, + "field_order": [ + "api_key", + "query", + "search_depth", + "topic", + "max_results", + "include_images", + "include_answer" + ], + "frozen": false, + "icon": "TavilyIcon", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "run_model", + "name": "api_run_model", + "required_inputs": [ + "api_key" + ], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Tool", + "method": "build_tool", + "name": "api_build_tool", + "required_inputs": [ + "api_key" + ], + "selected": "Tool", + "types": [ + "Tool" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "Tavily API Key", + "dynamic": false, + "info": "Your Tavily API Key.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from enum import Enum\n\nimport httpx\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass TavilySearchDepth(Enum):\n BASIC = \"basic\"\n ADVANCED = \"advanced\"\n\n\nclass TavilySearchTopic(Enum):\n GENERAL = \"general\"\n NEWS = \"news\"\n\n\nclass TavilySearchSchema(BaseModel):\n query: str = Field(..., description=\"The search query you want to execute with Tavily.\")\n search_depth: TavilySearchDepth = Field(TavilySearchDepth.BASIC, description=\"The depth of the search.\")\n topic: TavilySearchTopic = Field(TavilySearchTopic.GENERAL, description=\"The category of the search.\")\n max_results: int = Field(5, description=\"The maximum number of search results to return.\")\n include_images: bool = Field(default=False, description=\"Include a list of query-related images in the response.\")\n include_answer: bool = Field(default=False, description=\"Include a short answer to original query.\")\n\n\nclass TavilySearchToolComponent(LCToolComponent):\n display_name = \"Tavily AI Search\"\n description = \"\"\"**Tavily AI** is a search engine optimized for LLMs and RAG, \\\n aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n\"\"\"\n icon = \"TavilyIcon\"\n name = \"TavilyAISearch\"\n documentation = \"https://docs.tavily.com/\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Tavily API Key\",\n required=True,\n info=\"Your Tavily API Key.\",\n ),\n MessageTextInput(\n name=\"query\",\n display_name=\"Search Query\",\n info=\"The search query you want to execute with Tavily.\",\n ),\n DropdownInput(\n name=\"search_depth\",\n display_name=\"Search Depth\",\n info=\"The depth of the search.\",\n options=list(TavilySearchDepth),\n value=TavilySearchDepth.ADVANCED,\n advanced=True,\n ),\n DropdownInput(\n name=\"topic\",\n display_name=\"Search Topic\",\n info=\"The category of the search.\",\n options=list(TavilySearchTopic),\n value=TavilySearchTopic.GENERAL,\n advanced=True,\n ),\n IntInput(\n name=\"max_results\",\n display_name=\"Max Results\",\n info=\"The maximum number of search results to return.\",\n value=5,\n advanced=True,\n ),\n BoolInput(\n name=\"include_images\",\n display_name=\"Include Images\",\n info=\"Include a list of query-related images in the response.\",\n value=True,\n advanced=True,\n ),\n BoolInput(\n name=\"include_answer\",\n display_name=\"Include Answer\",\n info=\"Include a short answer to original query.\",\n value=True,\n advanced=True,\n ),\n ]\n\n def run_model(self) -> list[Data]:\n # Convert string values to enum instances with validation\n try:\n search_depth_enum = (\n self.search_depth\n if isinstance(self.search_depth, TavilySearchDepth)\n else TavilySearchDepth(str(self.search_depth).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid search depth value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n try:\n topic_enum = (\n self.topic if isinstance(self.topic, TavilySearchTopic) else TavilySearchTopic(str(self.topic).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid topic value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n return self._tavily_search(\n self.query,\n search_depth=search_depth_enum,\n topic=topic_enum,\n max_results=self.max_results,\n include_images=self.include_images,\n include_answer=self.include_answer,\n )\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"tavily_search\",\n description=\"Perform a web search using the Tavily API.\",\n func=self._tavily_search,\n args_schema=TavilySearchSchema,\n )\n\n def _tavily_search(\n self,\n query: str,\n *,\n search_depth: TavilySearchDepth = TavilySearchDepth.BASIC,\n topic: TavilySearchTopic = TavilySearchTopic.GENERAL,\n max_results: int = 5,\n include_images: bool = False,\n include_answer: bool = False,\n ) -> list[Data]:\n # Validate enum values\n if not isinstance(search_depth, TavilySearchDepth):\n msg = f\"Invalid search_depth value: {search_depth}\"\n raise TypeError(msg)\n if not isinstance(topic, TavilySearchTopic):\n msg = f\"Invalid topic value: {topic}\"\n raise TypeError(msg)\n\n try:\n url = \"https://api.tavily.com/search\"\n headers = {\n \"content-type\": \"application/json\",\n \"accept\": \"application/json\",\n }\n payload = {\n \"api_key\": self.api_key,\n \"query\": query,\n \"search_depth\": search_depth.value,\n \"topic\": topic.value,\n \"max_results\": max_results,\n \"include_images\": include_images,\n \"include_answer\": include_answer,\n }\n\n with httpx.Client() as client:\n response = client.post(url, json=payload, headers=headers)\n\n response.raise_for_status()\n search_results = response.json()\n\n data_results = [\n Data(\n data={\n \"title\": result.get(\"title\"),\n \"url\": result.get(\"url\"),\n \"content\": result.get(\"content\"),\n \"score\": result.get(\"score\"),\n }\n )\n for result in search_results.get(\"results\", [])\n ]\n\n if include_answer and search_results.get(\"answer\"):\n data_results.insert(0, Data(data={\"answer\": search_results[\"answer\"]}))\n\n if include_images and search_results.get(\"images\"):\n data_results.append(Data(data={\"images\": search_results[\"images\"]}))\n\n self.status = data_results # type: ignore[assignment]\n\n except httpx.HTTPStatusError as e:\n error_message = f\"HTTP error: {e.response.status_code} - {e.response.text}\"\n logger.debug(error_message)\n self.status = error_message\n raise ToolException(error_message) from e\n except Exception as e:\n error_message = f\"Unexpected error: {e}\"\n logger.opt(exception=True).debug(\"Error running Tavily Search\")\n self.status = error_message\n raise ToolException(error_message) from e\n return data_results\n" + }, + "include_answer": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Answer", + "dynamic": false, + "info": "Include a short answer to original query.", + "list": false, + "name": "include_answer", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "include_images": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Images", + "dynamic": false, + "info": "Include a list of query-related images in the response.", + "list": false, + "name": "include_images", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "max_results": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Results", + "dynamic": false, + "info": "The maximum number of search results to return.", + "list": false, + "name": "max_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 5 + }, + "query": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Search Query", + "dynamic": false, + "info": "The search query you want to execute with Tavily.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "search_depth": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Depth", + "dynamic": false, + "info": "The depth of the search.", + "load_from_db": false, + "name": "search_depth", + "options": [ + "basic", + "advanced" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "advanced" + }, + "topic": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Topic", + "dynamic": false, + "info": "The category of the search.", + "load_from_db": false, + "name": "topic", + "options": [ + "general", + "news" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "general" + } + }, + "tool_mode": false + }, + "type": "TavilyAISearch" + }, + "dragging": false, + "height": 481, + "id": "TavilyAISearch-ghguc", + "position": { + "x": 928.3794352018558, + "y": 797.2042255200732 + }, + "positionAbsolute": { + "x": 928.3794352018558, + "y": 797.2042255200732 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-Fs2b3", + "node": { + "description": "The StructuredOutputComponent, when utilized with our company information schema, performs the following functions:\n\n1. Accepts an input query regarding a company.\n2. Employs a Language Model (LLM) to analyze the query.\n3. Instructs the LLM to generate a structured response adhering to the predefined schema:\n - Domain\n - LinkedIn URL\n - Cheapest Plan\n - Has Free Trial\n - Has Enterprise Plan\n - Has API\n - Market\n - Pricing Tiers\n - Key Features\n - Target Industries\n\n4. Validates the LLM output against this schema.\n5. Returns a Data object containing the company information structured according to the schema.\n\nIn essence, this component transforms a free-text query about a company into a structured, consistent dataset, facilitating subsequent analysis and application of the information.", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 403, + "id": "note-Fs2b3", + "position": { + "x": 2089.5869930853464, + "y": 311.41660832449514 + }, + "positionAbsolute": { + "x": 2089.5869930853464, + "y": 311.41660832449514 + }, + "resizing": false, + "selected": false, + "style": { + "height": 403, + "width": 461 + }, + "type": "noteNode", + "width": 461 + }, + { + "data": { + "id": "note-BfWWs", + "node": { + "description": "PURPOSE:\nConverts unstructured company research into standardized JSON format\n\nKEY FUNCTIONS:\n- Extracts specific business data points\n- Validates and formats information\n- Ensures data consistency\n\nINPUT:\n- Raw company research data\n\nOUTPUT:\nStructured JSON with:\n- Domain information\n- Social links\n- Pricing details\n- Feature availability\n- Market classification\n- Product features\n- Industry focus\n\nRULES:\n1. Uses strict boolean values\n2. Standardizes pricing formats\n3. Validates market categories\n4. Handles missing data consistently", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 382, + "id": "note-BfWWs", + "position": { + "x": 1237.6627823432912, + "y": 111.53860932079613 + }, + "positionAbsolute": { + "x": 1237.6627823432912, + "y": 169.53860932079613 + }, + "resizing": false, + "selected": false, + "style": { + "height": 382, + "width": 398 + }, + "type": "noteNode", + "width": 398 + }, + { + "data": { + "id": "note-iNLPA", + "node": { + "description": "# Market Research\nThis flow helps you gather comprehensive information about companies for sales and business intelligence purposes.\n\n## Instructions\n\n1. Enter Company Name\n - In the Chat Input node, type the name of the company you want to research\n - Example inputs: \"Salesforce.com\", \"Shopify\", \"Zoom Video Communications\"\n\n2. Initiate Research\n - The Agent will use the Tavily AI Search tool to gather information\n - It will focus on key areas like pricing, features, and market positioning\n\n3. Review Structured Output\n - The flow will generate a structured JSON output with standardized fields\n - This includes domain, LinkedIn URL, pricing details, and key features\n\n4. Examine Formatted Results\n - The Parse Data component will convert the JSON into a readable format\n - You'll see a comprehensive company profile with organized sections\n\n5. Analyze and Use Data\n - Use the generated information for sales prospecting, competitive analysis, or market research\n - The structured format allows for easy comparison between different companies\n\nRemember: Always verify critical information from official sources before making business decisions! 🔍💼", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "emerald" + } + }, + "type": "note" + }, + "dragging": false, + "height": 513, + "id": "note-iNLPA", + "position": { + "x": 244.92297036777086, + "y": 340.99805740871204 + }, + "positionAbsolute": { + "x": 244.92297036777086, + "y": 340.99805740871204 + }, + "resizing": false, + "selected": true, + "style": { + "height": 513, + "width": 567 + }, + "type": "noteNode", + "width": 567 + }, + { + "data": { + "description": "Transforms LLM responses into **structured data formats**. Ideal for extracting specific information or creating consistent outputs.", + "display_name": "Structured Output", + "id": "StructuredOutputComponent-421WY", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Transforms LLM responses into **structured data formats**. Ideal for extracting specific information or creating consistent outputs.", + "display_name": "Structured Output", + "documentation": "", + "edited": false, + "field_order": [ + "llm", + "input_value", + "schema_name", + "output_schema", + "multiple" + ], + "frozen": false, + "icon": "braces", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Structured Output", + "method": "build_structured_output", + "name": "structured_output", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from typing import cast\n\nfrom pydantic import BaseModel, Field, create_model\n\nfrom langflow.base.models.chat_result import get_chat_result\nfrom langflow.custom import Component\nfrom langflow.field_typing.constants import LanguageModel\nfrom langflow.helpers.base_model import build_model_from_schema\nfrom langflow.io import BoolInput, HandleInput, MessageTextInput, Output, StrInput, TableInput\nfrom langflow.schema.data import Data\n\n\nclass StructuredOutputComponent(Component):\n display_name = \"Structured Output\"\n description = (\n \"Transforms LLM responses into **structured data formats**. Ideal for extracting specific information \"\n \"or creating consistent outputs.\"\n )\n icon = \"braces\"\n\n inputs = [\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"The language model to use to generate the structured output.\",\n input_types=[\"LanguageModel\"],\n ),\n MessageTextInput(name=\"input_value\", display_name=\"Input message\"),\n StrInput(\n name=\"schema_name\",\n display_name=\"Schema Name\",\n info=\"Provide a name for the output data schema.\",\n ),\n TableInput(\n name=\"output_schema\",\n display_name=\"Output Schema\",\n info=\"Define the structure and data types for the model's output.\",\n table_schema=[\n {\n \"name\": \"name\",\n \"display_name\": \"Name\",\n \"type\": \"str\",\n \"description\": \"Specify the name of the output field.\",\n },\n {\n \"name\": \"description\",\n \"display_name\": \"Description\",\n \"type\": \"str\",\n \"description\": \"Describe the purpose of the output field.\",\n },\n {\n \"name\": \"type\",\n \"display_name\": \"Type\",\n \"type\": \"str\",\n \"description\": (\n \"Indicate the data type of the output field \" \"(e.g., str, int, float, bool, list, dict).\"\n ),\n \"default\": \"text\",\n },\n {\n \"name\": \"multiple\",\n \"display_name\": \"Multiple\",\n \"type\": \"boolean\",\n \"description\": \"Set to True if this output field should be a list of the specified type.\",\n \"default\": \"False\",\n },\n ],\n ),\n BoolInput(\n name=\"multiple\",\n display_name=\"Generate Multiple\",\n info=\"Set to True if the model should generate a list of outputs instead of a single output.\",\n ),\n ]\n\n outputs = [\n Output(name=\"structured_output\", display_name=\"Structured Output\", method=\"build_structured_output\"),\n ]\n\n def build_structured_output(self) -> Data:\n if not hasattr(self.llm, \"with_structured_output\"):\n msg = \"Language model does not support structured output.\"\n raise TypeError(msg)\n if not self.output_schema:\n msg = \"Output schema cannot be empty\"\n raise ValueError(msg)\n\n _output_model = build_model_from_schema(self.output_schema)\n if self.multiple:\n output_model = create_model(\n self.schema_name,\n objects=(list[_output_model], Field(description=f\"A list of {self.schema_name}.\")), # type: ignore[valid-type]\n )\n else:\n output_model = _output_model\n try:\n llm_with_structured_output = cast(LanguageModel, self.llm).with_structured_output(schema=output_model) # type: ignore[valid-type, attr-defined]\n\n except NotImplementedError as exc:\n msg = f\"{self.llm.__class__.__name__} does not support structured output.\"\n raise TypeError(msg) from exc\n config_dict = {\n \"run_name\": self.display_name,\n \"project_name\": self.get_project_name(),\n \"callbacks\": self.get_langchain_callbacks(),\n }\n output = get_chat_result(runnable=llm_with_structured_output, input_value=self.input_value, config=config_dict)\n if isinstance(output, BaseModel):\n output_dict = output.model_dump()\n else:\n msg = f\"Output should be a Pydantic BaseModel, got {type(output)} ({output})\"\n raise TypeError(msg)\n return Data(data=output_dict)\n" + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input message", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "llm": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Language Model", + "dynamic": false, + "info": "The language model to use to generate the structured output.", + "input_types": [ + "LanguageModel" + ], + "list": false, + "name": "llm", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "multiple": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Generate Multiple", + "dynamic": false, + "info": "Set to True if the model should generate a list of outputs instead of a single output.", + "list": false, + "name": "multiple", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "output_schema": { + "_input_type": "TableInput", + "advanced": false, + "display_name": "Output Schema", + "dynamic": false, + "info": "Define the structure and data types for the model's output.", + "is_list": true, + "load_from_db": false, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "table_schema": { + "columns": [ + { + "description": "Specify the name of the output field.", + "display_name": "Name", + "filterable": true, + "formatter": "text", + "name": "name", + "sortable": true, + "type": "text" + }, + { + "description": "Describe the purpose of the output field.", + "display_name": "Description", + "filterable": true, + "formatter": "text", + "name": "description", + "sortable": true, + "type": "text" + }, + { + "default": "text", + "description": "Indicate the data type of the output field (e.g., str, int, float, bool, list, dict).", + "display_name": "Type", + "filterable": true, + "formatter": "text", + "name": "type", + "sortable": true, + "type": "text" + }, + { + "default": "False", + "description": "Set to True if this output field should be a list of the specified type.", + "display_name": "Multiple", + "filterable": true, + "formatter": "text", + "name": "multiple", + "sortable": true, + "type": "boolean" + } + ] + }, + "title_case": false, + "trace_as_metadata": true, + "type": "table", + "value": [ + { + "description": "Primary company domain name", + "multiple": "False", + "name": "domain", + "type": "text" + }, + { + "description": "Company's LinkedIn URL", + "multiple": "False", + "name": "linkedinUrl", + "type": "text" + }, + { + "description": "Lowest priced plan in USD (number only)", + "multiple": "False", + "name": "cheapestPlan", + "type": "text" + }, + { + "description": "Boolean indicating if they offer a free trial", + "multiple": "False", + "name": "hasFreeTrial", + "type": "bool" + }, + { + "description": "Boolean indicating if they have enterprise options", + "multiple": "False", + "name": "hasEnterprisePlan", + "type": "bool" + }, + { + "description": "Boolean indicating if they offer API access", + "multiple": "False", + "name": "hasAPI", + "type": "bool" + }, + { + "description": "Either 'B2B' or 'B2C' or 'Both", + "multiple": "False", + "name": "market", + "type": "text" + }, + { + "description": "List of available pricing tiers", + "multiple": "True", + "name": "pricingTiers", + "type": "text" + }, + { + "description": "List of main features", + "multiple": "True", + "name": "KeyFeatures", + "type": "text" + }, + { + "description": "List of target industries", + "multiple": "True", + "name": "targetIndustries", + "type": "text" + } + ] + }, + "schema_name": { + "_input_type": "StrInput", + "advanced": false, + "display_name": "Schema Name", + "dynamic": false, + "info": "Provide a name for the output data schema.", + "list": false, + "load_from_db": false, + "name": "schema_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "output_schema" + } + }, + "tool_mode": false + }, + "type": "StructuredOutputComponent" + }, + "dragging": false, + "height": 541, + "id": "StructuredOutputComponent-421WY", + "position": { + "x": 1770.7096106546323, + "y": 518.8182475390113 + }, + "positionAbsolute": { + "x": 1770.7096106546323, + "y": 518.8182475390113 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-1WzgM", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 543, + "id": "OpenAIModel-1WzgM", + "position": { + "x": 1631.501592565594, + "y": 1086.5741650125892 + }, + "positionAbsolute": { + "x": 1631.501592565594, + "y": 1086.5741650125892 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "ParseData-rO6Qs", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "category": "helpers", + "conditional_paths": [], + "custom_fields": {}, + "description": "Convert Data into plain text following a specified template.", + "display_name": "Parse Data", + "documentation": "", + "edited": false, + "field_order": [ + "data", + "template", + "sep" + ], + "frozen": false, + "icon": "braces", + "key": "ParseData", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "parse_data", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n name = \"ParseData\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. \"\n \"It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "data": { + "_input_type": "DataInput", + "advanced": false, + "display_name": "Data", + "dynamic": false, + "info": "The data to convert to text.", + "input_types": [ + "Data" + ], + "list": false, + "name": "data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "sep": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Separator", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "sep", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "\n" + }, + "template": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "# Company Profile\n\n## Basic Information\n- **Domain:** {domain}\n- **LinkedIn URL:** {linkedinUrl}\n\n## Pricing and Plans\n- **Cheapest Plan:** {cheapestPlan}\n- **Has Free Trial:** {hasFreeTrial}\n- **Has Enterprise Plan:** {hasEnterprisePlan}\n\n## Technical Capabilities\n- **Has API:** {hasAPI}\n\n## Market and Target Audience\n- **Market:** {market}\n- **Target Industries:** {targetIndustries}\n\n## Pricing Structure\n{pricingTiers}\n\n## Key Features\n{KeyFeatures}\n" + } + } + }, + "type": "ParseData" + }, + "dragging": false, + "height": 302, + "id": "ParseData-rO6Qs", + "position": { + "x": 2139.05558520377, + "y": 780.6849187394922 + }, + "positionAbsolute": { + "x": 2139.05558520377, + "y": 780.6849187394922 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "id": "Agent-QSS16", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Amazon Bedrock", + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix), display_name\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are an expert business research agent. Your task is to gather comprehensive information about companies. When researching a company, focus on the following key areas: 1. Basic company information (website, domain, social presence) 2. Product and pricing information 3. Technical capabilities and integrations 4. Market positioning and target audience 5. Key features and offerings For the company/domain provided, search thoroughly and provide detailed information about: - Their main website and domain - Their pricing structure - Product features and capabilities - Market presence and focus - Technical offerings like APIs - Social media presence, especially LinkedIn Search comprehensively and provide detailed, factual information that will help determine: - Pricing tiers and structure - Whether they offer free trials - If they have enterprise solutions - Their technical capabilities - Their primary market (B2B/B2C) INPUT: {input} Respond with detailed, factual information about these aspects, avoiding speculation. Include direct quotes or specific information you find." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-QSS16", + "position": { + "x": 1287.5681517817056, + "y": 519.8701526087884 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-uNkbX", + "node": { + "description": "# 🔑 Tavily AI Search Needs API Key\n\nYou can get 1000 searches/month free [here](https://tavily.com/) ", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "lime" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-uNkbX", + "position": { + "x": 921.6062384772317, + "y": 642.1140062279873 + }, + "positionAbsolute": { + "x": 921.6062384772317, + "y": 642.1140062279873 + }, + "selected": false, + "type": "noteNode", + "width": 325 + } + ], + "viewport": { + "x": -56.31509213451284, + "y": 23.784977680322072, + "zoom": 0.5068195797812174 + } + }, + "description": "Researches companies, extracts key business data, and presents structured information for efficient analysis. ", + "endpoint_name": null, + "icon": "PieChart", + "id": "153a05e5-86bd-4de8-b159-2cb4f9f94de5", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "Market Research", + "tags": [ + "assistants", + "agents" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json index ddd0b9087..56f5e9291 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json @@ -2,64 +2,12 @@ "data": { "edges": [ { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-6yuNd", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "user_message", - "id": "Prompt-tifRl", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-6yuNd{œdataTypeœ:œChatInputœ,œidœ:œChatInput-6yuNdœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-tifRl{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-tifRlœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-6yuNd", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-6yuNdœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-tifRl", - "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-tifRlœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-tifRl", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-ZIeE0", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-tifRl{œdataTypeœ:œPromptœ,œidœ:œPrompt-tifRlœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-ZIeE0{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-ZIeE0œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-tifRl", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-tifRlœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-ZIeE0", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-ZIeE0œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-ZIeE0", + "id": "OpenAIModel-4aid4", "name": "text_output", "output_types": [ "Message" @@ -67,33 +15,62 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-c3v9q", + "id": "ChatOutput-CL8qC", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-ZIeE0{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-ZIeE0œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-c3v9q{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-c3v9qœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-ZIeE0", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-ZIeE0œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-c3v9q", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-c3v9qœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-4aid4{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-4aid4œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-CL8qC{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-CL8qCœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "OpenAIModel-4aid4", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-4aid4œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-CL8qC", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-CL8qCœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-wnAdG", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-4aid4", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-wnAdG{œdataTypeœ:œChatInputœ,œidœ:œChatInput-wnAdGœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-4aid4{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-4aid4œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "ChatInput-wnAdG", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-wnAdGœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-4aid4", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-4aid4œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Memory", - "id": "Memory-6s5g1", + "id": "Memory-dsJro", "name": "messages_text", "output_types": [ "Message" ] }, "targetHandle": { - "fieldName": "context", - "id": "Prompt-tifRl", + "fieldName": "memory", + "id": "Prompt-JvUF7", "inputTypes": [ "Message", "Text" @@ -101,165 +78,43 @@ "type": "str" } }, - "id": "reactflow__edge-Memory-6s5g1{œdataTypeœ:œMemoryœ,œidœ:œMemory-6s5g1œ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-tifRl{œfieldNameœ:œcontextœ,œidœ:œPrompt-tifRlœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "Memory-6s5g1", - "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-6s5g1œ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-tifRl", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-tifRlœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Memory-dsJro{œdataTypeœ:œMemoryœ,œidœ:œMemory-dsJroœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-JvUF7{œfieldNameœ:œmemoryœ,œidœ:œPrompt-JvUF7œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "Memory-dsJro", + "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-dsJroœ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-JvUF7", + "targetHandle": "{œfieldNameœ: œmemoryœ, œidœ: œPrompt-JvUF7œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-JvUF7", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_message", + "id": "OpenAIModel-4aid4", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-JvUF7{œdataTypeœ:œPromptœ,œidœ:œPrompt-JvUF7œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-4aid4{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-4aid4œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-JvUF7", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-JvUF7œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-4aid4", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-4aid4œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ { "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-tifRl", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "context", - "user_message" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "edited": false, - "field_order": [ - "template" - ], - "frozen": false, - "icon": "prompts", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" - }, - "context": { - "advanced": false, - "display_name": "context", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "context", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "{context}\n\nUser: {user_message}\nAI: " - }, - "user_message": { - "advanced": false, - "display_name": "user_message", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_message", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 517, - "id": "Prompt-tifRl", - "position": { - "x": 1880.8227904110583, - "y": 625.8049209882275 - }, - "positionAbsolute": { - "x": 1880.8227904110583, - "y": 625.8049209882275 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "id": "ChatInput-6yuNd", + "id": "ChatInput-wnAdG", "node": { "base_classes": [ "Message" @@ -273,15 +128,19 @@ "edited": false, "field_order": [ "input_value", - "store_message", + "should_store_message", "sender", "sender_name", "session_id", - "files" + "files", + "background_color", + "chat_icon", + "text_color" ], "frozen": false, "icon": "MessagesSquare", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -316,6 +175,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -337,6 +197,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -361,6 +222,7 @@ "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" }, "files": { + "_input_type": "FileInput", "advanced": true, "display_name": "Files", "dynamic": false, @@ -402,6 +264,7 @@ "value": "" }, "input_value": { + "_input_type": "MultilineInput", "advanced": false, "display_name": "Text", "dynamic": false, @@ -417,13 +280,16 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "" + "value": "what is my name" }, "sender": { + "_input_type": "DropdownInput", "advanced": true, + "combobox": false, "display_name": "Sender Type", "dynamic": false, "info": "Type of sender.", @@ -436,11 +302,13 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "User" }, "sender_name": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Sender Name", "dynamic": false, @@ -455,12 +323,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "User" }, "session_id": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Session ID", "dynamic": false, @@ -475,6 +345,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -512,35 +383,371 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" } - } + }, + "tool_mode": false }, "type": "ChatInput" }, "dragging": false, - "height": 309, - "id": "ChatInput-6yuNd", + "height": 234, + "id": "ChatInput-wnAdG", "position": { - "x": 1275.9262193671882, - "y": 836.1228056896347 + "x": 2321.5543981677606, + "y": 374.0457826421628 }, "positionAbsolute": { - "x": 1275.9262193671882, - "y": 836.1228056896347 + "x": 2321.5543981677606, + "y": 374.0457826421628 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "id": "OpenAIModel-ZIeE0", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-CL8qC", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-CL8qC", + "position": { + "x": 3101.965731391458, + "y": 776.4408905693839 + }, + "positionAbsolute": { + "x": 3101.965731391458, + "y": 776.4408905693839 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-4FQUh", + "node": { + "description": "# Memory Chatbot\n\nA flexible chatbot implementation featuring advanced conversation memory capabilities. This serves as a foundational tool for building chat experiences with persistent context.\n\n## Core Components\n\n1. **Chat Input**\n - Accepts user messages\n - Configures conversation storage\n - Tracks session identity\n\n2. **Chat Memory**\n - Stores and retrieves up to 100 previous messages\n - Maintains conversation context\n - Tracks separate chat sessions\n - Preserves sender information and message order\n\n3. **Prompt**\n - Creates dynamic prompt templates\n - Integrates memory into conversation flow\n\n4. **OpenAI**\n - Processes user input with context\n - Accesses conversation history\n - Includes options for model configuration and API key setup\n\n5. **Chat Output**\n - Displays formatted responses\n - Maintains conversation flow\n - Syncs with memory storage\n\n## Memory Features\n\n- Stores message history\n- Plans conversation trajectory\n- Differentiates between chat sessions\n- Preserves sender and message metadata\n\n## Quick Start\n\n1. **Initialize** with a clear session ID\n2. **Enter** message in Chat Input\n3. **AI Processes** with context from memory\n4. **Response** appears in Chat Output\n5. Context remains available for follow-ups\n\nThis robust system demonstrates thorough memory integration with minimal complexity. 🧠💬\n", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 736, + "id": "note-4FQUh", + "position": { + "x": 1512.8976594415833, + "y": 312.9558305744385 + }, + "positionAbsolute": { + "x": 1512.8976594415833, + "y": 312.9558305744385 + }, + "resizing": false, + "selected": false, + "style": { + "height": 736, + "width": 382 + }, + "type": "noteNode", + "width": 382 + }, + { + "data": { + "id": "note-5ZvaH", + "node": { + "description": "## Get Your OpenAI API Key\n\n**Steps**:\n\n1. **Visit** [OpenAI's API Key Page](https://platform.openai.com/api-keys).\n\n2. **Log In/Sign Up**:\n - Log in or create a new OpenAI account.\n\n3. **Generate API Key**:\n - Click \"Create New Secret Key\" to obtain your key.\n\n4. **Store Your Key Securely**:\n - Note it down as it will only display once.\n\n5. **Enter API Key**:\n - Input your key in the OpenAI API Key field within the component setup.\n\nKeep your key safe and manage it responsibly!", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "rose" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-5ZvaH", + "position": { + "x": 2727.7060397092964, + "y": 115.42518754847691 + }, + "positionAbsolute": { + "x": 2727.7060397092964, + "y": 115.42518754847691 + }, + "selected": false, + "type": "noteNode", + "width": 325 + }, + { + "data": { + "id": "OpenAIModel-4aid4", "node": { "base_classes": [ "LanguageModel", @@ -555,21 +762,23 @@ "edited": false, "field_order": [ "input_value", + "system_message", + "stream", "max_tokens", "model_kwargs", "json_mode", "output_schema", "model_name", "openai_api_base", - "openai_api_key", + "api_key", "temperature", - "stream", - "system_message", - "seed" + "seed", + "output_parser" ], "frozen": false, "icon": "OpenAI", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -639,6 +848,7 @@ "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { + "_input_type": "MessageInput", "advanced": false, "display_name": "Input", "dynamic": false, @@ -659,6 +869,7 @@ "value": "" }, "json_mode": { + "_input_type": "BoolInput", "advanced": true, "display_name": "JSON Mode", "dynamic": false, @@ -674,6 +885,7 @@ "value": false }, "max_tokens": { + "_input_type": "IntInput", "advanced": true, "display_name": "Max Tokens", "dynamic": false, @@ -681,6 +893,12 @@ "list": false, "name": "max_tokens", "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, "required": false, "show": true, "title_case": false, @@ -689,6 +907,7 @@ "value": "" }, "model_kwargs": { + "_input_type": "DictInput", "advanced": true, "display_name": "Model Kwargs", "dynamic": false, @@ -704,7 +923,9 @@ "value": {} }, "model_name": { + "_input_type": "DropdownInput", "advanced": false, + "combobox": false, "display_name": "Model Name", "dynamic": false, "info": "", @@ -722,11 +943,13 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", - "value": "gpt-4o" + "value": "gpt-4o-mini" }, "openai_api_base": { + "_input_type": "StrInput", "advanced": true, "display_name": "OpenAI API Base", "dynamic": false, @@ -762,6 +985,7 @@ "value": "" }, "output_schema": { + "_input_type": "DictInput", "advanced": true, "display_name": "Schema", "dynamic": false, @@ -777,6 +1001,7 @@ "value": {} }, "seed": { + "_input_type": "IntInput", "advanced": true, "display_name": "Seed", "dynamic": false, @@ -792,7 +1017,8 @@ "value": 1 }, "stream": { - "advanced": true, + "_input_type": "BoolInput", + "advanced": false, "display_name": "Stream", "dynamic": false, "info": "Stream the response from the model. Streaming works only in Chat.", @@ -807,10 +1033,14 @@ "value": false }, "system_message": { - "advanced": true, + "_input_type": "MessageTextInput", + "advanced": false, "display_name": "System Message", "dynamic": false, "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], "list": false, "load_from_db": false, "name": "system_message", @@ -818,11 +1048,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, + "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "temperature": { + "_input_type": "FloatInput", "advanced": false, "display_name": "Temperature", "dynamic": false, @@ -837,287 +1070,31 @@ "type": "float", "value": 0.1 } - } + }, + "tool_mode": false }, "type": "OpenAIModel" }, "dragging": false, - "height": 623, - "id": "OpenAIModel-ZIeE0", + "height": 630, + "id": "OpenAIModel-4aid4", "position": { - "x": 2468.968379487559, - "y": 560.0689522326683 + "x": 2730.3374000311414, + "y": 465.98757723618604 }, "positionAbsolute": { - "x": 2468.968379487559, - "y": 560.0689522326683 + "x": 2730.3374000311414, + "y": 465.98757723618604 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "id": "ChatOutput-c3v9q", + "id": "Memory-dsJro", "node": { "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "store_message", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "height": 385, - "id": "ChatOutput-c3v9q", - "position": { - "x": 3083.1710516244116, - "y": 701.521688846004 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Retrieves stored chat messages from Langflow tables or an external memory.", - "display_name": "Chat Memory", - "id": "Memory-6s5g1", - "node": { - "base_classes": [ - "BaseChatMemory", "Data", "Message" ], @@ -1140,6 +1117,7 @@ "frozen": false, "icon": "message-square-more", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -1188,6 +1166,7 @@ "value": "from langchain.memory import ConversationBufferMemory\n\nfrom langflow.custom import Component\nfrom langflow.field_typing import BaseChatMemory\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import LCBuiltinChatMemory, get_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n icon = \"message-square-more\"\n name = \"Memory\"\n\n inputs = [\n HandleInput(\n name=\"memory\",\n display_name=\"External Memory\",\n input_types=[\"BaseChatMessageHistory\"],\n info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Filter by sender type.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Filter by sender name.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. \"\n \"It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Text\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n if self.memory:\n # override session_id\n self.memory.session_id = session_id\n\n stored = self.memory.messages\n # langchain memories are supposed to return messages in ascending order\n if order == \"DESC\":\n stored = stored[::-1]\n if n_messages:\n stored = stored[:n_messages]\n stored = [Message.from_lc_message(m) for m in stored]\n if sender:\n expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n stored = [m for m in stored if m.type == expected_type]\n else:\n stored = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = stored\n return stored\n\n def retrieve_messages_as_text(self) -> Message:\n stored_text = data_to_text(self.template, self.retrieve_messages())\n self.status = stored_text\n return Message(text=stored_text)\n\n def build_lc_memory(self) -> BaseChatMemory:\n chat_memory = self.memory or LCBuiltinChatMemory(flow_id=self.flow_id, session_id=self.session_id)\n return ConversationBufferMemory(chat_memory=chat_memory)\n" }, "memory": { + "_input_type": "HandleInput", "advanced": false, "display_name": "External Memory", "dynamic": false, @@ -1206,6 +1185,7 @@ "value": "" }, "n_messages": { + "_input_type": "IntInput", "advanced": true, "display_name": "Number of Messages", "dynamic": false, @@ -1221,7 +1201,9 @@ "value": 100 }, "order": { + "_input_type": "DropdownInput", "advanced": true, + "combobox": false, "display_name": "Order", "dynamic": false, "info": "Order of the messages.", @@ -1234,12 +1216,15 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "Ascending" }, "sender": { + "_input_type": "DropdownInput", "advanced": true, + "combobox": false, "display_name": "Sender Type", "dynamic": false, "info": "Filter by sender type.", @@ -1253,11 +1238,13 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "Machine and User" }, "sender_name": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Sender Name", "dynamic": false, @@ -1272,12 +1259,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "session_id": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Session ID", "dynamic": false, @@ -1292,12 +1281,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "template": { + "_input_type": "MultilineInput", "advanced": true, "display_name": "Template", "dynamic": false, @@ -1313,46 +1304,176 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "{sender_name}: {text}" } - } + }, + "tool_mode": false }, "type": "Memory" }, "dragging": false, - "height": 387, - "id": "Memory-6s5g1", + "height": 264, + "id": "Memory-dsJro", "position": { - "x": 1301.98330242754, - "y": 422.33865605652574 + "x": 1947.7805399474369, + "y": 766.1115984799474 }, "positionAbsolute": { - "x": 1301.98330242754, - "y": 422.33865605652574 + "x": 1947.7805399474369, + "y": 766.1115984799474 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 + }, + { + "data": { + "id": "Prompt-JvUF7", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "memory" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "memory": { + "advanced": false, + "display_name": "memory", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "You are a helpful assistant that answer questions.\n\nUse markdown to format your answer, properly embedding images and urls.\n\nHistory: \n\n{memory}\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 347, + "id": "Prompt-JvUF7", + "position": { + "x": 2327.422938009026, + "y": 675.992123914672 + }, + "positionAbsolute": { + "x": 2327.422938009026, + "y": 675.992123914672 + }, + "selected": false, + "type": "genericNode", + "width": 320 } ], "viewport": { - "x": -377.45799796990354, - "y": 18.161555190942522, - "zoom": 0.45494095964690673 + "x": -982.1139274661589, + "y": -37.00115573852611, + "zoom": 0.6716071677128489 } }, - "description": "This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.", + "description": "Create a chatbot that saves and references previous messages, enabling the model to maintain context throughout the conversation.", "endpoint_name": null, "icon": "MessagesSquare", - "id": "ff6810d0-1d7b-4455-9b35-c9f54f7d63b6", + "id": "7d334df6-6cf5-4d09-b6bf-169247b20446", "is_component": false, - "last_tested_version": "1.0.9", + "last_tested_version": "1.0.19.post2", "name": "Memory Chatbot", "tags": [ "chatbots", - "openai" + "openai", + "assistants" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Hierarchical Agent.json b/src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json similarity index 60% rename from src/backend/base/langflow/initial_setup/starter_projects/Hierarchical Agent.json rename to src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json index 76c0f4187..e34c34a8d 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Hierarchical Agent.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json @@ -2,207 +2,20 @@ "data": { "edges": [ { - "className": "", - "data": { - "sourceHandle": { - "dataType": "HierarchicalCrewComponent", - "id": "HierarchicalCrewComponent-Y0Uvf", - "name": "output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-VzVJK", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-HierarchicalCrewComponent-Y0Uvf{œdataTypeœ:œHierarchicalCrewComponentœ,œidœ:œHierarchicalCrewComponent-Y0Uvfœ,œnameœ:œoutputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-VzVJK{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-VzVJKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "selected": false, - "source": "HierarchicalCrewComponent-Y0Uvf", - "sourceHandle": "{œdataTypeœ: œHierarchicalCrewComponentœ, œidœ: œHierarchicalCrewComponent-Y0Uvfœ, œnameœ: œoutputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-VzVJK", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-VzVJKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "HierarchicalTaskComponent", - "id": "HierarchicalTaskComponent-hE8H5", - "name": "task_output", - "output_types": [ - "HierarchicalTask" - ] - }, - "targetHandle": { - "fieldName": "tasks", - "id": "HierarchicalCrewComponent-Y0Uvf", - "inputTypes": [ - "HierarchicalTask" - ], - "type": "other" - } - }, - "id": "reactflow__edge-HierarchicalTaskComponent-hE8H5{œdataTypeœ:œHierarchicalTaskComponentœ,œidœ:œHierarchicalTaskComponent-hE8H5œ,œnameœ:œtask_outputœ,œoutput_typesœ:[œHierarchicalTaskœ]}-HierarchicalCrewComponent-Y0Uvf{œfieldNameœ:œtasksœ,œidœ:œHierarchicalCrewComponent-Y0Uvfœ,œinputTypesœ:[œHierarchicalTaskœ],œtypeœ:œotherœ}", - "selected": false, - "source": "HierarchicalTaskComponent-hE8H5", - "sourceHandle": 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"selected": false, - "source": "OpenAIModel-HgNnu", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-HgNnuœ, œnameœ: œmodel_outputœ, œoutput_typesœ: [œLanguageModelœ]}", - "target": "CrewAIAgentComponent-9D8ao", - "targetHandle": "{œfieldNameœ: œllmœ, œidœ: œCrewAIAgentComponent-9D8aoœ, œinputTypesœ: [œLanguageModelœ], œtypeœ: œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-eqGhn", - "name": "prompt", + "id": "OpenAIModel-Rc3MO", + "name": "text_output", "output_types": [ "Message" ] }, "targetHandle": { - "fieldName": "task_description", - "id": "HierarchicalTaskComponent-hE8H5", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-eqGhn{œdataTypeœ:œPromptœ,œidœ:œPrompt-eqGhnœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-HierarchicalTaskComponent-hE8H5{œfieldNameœ:œtask_descriptionœ,œidœ:œHierarchicalTaskComponent-hE8H5œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-eqGhn", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-eqGhnœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "HierarchicalTaskComponent-hE8H5", - "targetHandle": "{œfieldNameœ: œtask_descriptionœ, œidœ: œHierarchicalTaskComponent-hE8H5œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-xgRl9", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "query", - "id": "Prompt-eqGhn", + "fieldName": "previous_response", + "id": "Prompt-u7GZR", "inputTypes": [ "Message", "Text" @@ -210,70 +23,105 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-xgRl9{œdataTypeœ:œChatInputœ,œidœ:œChatInput-xgRl9œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-eqGhn{œfieldNameœ:œqueryœ,œidœ:œPrompt-eqGhnœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-xgRl9", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-xgRl9œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-eqGhn", - "targetHandle": "{œfieldNameœ: œqueryœ, œidœ: œPrompt-eqGhnœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-Rc3MO{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Rc3MOœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-Prompt-u7GZR{œfieldNameœ:œprevious_responseœ,œidœ:œPrompt-u7GZRœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "selected": false, + "source": "OpenAIModel-Rc3MO", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-Rc3MOœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-u7GZR", + "targetHandle": "{œfieldNameœ: œprevious_responseœ, œidœ: œPrompt-u7GZRœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { - "dataType": "CrewAIAgentComponent", - "id": "CrewAIAgentComponent-UMpxO", - "name": "output", + "dataType": "Prompt", + "id": "Prompt-yDDjW", + "name": "prompt", "output_types": [ - "Agent" + "Message" ] }, "targetHandle": { - "fieldName": "agents", - "id": "HierarchicalCrewComponent-Y0Uvf", + "fieldName": "input_value", + "id": "OpenAIModel-zhgF5", "inputTypes": [ - "Agent" + "Message" ], - "type": "other" + "type": "str" } }, - "id": "reactflow__edge-CrewAIAgentComponent-UMpxO{œdataTypeœ:œCrewAIAgentComponentœ,œidœ:œCrewAIAgentComponent-UMpxOœ,œnameœ:œoutputœ,œoutput_typesœ:[œAgentœ]}-HierarchicalCrewComponent-Y0Uvf{œfieldNameœ:œagentsœ,œidœ:œHierarchicalCrewComponent-Y0Uvfœ,œinputTypesœ:[œAgentœ],œtypeœ:œotherœ}", - "source": "CrewAIAgentComponent-UMpxO", - "sourceHandle": "{œdataTypeœ: œCrewAIAgentComponentœ, œidœ: œCrewAIAgentComponent-UMpxOœ, œnameœ: œoutputœ, œoutput_typesœ: [œAgentœ]}", - "target": "HierarchicalCrewComponent-Y0Uvf", - "targetHandle": "{œfieldNameœ: œagentsœ, œidœ: œHierarchicalCrewComponent-Y0Uvfœ, œinputTypesœ: [œAgentœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-Prompt-yDDjW{œdataTypeœ:œPromptœ,œidœ:œPrompt-yDDjWœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-zhgF5{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-zhgF5œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "Prompt-yDDjW", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-yDDjWœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-zhgF5", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-zhgF5œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-Mzp4f", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "Prompt-yDDjW", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-Mzp4f{œdataTypeœ:œChatInputœ,œidœ:œChatInput-Mzp4fœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-yDDjW{œfieldNameœ:œinput_valueœ,œidœ:œPrompt-yDDjWœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "selected": false, + "source": "ChatInput-Mzp4f", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-Mzp4fœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-yDDjW", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œPrompt-yDDjWœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-Yjtpu", - "name": "model_output", + "id": "OpenAIModel-zhgF5", + "name": "text_output", "output_types": [ - "LanguageModel" + "Message" ] }, "targetHandle": { - "fieldName": "llm", - "id": "CrewAIAgentComponent-UMpxO", + "fieldName": "input_value", + "id": "ChatOutput-mWv8X", "inputTypes": [ - "LanguageModel" + "Message" ], - "type": "other" + "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-Yjtpu{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Yjtpuœ,œnameœ:œmodel_outputœ,œoutput_typesœ:[œLanguageModelœ]}-CrewAIAgentComponent-UMpxO{œfieldNameœ:œllmœ,œidœ:œCrewAIAgentComponent-UMpxOœ,œinputTypesœ:[œLanguageModelœ],œtypeœ:œotherœ}", - "source": "OpenAIModel-Yjtpu", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-Yjtpuœ, œnameœ: œmodel_outputœ, œoutput_typesœ: [œLanguageModelœ]}", - "target": "CrewAIAgentComponent-UMpxO", - "targetHandle": "{œfieldNameœ: œllmœ, œidœ: œCrewAIAgentComponent-UMpxOœ, œinputTypesœ: [œLanguageModelœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-OpenAIModel-zhgF5{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-zhgF5œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-mWv8X{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-mWv8Xœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "OpenAIModel-zhgF5", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-zhgF5œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-mWv8X", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-mWv8Xœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { - "dataType": "SearchAPI", - "id": "SearchAPI-Yokat", + "dataType": "TavilyAISearch", + "id": "TavilyAISearch-rI4aD", "name": "api_build_tool", "output_types": [ "Tool" @@ -281,1858 +129,167 @@ }, "targetHandle": { "fieldName": "tools", - "id": "CrewAIAgentComponent-EbpXd", + "id": "Agent-9E8IU", "inputTypes": [ - "Tool" + "Tool", + "BaseTool", + "StructuredTool" ], "type": "other" } }, - "id": "reactflow__edge-SearchAPI-Yokat{œdataTypeœ:œSearchAPIœ,œidœ:œSearchAPI-Yokatœ,œnameœ:œapi_build_toolœ,œoutput_typesœ:[œToolœ]}-CrewAIAgentComponent-EbpXd{œfieldNameœ:œtoolsœ,œidœ:œCrewAIAgentComponent-EbpXdœ,œinputTypesœ:[œToolœ],œtypeœ:œotherœ}", - "source": "SearchAPI-Yokat", - 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"dataType": "Prompt", + "id": "Prompt-u7GZR", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "Agent-9E8IU", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-u7GZR{œdataTypeœ:œPromptœ,œidœ:œPrompt-u7GZRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-Agent-9E8IU{œfieldNameœ:œinput_valueœ,œidœ:œAgent-9E8IUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "Prompt-u7GZR", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-u7GZRœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "Agent-9E8IU", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œAgent-9E8IUœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Agent", + "id": "Agent-9E8IU", + "name": "response", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": 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"reactflow__edge-Prompt-T4lL6{œdataTypeœ:œPromptœ,œidœ:œPrompt-T4lL6œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-Rc3MO{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-Rc3MOœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-T4lL6", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-T4lL6œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-Rc3MO", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-Rc3MOœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-Mzp4f", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-Rc3MO", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-Mzp4f{œdataTypeœ:œChatInputœ,œidœ:œChatInput-Mzp4fœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-Rc3MO{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Rc3MOœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-Mzp4f", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-Mzp4fœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-Rc3MO", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-Rc3MOœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-f4xQ5", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_message", + "id": "OpenAIModel-zhgF5", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-f4xQ5{œdataTypeœ:œPromptœ,œidœ:œPrompt-f4xQ5œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-zhgF5{œfieldNameœ:œsystem_messageœ,œidœ:œOpenAIModel-zhgF5œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-f4xQ5", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-f4xQ5œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-zhgF5", + "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œOpenAIModel-zhgF5œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ - { - "data": { - "description": "Represents a group of agents, defining how they should collaborate and the tasks they should perform.", - "display_name": "Hierarchical Crew", - "id": "HierarchicalCrewComponent-Y0Uvf", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Represents a group of agents, defining how they should collaborate and the tasks they should perform.", - "display_name": "Hierarchical Crew", - "documentation": "", - "edited": false, - "field_order": [ - "verbose", - "memory", - "use_cache", - "max_rpm", - "share_crew", - "function_calling_llm", - "agents", - "tasks", - "manager_llm", - "manager_agent" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Output", - "method": "build_output", - "name": "output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "agents": { - "advanced": false, - "display_name": "Agents", - "dynamic": false, - "info": "", - "input_types": [ - "Agent" - ], - "list": true, - "name": "agents", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import os\n\nfrom crewai import Crew, Process\n\nfrom langflow.base.agents.crewai.crew import BaseCrewComponent\nfrom langflow.io import HandleInput, SecretStrInput\n\n\nclass HierarchicalCrewComponent(BaseCrewComponent):\n display_name: str = \"Hierarchical Crew\"\n description: str = (\n \"Represents a group of agents, defining how they should collaborate and the tasks they should perform.\"\n )\n documentation: str = \"https://docs.crewai.com/how-to/Hierarchical/\"\n icon = \"CrewAI\"\n\n inputs = [\n *BaseCrewComponent._base_inputs,\n HandleInput(name=\"agents\", display_name=\"Agents\", input_types=[\"Agent\"], is_list=True),\n HandleInput(name=\"tasks\", display_name=\"Tasks\", input_types=[\"HierarchicalTask\"], is_list=True),\n HandleInput(name=\"manager_llm\", display_name=\"Manager LLM\", input_types=[\"LanguageModel\"], required=False),\n HandleInput(name=\"manager_agent\", display_name=\"Manager Agent\", input_types=[\"Agent\"], required=False),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n value=\"OPENAI_API_KEY\",\n ),\n ]\n\n def build_crew(self) -> Crew:\n tasks, agents = self.get_tasks_and_agents()\n\n # Set the OpenAI API Key\n if self.openai_api_key:\n os.environ[\"OPENAI_API_KEY\"] = self.openai_api_key\n\n return Crew(\n agents=agents,\n tasks=tasks,\n process=Process.hierarchical,\n verbose=self.verbose,\n memory=self.memory,\n cache=self.use_cache,\n max_rpm=self.max_rpm,\n share_crew=self.share_crew,\n function_calling_llm=self.function_calling_llm,\n manager_agent=self.manager_agent,\n manager_llm=self.manager_llm,\n step_callback=self.get_step_callback(),\n task_callback=self.get_task_callback(),\n )\n" - }, - "function_calling_llm": { - "advanced": true, - "display_name": "Function Calling LLM", - "dynamic": false, - "info": "Turns the ReAct CrewAI agent into a function-calling agent", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "function_calling_llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "manager_agent": { - "advanced": false, - "display_name": "Manager Agent", - "dynamic": false, - "info": "", - "input_types": [ - "Agent" - ], - "list": false, - "name": "manager_agent", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "manager_llm": { - "advanced": false, - "display_name": "Manager LLM", - "dynamic": false, - "info": "", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "manager_llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "max_rpm": { - "advanced": true, - "display_name": "Max RPM", - "dynamic": false, - "info": "", - "list": false, - "name": "max_rpm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 100 - }, - "memory": { - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "openai_api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "share_crew": { - "advanced": true, - "display_name": "Share Crew", - "dynamic": false, - "info": "", - "list": false, - "name": "share_crew", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "tasks": { - "advanced": false, - "display_name": "Tasks", - "dynamic": false, - "info": "", - "input_types": [ - "HierarchicalTask" - ], - "list": true, - "name": "tasks", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "use_cache": { - "advanced": true, - "display_name": "Cache", - "dynamic": false, - "info": "", - "list": false, - "name": "use_cache", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 0 - } - } - }, - "type": "HierarchicalCrewComponent" - }, - "dragging": false, - "height": 516, - "id": "HierarchicalCrewComponent-Y0Uvf", - "position": { - "x": 568, - "y": 352.296875 - }, - "selected": false, - "type": "genericNode", - "width": 432 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "id": "OpenAIModel-Yjtpu", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "system_message", - "stream", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "api_key", - "temperature", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "load_from_db": false, - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 700, - "id": "OpenAIModel-Yjtpu", - "position": { - "x": -1222.8457213471152, - "y": 699.9983009041272 - }, - "positionAbsolute": { - "x": -1222.8457213471152, - "y": 699.9983009041272 - }, - "selected": false, - "type": "genericNode", - "width": 432 - }, - { - "data": { - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "id": "ChatOutput-VzVJK", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "should_store_message", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 347, - "id": "ChatOutput-VzVJK", - "position": { - "x": 1070.9148596889393, - "y": 499.80777483894144 - }, - "positionAbsolute": { - "x": 1070.9148596889393, - "y": 499.80777483894144 - }, - "selected": false, - "type": "genericNode", - "width": 432 - }, - { - "data": { - "description": "Each task must have a description, an expected output and an agent responsible for execution.", - "display_name": "Hierarchical Task", - "id": "HierarchicalTaskComponent-hE8H5", - "node": { - "base_classes": [ - "HierarchicalTask" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Each task must have a description, an expected output and an agent responsible for execution.", - "display_name": "Hierarchical Task", - "documentation": "", - "edited": false, - "field_order": [ - "task_description", - "expected_output", - "tools" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Task", - "method": "build_task", - "name": "task_output", - "selected": "HierarchicalTask", - "types": [ - "HierarchicalTask" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.agents.crewai.tasks import HierarchicalTask\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, MultilineInput, Output\n\n\nclass HierarchicalTaskComponent(Component):\n display_name: str = \"Hierarchical Task\"\n description: str = \"Each task must have a description, an expected output and an agent responsible for execution.\"\n icon = \"CrewAI\"\n inputs = [\n MultilineInput(\n name=\"task_description\",\n display_name=\"Description\",\n info=\"Descriptive text detailing task's purpose and execution.\",\n ),\n MultilineInput(\n name=\"expected_output\",\n display_name=\"Expected Output\",\n info=\"Clear definition of expected task outcome.\",\n ),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"List of tools/resources limited for task execution. Uses the Agent tools by default.\",\n required=False,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Task\", name=\"task_output\", method=\"build_task\"),\n ]\n\n def build_task(self) -> HierarchicalTask:\n task = HierarchicalTask(\n description=self.task_description,\n expected_output=self.expected_output,\n tools=self.tools or [],\n )\n self.status = task\n return task\n" - }, - "expected_output": { - "advanced": false, - "display_name": "Expected Output", - "dynamic": false, - "info": "Clear definition of expected task outcome.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "expected_output", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Succinct response that answers the User's query." - }, - "task_description": { - "advanced": false, - "display_name": "Description", - "dynamic": false, - "info": "Descriptive text detailing task's purpose and execution.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "task_description", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "tools": { - "advanced": true, - "display_name": "Tools", - "dynamic": false, - "info": "List of tools/resources limited for task execution. Uses the Agent tools by default.", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - } - } - }, - "type": "HierarchicalTaskComponent" - }, - "dragging": false, - "height": 480, - "id": "HierarchicalTaskComponent-hE8H5", - "position": { - "x": 63.673086094601445, - "y": -375.5883288441139 - }, - "positionAbsolute": { - "x": 63.673086094601445, - "y": -375.5883288441139 - }, - "selected": false, - "type": "genericNode", - "width": 432 - }, - { - "data": { - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "id": "CrewAIAgentComponent-EbpXd", - "node": { - "base_classes": [ - "Agent" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "kwargs" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Agent", - "method": "build_output", - "name": "output", - "selected": "Agent", - "types": [ - "Agent" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "allow_code_execution": { - "advanced": true, - "display_name": "Allow Code Execution", - "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "advanced": false, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "backstory": { - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "backstory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You are a reliable researcher and journalist " - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent\n\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass CrewAIAgentComponent(Component):\n display_name = \"CrewAI Agent\"\n description = \"Represents an agent of CrewAI.\"\n documentation: str = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(name=\"backstory\", display_name=\"Backstory\", info=\"The backstory of the agent.\"),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agents disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=False,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"kwargs\",\n display_name=\"kwargs\",\n info=\"kwargs of agent.\",\n is_list=True,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Agent\", name=\"output\", method=\"build_output\"),\n ]\n\n def build_output(self) -> Agent:\n kwargs = self.kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **kwargs,\n )\n self.status = repr(agent)\n return agent\n" - }, - "goal": { - "advanced": false, - "display_name": "Goal", - "dynamic": false, - "info": "The objective of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Search for information about the User's query and answer as best as you can" - }, - "kwargs": { - "advanced": true, - "display_name": "kwargs", - "dynamic": false, - "info": "kwargs of agent.", - "list": true, - "name": "kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "llm": { - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "memory": { - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "Whether the agent should have memory or not", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "role": { - "advanced": false, - "display_name": "Role", - "dynamic": false, - "info": "The role of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Research" - }, - "tools": { - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "Tools at agents disposal", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": [] - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - } - } - }, - "type": "CrewAIAgentComponent" - }, - "dragging": false, - "height": 746, - "id": "CrewAIAgentComponent-EbpXd", - "position": { - "x": -479.3544836211363, - "y": 184.85118314299666 - }, - "positionAbsolute": { - "x": -479.3544836211363, - "y": 184.85118314299666 - }, - "selected": false, - "type": "genericNode", - "width": 432 - }, - { - "data": { - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "id": "CrewAIAgentComponent-9D8ao", - "node": { - "base_classes": [ - "Agent" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", - "edited": false, - "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "kwargs" - ], - "frozen": false, - "icon": "CrewAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Agent", - "method": "build_output", - "name": "output", - "selected": "Agent", - "types": [ - "Agent" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "allow_code_execution": { - "advanced": true, - "display_name": "Allow Code Execution", - "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "advanced": false, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "backstory": { - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "backstory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You are polite and helpful. You've always been a beacon of politeness." - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from crewai import Agent\n\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass CrewAIAgentComponent(Component):\n display_name = \"CrewAI Agent\"\n description = \"Represents an agent of CrewAI.\"\n documentation: str = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(name=\"backstory\", display_name=\"Backstory\", info=\"The backstory of the agent.\"),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agents disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=False,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"kwargs\",\n display_name=\"kwargs\",\n info=\"kwargs of agent.\",\n is_list=True,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Agent\", name=\"output\", method=\"build_output\"),\n ]\n\n def build_output(self) -> Agent:\n kwargs = self.kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **kwargs,\n )\n self.status = repr(agent)\n return agent\n" - }, - "goal": { - "advanced": false, - "display_name": "Goal", - "dynamic": false, - "info": "The objective of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "goal", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You can answer general questions from the User and may call others for help if needed." - }, - "kwargs": { - "advanced": true, - "display_name": "kwargs", - "dynamic": false, - "info": "kwargs of agent.", - "list": true, - "name": "kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "llm": { - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "memory": { - "advanced": true, - "display_name": "Memory", - "dynamic": false, - "info": "Whether the agent should have memory or not", - "list": false, - "name": "memory", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "role": { - "advanced": false, - "display_name": "Role", - "dynamic": false, - "info": "The role of the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "role", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Manager" - }, - "tools": { - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "Tools at agents disposal", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": [] - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - } - } - }, - "type": "CrewAIAgentComponent" - }, - "dragging": false, - "height": 746, - "id": "CrewAIAgentComponent-9D8ao", - "position": { - "x": -451.69853654304495, - "y": 1664.003205846104 - }, - "positionAbsolute": { - "x": -451.69853654304495, - "y": 1664.003205846104 - }, - "selected": false, - "type": "genericNode", - "width": 432 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "id": "OpenAIModel-HgNnu", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "system_message", - "stream", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "api_key", - "temperature", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "load_from_db": false, - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 700, - "id": "OpenAIModel-HgNnu", - "position": { - "x": -1157.0105401589535, - "y": 1699.4665001507685 - }, - "positionAbsolute": { - "x": -1157.0105401589535, - "y": 1699.4665001507685 - }, - "selected": false, - "type": "genericNode", - "width": 432 - }, { "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-eqGhn", + "id": "Prompt-u7GZR", "node": { "base_classes": [ "Message" @@ -2141,26 +298,21 @@ "conditional_paths": [], "custom_fields": { "template": [ - "query" + "previous_response" ] }, "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", "documentation": "", "edited": false, - "error": null, "field_order": [ "template" ], "frozen": false, - "full_path": null, "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, - "name": "", "output_types": [], "outputs": [ { @@ -2196,9 +348,9 @@ "type": "code", "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, - "query": { + "previous_response": { "advanced": false, - "display_name": "query", + "display_name": "previous_response", "dynamic": false, "field_type": "str", "fileTypes": [], @@ -2211,8 +363,7 @@ "list": false, "load_from_db": false, "multiline": true, - "name": "query", - "password": false, + "name": "previous_response", "placeholder": "", "required": false, "show": true, @@ -2221,47 +372,52 @@ "value": "" }, "template": { + "_input_type": "PromptInput", "advanced": false, "display_name": "Template", "dynamic": false, "info": "", "list": false, + "load_from_db": false, "name": "template", "placeholder": "", "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "type": "prompt", - "value": "User's query:\n{query}\n\nRespond to the user with as much as information as you can about the topic. Delete if needed. If it is just a general query (e.g a greeting) you can respond them directly." + "value": "\n\nRESEARCH PLAN: {previous_response}\n\nUse Tavily Search to investigate the queries and analyze the findings.\nFocus on academic and reliable sources.\n\nSteps:\n1. Search using provided queries\n2. Analyze search results\n3. Verify source credibility\n4. Extract key findings\n\nFormat findings as:\n\nSEARCH RESULTS:\n[Key findings from searches]\n\nSOURCE ANALYSIS:\n[Credibility assessment]\n\nMAIN INSIGHTS:\n[Critical discoveries]\n\nEVIDENCE QUALITY:\n[Evaluation of findings]" } - } + }, + "tool_mode": false }, "type": "Prompt" }, "dragging": false, - "height": 475, - "id": "Prompt-eqGhn", + "height": 347, + "id": "Prompt-u7GZR", "position": { - "x": -561.9017558579421, - "y": -433.5913161630874 + "x": 1803.2315476328304, + "y": 839.0423490089254 }, "positionAbsolute": { - "x": -561.9017558579421, - "y": -433.5913161630874 + "x": 1803.2315476328304, + "y": 839.0423490089254 }, "selected": false, "type": "genericNode", - "width": 432 + "width": 320 }, { "data": { - "id": "ChatInput-xgRl9", + "id": "ChatInput-Mzp4f", "node": { "base_classes": [ "Message" ], "beta": false, + "category": "inputs", "conditional_paths": [], "custom_fields": {}, "description": "Get chat inputs from the Playground.", @@ -2274,11 +430,16 @@ "sender", "sender_name", "session_id", - "files" + "files", + "background_color", + "chat_icon", + "text_color" ], "frozen": false, "icon": "MessagesSquare", + "key": "ChatInput", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -2358,6 +519,7 @@ "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" }, "files": { + "_input_type": "FileInput", "advanced": true, "display_name": "Files", "dynamic": false, @@ -2399,6 +561,7 @@ "value": "" }, "input_value": { + "_input_type": "MultilineInput", "advanced": false, "display_name": "Text", "dynamic": false, @@ -2417,10 +580,12 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "What is Langflow?" + "value": "Research the effectiveness of different prompt engineering techniques in controlling AI hallucinations, with focus on real-world applications and empirical studies." }, "sender": { + "_input_type": "DropdownInput", "advanced": true, + "combobox": false, "display_name": "Sender Type", "dynamic": false, "info": "Type of sender.", @@ -2438,6 +603,7 @@ "value": "User" }, "sender_name": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Sender Name", "dynamic": false, @@ -2458,6 +624,7 @@ "value": "User" }, "session_id": { + "_input_type": "MessageTextInput", "advanced": true, "display_name": "Session ID", "dynamic": false, @@ -2478,6 +645,7 @@ "value": "" }, "should_store_message": { + "_input_type": "BoolInput", "advanced": true, "display_name": "Store Messages", "dynamic": false, @@ -2518,62 +686,62 @@ "type": "ChatInput" }, "dragging": false, - "height": 347, - "id": "ChatInput-xgRl9", + "height": 234, + "id": "ChatInput-Mzp4f", "position": { - "x": -1227.1161422332996, - "y": -380.26504479310324 + "x": 756.0075981758582, + "y": 756.7423476254241 }, "positionAbsolute": { - "x": -1227.1161422332996, - "y": -380.26504479310324 + "x": 756.0075981758582, + "y": 756.7423476254241 }, "selected": false, "type": "genericNode", - "width": 432 + "width": 320 }, { "data": { - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "id": "CrewAIAgentComponent-UMpxO", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-mWv8X", "node": { "base_classes": [ - "Agent" + "Message" ], "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "Represents an agent of CrewAI.", - "display_name": "CrewAI Agent", - "documentation": "https://docs.crewai.com/how-to/LLM-Connections/", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", "edited": false, "field_order": [ - "role", - "goal", - "backstory", - "tools", - "llm", - "memory", - "verbose", - "allow_delegation", - "allow_code_execution", - "kwargs" + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" ], "frozen": false, - "icon": "CrewAI", + "icon": "MessagesSquare", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ { "cache": true, - "display_name": "Agent", - "method": "build_output", - "name": "output", - "selected": "Agent", + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Agent" + "Message" ], "value": "__UNDEFINED__" } @@ -2581,56 +749,49 @@ "pinned": false, "template": { "_type": "Component", - "allow_code_execution": { + "background_color": { + "_input_type": "MessageTextInput", "advanced": true, - "display_name": "Allow Code Execution", + "display_name": "Background Color", "dynamic": false, - "info": "Whether the agent is allowed to execute code.", - "list": false, - "name": "allow_code_execution", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "allow_delegation": { - "advanced": false, - "display_name": "Allow Delegation", - "dynamic": false, - "info": "Whether the agent is allowed to delegate tasks to other agents.", - "list": false, - "name": "allow_delegation", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "backstory": { - "advanced": false, - "display_name": "Backstory", - "dynamic": false, - "info": "The backstory of the agent.", + "info": "The background color of the icon.", "input_types": [ "Message" ], "list": false, "load_from_db": false, - "multiline": true, - "name": "backstory", + "name": "background_color", "placeholder": "", "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "You are a reliable researcher and journalist " + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" }, "code": { "advanced": true, @@ -2648,20 +809,42 @@ "show": true, "title_case": false, "type": "code", - "value": "from crewai import Agent\n\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output\n\n\nclass CrewAIAgentComponent(Component):\n display_name = \"CrewAI Agent\"\n description = \"Represents an agent of CrewAI.\"\n documentation: str = \"https://docs.crewai.com/how-to/LLM-Connections/\"\n icon = \"CrewAI\"\n\n inputs = [\n MultilineInput(name=\"role\", display_name=\"Role\", info=\"The role of the agent.\"),\n MultilineInput(name=\"goal\", display_name=\"Goal\", info=\"The objective of the agent.\"),\n MultilineInput(name=\"backstory\", display_name=\"Backstory\", info=\"The backstory of the agent.\"),\n HandleInput(\n name=\"tools\",\n display_name=\"Tools\",\n input_types=[\"Tool\"],\n is_list=True,\n info=\"Tools at agents disposal\",\n value=[],\n ),\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"Language model that will run the agent.\",\n input_types=[\"LanguageModel\"],\n ),\n BoolInput(\n name=\"memory\",\n display_name=\"Memory\",\n info=\"Whether the agent should have memory or not\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"verbose\",\n display_name=\"Verbose\",\n advanced=True,\n value=False,\n ),\n BoolInput(\n name=\"allow_delegation\",\n display_name=\"Allow Delegation\",\n info=\"Whether the agent is allowed to delegate tasks to other agents.\",\n value=True,\n ),\n BoolInput(\n name=\"allow_code_execution\",\n display_name=\"Allow Code Execution\",\n info=\"Whether the agent is allowed to execute code.\",\n value=False,\n advanced=True,\n ),\n DictInput(\n name=\"kwargs\",\n display_name=\"kwargs\",\n info=\"kwargs of agent.\",\n is_list=True,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Agent\", name=\"output\", method=\"build_output\"),\n ]\n\n def build_output(self) -> Agent:\n kwargs = self.kwargs or {}\n agent = Agent(\n role=self.role,\n goal=self.goal,\n backstory=self.backstory,\n llm=self.llm,\n verbose=self.verbose,\n memory=self.memory,\n tools=self.tools or [],\n allow_delegation=self.allow_delegation,\n allow_code_execution=self.allow_code_execution,\n **kwargs,\n )\n self.status = repr(agent)\n return agent\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" }, - "goal": { - "advanced": false, - "display_name": "Goal", + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", "dynamic": false, - "info": "The objective of the agent.", + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", "input_types": [ "Message" ], "list": false, "load_from_db": false, - "multiline": true, - "name": "goal", + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", "placeholder": "", "required": false, "show": true, @@ -2669,48 +852,81 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "Evaluate the information for misleading or biased data." - }, - "kwargs": { - "advanced": true, - "display_name": "kwargs", - "dynamic": false, - "info": "kwargs of agent.", - "list": true, - "name": "kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "llm": { - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "Language model that will run the agent.", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", "value": "" }, - "memory": { + "sender": { + "_input_type": "DropdownInput", "advanced": true, - "display_name": "Memory", + "combobox": false, + "display_name": "Sender Type", "dynamic": false, - "info": "Whether the agent should have memory or not", + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], "list": false, - "name": "memory", + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", "placeholder": "", "required": false, "show": true, @@ -2719,82 +935,201 @@ "type": "bool", "value": true }, - "role": { - "advanced": false, - "display_name": "Role", + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", "dynamic": false, - "info": "The role of the agent.", + "info": "The text color of the name", "input_types": [ "Message" ], "list": false, "load_from_db": false, - "multiline": true, - "name": "role", + "name": "text_color", "placeholder": "", "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "Editor" - }, - "tools": { - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "Tools at agents disposal", - "input_types": [ - "Tool" - ], - "list": true, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": [] - }, - "verbose": { - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false + "value": "" } - } + }, + "tool_mode": false }, - "type": "CrewAIAgentComponent" + "type": "ChatOutput" }, "dragging": false, - "height": 746, - "id": "CrewAIAgentComponent-UMpxO", + "height": 234, + "id": "ChatOutput-mWv8X", "position": { - "x": -397.2627184897183, - "y": 892.6280687419107 + "x": 3200.774558432761, + "y": 853.9881404769172 }, "positionAbsolute": { - "x": -397.2627184897183, - "y": 892.6280687419107 + "x": 3200.774558432761, + "y": 853.9881404769172 }, "selected": false, "type": "genericNode", - "width": 432 + "width": 320 }, { "data": { - "id": "SearchAPI-Yokat", + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-yDDjW", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "search_results", + "input_value" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "input_value": { + "advanced": false, + "display_name": "input_value", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "search_results": { + "advanced": false, + "display_name": "search_results", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "search_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "RESEARCH FINDINGS: {search_results}\nORIGINAL QUERY: {input_value}\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 433, + "id": "Prompt-yDDjW", + "position": { + "x": 2504.138359606453, + "y": 434.061360540584 + }, + "positionAbsolute": { + "x": 2504.138359606453, + "y": 434.061360540584 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "id": "TavilyAISearch-rI4aD", "node": { "base_classes": [ "Data", @@ -2803,18 +1138,23 @@ "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "Call the searchapi.io API with result limiting", - "display_name": "Search API", - "documentation": "https://www.searchapi.io/docs/google", + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "documentation": "https://docs.tavily.com/", "edited": false, "field_order": [ - "engine", "api_key", - "input_value", - "search_params" + "query", + "search_depth", + "topic", + "max_results", + "include_images", + "include_answer" ], "frozen": false, + "icon": "TavilyIcon", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -2851,10 +1191,11 @@ "template": { "_type": "Component", "api_key": { + "_input_type": "SecretStrInput", "advanced": false, - "display_name": "SearchAPI API Key", + "display_name": "Tavily API Key", "dynamic": false, - "info": "", + "info": "Your Tavily API Key.", "input_types": [ "Message" ], @@ -2884,55 +1225,46 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain.tools import StructuredTool\nfrom langchain_community.utilities.searchapi import SearchApiAPIWrapper\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import DictInput, IntInput, MessageTextInput, MultilineInput, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass SearchAPIComponent(LCToolComponent):\n display_name: str = \"Search API\"\n description: str = \"Call the searchapi.io API with result limiting\"\n name = \"SearchAPI\"\n documentation: str = \"https://www.searchapi.io/docs/google\"\n\n inputs = [\n MessageTextInput(name=\"engine\", display_name=\"Engine\", value=\"google\"),\n SecretStrInput(name=\"api_key\", display_name=\"SearchAPI API Key\", required=True),\n MultilineInput(\n name=\"input_value\",\n display_name=\"Input\",\n ),\n DictInput(name=\"search_params\", display_name=\"Search parameters\", advanced=True, is_list=True),\n IntInput(name=\"max_results\", display_name=\"Max Results\", value=5, advanced=True),\n IntInput(name=\"max_snippet_length\", display_name=\"Max Snippet Length\", value=100, advanced=True),\n ]\n\n class SearchAPISchema(BaseModel):\n query: str = Field(..., description=\"The search query\")\n params: dict[str, Any] = Field(default_factory=dict, description=\"Additional search parameters\")\n max_results: int = Field(5, description=\"Maximum number of results to return\")\n max_snippet_length: int = Field(100, description=\"Maximum length of each result snippet\")\n\n def _build_wrapper(self):\n return SearchApiAPIWrapper(engine=self.engine, searchapi_api_key=self.api_key)\n\n def build_tool(self) -> Tool:\n wrapper = self._build_wrapper()\n\n def search_func(\n query: str, params: dict[str, Any] | None = None, max_results: int = 5, max_snippet_length: int = 100\n ) -> list[dict[str, Any]]:\n params = params or {}\n full_results = wrapper.results(query=query, **params)\n organic_results = full_results.get(\"organic_results\", [])[:max_results]\n\n limited_results = []\n for result in organic_results:\n limited_result = {\n \"title\": result.get(\"title\", \"\")[:max_snippet_length],\n \"link\": result.get(\"link\", \"\"),\n \"snippet\": result.get(\"snippet\", \"\")[:max_snippet_length],\n }\n limited_results.append(limited_result)\n\n return limited_results\n\n tool = StructuredTool.from_function(\n name=\"search_api\",\n description=\"Search for recent results using searchapi.io with result limiting\",\n func=search_func,\n args_schema=self.SearchAPISchema,\n )\n\n self.status = f\"Search API Tool created with engine: {self.engine}\"\n return tool\n\n def run_model(self) -> list[Data]:\n tool = self.build_tool()\n results = tool.run(\n {\n \"query\": self.input_value,\n \"params\": self.search_params or {},\n \"max_results\": self.max_results,\n \"max_snippet_length\": self.max_snippet_length,\n }\n )\n\n data_list = [Data(data=result, text=result.get(\"snippet\", \"\")) for result in results]\n\n self.status = data_list\n return data_list\n" + "value": "from enum import Enum\n\nimport httpx\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass TavilySearchDepth(Enum):\n BASIC = \"basic\"\n ADVANCED = \"advanced\"\n\n\nclass TavilySearchTopic(Enum):\n GENERAL = \"general\"\n NEWS = \"news\"\n\n\nclass TavilySearchSchema(BaseModel):\n query: str = Field(..., description=\"The search query you want to execute with Tavily.\")\n search_depth: TavilySearchDepth = Field(TavilySearchDepth.BASIC, description=\"The depth of the search.\")\n topic: TavilySearchTopic = Field(TavilySearchTopic.GENERAL, description=\"The category of the search.\")\n max_results: int = Field(5, description=\"The maximum number of search results to return.\")\n include_images: bool = Field(default=False, description=\"Include a list of query-related images in the response.\")\n include_answer: bool = Field(default=False, description=\"Include a short answer to original query.\")\n\n\nclass TavilySearchToolComponent(LCToolComponent):\n display_name = \"Tavily AI Search\"\n description = \"\"\"**Tavily AI** is a search engine optimized for LLMs and RAG, \\\n aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n\"\"\"\n icon = \"TavilyIcon\"\n name = \"TavilyAISearch\"\n documentation = \"https://docs.tavily.com/\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Tavily API Key\",\n required=True,\n info=\"Your Tavily API Key.\",\n ),\n MessageTextInput(\n name=\"query\",\n display_name=\"Search Query\",\n info=\"The search query you want to execute with Tavily.\",\n ),\n DropdownInput(\n name=\"search_depth\",\n display_name=\"Search Depth\",\n info=\"The depth of the search.\",\n options=list(TavilySearchDepth),\n value=TavilySearchDepth.ADVANCED,\n advanced=True,\n ),\n DropdownInput(\n name=\"topic\",\n display_name=\"Search Topic\",\n info=\"The category of the search.\",\n options=list(TavilySearchTopic),\n value=TavilySearchTopic.GENERAL,\n advanced=True,\n ),\n IntInput(\n name=\"max_results\",\n display_name=\"Max Results\",\n info=\"The maximum number of search results to return.\",\n value=5,\n advanced=True,\n ),\n BoolInput(\n name=\"include_images\",\n display_name=\"Include Images\",\n info=\"Include a list of query-related images in the response.\",\n value=True,\n advanced=True,\n ),\n BoolInput(\n name=\"include_answer\",\n display_name=\"Include Answer\",\n info=\"Include a short answer to original query.\",\n value=True,\n advanced=True,\n ),\n ]\n\n def run_model(self) -> list[Data]:\n # Convert string values to enum instances with validation\n try:\n search_depth_enum = (\n self.search_depth\n if isinstance(self.search_depth, TavilySearchDepth)\n else TavilySearchDepth(str(self.search_depth).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid search depth value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n try:\n topic_enum = (\n self.topic if isinstance(self.topic, TavilySearchTopic) else TavilySearchTopic(str(self.topic).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid topic value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n return self._tavily_search(\n self.query,\n search_depth=search_depth_enum,\n topic=topic_enum,\n max_results=self.max_results,\n include_images=self.include_images,\n include_answer=self.include_answer,\n )\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"tavily_search\",\n description=\"Perform a web search using the Tavily API.\",\n func=self._tavily_search,\n args_schema=TavilySearchSchema,\n )\n\n def _tavily_search(\n self,\n query: str,\n *,\n search_depth: TavilySearchDepth = TavilySearchDepth.BASIC,\n topic: TavilySearchTopic = TavilySearchTopic.GENERAL,\n max_results: int = 5,\n include_images: bool = False,\n include_answer: bool = False,\n ) -> list[Data]:\n # Validate enum values\n if not isinstance(search_depth, TavilySearchDepth):\n msg = f\"Invalid search_depth value: {search_depth}\"\n raise TypeError(msg)\n if not isinstance(topic, TavilySearchTopic):\n msg = f\"Invalid topic value: {topic}\"\n raise TypeError(msg)\n\n try:\n url = \"https://api.tavily.com/search\"\n headers = {\n \"content-type\": \"application/json\",\n \"accept\": \"application/json\",\n }\n payload = {\n \"api_key\": self.api_key,\n \"query\": query,\n \"search_depth\": search_depth.value,\n \"topic\": topic.value,\n \"max_results\": max_results,\n \"include_images\": include_images,\n \"include_answer\": include_answer,\n }\n\n with httpx.Client() as client:\n response = client.post(url, json=payload, headers=headers)\n\n response.raise_for_status()\n search_results = response.json()\n\n data_results = [\n Data(\n data={\n \"title\": result.get(\"title\"),\n \"url\": result.get(\"url\"),\n \"content\": result.get(\"content\"),\n \"score\": result.get(\"score\"),\n }\n )\n for result in search_results.get(\"results\", [])\n ]\n\n if include_answer and search_results.get(\"answer\"):\n data_results.insert(0, Data(data={\"answer\": search_results[\"answer\"]}))\n\n if include_images and search_results.get(\"images\"):\n data_results.append(Data(data={\"images\": search_results[\"images\"]}))\n\n self.status = data_results # type: ignore[assignment]\n\n except httpx.HTTPStatusError as e:\n error_message = f\"HTTP error: {e.response.status_code} - {e.response.text}\"\n logger.debug(error_message)\n self.status = error_message\n raise ToolException(error_message) from e\n except Exception as e:\n error_message = f\"Unexpected error: {e}\"\n logger.opt(exception=True).debug(\"Error running Tavily Search\")\n self.status = error_message\n raise ToolException(error_message) from e\n return data_results\n" }, - "engine": { - "advanced": false, - "display_name": "Engine", + "include_answer": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Answer", "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], + "info": "Include a short answer to original query.", "list": false, - "load_from_db": false, - "name": "engine", + "name": "include_answer", "placeholder": "", "required": false, "show": true, "title_case": false, - "trace_as_input": true, "trace_as_metadata": true, - "type": "str", - "value": "google" + "type": "bool", + "value": true }, - "input_value": { - "advanced": false, - "display_name": "Input", + "include_images": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Images", "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], + "info": "Include a list of query-related images in the response.", "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", + "name": "include_images", "placeholder": "", "required": false, "show": true, "title_case": false, - "trace_as_input": true, "trace_as_metadata": true, - "type": "str", - "value": "" + "type": "bool", + "value": true }, "max_results": { "_input_type": "IntInput", "advanced": true, "display_name": "Max Results", "dynamic": false, - "info": "", + "info": "The maximum number of search results to return.", "list": false, "name": "max_results", "placeholder": "", @@ -2943,14 +1275,1150 @@ "type": "int", "value": 5 }, - "max_snippet_length": { + "query": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Search Query", + "dynamic": false, + "info": "The search query you want to execute with Tavily.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "search_depth": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Depth", + "dynamic": false, + "info": "The depth of the search.", + "load_from_db": false, + "name": "search_depth", + "options": [ + "basic", + "advanced" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "advanced" + }, + "topic": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Topic", + "dynamic": false, + "info": "The category of the search.", + "load_from_db": false, + "name": "topic", + "options": [ + "general", + "news" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "general" + } + }, + "tool_mode": false + }, + "type": "TavilyAISearch" + }, + "dragging": false, + "height": 481, + "id": "TavilyAISearch-rI4aD", + "position": { + "x": 1802.2291194402355, + "y": 381.88177151343945 + }, + "positionAbsolute": { + "x": 1802.2291194402355, + "y": 381.88177151343945 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-Rc3MO", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { "_input_type": "IntInput", "advanced": true, - "display_name": "Max Snippet Length", + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", "dynamic": false, "info": "", "list": false, - "name": "max_snippet_length", + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-Rc3MO", + "position": { + "x": 1457.8987895868838, + "y": 543.8838473503562 + }, + "positionAbsolute": { + "x": 1457.8987895868838, + "y": 543.8838473503562 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-zhgF5", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-zhgF5", + "position": { + "x": 2860.2941186979524, + "y": 561.8661152181708 + }, + "positionAbsolute": { + "x": 2860.2941186979524, + "y": 561.8661152181708 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-gBUJ9", + "node": { + "description": "# Research Agent \n\nWelcome to the Research Agent! This flow helps you conduct in-depth research on various topics using AI-powered tools and analysis.\n\n## Instructions\n1. Enter Your Research Query\n - Type your research question or topic into the Chat Input node.\n - Be specific and clear about what you want to investigate.\n\n2. Generate Research Plan\n - The system will create a focused research plan based on your query.\n - This plan includes key search queries and priorities.\n\n3. Conduct Web Search\n - The Tavily AI Search tool will perform web searches using the generated queries.\n - It focuses on finding academic and reliable sources.\n\n4. Analyze and Synthesize\n - The AI agent will review the search results and create a comprehensive synthesis.\n - The report includes an executive summary, methodology, findings, and conclusions.\n\n5. Review the Output\n - Read the final report in the Chat Output node.\n - Use this information as a starting point for further research or decision-making.\n\nRemember: You can refine your initial query for more specific results! 🔍📊", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "emerald" + } + }, + "type": "note" + }, + "dragging": false, + "height": 765, + "id": "note-gBUJ9", + "position": { + "x": 471.4335708918645, + "y": -9.732869247334605 + }, + "positionAbsolute": { + "x": 471.4335708918645, + "y": -9.732869247334605 + }, + "resizing": false, + "selected": false, + "style": { + "height": 765, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "id": "Agent-9E8IU", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Amazon Bedrock", + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix), display_name\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", "placeholder": "", "required": false, "show": true, @@ -2959,13 +2427,71 @@ "type": "int", "value": 100 }, - "search_params": { + "openai_api_base": { + "_input_type": "StrInput", "advanced": true, - "display_name": "Search parameters", + "display_name": "OpenAI API Base", "dynamic": false, - "info": "", + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", "list": true, - "name": "search_params", + "name": "output_schema", "placeholder": "", "required": false, "show": true, @@ -2973,43 +2499,450 @@ "trace_as_input": true, "type": "dict", "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are a research analyst with access to Tavily Search." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true } - } + }, + "tool_mode": false }, - "type": "SearchAPI" + "type": "Agent" }, "dragging": false, - "height": 612, - "id": "SearchAPI-Yokat", + "height": 658, + "id": "Agent-9E8IU", "position": { - "x": -1229.2392382339021, - "y": 59.93107827969652 + "x": 2156.60686936856, + "y": 439.4579572266066 }, "positionAbsolute": { - "x": -1229.2392382339021, - "y": 59.93107827969652 + "x": 2156.60686936856, + "y": 439.4579572266066 + }, + "selected": true, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-T4lL6", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "You are an expert research assistant.\n\nCreate a focused research plan that will guide our search.\n\nFormat your response exactly as:\n\nRESEARCH OBJECTIVE:\n[Clear statement of research goal]\n\nKEY SEARCH QUERIES:\n1. [Primary academic search query]\n2. [Secondary search query]\n3. [Alternative search approach]\n\nSEARCH PRIORITIES:\n- [What types of sources to focus on]\n- [Key aspects to investigate]\n- [Specific areas to explore]" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-T4lL6", + "position": { + "x": 1102.6079408836365, + "y": 550.2148817052229 + }, + "positionAbsolute": { + "x": 1102.6079408836365, + "y": 550.2148817052229 }, "selected": false, "type": "genericNode", - "width": 432 + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-f4xQ5", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "You are a research synthesis expert.\n\nCreate a comprehensive synthesis and report of our findings.\n\nFormat your response as:\n\nEXECUTIVE SUMMARY:\n[Key findings and implications]\n\nMETHODOLOGY:\n- Search Strategy Used\n- Sources Analyzed\n- Quality Assessment\n\nFINDINGS & ANALYSIS:\n[Detailed discussion of discoveries]\n\nCONCLUSIONS:\n[Main takeaways and insights]\n\nFUTURE DIRECTIONS:\n[Suggested next steps]\n\nIMPORTANT: For each major point or finding, include the relevant source link in square brackets at the end of the sentence or paragraph. For example: \"Harvard has developed a solid-state battery that charges in minutes. [Source: https://example.com/article]\"\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-f4xQ5", + "position": { + "x": 2498.9482347755306, + "y": 889.7491088138673 + }, + "positionAbsolute": { + "x": 2498.9482347755306, + "y": 889.7491088138673 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-86Le6", + "node": { + "description": "# 🔑 Tavily AI Search Needs API Key\n\nYou can get 1000 searches/month free [here](https://tavily.com/) ", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "lime" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-86Le6", + "position": { + "x": 1797.5781951055678, + "y": 206.30509875543274 + }, + "positionAbsolute": { + "x": 1797.5781951055678, + "y": 206.30509875543274 + }, + "selected": false, + "type": "noteNode", + "width": 325 } ], "viewport": { - "x": 538.2178429916559, - "y": 231.5938714083456, - "zoom": 0.25005698994252296 + "x": -1627.3021649072248, + "y": -234.56097308583958, + "zoom": 0.9538000505518524 } }, - "description": "This Agentic Flow has a Manager and a couple Workers. The manager can answer the user's question straightaway or delegate the task to other agents.", + "description": "Agent that generates focused plans, conducts web searches, and synthesizes findings into comprehensive reports.", "endpoint_name": null, - "icon": "GitFork", - "id": "6302081f-5af2-4b9f-bd19-2baaf7218ba6", + "icon": "TextSearchIcon", + "id": "67b16861-1344-465b-963a-c1c338623438", "is_component": false, - "last_tested_version": "1.0.12", - "name": "Hierarchical Tasks Agent", + "last_tested_version": "1.0.19.post2", + "name": "Research Agent", "tags": [ - "agents", - "openai", - "chatbots" + "assistants", + "agents" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json b/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json new file mode 100644 index 000000000..96214a4bc --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json @@ -0,0 +1,1132 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-FXOhu", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-E96kR", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-FXOhu{œdataTypeœ:œPromptœ,œidœ:œPrompt-FXOhuœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-E96kR{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-E96kRœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "selected": false, + "source": "Prompt-FXOhu", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-FXOhuœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-E96kR", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-E96kRœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + 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"conditional_paths": [], + "custom_fields": { + "template": [ + "product", + "pain_points", + "goals", + "current_solutions", + "target_audience", + "expertise_level" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "current_solutions": { + "advanced": false, + "display_name": "current_solutions", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "current_solutions", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "- Basic website blockers\n- Manual \"Do Not Disturb\" modes\n- Traditional time management apps\n- Paper planners and to-do lists\n- Pomodoro timer apps\n- Calendar blocking\n" + }, + "expertise_level": { + "advanced": false, + "display_name": "expertise_level", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "expertise_level", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Intermediate to Advanced - Users are familiar with basic productivity tools and concepts but seek more sophisticated solutions. They understand terms like \"deep work\" and \"time blocking\" and are comfortable adopting new technology that promises meaningful improvements to their workflow." + }, + "goals": { + "advanced": false, + "display_name": "goals", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "goals", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "- Achieve longer periods of uninterrupted focus\n- Improve work efficiency and output quality\n- Develop sustainable productivity habits\n- Better manage time and energy levels\n- Reduce stress from digital overwhelm\n- Create more balanced workdays" + }, + "pain_points": { + "advanced": false, + "display_name": "pain_points", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "pain_points", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "- Constant interruptions from notifications and social media\n- Difficulty maintaining sustained focus during deep work\n- Inconsistent productivity levels throughout the day\n- Struggle to build effective work routines\n- Time wasted switching between tasks\n- Burnout from poor work-life balance\n" + }, + "product": { + "advanced": false, + "display_name": "product", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "product", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "FocusFlow - An AI-powered productivity app that automatically detects and blocks digital distractions while learning from user behavior to create personalized focus schedules. Features include smart notification management, work pattern analysis, and adaptive focus modes." + }, + "target_audience": { + "advanced": false, + "display_name": "target_audience", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "target_audience", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Knowledge workers aged 25-45, primarily working in tech, creative, or professional services. They are tech-savvy professionals who work remotely or in hybrid settings, earning $75,000+ annually. They value work-life balance and are willing to invest in tools that boost their productivity. Many are active on LinkedIn and tech-focused platforms, regularly consuming content about personal development and productivity." + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "Product:\n{product}\n \nPain Points:\n{pain_points}\n \nGoals:\n{goals}\n \nCurrent Solutions:\n{current_solutions}\n \nSpecific Target Audience:\n{target_audience}\n\nExpertise Level:\n{expertise_level}\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 779, + "id": "Prompt-FXOhu", + "position": { + "x": 816.9328565352126, + "y": 189.70442453076902 + }, + "positionAbsolute": { + "x": 816.9328565352126, + "y": 189.70442453076902 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-5yMAo", + "node": { + "description": "# SEO Keyword Generator\nWelcome to the SEO Keywords Generator - an AI tool to create strategic keywords based on your product and audience profile!\n\n## Instructions\n\n1. **Fill Product Information**\n - Enter your product name and description\n - Keep it clear and specific\n - Highlight unique features and benefits\n\n2. **Define Pain Points**\n - List customer problems and challenges\n - Be specific about what frustrations they face\n - Include both practical and emotional pain points\n\n3. **Set Goals & Solutions**\n - Specify customer objectives\n - Detail how they currently solve problems\n - Outline desired outcomes\n\n4. **Target Audience Details**\n - Define demographics and characteristics\n - Include expertise level\n - Describe behavior patterns and preferences\n\n5. **Review Output**\n - Examine generated keywords\n - Check relevance and search intent\n - Use insights for SEO strategy planning\n\nRemember: The more detailed your input, the more targeted and effective your keywords will be! 🎯🔍✨", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 607, + "id": "note-5yMAo", + "position": { + "x": 221.74248905040588, + "y": 363.5469410934121 + }, + "positionAbsolute": { + "x": 221.74248905040588, + "y": 363.5469410934121 + }, + "resizing": false, + "selected": false, + "style": { + "height": 607, + "width": 489 + }, + "type": "noteNode", + "width": 489 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-aMAQ2", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "You are a digital marketing strategist specialized in generating highly relevant, optimized keywords for a product’s specific target audience. Your task is to create a list of keywords that are not only attractive and impactful but also resonate with the needs and desires of the customers, capturing the core motivations driving them to seek a solution.\n\nBelow are details about the product, including its target audience, the pain points faced by this audience, and the current solutions they consider or use. Use this information to generate precise keywords that connect directly with the unique value of the product and with the customers' goals. Consider factors like the customer’s level of expertise and major market trends to create a powerful and well-grounded keyword list.\n\n### Product Information:\n- **Product:** – A brief description of the product, including what sets it apart in the market.\n- **Customer Pain Points:** – Specific pain points that the audience faces and that the product aims to address.\n- **Customer Goals:** – The primary goals and aspirations of the target audience that the product helps to achieve.\n- **Current Solutions Used:** – How the audience currently tries to address these pain points, including competitor solutions or alternatives.\n- **Specific Target Audience:** – A detailed description of the target audience, including demographics, interests, lifestyle, and behavioral profile.\n- **Customer Expertise Level:**– The level of familiarity or experience the audience has with similar or related solutions.\n\n### Guidelines for Keyword Generation:\n1. **Focus on Pain Points and Solutions**: Generate keywords that accurately reflect the customers’ pain points, clearly conveying how the product offers an effective and unique solution.\n2. **Emphasize Goals and Benefits**: Highlight keywords aligned with customer goals, emphasizing the positive impact and achievable results of the product.\n3. **Consider Competition and Differentiators**: Think about existing solutions and how the product stands out. Create keywords that emphasize differentiators and help the product stand out in a competitive landscape.\n4. **Tailor to Target Audience**: Use terms and phrases that resonate directly with the target audience’s profile, utilizing language and themes most appealing to this segment.\n5. **Customize to Expertise Level**: Adjust the complexity of the keywords according to the audience’s experience level, ensuring they are appealing and accessible.\n6. **Incorporate Market Trends**: Where possible, include keywords that reflect the latest trends in the sector, increasing the content’s relevance and timeliness.\n\n### Example Keyword Suggestions:\n- **For customer pain points:** – Use keywords that reinforce customer pain points, making it clear how the product can be a solution.\n- **For goals and aspirations:** – Keywords that symbolize the outcomes and goals desired by customers, such as ‘stress relief,’ ‘productivity boost.’\n- **For product differentiators:** – Keywords that contrast the product with current solutions, highlighting its unique advantages.\n\nFor each keyword generated, provide a brief explanation of how it connects with the product details and the target audience, ensuring the final list is powerful, strategic, and well-founded for maximum market impact." + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-aMAQ2", + "position": { + "x": 813.5727530934735, + "y": 991.0702563306074 + }, + "positionAbsolute": { + "x": 813.5727530934735, + "y": 991.0702563306074 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-aCpBy", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-aCpBy", + "position": { + "x": 1598.2529634286327, + "y": 623.4799714496987 + }, + "positionAbsolute": { + "x": 1598.2529634286327, + "y": 623.4799714496987 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-E96kR", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 543, + "id": "OpenAIModel-E96kR", + "position": { + "x": 1207.6180121002271, + "y": 400.34849438035565 + }, + "positionAbsolute": { + "x": 1207.6180121002271, + "y": 400.34849438035565 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-qiq3C", + "node": { + "description": "## Make sure to add your OpenAI API key from [platform.openai.com](https://platform.openai.com). ", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-qiq3C", + "position": { + "x": 1207.1996899547116, + "y": 260.0148704431837 + }, + "positionAbsolute": { + "x": 1207.1996899547116, + "y": 260.0148704431837 + }, + "selected": false, + "type": "noteNode", + "width": 325 + } + ], + "viewport": { + "x": -106.23719516361678, + "y": -93.96601486484758, + "zoom": 0.7759242611491008 + } + }, + "description": "Generates targeted SEO keywords based on product information, pain points, and customer profiles for strategic marketing.", + "endpoint_name": null, + "icon": "List", + "id": "3432cbdf-c4af-43b2-96ef-5f8155cf24d1", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "SEO Keyword Generator", + "tags": [ + "chatbots", + "assistants" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json b/src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json new file mode 100644 index 000000000..2d8579efb --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json @@ -0,0 +1,1361 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "CalculatorTool", + "id": "CalculatorTool-DF8xQ", + "name": "api_build_tool", + "output_types": [ + "Tool" + ] + }, + "targetHandle": { + "fieldName": "tools", + "id": "Agent-5e01q", + "inputTypes": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "type": "other" + } + }, + "id": "reactflow__edge-CalculatorTool-DF8xQ{œdataTypeœ:œCalculatorToolœ,œidœ:œCalculatorTool-DF8xQœ,œnameœ:œapi_build_toolœ,œoutput_typesœ:[œToolœ]}-Agent-5e01q{œfieldNameœ:œtoolsœ,œidœ:œAgent-5e01qœ,œinputTypesœ:[œToolœ,œBaseToolœ,œStructuredToolœ],œtypeœ:œotherœ}", + "source": "CalculatorTool-DF8xQ", + "sourceHandle": "{œdataTypeœ: œCalculatorToolœ, œidœ: œCalculatorTool-DF8xQœ, œnameœ: œapi_build_toolœ, œoutput_typesœ: [œToolœ]}", + "target": "Agent-5e01q", + "targetHandle": "{œfieldNameœ: œtoolsœ, œidœ: œAgent-5e01qœ, œinputTypesœ: [œToolœ, œBaseToolœ, œStructuredToolœ], œtypeœ: œotherœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Agent", + "id": "Agent-5e01q", + "name": "response", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-s1eJK", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Agent-5e01q{œdataTypeœ:œAgentœ,œidœ:œAgent-5e01qœ,œnameœ:œresponseœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-s1eJK{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-s1eJKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Agent-5e01q", + "sourceHandle": "{œdataTypeœ: œAgentœ, œidœ: œAgent-5e01qœ, œnameœ: œresponseœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-s1eJK", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-s1eJKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-KkcsZ", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "Agent-5e01q", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-KkcsZ{œdataTypeœ:œPromptœ,œidœ:œPrompt-KkcsZœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-Agent-5e01q{œfieldNameœ:œinput_valueœ,œidœ:œAgent-5e01qœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-KkcsZ", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-KkcsZœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "Agent-5e01q", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œAgent-5e01qœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-KkcsZ", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "monthly_infrastructure_costs", + "customer_support_cost", + "continuous_development_cost", + "desired_profit_margin", + "estimated_subscribers" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "continuous_development_cost": { + "advanced": false, + "display_name": "continuous_development_cost", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "continuous_development_cost", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "3000" + }, + "customer_support_cost": { + "advanced": false, + "display_name": "customer_support_cost", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "customer_support_cost", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "1000" + }, + "desired_profit_margin": { + "advanced": false, + "display_name": "desired_profit_margin", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "desired_profit_margin", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "30" + }, + "estimated_subscribers": { + "advanced": false, + "display_name": "estimated_subscribers", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "estimated_subscribers", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "200" + }, + "monthly_infrastructure_costs": { + "advanced": false, + "display_name": "monthly_infrastructure_costs", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "monthly_infrastructure_costs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "2000" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "To calculate the monthly subscription price of the software based on the following data:\n\nMonthly infrastructure costs: ${monthly_infrastructure_costs}\nCustomer support: ${customer_support_cost}\nContinuous development: {continuous_development_cost}\nDesired profit margin: {desired_profit_margin}%\nEstimated number of subscribers: {estimated_subscribers}\n\nFollow the step to formulate the answer:\nFixed costs:\nProfit margin:\nTotal amount needed:\nPrice per subscriber:\nThe minimum subscription price per subscriber is:" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 693, + "id": "Prompt-KkcsZ", + "position": { + "x": 1349.861745038984, + "y": 347.90475109976467 + }, + "positionAbsolute": { + "x": 1349.861745038984, + "y": 347.90475109976467 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-s1eJK", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-s1eJK", + "position": { + "x": 2240.3625274769397, + "y": 355.16302699218204 + }, + "positionAbsolute": { + "x": 2240.3625274769397, + "y": 355.16302699218204 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-H6OpG", + "node": { + "description": "# SaaS Pricing Calculator\n\nWelcome to the SaaS Pricing Calculator! This flow helps you determine the optimal monthly subscription price for your software service.\n\n## Instructions\n\n1. Prepare Your Data\n - Gather information on monthly infrastructure costs\n - Calculate customer support expenses\n - Estimate continuous development costs\n - Decide on your desired profit margin\n - Determine the estimated number of subscribers\n\n2. Input Values\n - Enter the gathered data into the respective fields in the Prompt node\n - Double-check the accuracy of your inputs\n\n3. Run the Flow\n - Click the \"Run\" button to start the calculation process\n - The flow will use Chain-of-Thought prompting to guide the AI through the steps\n\n4. Review the Results\n - Examine the output in the Chat Output node\n - The result will show a breakdown of costs and the final subscription price\n\n5. Adjust and Refine\n - If needed, modify your inputs to explore different pricing scenarios\n - Re-run the flow to see how changes affect the final price\n\nRemember: Regularly update your costs and subscriber estimates to keep your pricing model accurate and competitive! 💼📊", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 800, + "id": "note-H6OpG", + "position": { + "x": 689.7659055360411, + "y": 68.95847391680593 + }, + "positionAbsolute": { + "x": 689.7659055360411, + "y": 68.95847391680593 + }, + "resizing": false, + "selected": false, + "style": { + "height": 800, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "id": "Agent-5e01q", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Amazon Bedrock", + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix), display_name\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "# Subscription Pricing Calculator\n\n## Purpose\nCalculate the optimal monthly subscription price for a software product based on operational costs, desired profit margin, and estimated subscriber base.\n\n## Input Variables\nThe system requires the following inputs:\n- Monthly infrastructure costs (numeric)\n- Customer support costs (numeric)\n- Continuous development costs (numeric)\n- Desired profit margin (percentage)\n- Estimated number of subscribers (numeric)\n\n## Calculation Process\nFollow these steps to determine the subscription price:\n\n### Step 1: Total Monthly Costs\nCalculate the sum of all fixed operational costs:\n```\ntotal_monthly_costs = infrastructure_costs + support_costs + development_costs\n```\n\n### Step 2: Profit Margin Calculation\nCalculate the profit margin amount based on total costs:\n```\nprofit_amount = total_monthly_costs × (profit_margin_percentage / 100)\n```\n\n### Step 3: Total Revenue Required\nCalculate the total monthly revenue needed:\n```\ntotal_revenue_needed = total_monthly_costs + profit_amount\n```\n\n### Step 4: Per-Subscriber Price\nCalculate the minimum price per subscriber:\n```\nsubscription_price = total_revenue_needed ÷ estimated_subscribers\n```\n\n## Output Format\nPresent the results in the following structure:\n\nFixed costs: [sum of all costs]\nProfit margin: [calculated profit amount]\nTotal amount needed: [total revenue required]\nPrice per subscriber: [calculated subscription price]\n\nFinal recommendation: \"The minimum subscription price per subscriber should be [price] to achieve the desired profit margin of [percentage]%\"\n\n## Notes\n- All monetary values should be rounded to 2 decimal places\n- Ensure all input values are positive numbers\n- Validate that the estimated subscribers count is greater than zero\n- The profit margin percentage should be between 0 and 100" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-5e01q", + "position": { + "x": 1819.2633856623966, + "y": 138.32023808479687 + }, + "positionAbsolute": { + "x": 1819.2633856623966, + "y": 138.32023808479687 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "CalculatorTool-DF8xQ", + "node": { + "base_classes": [ + "Data", + "Tool" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Perform basic arithmetic operations on a given expression.", + "display_name": "Calculator", + "documentation": "", + "edited": false, + "field_order": [ + "expression" + ], + "frozen": false, + "icon": "calculator", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "run_model", + "name": "api_run_model", + "required_inputs": [], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Tool", + "method": "build_tool", + "name": "api_build_tool", + "required_inputs": [], + "selected": "Tool", + "types": [ + "Tool" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import ast\nimport operator\n\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import MessageTextInput\nfrom langflow.schema import Data\n\n\nclass CalculatorToolComponent(LCToolComponent):\n display_name = \"Calculator\"\n description = \"Perform basic arithmetic operations on a given expression.\"\n icon = \"calculator\"\n name = \"CalculatorTool\"\n\n inputs = [\n MessageTextInput(\n name=\"expression\",\n display_name=\"Expression\",\n info=\"The arithmetic expression to evaluate (e.g., '4*4*(33/22)+12-20').\",\n tool_mode=True,\n ),\n ]\n\n class CalculatorToolSchema(BaseModel):\n expression: str = Field(..., description=\"The arithmetic expression to evaluate.\")\n\n def run_model(self) -> list[Data]:\n return self._evaluate_expression(self.expression)\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"calculator\",\n description=\"Evaluate basic arithmetic expressions. Input should be a string containing the expression.\",\n func=self._eval_expr_with_error,\n args_schema=self.CalculatorToolSchema,\n )\n\n def _eval_expr(self, node):\n # Define the allowed operators\n operators = {\n ast.Add: operator.add,\n ast.Sub: operator.sub,\n ast.Mult: operator.mul,\n ast.Div: operator.truediv,\n ast.Pow: operator.pow,\n }\n if isinstance(node, ast.Num):\n return node.n\n if isinstance(node, ast.BinOp):\n return operators[type(node.op)](self._eval_expr(node.left), self._eval_expr(node.right))\n if isinstance(node, ast.UnaryOp):\n return operators[type(node.op)](self._eval_expr(node.operand))\n if isinstance(node, ast.Call):\n msg = (\n \"Function calls like sqrt(), sin(), cos() etc. are not supported. \"\n \"Only basic arithmetic operations (+, -, *, /, **) are allowed.\"\n )\n raise TypeError(msg)\n msg = f\"Unsupported operation or expression type: {type(node).__name__}\"\n raise TypeError(msg)\n\n def _eval_expr_with_error(self, expression: str) -> list[Data]:\n try:\n return self._evaluate_expression(expression)\n except Exception as e:\n raise ToolException(str(e)) from e\n\n def _evaluate_expression(self, expression: str) -> list[Data]:\n try:\n # Parse the expression and evaluate it\n tree = ast.parse(expression, mode=\"eval\")\n result = self._eval_expr(tree.body)\n\n # Format the result to a reasonable number of decimal places\n formatted_result = f\"{result:.6f}\".rstrip(\"0\").rstrip(\".\")\n\n self.status = formatted_result\n return [Data(data={\"result\": formatted_result})]\n\n except (SyntaxError, TypeError, KeyError) as e:\n error_message = f\"Invalid expression: {e}\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n except ZeroDivisionError:\n error_message = \"Error: Division by zero\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n except Exception as e: # noqa: BLE001\n logger.opt(exception=True).debug(\"Error evaluating expression\")\n error_message = f\"Error: {e}\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n" + }, + "expression": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Expression", + "dynamic": false, + "info": "The arithmetic expression to evaluate (e.g., '4*4*(33/22)+12-20').", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "expression", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "CalculatorTool" + }, + "dragging": false, + "height": 167, + "id": "CalculatorTool-DF8xQ", + "position": { + "x": 1347.154214046272, + "y": 28.770424745017564 + }, + "positionAbsolute": { + "x": 1347.154214046272, + "y": 28.770424745017564 + }, + "selected": false, + "type": "genericNode", + "width": 320 + } + ], + "viewport": { + "x": -251.17743782763955, + "y": 134.52045967838717, + "zoom": 0.6368650431844803 + } + }, + "description": "Calculate SaaS subscription price based on costs, profit margin, and subscribers using step-by-step method and Chain-of-Thought prompting. ", + "endpoint_name": null, + "icon": "calculator", + "id": "9357f72e-2121-4541-8e7d-74b7ba2ada2b", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "SaaS Pricing", + "tags": [ + "agents", + "assistants" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json b/src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json new file mode 100644 index 000000000..f76e5b5e4 --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json @@ -0,0 +1,3758 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-rPwbg", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "system_prompt", + "id": "Agent-rH74C", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": 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"reactflow__edge-Prompt-DGXf4{œdataTypeœ:œPromptœ,œidœ:œPrompt-DGXf4œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-Agent-vIPAK{œfieldNameœ:œsystem_promptœ,œidœ:œAgent-vIPAKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-DGXf4", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-DGXf4œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "Agent-vIPAK", + "targetHandle": "{œfieldNameœ: œsystem_promptœ, œidœ: œAgent-vIPAKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Agent", + "id": "Agent-rH74C", + "name": "response", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-oAzS1", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": 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"reactflow__edge-Agent-uaR2o{œdataTypeœ:œAgentœ,œidœ:œAgent-uaR2oœ,œnameœ:œresponseœ,œoutput_typesœ:[œMessageœ]}-Agent-vIPAK{œfieldNameœ:œinput_valueœ,œidœ:œAgent-vIPAKœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Agent-uaR2o", + "sourceHandle": "{œdataTypeœ: œAgentœ, œidœ: œAgent-uaR2oœ, œnameœ: œresponseœ, œoutput_typesœ: [œMessageœ]}", + "target": "Agent-vIPAK", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œAgent-vIPAKœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "Agent", + "id": "Agent-uaR2o", + "name": "response", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "research_agent_output", + "id": "Prompt-rPwbg", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Agent-uaR2o{œdataTypeœ:œAgentœ,œidœ:œAgent-uaR2oœ,œnameœ:œresponseœ,œoutput_typesœ:[œMessageœ]}-Prompt-rPwbg{œfieldNameœ:œresearch_agent_outputœ,œidœ:œPrompt-rPwbgœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "Agent-uaR2o", + "sourceHandle": "{œdataTypeœ: œAgentœ, œidœ: œAgent-uaR2oœ, œnameœ: œresponseœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-rPwbg", + "targetHandle": "{œfieldNameœ: œresearch_agent_outputœ, œidœ: œPrompt-rPwbgœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-oAzS1", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-oAzS1", + "position": { + "x": 1239.222567317785, + "y": -920.0283175735606 + }, + "positionAbsolute": { + "x": 1239.222567317785, + "y": -920.0283175735606 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Finance Agent", + "id": "Agent-vIPAK", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Finance Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model = self.get_llm()\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix)\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Finance Agent" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are the chief editor of a prestigious publication known for transforming complex information into clear, engaging content. Review and refine the researcher's document about {topic}.\n\nYour editing process should:\n- Verify and challenge any questionable claims\n- Restructure content for better flow and readability\n- Remove redundancies and unclear statements\n- Add context where needed\n- Ensure balanced coverage of the topic\n- Transform technical language into accessible explanations\n\nMaintain high editorial standards while making the content engaging for an educated general audience. Present the revised version in a clean, well-structured format." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-vIPAK", + "position": { + "x": 45.70736046026991, + "y": -1369.035463408626 + }, + "positionAbsolute": { + "x": 45.70736046026991, + "y": -1369.035463408626 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Analysis & Editor Agent", + "id": "Agent-rH74C", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Analysis & Editor Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model = self.get_llm()\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix)\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Start the analysis" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Analysis & Editor Agent" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are a brilliant comedy writer known for making complex topics entertaining and memorable. Using the editor's refined document about {topic}, create an engaging, humorous blog post.\n\nYour approach should:\n- Find unexpected angles and amusing parallels\n- Use clever wordplay and wit (avoid cheap jokes)\n- Maintain accuracy while being entertaining\n- Include relatable examples and analogies\n- Keep a smart, sophisticated tone\n- Make the topic more approachable through humor\n\nCreate a blog post that makes people laugh while actually teaching them about {topic}. The humor should enhance, not overshadow, the educational value." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-rH74C", + "position": { + "x": 815.1900903820148, + "y": -1365.4053932711827 + }, + "positionAbsolute": { + "x": 815.1900903820148, + "y": -1365.4053932711827 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-BS8ii", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": true, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "# Expert Research Agent Protocol\n\n[Previous content remains the same, but adding this critical section about image handling:]\n\n## Image and Visual Data Handling\nWhen using Tavily Search with images enabled:\n\n1. Image Collection\n - Always enable include_images in Tavily search\n - Collect relevant stock charts, product images, and news photos\n - Save image URLs from reliable sources\n - Focus on recent, high-quality images\n\n2. Image Categories to Collect\n - Product showcase images\n - Stock performance charts\n - Company facilities\n - Key executive photos\n - Recent event images\n - Market share visualizations\n\n3. Image Documentation\n - Include full image URL\n - Add clear descriptions\n - Note image source and date\n - Explain image relevance\n\n4. Image Presentation in Output\n ```markdown\n ![Image Description](image_url)\n - Source: [Source Name]\n - Date: [Image Date]\n - Context: [Brief explanation of image relevance]\n ```\n\n## Output Structure\nPresent your findings in this format:\n\n### Company Overview\n[Comprehensive overview based on search results]\n\n### Recent Developments\n[Latest news and announcements with dates]\n\n### Market Context\n[Industry trends and competitive position]\n\n### Visual Insights\n[Reference relevant images from search]\n\n### Key Risk Factors\n[Identified risks and challenges]\n\n### Sources\n[List of key sources consulted]\n\nRemember to:\n- Use Markdown formatting for clear structure\n- Include dates for all time-sensitive information\n- Quote significant statistics and statements\n- Reference any included images\n- Highlight conflicting information or viewpoints\n- Pass all gathered data to the Finance Agent for detailed financial analysis" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-BS8ii", + "position": { + "x": -1142.2312935529987, + "y": -1107.442614776065 + }, + "positionAbsolute": { + "x": -1142.2312935529987, + "y": -1107.442614776065 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-DGXf4", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "# Financial Analysis Expert Protocol\n\nYou are an elite financial analyst with access to Yahoo Finance tools. Your role is to perform comprehensive financial analysis based on the research provided and the data available through Yahoo Finance methods.\n\n## CRITICAL: Stock Symbol Usage\n- Always use correct stock ticker symbols in UPPERCASE format\n- Examples of valid symbols:\n * AAPL (Apple Inc.)\n * MSFT (Microsoft)\n * NVDA (NVIDIA)\n * GOOGL (Alphabet/Google)\n * TSLA (Tesla)\n- Invalid formats to avoid:\n * ❌ Apple (company name instead of symbol)\n * ❌ aapl (lowercase)\n * ❌ $AAPL (with dollar sign)\n * ❌ AAPL.US (with extension)\n\n## Data Collection Strategy\n\n1. Initial Symbol Verification\n - Confirm valid stock symbol format before any analysis\n - Use get_info first to verify symbol validity\n - Cross-reference with get_fast_info to ensure data availability\n - If symbol is invalid, immediately report the error\n\n2. Core Company Analysis\n - Get basic info (get_info): Full company details\n - Fast metrics (get_fast_info): Quick market data\n - Earnings data (get_earnings): Performance history\n - Calendar events (get_calendar): Upcoming events\n\n3. Financial Statement Analysis\n - Income statements (get_income_stmt)\n - Balance sheets (get_balance_sheet)\n - Cash flow statements (get_cashflow)\n\n4. Market Intelligence\n - Latest recommendations (get_recommendations)\n - Recommendation trends (get_recommendations_summary)\n - Recent rating changes (get_upgrades_downgrades)\n - Breaking news (get_news, specify number of articles needed)\n\n5. Ownership Structure\n - Institutional holdings (get_institutional_holders)\n - Major stakeholders (get_major_holders)\n - Fund ownership (get_mutualfund_holders)\n - Insider activity:\n * Recent purchases (get_insider_purchases)\n * Transaction history (get_insider_transactions)\n * Insider roster (get_insider_roster_holders)\n\n6. Historical Patterns\n - Corporate actions (get_actions)\n - Dividend history (get_dividends)\n - Split history (get_splits)\n - Capital gains (get_capital_gains)\n - Regulatory filings (get_sec_filings)\n - ESG metrics (get_sustainability)\n\n## Analysis Framework\n\n1. Profitability Metrics\n - Revenue trends\n - Margin analysis\n - Efficiency ratios\n - Return metrics\n\n2. Financial Health\n - Liquidity ratios\n - Debt analysis\n - Working capital\n - Cash flow quality\n\n3. Growth Assessment\n - Historical rates\n - Future projections\n - Market opportunity\n - Expansion plans\n\n4. Risk Evaluation\n - Financial risks\n - Market position\n - Operational challenges\n - Competitive threats\n\n## Output Structure\n\n### Symbol Information\n[Confirm stock symbol and basic company information]\n\n### Financial Overview\n[Key metrics summary with actual numbers]\n\n### Profitability Analysis\n[Detailed profit metrics with comparisons]\n\n### Balance Sheet Review\n[Asset and liability analysis]\n\n### Cash Flow Assessment\n[Cash generation and usage patterns]\n\n### Market Sentiment\n[Analyst views and institutional activity]\n\n### Growth Analysis\n[Historical and projected growth]\n\n### Risk Factors\n[Comprehensive risk assessment]\n\nRemember to:\n- ALWAYS verify stock symbol validity first\n- Use exact numbers from the data\n- Compare with industry standards\n- Highlight significant trends\n- Flag data anomalies\n- Identify key risks\n- Provide metric context\n- Focus on material information\n\nPass your comprehensive financial analysis to the Analysis & Editor Agent for final synthesis and recommendations. Include any invalid symbol errors or data availability issues in your report." + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 260, + "id": "Prompt-DGXf4", + "position": { + "x": -344.9674638932195, + "y": -1280.1782190739505 + }, + "positionAbsolute": { + "x": -344.9674638932195, + "y": -1280.1782190739505 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-rPwbg", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "research_agent_output", + "finance_agent_output" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "finance_agent_output": { + "advanced": false, + "display_name": "finance_agent_output", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "finance_agent_output", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "research_agent_output": { + "advanced": false, + "display_name": "research_agent_output", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "research_agent_output", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "# Investment Analysis & Editorial Protocol\n\nYou are an elite financial analyst and editorial expert responsible for creating the final investment analysis report. Your role is to synthesize research and financial data into a visually appealing, data-rich investment analysis using proper markdown formatting.\n\n## Input Processing\n1. Research Agent Input (Visual + Market Research):\n - Market research and news\n - Industry trends\n - Competitive analysis\n - Images and charts\n - News sentiment\n - {research_agent_output}\n\n2. Finance Agent Input (Quantitative Data):\n - Detailed financial metrics\n - Stock statistics\n - Analyst ratings\n - Growth metrics\n - Risk factors\n - {finance_agent_output}\n\n## Output Format Requirements\n\n1. Header Format\n Use single # for main title, increment for subsections\n \n2. Image Placement\n - Place images immediately after relevant sections\n - Use proper markdown format: ![Alt Text](url)\n - Always include source and context\n - Use *italics* for image captions\n\n3. Table Formatting\n - Use standard markdown tables\n - Align numbers right, text left\n - Include header separators\n - Keep consistent column widths\n\n4. Data Presentation\n - Use bold (**) for key metrics\n - Include percentage changes\n - Show comparisons\n - Include trends (↑/↓)\n\n## Report Structure\n\n# Investment Analysis Report: [Company Name] ($SYMBOL)\n*Generated: [Date] | Type: Comprehensive Evaluation*\n\n[Executive Summary - 3 paragraphs max]\n\n## Quick Take\n- **Recommendation**: [BUY/HOLD/SELL]\n- **Target Price**: $XXX\n- **Risk Level**: [LOW/MEDIUM/HIGH]\n- **Investment Horizon**: [SHORT/MEDIUM/LONG]-term\n\n## Market Analysis\n[Insert most relevant market image here]\n*Source: [Name] - [Context]*\n\n### Industry Position\n- Market share data\n- Competitive analysis\n- Recent developments\n\n## Financial Health\n| Metric | Value | YoY Change | Industry Avg |\n|:-------|------:|-----------:|-------------:|\n| Revenue | $XXX | XX% | $XXX |\n[Additional metrics]\n\n### Key Performance Indicators\n- **Revenue Growth**: XX%\n- **Profit Margin**: XX%\n- **ROE**: XX%\n\n## Growth Drivers\n1. Short-term Catalysts\n2. Long-term Opportunities\n3. Innovation Pipeline\n\n## Risk Assessment\n| Risk Factor | Severity | Probability | Impact |\n|:------------|:---------|:------------|:-------|\n| [Risk 1] | HIGH/MED/LOW | H/M/L | Details |\n\n## Technical Analysis\n[Insert technical chart]\n*Source: [Name] - Analysis of key technical indicators*\n\n## Investment Strategy\n### Long-term (18+ months)\n- Entry points\n- Position sizing\n- Risk management\n\n### Medium-term (6-18 months)\n- Technical levels\n- Catalysts timeline\n\n### Short-term (0-6 months)\n- Support/Resistance\n- Trading parameters\n\n## Price Targets\n- **Bear Case**: $XXX (-XX%)\n- **Base Case**: $XXX\n- **Bull Case**: $XXX (+XX%)\n\n## Monitoring Checklist\n1. [Metric 1]\n2. [Metric 2]\n3. [Metric 3]\n\n## Visual Evidence\n[Insert additional relevant images]\n*Source: [Name] - [Specific context and analysis]*\n\n*Disclaimer: This analysis is for informational purposes only. Always conduct your own research before making investment decisions.*\n\n## Output Requirements\n\n1. Visual Excellence\n - Strategic image placement\n - Clear data visualization\n - Consistent formatting\n - Professional appearance\n\n2. Data Accuracy\n - Cross-reference numbers\n - Verify calculations\n - Include trends\n - Show comparisons\n\n3. Action Focus\n - Clear recommendations\n - Specific entry/exit points\n - Risk management guidelines\n - Monitoring triggers\n\n4. Professional Standards\n - No spelling errors\n - Consistent formatting\n - Proper citations\n - Clear attribution\n\nRemember:\n- Never use triple backticks\n- Include all images with proper markdown\n- Maintain consistent formatting\n- Provide specific, actionable insights\n- Use emojis sparingly and professionally\n- Cross-validate all data points" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 433, + "id": "Prompt-rPwbg", + "position": { + "x": 416.02309796632085, + "y": -1081.5957453651372 + }, + "positionAbsolute": { + "x": 416.02309796632085, + "y": -1081.5957453651372 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "ChatInput-3mEtf", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": true, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Should I invest in Tesla (TSLA) stock right now? Please analyze the company's current position, market trends, financial health, and provide a clear investment recommendation." + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-3mEtf", + "position": { + "x": -1510.6054210793818, + "y": -947.702056394023 + }, + "positionAbsolute": { + "x": -1510.6054210793818, + "y": -947.702056394023 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "CalculatorTool-xo5ux", + "node": { + "base_classes": [ + "Data", + "Tool" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Perform basic arithmetic operations on a given expression.", + "display_name": "Calculator", + "documentation": "", + "edited": false, + "field_order": [ + "expression" + ], + "frozen": false, + "icon": "calculator", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "run_model", + "name": "api_run_model", + "required_inputs": [], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Tool", + "method": "build_tool", + "name": "api_build_tool", + "required_inputs": [], + "selected": "Tool", + "types": [ + "Tool" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import ast\nimport operator\n\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import MessageTextInput\nfrom langflow.schema import Data\n\n\nclass CalculatorToolComponent(LCToolComponent):\n display_name = \"Calculator\"\n description = \"Perform basic arithmetic operations on a given expression.\"\n icon = \"calculator\"\n name = \"CalculatorTool\"\n\n inputs = [\n MessageTextInput(\n name=\"expression\",\n display_name=\"Expression\",\n info=\"The arithmetic expression to evaluate (e.g., '4*4*(33/22)+12-20').\",\n tool_mode=True,\n ),\n ]\n\n class CalculatorToolSchema(BaseModel):\n expression: str = Field(..., description=\"The arithmetic expression to evaluate.\")\n\n def run_model(self) -> list[Data]:\n return self._evaluate_expression(self.expression)\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"calculator\",\n description=\"Evaluate basic arithmetic expressions. Input should be a string containing the expression.\",\n func=self._eval_expr_with_error,\n args_schema=self.CalculatorToolSchema,\n )\n\n def _eval_expr(self, node):\n # Define the allowed operators\n operators = {\n ast.Add: operator.add,\n ast.Sub: operator.sub,\n ast.Mult: operator.mul,\n ast.Div: operator.truediv,\n ast.Pow: operator.pow,\n }\n if isinstance(node, ast.Num):\n return node.n\n if isinstance(node, ast.BinOp):\n return operators[type(node.op)](self._eval_expr(node.left), self._eval_expr(node.right))\n if isinstance(node, ast.UnaryOp):\n return operators[type(node.op)](self._eval_expr(node.operand))\n if isinstance(node, ast.Call):\n msg = (\n \"Function calls like sqrt(), sin(), cos() etc. are not supported. \"\n \"Only basic arithmetic operations (+, -, *, /, **) are allowed.\"\n )\n raise TypeError(msg)\n msg = f\"Unsupported operation or expression type: {type(node).__name__}\"\n raise TypeError(msg)\n\n def _eval_expr_with_error(self, expression: str) -> list[Data]:\n try:\n return self._evaluate_expression(expression)\n except Exception as e:\n raise ToolException(str(e)) from e\n\n def _evaluate_expression(self, expression: str) -> list[Data]:\n try:\n # Parse the expression and evaluate it\n tree = ast.parse(expression, mode=\"eval\")\n result = self._eval_expr(tree.body)\n\n # Format the result to a reasonable number of decimal places\n formatted_result = f\"{result:.6f}\".rstrip(\"0\").rstrip(\".\")\n\n self.status = formatted_result\n return [Data(data={\"result\": formatted_result})]\n\n except (SyntaxError, TypeError, KeyError) as e:\n error_message = f\"Invalid expression: {e}\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n except ZeroDivisionError:\n error_message = \"Error: Division by zero\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n except Exception as e: # noqa: BLE001\n logger.opt(exception=True).debug(\"Error evaluating expression\")\n error_message = f\"Error: {e}\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n" + }, + "expression": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Expression", + "dynamic": false, + "info": "The arithmetic expression to evaluate (e.g., '4*4*(33/22)+12-20').", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "expression", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "CalculatorTool" + }, + "dragging": false, + "height": 254, + "id": "CalculatorTool-xo5ux", + "position": { + "x": 415.51528601650625, + "y": -603.8178818852236 + }, + "positionAbsolute": { + "x": 415.51528601650625, + "y": -603.8178818852236 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "id": "TavilyAISearch-YfG8u", + "node": { + "base_classes": [ + "Data", + "Tool" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n", + "display_name": "Tavily AI Search", + "documentation": "https://docs.tavily.com/", + "edited": false, + "field_order": [ + "api_key", + "query", + "search_depth", + "topic", + "max_results", + "include_images", + "include_answer" + ], + "frozen": false, + "icon": "TavilyIcon", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "run_model", + "name": "api_run_model", + "required_inputs": [ + "api_key" + ], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Tool", + "method": "build_tool", + "name": "api_build_tool", + "required_inputs": [ + "api_key" + ], + "selected": "Tool", + "types": [ + "Tool" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "Tavily API Key", + "dynamic": false, + "info": "Your Tavily API Key.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from enum import Enum\n\nimport httpx\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass TavilySearchDepth(Enum):\n BASIC = \"basic\"\n ADVANCED = \"advanced\"\n\n\nclass TavilySearchTopic(Enum):\n GENERAL = \"general\"\n NEWS = \"news\"\n\n\nclass TavilySearchSchema(BaseModel):\n query: str = Field(..., description=\"The search query you want to execute with Tavily.\")\n search_depth: TavilySearchDepth = Field(TavilySearchDepth.BASIC, description=\"The depth of the search.\")\n topic: TavilySearchTopic = Field(TavilySearchTopic.GENERAL, description=\"The category of the search.\")\n max_results: int = Field(5, description=\"The maximum number of search results to return.\")\n include_images: bool = Field(default=False, description=\"Include a list of query-related images in the response.\")\n include_answer: bool = Field(default=False, description=\"Include a short answer to original query.\")\n\n\nclass TavilySearchToolComponent(LCToolComponent):\n display_name = \"Tavily AI Search\"\n description = \"\"\"**Tavily AI** is a search engine optimized for LLMs and RAG, \\\n aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.\n\nNote: Check 'Advanced' for all options.\n\"\"\"\n icon = \"TavilyIcon\"\n name = \"TavilyAISearch\"\n documentation = \"https://docs.tavily.com/\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Tavily API Key\",\n required=True,\n info=\"Your Tavily API Key.\",\n ),\n MessageTextInput(\n name=\"query\",\n display_name=\"Search Query\",\n info=\"The search query you want to execute with Tavily.\",\n ),\n DropdownInput(\n name=\"search_depth\",\n display_name=\"Search Depth\",\n info=\"The depth of the search.\",\n options=list(TavilySearchDepth),\n value=TavilySearchDepth.ADVANCED,\n advanced=True,\n ),\n DropdownInput(\n name=\"topic\",\n display_name=\"Search Topic\",\n info=\"The category of the search.\",\n options=list(TavilySearchTopic),\n value=TavilySearchTopic.GENERAL,\n advanced=True,\n ),\n IntInput(\n name=\"max_results\",\n display_name=\"Max Results\",\n info=\"The maximum number of search results to return.\",\n value=5,\n advanced=True,\n ),\n BoolInput(\n name=\"include_images\",\n display_name=\"Include Images\",\n info=\"Include a list of query-related images in the response.\",\n value=True,\n advanced=True,\n ),\n BoolInput(\n name=\"include_answer\",\n display_name=\"Include Answer\",\n info=\"Include a short answer to original query.\",\n value=True,\n advanced=True,\n ),\n ]\n\n def run_model(self) -> list[Data]:\n # Convert string values to enum instances with validation\n try:\n search_depth_enum = (\n self.search_depth\n if isinstance(self.search_depth, TavilySearchDepth)\n else TavilySearchDepth(str(self.search_depth).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid search depth value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n try:\n topic_enum = (\n self.topic if isinstance(self.topic, TavilySearchTopic) else TavilySearchTopic(str(self.topic).lower())\n )\n except ValueError as e:\n error_message = f\"Invalid topic value: {e!s}\"\n self.status = error_message\n return [Data(data={\"error\": error_message})]\n\n return self._tavily_search(\n self.query,\n search_depth=search_depth_enum,\n topic=topic_enum,\n max_results=self.max_results,\n include_images=self.include_images,\n include_answer=self.include_answer,\n )\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"tavily_search\",\n description=\"Perform a web search using the Tavily API.\",\n func=self._tavily_search,\n args_schema=TavilySearchSchema,\n )\n\n def _tavily_search(\n self,\n query: str,\n *,\n search_depth: TavilySearchDepth = TavilySearchDepth.BASIC,\n topic: TavilySearchTopic = TavilySearchTopic.GENERAL,\n max_results: int = 5,\n include_images: bool = False,\n include_answer: bool = False,\n ) -> list[Data]:\n # Validate enum values\n if not isinstance(search_depth, TavilySearchDepth):\n msg = f\"Invalid search_depth value: {search_depth}\"\n raise TypeError(msg)\n if not isinstance(topic, TavilySearchTopic):\n msg = f\"Invalid topic value: {topic}\"\n raise TypeError(msg)\n\n try:\n url = \"https://api.tavily.com/search\"\n headers = {\n \"content-type\": \"application/json\",\n \"accept\": \"application/json\",\n }\n payload = {\n \"api_key\": self.api_key,\n \"query\": query,\n \"search_depth\": search_depth.value,\n \"topic\": topic.value,\n \"max_results\": max_results,\n \"include_images\": include_images,\n \"include_answer\": include_answer,\n }\n\n with httpx.Client() as client:\n response = client.post(url, json=payload, headers=headers)\n\n response.raise_for_status()\n search_results = response.json()\n\n data_results = [\n Data(\n data={\n \"title\": result.get(\"title\"),\n \"url\": result.get(\"url\"),\n \"content\": result.get(\"content\"),\n \"score\": result.get(\"score\"),\n }\n )\n for result in search_results.get(\"results\", [])\n ]\n\n if include_answer and search_results.get(\"answer\"):\n data_results.insert(0, Data(data={\"answer\": search_results[\"answer\"]}))\n\n if include_images and search_results.get(\"images\"):\n data_results.append(Data(data={\"images\": search_results[\"images\"]}))\n\n self.status = data_results # type: ignore[assignment]\n\n except httpx.HTTPStatusError as e:\n error_message = f\"HTTP error: {e.response.status_code} - {e.response.text}\"\n logger.debug(error_message)\n self.status = error_message\n raise ToolException(error_message) from e\n except Exception as e:\n error_message = f\"Unexpected error: {e}\"\n logger.opt(exception=True).debug(\"Error running Tavily Search\")\n self.status = error_message\n raise ToolException(error_message) from e\n return data_results\n" + }, + "include_answer": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Answer", + "dynamic": false, + "info": "Include a short answer to original query.", + "list": false, + "name": "include_answer", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "include_images": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Include Images", + "dynamic": false, + "info": "Include a list of query-related images in the response.", + "list": false, + "name": "include_images", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "max_results": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Results", + "dynamic": false, + "info": "The maximum number of search results to return.", + "list": false, + "name": "max_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 5 + }, + "query": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Search Query", + "dynamic": false, + "info": "The search query you want to execute with Tavily.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "search_depth": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Depth", + "dynamic": false, + "info": "The depth of the search.", + "load_from_db": false, + "name": "search_depth", + "options": [ + "basic", + "advanced" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "advanced" + }, + "topic": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Topic", + "dynamic": false, + "info": "The category of the search.", + "load_from_db": false, + "name": "topic", + "options": [ + "general", + "news" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "general" + } + }, + "tool_mode": false + }, + "type": "TavilyAISearch" + }, + "dragging": false, + "height": 394, + "id": "TavilyAISearch-YfG8u", + "position": { + "x": -1132.8634419233736, + "y": -770.0391255413992 + }, + "positionAbsolute": { + "x": -1132.8634419233736, + "y": -770.0391255413992 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-8beLl", + "node": { + "description": "# Sequential Tasks Agents\n\n## Overview\nThis flow demonstrates how to chain multiple AI agents for comprehensive research and analysis. Each agent specializes in different aspects of the research process, building upon the previous agent's work.\n\n## How to Use the Flow\n\n1. **Input Your Query** 🎯\n - Be specific and clear\n - Include key aspects you want analyzed\n - Examples:\n ```\n Good: \"Should I invest in Tesla (TSLA)? Focus on AI development impact\"\n Bad: \"Tell me about Tesla\"\n ```\n\n2. **Research Agent Process** 🔍\n - Utilizes Tavily Search for comprehensive research\n\n\n3. **Specialized Analysis** 📊\n - Each agent adds unique value:\n ```\n Research Agent → Deep Research & Context\n ↓\n Finance Agent → Data Analysis & Metrics\n ↓\n Editor Agent → Final Synthesis & Report\n ```\n\n4. **Output Format** 📝\n - Structured report\n - Embedded images and charts\n - Data-backed insights\n - Clear recommendations\n\n## Pro Tips\n\n### Query Construction\n- Include specific points of interest\n- Mention required metrics or data points\n- Specify time frames if relevant\n\n### Flow Customization\n- Modify agent prompts for different use cases\n- Add or remove tools as needed\n\n## Common Applications\n- Investment Research\n- Market Analysis\n- Competitive Intelligence\n- Industry Reports\n- Technology Impact Studies\n\n⚡ **Best Practice**: Start with a test query to understand the flow's capabilities before running complex analyses.\n\n---\n*Note: This flow template uses financial analysis as an example but can be adapted for any research-intensive task requiring multiple perspectives and data sources.*", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 800, + "id": "note-8beLl", + "position": { + "x": -2122.739127560837, + "y": -1302.6582482086806 + }, + "positionAbsolute": { + "x": -2122.739127560837, + "y": -1302.6582482086806 + }, + "resizing": false, + "selected": false, + "style": { + "height": 800, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "id": "note-tB2J2", + "node": { + "description": "## What Are Sequential Task Agents?\nA system where multiple AI agents work in sequence, each specializing in specific tasks and passing their output to the next agent in the chain. Think of it as an assembly line where each agent adds value to the final result.\n\n## How It Works\n1. **First Agent** → **Second Agent** → **Third Agent** → **Final Output**\n - Each agent receives input from the previous one\n - Processes and enhances the information\n - Passes refined output forward\n\n## Key Benefits\n- **Specialization**: Each agent focuses on specific tasks\n- **Progressive Refinement**: Information gets enhanced at each step\n- **Structured Output**: Final result combines multiple perspectives\n- **Quality Control**: Each agent validates and improves previous work\n\n## Building Your Own Sequence\n1. **Plan Your Chain**\n - Identify distinct tasks\n - Determine logical order\n - Define input/output requirements\n\n2. **Configure Agents**\n - Give each agent clear instructions\n - Ensure compatible outputs/inputs\n - Set appropriate tools for each agent\n\n3. **Connect the Flow**\n - Link agents in proper order\n - Test data flow between agents\n - Verify final output format\n\n## Example Applications\n- Research → Analysis → Report Writing\n- Data Collection → Processing → Visualization\n- Content Research → Writing → Editing\n- Market Analysis → Financial Review → Investment Advice\n\n⭐ **Pro Tip**: The strength of sequential agents comes from how well they complement each other's capabilities.\n\nThis template uses financial analysis as an example, but you can adapt it for any multi-step process requiring different expertise at each stage.", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 800, + "id": "note-tB2J2", + "position": { + "x": -1456.0688717707517, + "y": -1916.6876704866322 + }, + "positionAbsolute": { + "x": -1456.0688717707517, + "y": -1916.6876704866322 + }, + "resizing": false, + "selected": false, + "style": { + "height": 800, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "id": "YahooFinanceTool-YmOKx", + "node": { + "base_classes": [ + "Data", + "Tool" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Access financial data and market information using Yahoo Finance.", + "display_name": "Yahoo Finance", + "documentation": "", + "edited": false, + "field_order": [ + "symbol", + "method", + "num_news" + ], + "frozen": false, + "icon": "trending-up", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "run_model", + "name": "api_run_model", + "required_inputs": [], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Tool", + "method": "build_tool", + "name": "api_build_tool", + "required_inputs": [], + "selected": "Tool", + "types": [ + "Tool" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import ast\nimport pprint\nfrom enum import Enum\n\nimport yfinance as yf\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import DropdownInput, IntInput, MessageTextInput\nfrom langflow.schema import Data\n\n\nclass YahooFinanceMethod(Enum):\n GET_INFO = \"get_info\"\n GET_NEWS = \"get_news\"\n GET_ACTIONS = \"get_actions\"\n GET_ANALYSIS = \"get_analysis\"\n GET_BALANCE_SHEET = \"get_balance_sheet\"\n GET_CALENDAR = \"get_calendar\"\n GET_CASHFLOW = \"get_cashflow\"\n GET_INSTITUTIONAL_HOLDERS = \"get_institutional_holders\"\n GET_RECOMMENDATIONS = \"get_recommendations\"\n GET_SUSTAINABILITY = \"get_sustainability\"\n GET_MAJOR_HOLDERS = \"get_major_holders\"\n GET_MUTUALFUND_HOLDERS = \"get_mutualfund_holders\"\n GET_INSIDER_PURCHASES = \"get_insider_purchases\"\n GET_INSIDER_TRANSACTIONS = \"get_insider_transactions\"\n GET_INSIDER_ROSTER_HOLDERS = \"get_insider_roster_holders\"\n GET_DIVIDENDS = \"get_dividends\"\n GET_CAPITAL_GAINS = \"get_capital_gains\"\n GET_SPLITS = \"get_splits\"\n GET_SHARES = \"get_shares\"\n GET_FAST_INFO = \"get_fast_info\"\n GET_SEC_FILINGS = \"get_sec_filings\"\n GET_RECOMMENDATIONS_SUMMARY = \"get_recommendations_summary\"\n GET_UPGRADES_DOWNGRADES = \"get_upgrades_downgrades\"\n GET_EARNINGS = \"get_earnings\"\n GET_INCOME_STMT = \"get_income_stmt\"\n\n\nclass YahooFinanceSchema(BaseModel):\n symbol: str = Field(..., description=\"The stock symbol to retrieve data for.\")\n method: YahooFinanceMethod = Field(YahooFinanceMethod.GET_INFO, description=\"The type of data to retrieve.\")\n num_news: int | None = Field(5, description=\"The number of news articles to retrieve.\")\n\n\nclass YfinanceToolComponent(LCToolComponent):\n display_name = \"Yahoo Finance\"\n description = \"Access financial data and market information using Yahoo Finance.\"\n icon = \"trending-up\"\n name = \"YahooFinanceTool\"\n\n inputs = [\n MessageTextInput(\n name=\"symbol\",\n display_name=\"Stock Symbol\",\n info=\"The stock symbol to retrieve data for (e.g., AAPL, GOOG).\",\n ),\n DropdownInput(\n name=\"method\",\n display_name=\"Data Method\",\n info=\"The type of data to retrieve.\",\n options=list(YahooFinanceMethod),\n value=\"get_news\",\n ),\n IntInput(\n name=\"num_news\",\n display_name=\"Number of News\",\n info=\"The number of news articles to retrieve (only applicable for get_news).\",\n value=5,\n ),\n ]\n\n def run_model(self) -> list[Data]:\n return self._yahoo_finance_tool(\n self.symbol,\n self.method,\n self.num_news,\n )\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"yahoo_finance\",\n description=\"Access financial data and market information from Yahoo Finance.\",\n func=self._yahoo_finance_tool,\n args_schema=YahooFinanceSchema,\n )\n\n def _yahoo_finance_tool(\n self,\n symbol: str,\n method: YahooFinanceMethod,\n num_news: int | None = 5,\n ) -> list[Data]:\n ticker = yf.Ticker(symbol)\n\n try:\n if method == YahooFinanceMethod.GET_INFO:\n result = ticker.info\n elif method == YahooFinanceMethod.GET_NEWS:\n result = ticker.news[:num_news]\n else:\n result = getattr(ticker, method.value)()\n\n result = pprint.pformat(result)\n\n if method == YahooFinanceMethod.GET_NEWS:\n data_list = [Data(data=article) for article in ast.literal_eval(result)]\n else:\n data_list = [Data(data={\"result\": result})]\n\n except Exception as e:\n error_message = f\"Error retrieving data: {e}\"\n logger.debug(error_message)\n self.status = error_message\n raise ToolException(error_message) from e\n\n return data_list\n" + }, + "method": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Data Method", + "dynamic": false, + "info": "The type of data to retrieve.", + "name": "method", + "options": [ + "get_info", + "get_news", + "get_actions", + "get_analysis", + "get_balance_sheet", + "get_calendar", + "get_cashflow", + "get_institutional_holders", + "get_recommendations", + "get_sustainability", + "get_major_holders", + "get_mutualfund_holders", + "get_insider_purchases", + "get_insider_transactions", + "get_insider_roster_holders", + "get_dividends", + "get_capital_gains", + "get_splits", + "get_shares", + "get_fast_info", + "get_sec_filings", + "get_recommendations_summary", + "get_upgrades_downgrades", + "get_earnings", + "get_income_stmt" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "get_news" + }, + "num_news": { + "_input_type": "IntInput", + "advanced": false, + "display_name": "Number of News", + "dynamic": false, + "info": "The number of news articles to retrieve (only applicable for get_news).", + "list": false, + "name": "num_news", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 5 + }, + "symbol": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Stock Symbol", + "dynamic": false, + "info": "The stock symbol to retrieve data for (e.g., AAPL, GOOG).", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "symbol", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AAPL" + } + }, + "tool_mode": false + }, + "type": "YahooFinanceTool" + }, + "dragging": false, + "height": 475, + "id": "YahooFinanceTool-YmOKx", + "position": { + "x": -338.2658218008318, + "y": -945.7435123503128 + }, + "positionAbsolute": { + "x": -338.2658218008318, + "y": -945.7435123503128 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Researcher Agent", + "id": "Agent-uaR2o", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Researcher Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": true, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model = self.get_llm()\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix)\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are a helpful assistant that can use tools to answer questions and perform tasks." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-uaR2o", + "position": { + "x": -715.1798010873374, + "y": -1342.256094001045 + }, + "positionAbsolute": { + "x": -715.1798010873374, + "y": -1342.256094001045 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-9ZCze", + "node": { + "description": "## Get your API key at [https://tavily.ai](https://tavily.ai)\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "rose" + } + }, + "type": "note" + }, + "dragging": false, + "height": 324, + "id": "note-9ZCze", + "position": { + "x": -1144.3898055225054, + "y": -844.3506743985376 + }, + "positionAbsolute": { + "x": -1144.3898055225054, + "y": -844.3506743985376 + }, + "resizing": false, + "selected": false, + "style": { + "height": 324, + "width": 347 + }, + "type": "noteNode", + "width": 347 + }, + { + "data": { + "id": "note-ynS9s", + "node": { + "description": "## Configure the agent by obtaining your OpenAI API key from [platform.openai.com](https://platform.openai.com). Under \"Model Provider\", choose:\n- OpenAI: Default, requires only API key\n- Anthropic/Azure/Groq/NVIDIA: Each requires their own API keys\n- Custom: Use your own model endpoint + authentication\n\nSelect model and input API key before running the flow.", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "rose" + } + }, + "type": "note" + }, + "dragging": false, + "height": 324, + "id": "note-ynS9s", + "position": { + "x": -739.4383746675942, + "y": -1672.0874594411662 + }, + "positionAbsolute": { + "x": -739.4383746675942, + "y": -1672.0874594411662 + }, + "resizing": false, + "selected": false, + "style": { + "height": 324, + "width": 370 + }, + "type": "noteNode", + "width": 370 + } + ], + "viewport": { + "x": 988.287937756906, + "y": 1011.1045224025538, + "zoom": 0.5418943314819052 + } + }, + "description": "This Agent is designed to systematically execute a series of tasks following a meticulously predefined sequence. By adhering to this structured order, the Agent ensures that each task is completed efficiently and effectively, optimizing overall performance and maintaining a high level of accuracy.", + "endpoint_name": null, + "icon": "ListChecks", + "id": "673f26a7-66f4-410a-8ccb-3e635c022023", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "Sequential Tasks Agents", + "tags": [ + "assistants", + "agents", + "web-scraping" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Agent Flow.json b/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent .json similarity index 78% rename from src/backend/base/langflow/initial_setup/starter_projects/Agent Flow.json rename to src/backend/base/langflow/initial_setup/starter_projects/Simple Agent .json index 1a3b3938d..0efa7b57a 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Agent Flow.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent .json @@ -6,8 +6,8 @@ "className": "", "data": { "sourceHandle": { - "dataType": "PythonREPLTool", - "id": "PythonREPLTool-QaSW0", + "dataType": "YahooFinanceTool", + "id": "YahooFinanceTool-PzHUy", "name": "api_build_tool", "output_types": [ "Tool" @@ -15,7 +15,7 @@ }, "targetHandle": { "fieldName": "tools", - "id": "Agent-7mKwO", + "id": "Agent-KhAae", "inputTypes": [ "Tool", "BaseTool", @@ -24,40 +24,11 @@ "type": "other" } }, - "id": "reactflow__edge-PythonREPLTool-QaSW0{œdataTypeœ:œPythonREPLToolœ,œidœ:œPythonREPLTool-QaSW0œ,œnameœ:œapi_build_toolœ,œoutput_typesœ:[œToolœ]}-Agent-7mKwO{œfieldNameœ:œtoolsœ,œidœ:œAgent-7mKwOœ,œinputTypesœ:[œToolœ,œBaseToolœ,œStructuredToolœ],œtypeœ:œotherœ}", - "source": "PythonREPLTool-QaSW0", - "sourceHandle": "{œdataTypeœ: œPythonREPLToolœ, œidœ: œPythonREPLTool-QaSW0œ, œnameœ: œapi_build_toolœ, œoutput_typesœ: [œToolœ]}", - "target": "Agent-7mKwO", - "targetHandle": "{œfieldNameœ: œtoolsœ, œidœ: œAgent-7mKwOœ, œinputTypesœ: [œToolœ, œBaseToolœ, œStructuredToolœ], œtypeœ: œotherœ}" - }, - { - "animated": false, - "className": "", - "data": { - "sourceHandle": { - "dataType": "CalculatorTool", - "id": "CalculatorTool-2c9q3", - "name": "api_build_tool", - "output_types": [ - "Tool" - ] - }, - "targetHandle": { - "fieldName": "tools", - "id": "Agent-7mKwO", - "inputTypes": [ - "Tool", - "BaseTool", - "StructuredTool" - ], - "type": "other" - } - }, - "id": "reactflow__edge-CalculatorTool-2c9q3{œdataTypeœ:œCalculatorToolœ,œidœ:œCalculatorTool-2c9q3œ,œnameœ:œapi_build_toolœ,œoutput_typesœ:[œToolœ]}-Agent-7mKwO{œfieldNameœ:œtoolsœ,œidœ:œAgent-7mKwOœ,œinputTypesœ:[œToolœ,œBaseToolœ,œStructuredToolœ],œtypeœ:œotherœ}", - "source": "CalculatorTool-2c9q3", - "sourceHandle": "{œdataTypeœ: œCalculatorToolœ, œidœ: œCalculatorTool-2c9q3œ, œnameœ: œapi_build_toolœ, œoutput_typesœ: [œToolœ]}", - "target": "Agent-7mKwO", - "targetHandle": "{œfieldNameœ: œtoolsœ, œidœ: œAgent-7mKwOœ, œinputTypesœ: [œToolœ, œBaseToolœ, œStructuredToolœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-YahooFinanceTool-PzHUy{œdataTypeœ:œYahooFinanceToolœ,œidœ:œYahooFinanceTool-PzHUyœ,œnameœ:œapi_build_toolœ,œoutput_typesœ:[œToolœ]}-Agent-KhAae{œfieldNameœ:œtoolsœ,œidœ:œAgent-KhAaeœ,œinputTypesœ:[œToolœ,œBaseToolœ,œStructuredToolœ],œtypeœ:œotherœ}", + "source": "YahooFinanceTool-PzHUy", + "sourceHandle": "{œdataTypeœ: œYahooFinanceToolœ, œidœ: œYahooFinanceTool-PzHUyœ, œnameœ: œapi_build_toolœ, œoutput_typesœ: [œToolœ]}", + "target": "Agent-KhAae", + "targetHandle": "{œfieldNameœ: œtoolsœ, œidœ: œAgent-KhAaeœ, œinputTypesœ: [œToolœ, œBaseToolœ, œStructuredToolœ], œtypeœ: œotherœ}" }, { "animated": false, @@ -65,7 +36,7 @@ "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-GA9eO", + "id": "ChatInput-dBek4", "name": "message", "output_types": [ "Message" @@ -73,18 +44,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "Agent-7mKwO", + "id": "Agent-KhAae", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-ChatInput-GA9eO{œdataTypeœ:œChatInputœ,œidœ:œChatInput-GA9eOœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Agent-7mKwO{œfieldNameœ:œinput_valueœ,œidœ:œAgent-7mKwOœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "ChatInput-GA9eO", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-GA9eOœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Agent-7mKwO", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œAgent-7mKwOœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-dBek4{œdataTypeœ:œChatInputœ,œidœ:œChatInput-dBek4œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Agent-KhAae{œfieldNameœ:œinput_valueœ,œidœ:œAgent-KhAaeœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-dBek4", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-dBek4œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Agent-KhAae", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œAgent-KhAaeœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "animated": false, @@ -92,7 +63,7 @@ "data": { "sourceHandle": { "dataType": "Agent", - "id": "Agent-7mKwO", + "id": "Agent-KhAae", "name": "response", "output_types": [ "Message" @@ -100,24 +71,26 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-iwrl6", + "id": "ChatOutput-ULcvr", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Agent-7mKwO{œdataTypeœ:œAgentœ,œidœ:œAgent-7mKwOœ,œnameœ:œresponseœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-iwrl6{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-iwrl6œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Agent-7mKwO", - "sourceHandle": "{œdataTypeœ: œAgentœ, œidœ: œAgent-7mKwOœ, œnameœ: œresponseœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-iwrl6", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-iwrl6œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Agent-KhAae{œdataTypeœ:œAgentœ,œidœ:œAgent-KhAaeœ,œnameœ:œresponseœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-ULcvr{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-ULcvrœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Agent-KhAae", + "sourceHandle": "{œdataTypeœ: œAgentœ, œidœ: œAgent-KhAaeœ, œnameœ: œresponseœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-ULcvr", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-ULcvrœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ { "data": { - "id": "ChatInput-GA9eO", + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "id": "Agent-KhAae", "node": { "base_classes": [ "Message" @@ -125,816 +98,6 @@ "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "should_store_message", - "sender", - "sender_name", - "session_id", - "files" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "lf_version": "1.0.19", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "files": { - "_input_type": "FileInput", - "advanced": true, - "display_name": "Files", - "dynamic": false, - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx", - "jpg", - "jpeg", - "png", - "bmp", - "image" - ], - "file_path": "", - "info": "Files to be sent with the message.", - "list": true, - "name": "files", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "file", - "value": "" - }, - "input_value": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as input.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "Write a short python script to calculate 4+4, run it and display the result by printing it." - }, - "sender": { - "_input_type": "DropdownInput", - "advanced": true, - "combobox": false, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "sender_name": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "session_id": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatInput" - }, - "dragging": false, - "height": 234, - "id": "ChatInput-GA9eO", - "position": { - "x": 62.413733671682394, - "y": 1065.4595268030878 - }, - "positionAbsolute": { - "x": 62.413733671682394, - "y": 1065.4595268030878 - }, - "selected": false, - "type": "genericNode", - "width": 320 - }, - { - "data": { - "id": "ChatOutput-iwrl6", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "should_store_message", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "lf_version": "1.0.19", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "data_template": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "_input_type": "MessageTextInput", - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "_input_type": "DropdownInput", - "advanced": true, - "combobox": false, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 234, - "id": "ChatOutput-iwrl6", - "position": { - "x": 1503.4431369392628, - "y": 552.5679265365819 - }, - "positionAbsolute": { - "x": 1503.4431369392628, - "y": 552.5679265365819 - }, - "selected": true, - "type": "genericNode", - "width": 320 - }, - { - "data": { - "id": "CalculatorTool-2c9q3", - "node": { - "base_classes": [ - "Data", - "list", - "Sequence", - "Tool" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Perform basic arithmetic operations on a given expression.", - "display_name": "Calculator", - "documentation": "", - "edited": false, - "field_order": [ - "expression" - ], - "frozen": false, - "icon": "calculator", - "legacy": false, - "lf_version": "1.0.19", - "metadata": {}, - "official": false, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "run_model", - "name": "api_run_model", - "required_inputs": [], - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Tool", - "method": "build_tool", - "name": "api_build_tool", - "required_inputs": [], - "selected": "Tool", - "types": [ - "Tool" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import ast\nimport operator\n\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import MessageTextInput\nfrom langflow.schema import Data\n\n\nclass CalculatorToolComponent(LCToolComponent):\n display_name = \"Calculator\"\n description = \"Perform basic arithmetic operations on a given expression.\"\n icon = \"calculator\"\n name = \"CalculatorTool\"\n\n inputs = [\n MessageTextInput(\n name=\"expression\",\n display_name=\"Expression\",\n info=\"The arithmetic expression to evaluate (e.g., '4*4*(33/22)+12-20').\",\n tool_mode=True,\n ),\n ]\n\n class CalculatorToolSchema(BaseModel):\n expression: str = Field(..., description=\"The arithmetic expression to evaluate.\")\n\n def run_model(self) -> list[Data]:\n return self._evaluate_expression(self.expression)\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"calculator\",\n description=\"Evaluate basic arithmetic expressions. Input should be a string containing the expression.\",\n func=self._eval_expr_with_error,\n args_schema=self.CalculatorToolSchema,\n )\n\n def _eval_expr(self, node):\n # Define the allowed operators\n operators = {\n ast.Add: operator.add,\n ast.Sub: operator.sub,\n ast.Mult: operator.mul,\n ast.Div: operator.truediv,\n ast.Pow: operator.pow,\n }\n if isinstance(node, ast.Num):\n return node.n\n if isinstance(node, ast.BinOp):\n return operators[type(node.op)](self._eval_expr(node.left), self._eval_expr(node.right))\n if isinstance(node, ast.UnaryOp):\n return operators[type(node.op)](self._eval_expr(node.operand))\n if isinstance(node, ast.Call):\n msg = (\n \"Function calls like sqrt(), sin(), cos() etc. are not supported. \"\n \"Only basic arithmetic operations (+, -, *, /, **) are allowed.\"\n )\n raise TypeError(msg)\n msg = f\"Unsupported operation or expression type: {type(node).__name__}\"\n raise TypeError(msg)\n\n def _eval_expr_with_error(self, expression: str) -> list[Data]:\n try:\n return self._evaluate_expression(expression)\n except Exception as e:\n raise ToolException(str(e)) from e\n\n def _evaluate_expression(self, expression: str) -> list[Data]:\n try:\n # Parse the expression and evaluate it\n tree = ast.parse(expression, mode=\"eval\")\n result = self._eval_expr(tree.body)\n\n # Format the result to a reasonable number of decimal places\n formatted_result = f\"{result:.6f}\".rstrip(\"0\").rstrip(\".\")\n\n self.status = formatted_result\n return [Data(data={\"result\": formatted_result})]\n\n except (SyntaxError, TypeError, KeyError) as e:\n error_message = f\"Invalid expression: {e}\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n except ZeroDivisionError:\n error_message = \"Error: Division by zero\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n except Exception as e: # noqa: BLE001\n logger.opt(exception=True).debug(\"Error evaluating expression\")\n error_message = f\"Error: {e}\"\n self.status = error_message\n return [Data(data={\"error\": error_message, \"input\": expression})]\n" - }, - "expression": { - "_input_type": "MessageTextInput", - "advanced": false, - "display_name": "Expression", - "dynamic": false, - "info": "The arithmetic expression to evaluate (e.g., '4*4*(33/22)+12-20').", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "expression", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "2+2" - } - } - }, - "type": "CalculatorTool" - }, - "dragging": false, - "height": 302, - "id": "CalculatorTool-2c9q3", - "position": { - "x": 57.99937502347552, - "y": 149.36767868834886 - }, - "positionAbsolute": { - "x": 57.99937502347552, - "y": 149.36767868834886 - }, - "selected": false, - "type": "genericNode", - "width": 320 - }, - { - "data": { - "description": "A tool for running Python code in a REPL environment.", - "display_name": "Python REPL Tool", - "id": "PythonREPLTool-QaSW0", - "node": { - "base_classes": [ - "Data", - "Tool" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "A tool for running Python code in a REPL environment.", - "display_name": "Python REPL Tool", - "documentation": "", - "edited": false, - "field_order": [ - "name", - "description", - "global_imports", - "code" - ], - "frozen": false, - "legacy": false, - "lf_version": "1.0.19", - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "run_model", - "name": "api_run_model", - "required_inputs": [], - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Tool", - "method": "build_tool", - "name": "api_build_tool", - "required_inputs": [], - "selected": "Tool", - "types": [ - "Tool" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import importlib\n\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom langchain_experimental.utilities import PythonREPL\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import StrInput\nfrom langflow.schema import Data\n\n\nclass PythonREPLToolComponent(LCToolComponent):\n display_name = \"Python REPL Tool\"\n description = \"A tool for running Python code in a REPL environment.\"\n name = \"PythonREPLTool\"\n\n inputs = [\n StrInput(\n name=\"name\",\n display_name=\"Tool Name\",\n info=\"The name of the tool.\",\n value=\"python_repl\",\n ),\n StrInput(\n name=\"description\",\n display_name=\"Tool Description\",\n info=\"A description of the tool.\",\n value=\"A Python shell. Use this to execute python commands. \"\n \"Input should be a valid python command. \"\n \"If you want to see the output of a value, you should print it out with `print(...)`.\",\n ),\n StrInput(\n name=\"global_imports\",\n display_name=\"Global Imports\",\n info=\"A comma-separated list of modules to import globally, e.g. 'math,numpy'.\",\n value=\"math\",\n ),\n StrInput(\n name=\"code\",\n display_name=\"Python Code\",\n info=\"The Python code to execute.\",\n value=\"print('Hello, World!')\",\n ),\n ]\n\n class PythonREPLSchema(BaseModel):\n code: str = Field(..., description=\"The Python code to execute.\")\n\n def get_globals(self, global_imports: str | list[str]) -> dict:\n global_dict = {}\n if isinstance(global_imports, str):\n modules = [module.strip() for module in global_imports.split(\",\")]\n elif isinstance(global_imports, list):\n modules = global_imports\n else:\n msg = \"global_imports must be either a string or a list\"\n raise TypeError(msg)\n\n for module in modules:\n try:\n imported_module = importlib.import_module(module)\n global_dict[imported_module.__name__] = imported_module\n except ImportError as e:\n msg = f\"Could not import module {module}\"\n raise ImportError(msg) from e\n return global_dict\n\n def build_tool(self) -> Tool:\n _globals = self.get_globals(self.global_imports)\n python_repl = PythonREPL(_globals=_globals)\n\n def run_python_code(code: str) -> str:\n try:\n return python_repl.run(code)\n except Exception as e:\n logger.opt(exception=True).debug(\"Error running Python code\")\n raise ToolException(str(e)) from e\n\n tool = StructuredTool.from_function(\n name=self.name,\n description=self.description,\n func=run_python_code,\n args_schema=self.PythonREPLSchema,\n )\n\n self.status = f\"Python REPL Tool created with global imports: {self.global_imports}\"\n return tool\n\n def run_model(self) -> list[Data]:\n tool = self.build_tool()\n result = tool.run(self.code)\n return [Data(data={\"result\": result})]\n" - }, - "description": { - "_input_type": "StrInput", - "advanced": false, - "display_name": "Tool Description", - "dynamic": false, - "info": "A description of the tool.", - "list": false, - "load_from_db": false, - "name": "description", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "A Python shell. Use this to execute python commands. Input should be a valid python command. If you want to see the output of a value, you should print it out with `print(...)`." - }, - "global_imports": { - "_input_type": "StrInput", - "advanced": false, - "display_name": "Global Imports", - "dynamic": false, - "info": "A comma-separated list of modules to import globally, e.g. 'math,numpy'.", - "list": false, - "load_from_db": false, - "name": "global_imports", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "math" - }, - "name": { - "_input_type": "StrInput", - "advanced": false, - "display_name": "Tool Name", - "dynamic": false, - "info": "The name of the tool.", - "list": false, - "load_from_db": false, - "name": "name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "python_repl" - } - } - }, - "type": "PythonREPLTool" - }, - "dragging": false, - "height": 475, - "id": "PythonREPLTool-QaSW0", - "position": { - "x": 63.43047038993518, - "y": 536.9058769625287 - }, - "positionAbsolute": { - "x": 63.43047038993518, - "y": 536.9058769625287 - }, - "selected": false, - "type": "genericNode", - "width": 320 - }, - { - "data": { - "id": "Agent-7mKwO", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "category": "agents", - "conditional_paths": [], - "custom_fields": {}, "description": "Define the agent's instructions, then enter a task to complete using tools.", "display_name": "Agent", "documentation": "", @@ -957,19 +120,19 @@ "handle_parsing_errors", "verbose", "max_iterations", + "agent_description", "memory", "sender", "sender_name", "n_messages", "session_id", "order", - "template" + "template", + "add_current_date_tool" ], "frozen": false, "icon": "bot", - "key": "Agent", "legacy": false, - "lf_version": "1.0.19", "metadata": {}, "output_types": [], "outputs": [ @@ -1025,7 +188,7 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "A helpful assistant with access to tools." + "value": "A helpful assistant with access to the following tools:" }, "agent_llm": { "_input_type": "DropdownInput", @@ -1047,10 +210,10 @@ ], "placeholder": "", "real_time_refresh": true, - "refresh_button": false, "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "OpenAI" @@ -1072,7 +235,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "OPENAI_API_KEY" }, "code": { "advanced": true, @@ -1124,6 +287,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": true, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -1239,6 +403,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "gpt-4o-mini" @@ -1292,6 +457,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "Ascending" @@ -1364,6 +530,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "Machine and User" @@ -1384,6 +551,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -1405,6 +573,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -1427,10 +596,11 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "You are a helpful assistant that can use tools to answer questions and perform tasks." + "value": "You are a helpful assistant that can use tools to answer questions and perform tasks.\nUse markdown to format your answer, properly embedding images and urls." }, "temperature": { "_input_type": "FloatInput", @@ -1465,6 +635,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -1507,42 +678,823 @@ "type": "bool", "value": true } - } + }, + "tool_mode": false }, "type": "Agent" }, "dragging": false, - "height": 680, - "id": "Agent-7mKwO", + "height": 650, + "id": "Agent-KhAae", "position": { - "x": 966.8637275749741, - "y": 198.5272428958864 + "x": 2306.5155821255557, + "y": 335.1151630488809 }, "positionAbsolute": { - "x": 966.8637275749741, - "y": 198.5272428958864 + "x": 2306.5155821255557, + "y": 335.1151630488809 }, "selected": false, "type": "genericNode", "width": 320 + }, + { + "data": { + "description": "Access financial data and market information using Yahoo Finance.", + "display_name": "Yahoo Finance Tool", + "id": "YahooFinanceTool-PzHUy", + "node": { + "base_classes": [ + "Data", + "Tool" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Access financial data and market information using Yahoo Finance.", + "display_name": "Yahoo Finance Tool", + "documentation": "", + "edited": false, + "field_order": [ + "symbol", + "method", + "num_news" + ], + "frozen": false, + "icon": "trending-up", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "run_model", + "name": "api_run_model", + "required_inputs": [], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Tool", + "method": "build_tool", + "name": "api_build_tool", + "required_inputs": [], + "selected": "Tool", + "types": [ + "Tool" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import ast\nimport pprint\nfrom enum import Enum\n\nimport yfinance as yf\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import DropdownInput, IntInput, MessageTextInput\nfrom langflow.schema import Data\n\n\nclass YahooFinanceMethod(Enum):\n GET_INFO = \"get_info\"\n GET_NEWS = \"get_news\"\n GET_ACTIONS = \"get_actions\"\n GET_ANALYSIS = \"get_analysis\"\n GET_BALANCE_SHEET = \"get_balance_sheet\"\n GET_CALENDAR = \"get_calendar\"\n GET_CASHFLOW = \"get_cashflow\"\n GET_INSTITUTIONAL_HOLDERS = \"get_institutional_holders\"\n GET_RECOMMENDATIONS = \"get_recommendations\"\n GET_SUSTAINABILITY = \"get_sustainability\"\n GET_MAJOR_HOLDERS = \"get_major_holders\"\n GET_MUTUALFUND_HOLDERS = \"get_mutualfund_holders\"\n GET_INSIDER_PURCHASES = \"get_insider_purchases\"\n GET_INSIDER_TRANSACTIONS = \"get_insider_transactions\"\n GET_INSIDER_ROSTER_HOLDERS = \"get_insider_roster_holders\"\n GET_DIVIDENDS = \"get_dividends\"\n GET_CAPITAL_GAINS = \"get_capital_gains\"\n GET_SPLITS = \"get_splits\"\n GET_SHARES = \"get_shares\"\n GET_FAST_INFO = \"get_fast_info\"\n GET_SEC_FILINGS = \"get_sec_filings\"\n GET_RECOMMENDATIONS_SUMMARY = \"get_recommendations_summary\"\n GET_UPGRADES_DOWNGRADES = \"get_upgrades_downgrades\"\n GET_EARNINGS = \"get_earnings\"\n GET_INCOME_STMT = \"get_income_stmt\"\n\n\nclass YahooFinanceSchema(BaseModel):\n symbol: str = Field(..., description=\"The stock symbol to retrieve data for.\")\n method: YahooFinanceMethod = Field(YahooFinanceMethod.GET_INFO, description=\"The type of data to retrieve.\")\n num_news: int | None = Field(5, description=\"The number of news articles to retrieve.\")\n\n\nclass YfinanceToolComponent(LCToolComponent):\n display_name = \"Yahoo Finance\"\n description = \"Access financial data and market information using Yahoo Finance.\"\n icon = \"trending-up\"\n name = \"YahooFinanceTool\"\n\n inputs = [\n MessageTextInput(\n name=\"symbol\",\n display_name=\"Stock Symbol\",\n info=\"The stock symbol to retrieve data for (e.g., AAPL, GOOG).\",\n ),\n DropdownInput(\n name=\"method\",\n display_name=\"Data Method\",\n info=\"The type of data to retrieve.\",\n options=list(YahooFinanceMethod),\n value=\"get_news\",\n ),\n IntInput(\n name=\"num_news\",\n display_name=\"Number of News\",\n info=\"The number of news articles to retrieve (only applicable for get_news).\",\n value=5,\n ),\n ]\n\n def run_model(self) -> list[Data]:\n return self._yahoo_finance_tool(\n self.symbol,\n self.method,\n self.num_news,\n )\n\n def build_tool(self) -> Tool:\n return StructuredTool.from_function(\n name=\"yahoo_finance\",\n description=\"Access financial data and market information from Yahoo Finance.\",\n func=self._yahoo_finance_tool,\n args_schema=YahooFinanceSchema,\n )\n\n def _yahoo_finance_tool(\n self,\n symbol: str,\n method: YahooFinanceMethod,\n num_news: int | None = 5,\n ) -> list[Data]:\n ticker = yf.Ticker(symbol)\n\n try:\n if method == YahooFinanceMethod.GET_INFO:\n result = ticker.info\n elif method == YahooFinanceMethod.GET_NEWS:\n result = ticker.news[:num_news]\n else:\n result = getattr(ticker, method.value)()\n\n result = pprint.pformat(result)\n\n if method == YahooFinanceMethod.GET_NEWS:\n data_list = [Data(data=article) for article in ast.literal_eval(result)]\n else:\n data_list = [Data(data={\"result\": result})]\n\n except Exception as e:\n error_message = f\"Error retrieving data: {e}\"\n logger.debug(error_message)\n self.status = error_message\n raise ToolException(error_message) from e\n\n return data_list\n" + }, + "method": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Data Method", + "dynamic": false, + "info": "The type of data to retrieve.", + "name": "method", + "options": [ + "get_info", + "get_news", + "get_actions", + "get_analysis", + "get_balance_sheet", + "get_calendar", + "get_cashflow", + "get_institutional_holders", + "get_recommendations", + "get_sustainability", + "get_major_holders", + "get_mutualfund_holders", + "get_insider_purchases", + "get_insider_transactions", + "get_insider_roster_holders", + "get_dividends", + "get_capital_gains", + "get_splits", + "get_shares", + "get_fast_info", + "get_sec_filings", + "get_recommendations_summary", + "get_upgrades_downgrades", + "get_earnings", + "get_income_stmt" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "get_news" + }, + "num_news": { + "_input_type": "IntInput", + "advanced": false, + "display_name": "Number of News", + "dynamic": false, + "info": "The number of news articles to retrieve (only applicable for get_news).", + "list": false, + "name": "num_news", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 5 + }, + "symbol": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Stock Symbol", + "dynamic": false, + "info": "The stock symbol to retrieve data for (e.g., AAPL, GOOG).", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "symbol", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "NVDA" + } + }, + "tool_mode": false + }, + "type": "YahooFinanceTool" + }, + "dragging": false, + "height": 475, + "id": "YahooFinanceTool-PzHUy", + "position": { + "x": 1905.5096784216487, + "y": 313.6052678310467 + }, + "positionAbsolute": { + "x": 1905.5096784216487, + "y": 313.6052678310467 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "ChatInput-dBek4", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "search news about AAPL" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-dBek4", + "position": { + "x": 1907.4497817799925, + "y": 817.955066634514 + }, + "positionAbsolute": { + "x": 1907.4497817799925, + "y": 817.955066634514 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-ULcvr", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-ULcvr", + "position": { + "x": 2683.9938458383212, + "y": 556.5828467235146 + }, + "positionAbsolute": { + "x": 2683.9938458383212, + "y": 556.5828467235146 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-FSVUJ", + "node": { + "description": "# Simple Agent\nA straightforward implementation of a chatbot focusing on processing inputs and generating responses employing conversation memory capabilities.\n## Core Components\n1. **Chat Input**\n - Collects user messages for processing.\n2. **Agent**\n - Analyzes user input.\n - Generates contextually relevant responses.\n - Utilizes tools to refine and enhance replies as needed.\n3. **Chat Output**\n - Presents formatted responses to the user.\n - Ensures consistent conversational flow.\n## Features\n- Processes each message independently.\n- Focuses on generating relevant, immediate responses.\n- Handles each chat interaction as a standalone session.\n## Quick Start\n1. Initiate a chat by sending a message in Chat Input.\n2. The Agent processes the message, considering any immediate context.\n3. Receive a response in Chat Output.\n\nThis simple agent chatbot provides a streamlined conversational flow without the complexity of managing conversation memory.", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 736, + "id": "note-FSVUJ", + "position": { + "x": 1512.8976594415833, + "y": 312.9558305744385 + }, + "positionAbsolute": { + "x": 1512.8976594415833, + "y": 312.9558305744385 + }, + "resizing": false, + "selected": false, + "style": { + "height": 736, + "width": 382 + }, + "type": "noteNode", + "width": 382 } ], "viewport": { - "x": 147.77504195332347, - "y": 14.254381863292224, - "zoom": 0.5119423065126806 + "x": -1275.792144730309, + "y": -144.09980323772618, + "zoom": 0.8828160439097184 } }, - "description": "Single Agent Flow to get you started. This flow contains a calculator and a Python REPL tool, that could be used by our tool calling agent.", + "description": "A basic agent linked to the Yahoo Finance tool for quick access to stock prices, market trends, and financial data.", "endpoint_name": null, - "icon": "Users", - "id": "ad7caf8a-3357-4a2c-81d5-90c0ffb4ad3f", + "icon": "Bot", + "id": "a774332d-6fb5-43b6-96a4-d3eb8e62ddc0", "is_component": false, - "last_tested_version": "1.0.19", + "last_tested_version": "1.0.19.post2", "name": "Simple Agent", "tags": [ - "agents", - "openai", - "chatbots" + "assistants", + "agents" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json b/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json index afe21528d..a68e56d94 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json @@ -2,37 +2,180 @@ "data": { "edges": [ { + "animated": false, "className": "", "data": { "sourceHandle": { - 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"inputTypes": [ - "LanguageModel" - ], - "type": "other" - } - }, - "id": "reactflow__edge-OpenAIModel-gRakF{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-gRakFœ,œnameœ:œmodel_outputœ,œoutput_typesœ:[œLanguageModelœ]}-ToolCallingAgent-KLe5u{œfieldNameœ:œllmœ,œidœ:œToolCallingAgent-KLe5uœ,œinputTypesœ:[œLanguageModelœ],œtypeœ:œotherœ}", - "source": "OpenAIModel-gRakF", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-gRakFœ, œnameœ: œmodel_outputœ, œoutput_typesœ: [œLanguageModelœ]}", - "target": "ToolCallingAgent-KLe5u", - "targetHandle": "{œfieldNameœ: œllmœ, œidœ: œToolCallingAgent-KLe5uœ, œinputTypesœ: [œLanguageModelœ], œtypeœ: œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "CalculatorTool", - "id": "CalculatorTool-5S6u9", - "name": "api_build_tool", - "output_types": [ - "Tool" - ] - }, - "targetHandle": { - "fieldName": "tools", - "id": "ToolCallingAgent-VYDK9", - "inputTypes": [ - "Tool", - "BaseTool" - ], - "type": "other" - } - }, - "id": "reactflow__edge-CalculatorTool-5S6u9{œdataTypeœ:œCalculatorToolœ,œidœ:œCalculatorTool-5S6u9œ,œnameœ:œapi_build_toolœ,œoutput_typesœ:[œToolœ]}-ToolCallingAgent-VYDK9{œfieldNameœ:œtoolsœ,œidœ:œToolCallingAgent-VYDK9œ,œinputTypesœ:[œToolœ,œBaseToolœ],œtypeœ:œotherœ}", - "source": "CalculatorTool-5S6u9", - "sourceHandle": "{œdataTypeœ: œCalculatorToolœ, œidœ: œCalculatorTool-5S6u9œ, œnameœ: œapi_build_toolœ, œoutput_typesœ: [œToolœ]}", - "target": "ToolCallingAgent-VYDK9", - "targetHandle": "{œfieldNameœ: œtoolsœ, œidœ: œToolCallingAgent-VYDK9œ, œinputTypesœ: [œToolœ, œBaseToolœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-ChatInput-CIU0F{œdataTypeœ:œChatInputœ,œidœ:œChatInput-CIU0Fœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Agent-rPh1n{œfieldNameœ:œinput_valueœ,œidœ:œAgent-rPh1nœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-CIU0F", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-CIU0Fœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Agent-rPh1n", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œAgent-rPh1nœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ { "data": { - "id": "ChatInput-uYdzQ", + "id": "ChatInput-CIU0F", "node": { "base_classes": [ "Message" @@ -399,7 +223,7 @@ "frozen": false, "icon": "MessagesSquare", "legacy": false, - "lf_version": "1.0.15", + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -646,23 +470,25 @@ "type": "ChatInput" }, "dragging": false, - "height": 302, - "id": "ChatInput-uYdzQ", + "height": 234, + "id": "ChatInput-CIU0F", "position": { - "x": 1702.183330569805, - "y": 313.3797217631409 + "x": 1756.77096149088, + "y": 305.19157712497963 }, "positionAbsolute": { - "x": 1702.183330569805, - "y": 313.3797217631409 + "x": 1756.77096149088, + "y": 305.19157712497963 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "id": "ChatOutput-O63dG", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-ZNoa2", "node": { "base_classes": [ "Message" @@ -680,12 +506,15 @@ "sender", "sender_name", "session_id", - "data_template" + "data_template", + "background_color", + "chat_icon", + "text_color" ], "frozen": false, "icon": "MessagesSquare", "legacy": false, - "lf_version": "1.0.15", + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -720,6 +549,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -741,6 +571,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -780,13 +611,14 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "{text}" }, "input_value": { - "_input_type": "MessageTextInput", + "_input_type": "MessageInput", "advanced": false, "display_name": "Text", "dynamic": false, @@ -822,6 +654,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "Machine" @@ -842,6 +675,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -863,6 +697,7 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", @@ -900,643 +735,35 @@ "required": false, "show": true, "title_case": false, + "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" } - } + }, + "tool_mode": false }, "type": "ChatOutput" }, "dragging": false, - "height": 302, - "id": "ChatOutput-O63dG", + "height": 234, + "id": "ChatOutput-ZNoa2", "position": { - "x": 3968.8870036313238, - "y": 627.770746142633 + "x": 4349.229697347143, + "y": 620.5490494265098 }, "positionAbsolute": { - "x": 3968.8870036313238, - "y": 627.770746142633 + "x": 4349.229697347143, + "y": 620.5490494265098 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "id": "OpenAIModel-gRakF", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "system_message", - "stream", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "api_key", - "temperature", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "_input_type": "SecretStrInput", - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "_input_type": "MessageInput", - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "_input_type": "IntInput", - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "range_spec": { - "max": 128000, - "min": 0, - "step": 0.1, - "step_type": "float" - }, - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "_input_type": "DropdownInput", - "advanced": false, - "combobox": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "load_from_db": false, - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "_input_type": "StrInput", - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "_input_type": "IntInput", - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "_input_type": "FloatInput", - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 605, - "id": "OpenAIModel-gRakF", - "position": { - "x": 2141.564227810534, - "y": 492.8566267469695 - }, - "positionAbsolute": { - "x": 2141.564227810534, - "y": 492.8566267469695 - }, - "selected": true, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ToolCallingAgent-0QzrL", - "node": { - "base_classes": [ - "AgentExecutor", - "Message" - ], - "beta": true, - "conditional_paths": [], - "custom_fields": {}, - "description": "Agent that uses tools", - "display_name": "City Selection Agent", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "handle_parsing_errors", - "verbose", - "max_iterations", - "tools", - "llm", - "system_prompt", - "user_prompt", - "chat_history" - ], - "frozen": false, - "icon": "bot-message-square", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Agent", - "hidden": true, - "method": "build_agent", - "name": "agent", - "selected": "AgentExecutor", - "types": [ - "AgentExecutor" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Response", - "method": "message_response", - "name": "response", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "chat_history": { - "_input_type": "DataInput", - "advanced": true, - "display_name": "Chat History", - "dynamic": false, - "info": "", - "input_types": [ - "Data" - ], - "list": true, - "name": "chat_history", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import Optional, List\n\nfrom langchain.agents import create_tool_calling_agent\nfrom langchain_core.prompts import ChatPromptTemplate, PromptTemplate, HumanMessagePromptTemplate\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.inputs import MultilineInput\nfrom langflow.inputs.inputs import HandleInput, DataInput\nfrom langflow.schema import Data\n\n\nclass ToolCallingAgentComponent(LCToolsAgentComponent):\n display_name: str = \"Tool Calling Agent\"\n description: str = \"Agent that uses tools\"\n icon = \"bot-message-square\"\n beta = True\n name = \"ToolCallingAgent\"\n\n inputs = LCToolsAgentComponent._base_inputs + [\n HandleInput(name=\"llm\", display_name=\"Language Model\", input_types=[\"LanguageModel\"], required=True),\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"System Prompt\",\n info=\"System prompt for the agent.\",\n value=\"You are a helpful assistant\",\n ),\n MultilineInput(\n name=\"user_prompt\", display_name=\"Prompt\", info=\"This prompt must contain 'input' key.\", value=\"{input}\"\n ),\n DataInput(name=\"chat_history\", display_name=\"Chat History\", is_list=True, advanced=True),\n ]\n\n def get_chat_history_data(self) -> Optional[List[Data]]:\n return self.chat_history\n\n def create_agent_runnable(self):\n if \"input\" not in self.user_prompt:\n raise ValueError(\"Prompt must contain 'input' key.\")\n messages = [\n (\"system\", self.system_prompt),\n (\"placeholder\", \"{chat_history}\"),\n HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=[\"input\"], template=self.user_prompt)),\n (\"placeholder\", \"{agent_scratchpad}\"),\n ]\n prompt = ChatPromptTemplate.from_messages(messages)\n return create_tool_calling_agent(self.llm, self.tools, prompt)\n" - }, - "handle_parsing_errors": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Handle Parse Errors", - "dynamic": false, - "info": "", - "list": false, - "name": "handle_parsing_errors", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "input_value": { - "_input_type": "MessageTextInput", - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "llm": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "max_iterations": { - "_input_type": "IntInput", - "advanced": true, - "display_name": "Max Iterations", - "dynamic": false, - "info": "", - "list": false, - "name": "max_iterations", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 15 - }, - "system_prompt": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "System Prompt", - "dynamic": false, - "info": "System prompt for the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "system_prompt", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You are a City Selection Expert, skilled in analyzing travel data to pick ideal destinations. Your goal is to select the best city based on weather, season, and prices. Use the provided tools to gather information and make an informed decision. Your final output should be a detailed report on the chosen city, including flight costs, weather forecasts, and attractions." - }, - "tools": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "", - "input_types": [ - "Tool", - "BaseTool" - ], - "list": true, - "load_from_db": false, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "user_prompt": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Prompt", - "dynamic": false, - "info": "This prompt must contain 'input' key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_prompt", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{input}" - }, - "verbose": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - } - } - }, - "type": "ToolCallingAgent" - }, - "dragging": false, - "height": 570, - "id": "ToolCallingAgent-0QzrL", - "position": { - "x": 2624.854312225424, - "y": 459.94036227507735 - }, - "positionAbsolute": { - "x": 2624.854312225424, - "y": 459.94036227507735 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "SearchAPI-I4yU0", + "id": "SearchAPI-Aez0t", "node": { "base_classes": [ "Data", @@ -1558,7 +785,7 @@ ], "frozen": false, "legacy": false, - "lf_version": "1.0.15", + "lf_version": "1.0.19.post2", "metadata": {}, "official": false, "output_types": [], @@ -1612,7 +839,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "EnE19gGWNyewCPsMj5c1fMGx" }, "code": { "advanced": true, @@ -1728,23 +955,23 @@ "type": "SearchAPI" }, "dragging": false, - "height": 519, - "id": "SearchAPI-I4yU0", + "height": 407, + "id": "SearchAPI-Aez0t", "position": { - "x": 2147.8260389952898, - "y": -42.27285098321369 + "x": 2101.519951743063, + "y": 949.7032293566349 }, "positionAbsolute": { - "x": 2147.8260389952898, - "y": -42.27285098321369 + "x": 2101.519951743063, + "y": 949.7032293566349 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "id": "url_content_fetcher-1FugB", + "id": "url_content_fetcher-AyGpn", "node": { "base_classes": [ "Data", @@ -1764,13 +991,14 @@ ], "frozen": false, "icon": "globe", - "lf_version": "1.0.15", + "lf_version": "1.0.19.post2", "official": false, "output_types": [], "outputs": [ { "cache": true, "display_name": "Data", + "hidden": true, "method": "run_model", "name": "api_run_model", "selected": "Data", @@ -1855,557 +1083,23 @@ "type": "url_content_fetcher" }, "dragging": false, - "height": 347, - "id": "url_content_fetcher-1FugB", + "height": 234, + "id": "url_content_fetcher-AyGpn", "position": { - "x": 2629.911251521856, - "y": 77.86269189756271 + "x": 2834.525991812012, + "y": 939.6518333549263 }, "positionAbsolute": { - "x": 2629.911251521856, - "y": 77.86269189756271 + "x": 2834.525991812012, + "y": 939.6518333549263 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "id": "ToolCallingAgent-KLe5u", - "node": { - "base_classes": [ - "AgentExecutor", - "Message" - ], - "beta": true, - "conditional_paths": [], - "custom_fields": {}, - "description": "Agent that uses tools", - "display_name": "Local Expert Agent", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "handle_parsing_errors", - "verbose", - "max_iterations", - "tools", - "llm", - "system_prompt", - "user_prompt", - "chat_history" - ], - "frozen": false, - "icon": "bot-message-square", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Agent", - "hidden": true, - "method": "build_agent", - "name": "agent", - "selected": "AgentExecutor", - "types": [ - "AgentExecutor" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Response", - "method": "message_response", - "name": "response", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "chat_history": { - "_input_type": "DataInput", - "advanced": true, - "display_name": "Chat History", - "dynamic": false, - "info": "", - "input_types": [ - "Data" - ], - "list": true, - "name": "chat_history", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import Optional, List\n\nfrom langchain.agents import create_tool_calling_agent\nfrom langchain_core.prompts import ChatPromptTemplate, PromptTemplate, HumanMessagePromptTemplate\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.inputs import MultilineInput\nfrom langflow.inputs.inputs import HandleInput, DataInput\nfrom langflow.schema import Data\n\n\nclass ToolCallingAgentComponent(LCToolsAgentComponent):\n display_name: str = \"Tool Calling Agent\"\n description: str = \"Agent that uses tools\"\n icon = \"bot-message-square\"\n beta = True\n name = \"ToolCallingAgent\"\n\n inputs = LCToolsAgentComponent._base_inputs + [\n HandleInput(name=\"llm\", display_name=\"Language Model\", input_types=[\"LanguageModel\"], required=True),\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"System Prompt\",\n info=\"System prompt for the agent.\",\n value=\"You are a helpful assistant\",\n ),\n MultilineInput(\n name=\"user_prompt\", display_name=\"Prompt\", info=\"This prompt must contain 'input' key.\", value=\"{input}\"\n ),\n DataInput(name=\"chat_history\", display_name=\"Chat History\", is_list=True, advanced=True),\n ]\n\n def get_chat_history_data(self) -> Optional[List[Data]]:\n return self.chat_history\n\n def create_agent_runnable(self):\n if \"input\" not in self.user_prompt:\n raise ValueError(\"Prompt must contain 'input' key.\")\n messages = [\n (\"system\", self.system_prompt),\n (\"placeholder\", \"{chat_history}\"),\n HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=[\"input\"], template=self.user_prompt)),\n (\"placeholder\", \"{agent_scratchpad}\"),\n ]\n prompt = ChatPromptTemplate.from_messages(messages)\n return create_tool_calling_agent(self.llm, self.tools, prompt)\n" - }, - "handle_parsing_errors": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Handle Parse Errors", - "dynamic": false, - "info": "", - "list": false, - "name": "handle_parsing_errors", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "input_value": { - "_input_type": "MessageTextInput", - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "llm": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "max_iterations": { - "_input_type": "IntInput", - "advanced": true, - "display_name": "Max Iterations", - "dynamic": false, - "info": "", - "list": false, - "name": "max_iterations", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 15 - }, - "system_prompt": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "System Prompt", - "dynamic": false, - "info": "System prompt for the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "system_prompt", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You are a knowledgeable Local Expert with extensive information about the selected city, its attractions, and customs. Your goal is to provide the BEST insights about the city. Compile an in-depth guide for travelers, including key attractions, local customs, special events, and daily activity recommendations. Focus on hidden gems and local hotspots. Your final output should be a comprehensive city guide, rich in cultural insights and practical tips." - }, - "tools": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "", - "input_types": [ - "Tool", - "BaseTool" - ], - "list": true, - "load_from_db": false, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "user_prompt": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Prompt", - "dynamic": false, - "info": "This prompt must contain 'input' key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_prompt", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{input}" - }, - "verbose": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - } - } - }, - "type": "ToolCallingAgent" - }, - "dragging": false, - "height": 570, - "id": "ToolCallingAgent-KLe5u", - "position": { - "x": 3092.2977772950007, - "y": 456.1302150057377 - }, - "positionAbsolute": { - "x": 3092.2977772950007, - "y": 456.1302150057377 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ToolCallingAgent-VYDK9", - "node": { - "base_classes": [ - "AgentExecutor", - "Message" - ], - "beta": true, - "conditional_paths": [], - "custom_fields": {}, - "description": "Agent that uses tools", - "display_name": "Travel Concierge Agent", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "handle_parsing_errors", - "verbose", - "max_iterations", - "tools", - "llm", - "system_prompt", - "user_prompt", - "chat_history" - ], - "frozen": false, - "icon": "bot-message-square", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Agent", - "hidden": true, - "method": "build_agent", - "name": "agent", - "selected": "AgentExecutor", - "types": [ - "AgentExecutor" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Response", - "method": "message_response", - "name": "response", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "chat_history": { - "_input_type": "DataInput", - "advanced": true, - "display_name": "Chat History", - "dynamic": false, - "info": "", - "input_types": [ - "Data" - ], - "list": true, - "name": "chat_history", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import Optional, List\n\nfrom langchain.agents import create_tool_calling_agent\nfrom langchain_core.prompts import ChatPromptTemplate, PromptTemplate, HumanMessagePromptTemplate\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.inputs import MultilineInput\nfrom langflow.inputs.inputs import HandleInput, DataInput\nfrom langflow.schema import Data\n\n\nclass ToolCallingAgentComponent(LCToolsAgentComponent):\n display_name: str = \"Tool Calling Agent\"\n description: str = \"Agent that uses tools\"\n icon = \"bot-message-square\"\n beta = True\n name = \"ToolCallingAgent\"\n\n inputs = LCToolsAgentComponent._base_inputs + [\n HandleInput(name=\"llm\", display_name=\"Language Model\", input_types=[\"LanguageModel\"], required=True),\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"System Prompt\",\n info=\"System prompt for the agent.\",\n value=\"You are a helpful assistant\",\n ),\n MultilineInput(\n name=\"user_prompt\", display_name=\"Prompt\", info=\"This prompt must contain 'input' key.\", value=\"{input}\"\n ),\n DataInput(name=\"chat_history\", display_name=\"Chat History\", is_list=True, advanced=True),\n ]\n\n def get_chat_history_data(self) -> Optional[List[Data]]:\n return self.chat_history\n\n def create_agent_runnable(self):\n if \"input\" not in self.user_prompt:\n raise ValueError(\"Prompt must contain 'input' key.\")\n messages = [\n (\"system\", self.system_prompt),\n (\"placeholder\", \"{chat_history}\"),\n HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=[\"input\"], template=self.user_prompt)),\n (\"placeholder\", \"{agent_scratchpad}\"),\n ]\n prompt = ChatPromptTemplate.from_messages(messages)\n return create_tool_calling_agent(self.llm, self.tools, prompt)\n" - }, - "handle_parsing_errors": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Handle Parse Errors", - "dynamic": false, - "info": "", - "list": false, - "name": "handle_parsing_errors", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "input_value": { - "_input_type": "MessageTextInput", - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "llm": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Language Model", - "dynamic": false, - "info": "", - "input_types": [ - "LanguageModel" - ], - "list": false, - "name": "llm", - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "max_iterations": { - "_input_type": "IntInput", - "advanced": true, - "display_name": "Max Iterations", - "dynamic": false, - "info": "", - "list": false, - "name": "max_iterations", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 15 - }, - "system_prompt": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "System Prompt", - "dynamic": false, - "info": "System prompt for the agent.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "system_prompt", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "You are an Amazing Travel Concierge, a specialist in travel planning and logistics with decades of experience. Your goal is to create the most amazing travel itineraries with budget and packing suggestions for the city. Expand the city guide into a full 7-day travel itinerary with detailed per-day plans. Include weather forecasts, places to eat, packing suggestions, and a budget breakdown. Suggest actual places to visit, hotels to stay, and restaurants to go to. Your final output should be a complete expanded travel plan, formatted as markdown, encompassing a daily schedule, anticipated weather conditions, recommended clothing and items to pack, and a detailed budget." - }, - "tools": { - "_input_type": "HandleInput", - "advanced": false, - "display_name": "Tools", - "dynamic": false, - "info": "", - "input_types": [ - "Tool", - "BaseTool" - ], - "list": true, - "load_from_db": false, - "name": "tools", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "user_prompt": { - "_input_type": "MultilineInput", - "advanced": false, - "display_name": "Prompt", - "dynamic": false, - "info": "This prompt must contain 'input' key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_prompt", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{input}" - }, - "verbose": { - "_input_type": "BoolInput", - "advanced": true, - "display_name": "Verbose", - "dynamic": false, - "info": "", - "list": false, - "name": "verbose", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - } - } - }, - "type": "ToolCallingAgent" - }, - "dragging": false, - "height": 570, - "id": "ToolCallingAgent-VYDK9", - "position": { - "x": 3515.829696775688, - "y": 461.15233262803827 - }, - "positionAbsolute": { - "x": 3515.829696775688, - "y": 461.15233262803827 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "CalculatorTool-5S6u9", + "id": "CalculatorTool-dGfrj", "node": { "base_classes": [ "Data", @@ -2426,7 +1120,7 @@ "frozen": false, "icon": "calculator", "legacy": false, - "lf_version": "1.0.15", + "lf_version": "1.0.19.post2", "metadata": {}, "official": false, "output_types": [], @@ -2503,37 +1197,2030 @@ "type": "CalculatorTool" }, "dragging": false, - "height": 375, - "id": "CalculatorTool-5S6u9", + "height": 254, + "id": "CalculatorTool-dGfrj", "position": { - "x": 3094.040233522674, - "y": 59.811211480422756 + "x": 3546.599894399727, + "y": 972.1522299506486 }, "positionAbsolute": { - "x": 3094.040233522674, - "y": 59.811211480422756 + "x": 3546.599894399727, + "y": 972.1522299506486 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "City Selection Agent", + "id": "Agent-rPh1n", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "City Selection Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model = self.get_llm()\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix)\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are a helpful assistant that can use tools to answer questions and perform tasks." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": true, + "height": 650, + "id": "Agent-rPh1n", + "position": { + "x": 2472.7748760933105, + "y": 335.66187210240537 + }, + "positionAbsolute": { + "x": 2472.7748760933105, + "y": 335.66187210240537 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Local Expert Agent", + "id": "Agent-cj2PH", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Local Expert Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model = self.get_llm()\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix)\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are a knowledgeable Local Expert with extensive information about the selected city, its attractions, and customs. Your goal is to provide the BEST insights about the city. Compile an in-depth guide for travelers, including key attractions, local customs, special events, and daily activity recommendations. Focus on hidden gems and local hotspots. Your final output should be a comprehensive city guide, rich in cultural insights and practical tips." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-cj2PH", + "position": { + "x": 3185.66991544494, + "y": 355.95841004876377 + }, + "positionAbsolute": { + "x": 3185.66991544494, + "y": 355.95841004876377 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Travel Concierge Agent", + "id": "Agent-ImgzA", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Travel Concierge Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model = self.get_llm()\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix)\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are an Amazing Travel Concierge, a specialist in travel planning and logistics with decades of experience. Your goal is to create the most amazing travel itineraries with budget and packing suggestions for the city. Expand the city guide into a full 7-day travel itinerary with detailed per-day plans. Include weather forecasts, places to eat, packing suggestions, and a budget breakdown. Suggest actual places to visit, hotels to stay, and restaurants to go to. Your final output should be a complete expanded travel plan, formatted as markdown, encompassing a daily schedule, anticipated weather conditions, recommended clothing and items to pack, and a detailed budget." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-ImgzA", + "position": { + "x": 3889.695953842898, + "y": 370.3161168611889 + }, + "positionAbsolute": { + "x": 3889.695953842898, + "y": 370.3161168611889 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-jCp1N", + "node": { + "description": "# Travel Planning Agents \n\nThe travel planning system is a smart setup that uses several specialized \"agents\" to help plan incredible trips. Imagine each agent as a travel expert focusing on a part of your journey. Here's how it works:\n\n- **User-Friendly Start:** You start by telling the system about your travel needs—where you want to go and what you love to do.\n\n- **Data Collection:** The agents uses its tools to gather current info about various destinations, like the best travel times, weather, and costs.\n\n- **Three Key Agents:**\n - **City Selection Agent:** Picks the best places to visit based on your likes and current data.\n - **Local Expert Agent:** Gathers interesting details about what to do and see in the chosen city.\n - **Travel Concierge Agent:** Builds a day-by-day plan that includes where to stay, eat, and explore!\n\n- **Tools and Data:** Each agent uses tools to find and organize the latest information so you get recommendations that are both accurate and exciting.\n\n- **Final Plan:** Once everything is put together, you receive a complete, easy-to-follow travel itinerary, perfect for your adventure!\n", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 636, + "id": "note-jCp1N", + "position": { + "x": 1076.3710803600266, + "y": 92.06058855045646 + }, + "positionAbsolute": { + "x": 1076.3710803600266, + "y": 92.06058855045646 + }, + "resizing": false, + "selected": false, + "style": { + "height": 636, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "id": "note-jgIF0", + "node": { + "description": "# **City Selection Agent**\n - **Purpose:** This agent evaluates potential travel destinations based on user input and external data sources.\n - **Core Functions:** Analyzes factors such as weather, local events, and travel costs to recommend optimal cities.\n - **Tools Utilized:** Employs APIs and data-fetching tools to gather real-time information for decision-making.\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 362, + "id": "note-jgIF0", + "position": { + "x": 2122.4146132377227, + "y": 485.2212661145467 + }, + "positionAbsolute": { + "x": 2122.4146132377227, + "y": 485.2212661145467 + }, + "resizing": false, + "selected": false, + "style": { + "height": 362, + "width": 331 + }, + "type": "noteNode", + "width": 331 + }, + { + "data": { + "id": "note-NTTln", + "node": { + "description": "# **Local Expert Agent**\n - **Purpose:** Focused on gathering and providing an in-depth guide to the selected city.\n - **Core Functions:** Compiles insights into cultural attractions, local customs, and unique experiences.\n - **Tools Utilized:** Uses web content fetchers and data APIs to collect detailed local insights and enhance the user understanding with hidden gems.\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 366, + "id": "note-NTTln", + "position": { + "x": 2827.660803823376, + "y": 488.6092281195304 + }, + "positionAbsolute": { + "x": 2827.660803823376, + "y": 488.6092281195304 + }, + "resizing": false, + "selected": false, + "style": { + "height": 366, + "width": 351 + }, + "type": "noteNode", + "width": 351 + }, + { + "data": { + "id": "note-45aOQ", + "node": { + "description": "# **Travel Concierge Agent**\n - **Purpose:** Crafts detailed travel itineraries that are customized to the traveler's interests and needs.\n - **Core Functions:** Offers a comprehensive daily schedule, including accommodations, dining spots, and activities.\n - **Tools Utilized:** Integrates calculators and data tools for accurate budget planning and itinerary logistics.", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 344, + "id": "note-45aOQ", + "position": { + "x": 3536.084279543714, + "y": 496.3155992003396 + }, + "positionAbsolute": { + "x": 3536.084279543714, + "y": 496.3155992003396 + }, + "resizing": false, + "selected": false, + "style": { + "height": 344, + "width": 344 + }, + "type": "noteNode", + "width": 344 + }, + { + "data": { + "id": "note-elTLU", + "node": { + "description": "## Configure the agent by obtaining your OpenAI API key from [platform.openai.com](https://platform.openai.com). Under \"Model Provider\", choose:\n- OpenAI: Default, requires only API key\n- Anthropic/Azure/Groq/NVIDIA: Each requires their own API keys\n- Custom: Use your own model endpoint + authentication\n\nSelect model and input API key before running the flow.", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "rose" + } + }, + "type": "note" + }, + "dragging": false, + "height": 325, + "id": "note-elTLU", + "position": { + "x": 2463.3881993480218, + "y": 42.83594355441298 + }, + "positionAbsolute": { + "x": 2463.3881993480218, + "y": 42.83594355441298 + }, + "selected": false, + "type": "noteNode", + "width": 325 } ], "viewport": { - "x": -805.3414274486533, - "y": 202.2051258636879, - "zoom": 0.5130713077517347 + "x": -1078.5758749396496, + "y": -166.63499501100648, + "zoom": 0.6513143480813044 } }, - "description": "Multi Agent system to plan trips.", + "description": "Create a travel planning chatbot that uses specialized agents to craft personalized trip itineraries.", "endpoint_name": null, "icon": "Plane", - "id": "c15755c5-264b-4ca7-bed8-9bbf605307f1", + "id": "d6d33090-44c4-4a4b-8d06-c93fcf426446", "is_component": false, - "last_tested_version": "1.0.17", + "last_tested_version": "1.0.19.post2", "name": "Travel Planning Agents", "tags": [ "agents", - "openai", - "chatbots" + "openai" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json b/src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json new file mode 100644 index 000000000..998719116 --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json @@ -0,0 +1,2052 @@ +{ + "data": { + "edges": [ + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-t1to9", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + 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"reactflow__edge-ChatInput-tE8u3{œdataTypeœ:œChatInputœ,œidœ:œChatInput-tE8u3œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-t1to9{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-t1to9œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-tE8u3", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-tE8u3œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-t1to9", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-t1to9œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "id": "ChatInput-tE8u3", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "*Objective:* Create an engaging Twitter thread that narrates the innovative journey of our LangFlow project, highlighting how we created a specialized flow for generating dynamic prompts for other flows, culminating in a model specialized in writing tweets/threads. *Project Stages:* 1. *Development in LangFlow:* - Created a flow focused on generating dynamic prompts - System serves as foundation for optimizing prompt generation in other flows 2. *Template Creation:* - Developed specific templates for tweets/threads - Focus on engagement and message clarity 3. *Results:* - 60% reduction in content creation time - Greater message consistency - Better social media engagement - Fully automated process *Thread Objectives:* - Educate about LangFlow's capabilities in content creation - Demonstrate the development process step by step - Inspire other developers to explore LangFlow - Strengthen the developer community" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-tE8u3", + "position": { + "x": 863.3241377184722, + "y": 1053.9324095084933 + }, + "positionAbsolute": { + "x": 863.3241377184722, + "y": 1053.9324095084933 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "TextInput-0yHbX", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get text inputs from the Playground.", + "display_name": "Content Guidelines", + "documentation": "", + "edited": false, + "field_order": [ + "input_value" + ], + "frozen": false, + "icon": "type", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n return Message(\n text=self.input_value,\n )\n" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Text to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "- Thread must be 5-7 tweets long - Each tweet should be self-contained but flow naturally to the next - Include relevant technical details while keeping language accessible - Use emojis sparingly but effectively - Include a clear call-to-action in the final tweet - Highlight key benefits and innovative aspects - Maintain professional but engaging tone" + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 234, + "id": "TextInput-0yHbX", + "position": { + "x": 1300.291760633212, + "y": 417.7819626108867 + }, + "positionAbsolute": { + "x": 1300.291760633212, + "y": 417.7819626108867 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "id": "OpenAIModel-t1to9", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 630, + "id": "OpenAIModel-t1to9", + "position": { + "x": 2072.0401998064262, + "y": 828.7738120746212 + }, + "positionAbsolute": { + "x": 2072.0401998064262, + "y": 828.7738120746212 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-n8Wmg", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-n8Wmg", + "position": { + "x": 2470.223353127597, + "y": 1055.4039338762416 + }, + "positionAbsolute": { + "x": 2470.223353127597, + "y": 1055.4039338762416 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "TextInput-HVGJ1", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get text inputs from the Playground.", + "display_name": "Output Format", + "documentation": "", + "edited": false, + "field_order": [ + "input_value" + ], + "frozen": false, + "icon": "type", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n return Message(\n text=self.input_value,\n )\n" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Text to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "thread" + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 234, + "id": "TextInput-HVGJ1", + "position": { + "x": 1300.639277084099, + "y": 665.0274048594538 + }, + "positionAbsolute": { + "x": 1300.639277084099, + "y": 665.0274048594538 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "TextInput-0s9hL", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get text inputs from the Playground.", + "display_name": "Output Language", + "documentation": "", + "edited": false, + "field_order": [ + "input_value" + ], + "frozen": false, + "icon": "type", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n return Message(\n text=self.input_value,\n )\n" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Text to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "English" + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 234, + "id": "TextInput-0s9hL", + "position": { + "x": 1302.1321888373375, + "y": 910.3592488005739 + }, + "positionAbsolute": { + "x": 1302.1321888373375, + "y": 910.3592488005739 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "TextInput-ZUCJB", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get text inputs from the Playground.", + "display_name": "Profile Details", + "documentation": "", + "edited": false, + "field_order": [ + "input_value" + ], + "frozen": false, + "icon": "type", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n return Message(\n text=self.input_value,\n )\n" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Text to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "- Tech startup focused on AI/ML innovation - Active in open-source community - Experienced in building developer tools - Known for clear technical communication - Engaged audience of developers and AI enthusiasts" + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 234, + "id": "TextInput-ZUCJB", + "position": { + "x": 1302.0774628387737, + "y": 1167.3244357663511 + }, + "positionAbsolute": { + "x": 1302.0774628387737, + "y": 1167.3244357663511 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "TextInput-hSMuv", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get text inputs from the Playground.", + "display_name": "Tone And Style", + "documentation": "", + "edited": false, + "field_order": [ + "input_value" + ], + "frozen": false, + "icon": "type", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n return Message(\n text=self.input_value,\n )\n" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Text to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "- Professional yet approachable - Technical but accessible - Enthusiastic about innovation - Educational and informative - Collaborative and community-focused - Clear and concise - Solution-oriented" + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 234, + "id": "TextInput-hSMuv", + "position": { + "x": 1301.68182643676, + "y": 1699.978793221378 + }, + "positionAbsolute": { + "x": 1301.68182643676, + "y": 1699.978793221378 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "TextInput-b4m4C", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get text inputs from the Playground.", + "display_name": "Profile Type", + "documentation": "", + "edited": false, + "field_order": [ + "input_value" + ], + "frozen": false, + "icon": "type", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n name = \"TextInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n return Message(\n text=self.input_value,\n )\n" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Text to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "Tech Company / AI Developer Platform" + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 234, + "id": "TextInput-b4m4C", + "position": { + "x": 1301.4778537945892, + "y": 1428.1749742780207 + }, + "positionAbsolute": { + "x": 1301.4778537945892, + "y": 1428.1749742780207 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-oQQCJ", + "node": { + "description": "# Twitter Thread Generator\n\nWelcome to the Twitter Thread Generator! This flow helps you create compelling Twitter threads by transforming your structured inputs into engaging content.\n\n## Instructions\n\n1. Prepare Your Inputs\n - Fill in the \"Context\" with your main message or story\n - Define \"Content Guidelines\" for thread structure and style\n - Specify \"Profile Type\" and \"Profile Details\" to reflect your brand identity\n - Set \"Tone and Style\" to guide the communication approach\n - Choose \"Output Format\" (thread) and desired language\n\n2. Configure the Prompt\n - The flow uses a specialized prompt template to generate content\n - Ensure all input fields are connected to the prompt node\n\n3. Run the Generation\n - Execute the flow to process your inputs\n - The OpenAI model will create the thread based on your specifications\n\n4. Review and Refine\n - Examine the output in the Chat Output node\n - If needed, adjust your inputs and re-run for better results\n\n5. Finalize and Post\n - Once satisfied, copy the generated thread\n - Post to Twitter, maintaining the structure and flow\n\nRemember: Be specific in your context and guidelines for the best results! 🚀\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "amber" + } + }, + "type": "note" + }, + "dragging": false, + "height": 800, + "id": "note-oQQCJ", + "position": { + "x": 675.0099418843004, + "y": 233.23451233469402 + }, + "positionAbsolute": { + "x": 675.0099418843004, + "y": 233.23451233469402 + }, + "resizing": false, + "selected": false, + "style": { + "height": 800, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-nDs5I", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "PROFILE_TYPE", + "PROFILE_DETAILS", + "CONTENT_GUIDELINES", + "TONE_AND_STYLE", + "OUTPUT_FORMAT", + "OUTPUT_LANGUAGE" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "CONTENT_GUIDELINES": { + "advanced": false, + "display_name": "CONTENT_GUIDELINES", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "CONTENT_GUIDELINES", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "OUTPUT_FORMAT": { + "advanced": false, + "display_name": "OUTPUT_FORMAT", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "OUTPUT_FORMAT", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "OUTPUT_LANGUAGE": { + "advanced": false, + "display_name": "OUTPUT_LANGUAGE", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "OUTPUT_LANGUAGE", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "PROFILE_DETAILS": { + "advanced": false, + "display_name": "PROFILE_DETAILS", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "PROFILE_DETAILS", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "PROFILE_TYPE": { + "advanced": false, + "display_name": "PROFILE_TYPE", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "PROFILE_TYPE", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "TONE_AND_STYLE": { + "advanced": false, + "display_name": "TONE_AND_STYLE", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "TONE_AND_STYLE", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + }, + "template": { + "_input_type": "PromptInput", + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "type": "prompt", + "value": "\nIntroduce the task of generating tweets or tweet threads based on the provided inputs\n\nExplain each input variable:\n\n{{PROFILE_TYPE}}\n\n{{PROFILE_DETAILS}}\n\n{{CONTENT_GUIDELINES}}\n\n{{TONE_AND_STYLE}}\n\n{{CONTEXT}}\n\n{{OUTPUT_FORMAT}}\n\n{{OUTPUT_LANGUAGE}}\n\nProvide step-by-step instructions on how to analyze the inputs to determine if a single tweet or thread is appropriate\n\nGive guidance on generating tweet content that aligns with the profile, guidelines, tone, style, and context\n\nExplain how to format the output based on the {{OUTPUT_FORMAT}} value\n\nProvide tips for creating engaging, coherent tweet content\n\n\n\n\nYou are an AI tweet generator that can create standalone tweets or multi-tweet threads based on a variety of inputs about the desired content. Here are the key inputs you will use to generate the tweet(s):\n\n\n\n{PROFILE_TYPE}\n\n\n\n\n\n{PROFILE_DETAILS}\n\n\n\n\n\n{CONTENT_GUIDELINES}\n\n\n\n\n\n{TONE_AND_STYLE}\n\n\n\n\n\n{OUTPUT_FORMAT}\n\n\n\n\n\n\n{OUTPUT_LANGUAGE}\n\n\n\nTo generate the appropriate tweet(s), follow these steps:\n\n\n\nCarefully analyze the {{PROFILE_TYPE}}, {{PROFILE_DETAILS}}, {{CONTENT_GUIDELINES}}, {{TONE_AND_STYLE}}, and {{CONTEXT}} to determine the depth and breadth of content needed.\n\nIf the {{OUTPUT_FORMAT}} is \"single_tweet\", plan to convey the key information in a concise, standalone tweet.\n\nIf the {{OUTPUT_FORMAT}} is \"thread\" or if the content seems too complex for a single tweet, outline a series of connected tweets that flow together to cover the topic.\n\n\n\n\n\nBrainstorm tweet content that aligns with the {{PROFILE_TYPE}} and {{PROFILE_DETAILS}}, adheres to the {{CONTENT_GUIDELINES}}, matches the {{TONE_AND_STYLE}}, and incorporates the {{CONTEXT}}.\n\nFor a single tweet, craft the most engaging, informative message possible within the 280 character limit.\n\nFor a thread, break down the content into distinct yet connected tweet-sized chunks. Ensure each tweet flows logically into the next to maintain reader engagement. Use transitional phrases as needed to link tweets.\n\n\n\n\nFormat the output based on the {{OUTPUT_FORMAT}}:\n\nFor a single tweet, provide the content.\n\nFor a thread, include each tweet inside numbered markdown list.\n\n \nFocus on creating original, engaging content that provides value to the intended audience.\n\nOptimize the tweet(s) for the 280 character limit. Be concise yet impactful.\n\nMaintain a consistent voice that matches the {{TONE_AND_STYLE}} throughout the tweet(s).\n\nInclude calls-to-action or questions to drive engagement when appropriate.\n\nDouble check that the final output aligns with the {{PROFILE_DETAILS}} and {{CONTENT_GUIDELINES}}.\n\n\n\nNow create a Tweet or Twitter Thread for this context:\n\n" + } + }, + "tool_mode": false + }, + "type": "Prompt" + }, + "dragging": false, + "height": 779, + "id": "Prompt-nDs5I", + "position": { + "x": 1697.1682096049744, + "y": 675.4022940880462 + }, + "positionAbsolute": { + "x": 1697.1682096049744, + "y": 675.4022940880462 + }, + "selected": false, + "type": "genericNode", + "width": 320 + } + ], + "viewport": { + "x": -137.29857182316698, + "y": -73.67014598946389, + "zoom": 0.49710856297206957 + } + }, + "description": "Transform structured inputs into engaging Twitter threads with this prompt-based flow, maintaining brand voice and technical accuracy.", + "endpoint_name": null, + "icon": "TwitterLogoIcon", + "id": "e73336f0-7ac5-42a5-827c-4b060a0556c6", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "Twitter Thread Generator", + "tags": [ + "chatbots", + "content-generation" + ] +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json index 2e7bfa93f..fee0bfc8e 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json @@ -2,37 +2,12 @@ "data": { "edges": [ { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-jvvNM", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "search_input", - "id": "AstraVectorStoreComponent-0WT85", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-jvvNM{œdataTypeœ:œChatInputœ,œidœ:œChatInput-jvvNMœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraVectorStoreComponent-0WT85{œfieldNameœ:œsearch_inputœ,œidœ:œAstraVectorStoreComponent-0WT85œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "ChatInput-jvvNM", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-jvvNMœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "AstraVectorStoreComponent-0WT85", - "targetHandle": "{œfieldNameœ: œsearch_inputœ, œidœ: œAstraVectorStoreComponent-0WT85œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "ParseData", - "id": "ParseData-f6Jhl", + "id": "ParseData-pqaC7", "name": "text", "output_types": [ "Message" @@ -40,7 +15,7 @@ }, "targetHandle": { "fieldName": "context", - "id": "Prompt-oJ8Eh", + "id": "Prompt-uqDcR", "inputTypes": [ "Message", "Text" @@ -48,149 +23,19 @@ "type": "str" } }, - "id": "reactflow__edge-ParseData-f6Jhl{œdataTypeœ:œParseDataœ,œidœ:œParseData-f6Jhlœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-oJ8Eh{œfieldNameœ:œcontextœ,œidœ:œPrompt-oJ8Ehœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ParseData-f6Jhl", - "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-f6Jhlœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-oJ8Eh", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-oJ8Ehœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-jvvNM", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "question", - "id": "Prompt-oJ8Eh", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-jvvNM{œdataTypeœ:œChatInputœ,œidœ:œChatInput-jvvNMœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-oJ8Eh{œfieldNameœ:œquestionœ,œidœ:œPrompt-oJ8Ehœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-jvvNM", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-jvvNMœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-oJ8Eh", - "targetHandle": "{œfieldNameœ: œquestionœ, œidœ: œPrompt-oJ8Ehœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "File", - "id": "File-JZzdd", - "name": "data", - "output_types": [ - "Data" - ] - }, - "targetHandle": { - "fieldName": "data_inputs", - "id": "SplitText-Kl7VQ", - "inputTypes": [ - "Data" - ], - "type": "other" - } - }, - "id": "reactflow__edge-File-JZzdd{œdataTypeœ:œFileœ,œidœ:œFile-JZzddœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-SplitText-Kl7VQ{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-Kl7VQœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "File-JZzdd", - "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-JZzddœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "SplitText-Kl7VQ", - "targetHandle": "{œfieldNameœ: œdata_inputsœ, œidœ: œSplitText-Kl7VQœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "SplitText", - "id": "SplitText-Kl7VQ", - "name": "chunks", - "output_types": [ - "Data" - ] - }, - "targetHandle": { - "fieldName": "ingest_data", - "id": "AstraVectorStoreComponent-EUhWZ", - "inputTypes": [ - "Data" - ], - "type": "other" - } - }, - "id": "reactflow__edge-SplitText-Kl7VQ{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-Kl7VQœ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}-AstraVectorStoreComponent-EUhWZ{œfieldNameœ:œingest_dataœ,œidœ:œAstraVectorStoreComponent-EUhWZœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "SplitText-Kl7VQ", - "sourceHandle": "{œdataTypeœ: œSplitTextœ, œidœ: œSplitText-Kl7VQœ, œnameœ: œchunksœ, œoutput_typesœ: [œDataœ]}", - "target": "AstraVectorStoreComponent-EUhWZ", - "targetHandle": "{œfieldNameœ: œingest_dataœ, œidœ: œAstraVectorStoreComponent-EUhWZœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIEmbeddings", - "id": "OpenAIEmbeddings-Mf9md", - "name": "embeddings", - "output_types": [ - "Embeddings" - ] - }, - "targetHandle": { - "fieldName": "embedding", - "id": "AstraVectorStoreComponent-EUhWZ", - "inputTypes": [ - "Embeddings" - ], - "type": "other" - } - }, - "id": "reactflow__edge-OpenAIEmbeddings-Mf9md{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-Mf9mdœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraVectorStoreComponent-EUhWZ{œfieldNameœ:œembeddingœ,œidœ:œAstraVectorStoreComponent-EUhWZœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", - "source": "OpenAIEmbeddings-Mf9md", - "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-Mf9mdœ, œnameœ: œembeddingsœ, œoutput_typesœ: [œEmbeddingsœ]}", - "target": "AstraVectorStoreComponent-EUhWZ", - "targetHandle": "{œfieldNameœ: œembeddingœ, œidœ: œAstraVectorStoreComponent-EUhWZœ, œinputTypesœ: [œEmbeddingsœ], œtypeœ: œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIEmbeddings", - "id": "OpenAIEmbeddings-q2lBh", - "name": "embeddings", - "output_types": [ - "Embeddings" - ] - }, - "targetHandle": { - "fieldName": "embedding", - "id": "AstraVectorStoreComponent-0WT85", - "inputTypes": [ - "Embeddings" - ], - "type": "other" - } - }, - "id": "reactflow__edge-OpenAIEmbeddings-q2lBh{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-q2lBhœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraVectorStoreComponent-0WT85{œfieldNameœ:œembeddingœ,œidœ:œAstraVectorStoreComponent-0WT85œ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", - "source": "OpenAIEmbeddings-q2lBh", - "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-q2lBhœ, œnameœ: œembeddingsœ, œoutput_typesœ: [œEmbeddingsœ]}", - "target": "AstraVectorStoreComponent-0WT85", - "targetHandle": "{œfieldNameœ: œembeddingœ, œidœ: œAstraVectorStoreComponent-0WT85œ, œinputTypesœ: [œEmbeddingsœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-ParseData-pqaC7{œdataTypeœ:œParseDataœ,œidœ:œParseData-pqaC7œ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-uqDcR{œfieldNameœ:œcontextœ,œidœ:œPrompt-uqDcRœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-pqaC7", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-pqaC7œ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-uqDcR", + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-uqDcRœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-oJ8Eh", + "id": "Prompt-uqDcR", "name": "prompt", "output_types": [ "Message" @@ -198,25 +43,26 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-3v8LQ", + "id": "OpenAIModel-H0ANr", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-oJ8Eh{œdataTypeœ:œPromptœ,œidœ:œPrompt-oJ8Ehœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-3v8LQ{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-3v8LQœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-oJ8Eh", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-oJ8Ehœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-3v8LQ", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-3v8LQœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-uqDcR{œdataTypeœ:œPromptœ,œidœ:œPrompt-uqDcRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-H0ANr{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-H0ANrœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-uqDcR", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-uqDcRœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-H0ANr", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-H0ANrœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-3v8LQ", + "id": "OpenAIModel-H0ANr", "name": "text_output", "output_types": [ "Message" @@ -224,25 +70,26 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-oPZbw", + "id": "ChatOutput-a4EPO", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-3v8LQ{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-3v8LQœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-oPZbw{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-oPZbwœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-3v8LQ", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-3v8LQœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-oPZbw", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-oPZbwœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-H0ANr{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-H0ANrœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-a4EPO{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-a4EPOœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-H0ANr", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-H0ANrœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-a4EPO", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-a4EPOœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { + "animated": false, "className": "", "data": { "sourceHandle": { - "dataType": "AstraVectorStoreComponent", - "id": "AstraVectorStoreComponent-0WT85", + "dataType": "AstraDB", + "id": "AstraDB-3buPx", "name": "search_results", "output_types": [ "Data" @@ -250,18 +97,180 @@ }, "targetHandle": { "fieldName": "data", - "id": "ParseData-f6Jhl", + "id": "ParseData-pqaC7", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-AstraVectorStoreComponent-0WT85{œdataTypeœ:œAstraVectorStoreComponentœ,œidœ:œAstraVectorStoreComponent-0WT85œ,œnameœ:œsearch_resultsœ,œoutput_typesœ:[œDataœ]}-ParseData-f6Jhl{œfieldNameœ:œdataœ,œidœ:œParseData-f6Jhlœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "AstraVectorStoreComponent-0WT85", - "sourceHandle": "{œdataTypeœ: œAstraVectorStoreComponentœ, œidœ: œAstraVectorStoreComponent-0WT85œ, œnameœ: œsearch_resultsœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-f6Jhl", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-f6Jhlœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-AstraDB-3buPx{œdataTypeœ:œAstraDBœ,œidœ:œAstraDB-3buPxœ,œnameœ:œsearch_resultsœ,œoutput_typesœ:[œDataœ]}-ParseData-pqaC7{œfieldNameœ:œdataœ,œidœ:œParseData-pqaC7œ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "AstraDB-3buPx", + "sourceHandle": "{œdataTypeœ: œAstraDBœ, œidœ: œAstraDB-3buPxœ, œnameœ: œsearch_resultsœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-pqaC7", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-pqaC7œ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIEmbeddings", + "id": "OpenAIEmbeddings-CeoV9", + "name": "embeddings", + "output_types": [ + "Embeddings" + ] + }, + "targetHandle": { + "fieldName": "embedding", + "id": "AstraDB-3buPx", + "inputTypes": [ + "Embeddings" + ], + "type": "other" + } + }, + "id": "reactflow__edge-OpenAIEmbeddings-CeoV9{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-CeoV9œ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-3buPx{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-3buPxœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "source": "OpenAIEmbeddings-CeoV9", + "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-CeoV9œ, œnameœ: œembeddingsœ, œoutput_typesœ: [œEmbeddingsœ]}", + "target": "AstraDB-3buPx", + "targetHandle": "{œfieldNameœ: œembeddingœ, œidœ: œAstraDB-3buPxœ, œinputTypesœ: [œEmbeddingsœ], œtypeœ: œotherœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-nd3Fq", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "search_input", + "id": "AstraDB-3buPx", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-nd3Fq{œdataTypeœ:œChatInputœ,œidœ:œChatInput-nd3Fqœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraDB-3buPx{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-3buPxœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "ChatInput-nd3Fq", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-nd3Fqœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "AstraDB-3buPx", + "targetHandle": "{œfieldNameœ: œsearch_inputœ, œidœ: œAstraDB-3buPxœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-nd3Fq", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "question", + "id": "Prompt-uqDcR", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-nd3Fq{œdataTypeœ:œChatInputœ,œidœ:œChatInput-nd3Fqœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-uqDcR{œfieldNameœ:œquestionœ,œidœ:œPrompt-uqDcRœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-nd3Fq", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-nd3Fqœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-uqDcR", + "targetHandle": "{œfieldNameœ: œquestionœ, œidœ: œPrompt-uqDcRœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "SplitText", + "id": "SplitText-QakmY", + "name": "chunks", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "ingest_data", + "id": "AstraDB-laybz", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-SplitText-QakmY{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-QakmYœ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}-AstraDB-laybz{œfieldNameœ:œingest_dataœ,œidœ:œAstraDB-laybzœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "SplitText-QakmY", + "sourceHandle": "{œdataTypeœ: œSplitTextœ, œidœ: œSplitText-QakmYœ, œnameœ: œchunksœ, œoutput_typesœ: [œDataœ]}", + "target": "AstraDB-laybz", + "targetHandle": "{œfieldNameœ: œingest_dataœ, œidœ: œAstraDB-laybzœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + }, + { + "animated": false, + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIEmbeddings", + "id": "OpenAIEmbeddings-ANgku", + "name": "embeddings", + "output_types": [ + "Embeddings" + ] + }, + "targetHandle": { + "fieldName": "embedding", + "id": "AstraDB-laybz", + "inputTypes": [ + "Embeddings" + ], + "type": "other" + } + }, + "id": "reactflow__edge-OpenAIEmbeddings-ANgku{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-ANgkuœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-laybz{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-laybzœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "source": "OpenAIEmbeddings-ANgku", + "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-ANgkuœ, œnameœ: œembeddingsœ, œoutput_typesœ: [œEmbeddingsœ]}", + "target": "AstraDB-laybz", + "targetHandle": "{œfieldNameœ: œembeddingœ, œidœ: œAstraDB-laybzœ, œinputTypesœ: [œEmbeddingsœ], œtypeœ: œotherœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "File", + "id": "File-FJIuH", + "name": "data", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "data_inputs", + "id": "SplitText-QakmY", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-File-FJIuH{œdataTypeœ:œFileœ,œidœ:œFile-FJIuHœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-SplitText-QakmY{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-QakmYœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "File-FJIuH", + "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-FJIuHœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "SplitText-QakmY", + "targetHandle": "{œfieldNameœ: œdata_inputsœ, œidœ: œSplitText-QakmYœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" } ], "nodes": [ @@ -269,7 +278,7 @@ "data": { "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", - "id": "ChatInput-jvvNM", + "id": "ChatInput-nd3Fq", "node": { "base_classes": [ "Message" @@ -292,6 +301,7 @@ "frozen": false, "icon": "MessagesSquare", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -430,7 +440,7 @@ "trace_as_input": true, "trace_as_metadata": true, "type": "str", - "value": "" + "value": "What is the document is about?" }, "sender": { "advanced": true, @@ -531,513 +541,25 @@ "type": "ChatInput" }, "dragging": false, - "height": 297, - "id": "ChatInput-jvvNM", + "height": 234, + "id": "ChatInput-nd3Fq", "position": { - "x": 642.3545710150049, - "y": 220.22556606238678 + "x": 743.9745420290319, + "y": 463.6977510207854 }, "positionAbsolute": { - "x": 642.3545710150049, - "y": 220.22556606238678 + "x": 743.9745420290319, + "y": 463.6977510207854 }, "selected": false, "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "💡 Select a Database and a Collection, or create new ones. \n\n*If you're using OS Langflow, Paste your Astra DB Application Token here.*", - "display_name": "Astra DB", - "edited": false, - "id": "AstraVectorStoreComponent-0WT85", - "node": { - "base_classes": [ - "Data", - "Retriever" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "💡 Select a Database and a Collection, or create new ones. \n\n*If you're using OS Langflow, Paste your Astra DB Application Token here.*", - "display_name": "Astra DB", - "documentation": "https://docs.langflow.org/starter-projects-vector-store-rag", - "edited": false, - "field_order": [ - "collection_name", - "token", - "api_endpoint", - "search_input", - "ingest_data", - "namespace", - "metric", - "batch_size", - "bulk_insert_batch_concurrency", - "bulk_insert_overwrite_concurrency", - "bulk_delete_concurrency", - "setup_mode", - "pre_delete_collection", - "metadata_indexing_include", - "embedding", - "metadata_indexing_exclude", - "collection_indexing_policy", - "number_of_results", - "search_type", - "search_score_threshold", - "search_filter" - ], - "frozen": false, - "icon": "AstraDB", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Retriever", - "method": "build_base_retriever", - "name": "base_retriever", - "required_inputs": [], - "selected": "Retriever", - "types": [ - "Retriever" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Search Results", - "method": "search_documents", - "name": "search_results", - "required_inputs": [ - "api_endpoint", - "collection_name", - "token" - ], - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_endpoint": { - "advanced": false, - "display_name": "API Endpoint", - "dynamic": false, - "info": "API endpoint URL for the Astra DB service.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_endpoint", - "password": true, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "str", - "value": "ASTRA_DB_API_ENDPOINT" - }, - "batch_size": { - "advanced": true, - "display_name": "Batch Size", - "dynamic": false, - "info": "Optional number of data to process in a single batch.", - "list": false, - "name": "batch_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "bulk_delete_concurrency": { - "advanced": true, - "display_name": "Bulk Delete Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk delete operations.", - "list": false, - "name": "bulk_delete_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "bulk_insert_batch_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Batch Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations.", - "list": false, - "name": "bulk_insert_batch_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "bulk_insert_overwrite_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Overwrite Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", - "list": false, - "name": "bulk_insert_overwrite_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import os\n\nimport orjson\nfrom astrapy.admin import parse_api_endpoint\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n VECTORIZE_PROVIDERS_MAPPING = {\n \"Azure OpenAI\": [\"azureOpenAI\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"NVIDIA\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n }\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n ),\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n is_list=True,\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n is_list=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n if field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n self.del_fields(build_config, [\"embedding\"])\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=self.VECTORIZE_PROVIDERS_MAPPING.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n new_parameter = HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding\": new_parameter})\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n model_options = self.VECTORIZE_PROVIDERS_MAPPING[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n is_list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n is_list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_value = self.VECTORIZE_PROVIDERS_MAPPING.get(self.embedding_provider, [None])[0] or kwargs.get(\n \"embedding_provider\"\n )\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or kwargs.get(\"z_04_authentication\", {}))}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Fetch values from kwargs if any self.* attributes are None\n dict_options = vectorize_options or self.build_vectorize_options()\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n try:\n vector_store = AstraDBVectorStore(\n collection_name=self.collection_name,\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.namespace or None,\n environment=parse_api_endpoint(self.api_endpoint).environment if self.api_endpoint else None,\n metric=self.metric or None,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n args = {\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n\n if self.search_filter:\n clean_filter = {k: v for k, v in self.search_filter.items() if k and v}\n if len(clean_filter) > 0:\n args[\"filter\"] = clean_filter\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n if not vector_store:\n vector_store = self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n search_type = self._map_search_type()\n search_args = self._build_search_args()\n\n docs = vector_store.search(query=self.search_input, search_type=search_type, **search_args)\n except Exception as e:\n msg = f\"Error performing search in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n self.log(\"No search input provided. Skipping search.\")\n return []\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" - }, - "collection_indexing_policy": { - "advanced": true, - "display_name": "Collection Indexing Policy", - "dynamic": false, - "info": "Optional JSON string for the \"indexing\" field of the collection. See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option", - "list": false, - "load_from_db": false, - "name": "collection_indexing_policy", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "collection_name": { - "advanced": false, - "display_name": "Collection Name", - "dynamic": false, - "info": "The name of the collection within Astra DB where the vectors will be stored.", - "list": false, - "load_from_db": false, - "name": "collection_name", - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "langflow" - }, - "embedding": { - "advanced": false, - "display_name": "Embedding Model", - "dynamic": false, - "info": "Allows an embedding model configuration.", - "input_types": [ - "Embeddings" - ], - "list": false, - "name": "embedding", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "embedding_choice": { - "_input_type": "DropdownInput", - "advanced": false, - "combobox": false, - "display_name": "Embedding Model or Astra Vectorize", - "dynamic": false, - "info": "Determines whether to use Astra Vectorize for the collection.", - "name": "embedding_choice", - "options": [ - "Embedding Model", - "Astra Vectorize" - ], - "placeholder": "", - "real_time_refresh": true, - "required": false, - "show": true, - "title_case": false, - "tool_mode": false, - "trace_as_metadata": true, - "type": "str", - "value": "Embedding Model" - }, - "ingest_data": { - "advanced": false, - "display_name": "Ingest Data", - "dynamic": false, - "info": "", - "input_types": [ - "Data" - ], - "list": true, - "name": "ingest_data", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "metadata_indexing_exclude": { - "advanced": true, - "display_name": "Metadata Indexing Exclude", - "dynamic": false, - "info": "Optional list of metadata fields to exclude from the indexing.", - "list": true, - "load_from_db": false, - "name": "metadata_indexing_exclude", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "metadata_indexing_include": { - "advanced": true, - "display_name": "Metadata Indexing Include", - "dynamic": false, - "info": "Optional list of metadata fields to include in the indexing.", - "list": true, - "load_from_db": false, - "name": "metadata_indexing_include", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "metric": { - "advanced": true, - "display_name": "Metric", - "dynamic": false, - "info": "Optional distance metric for vector comparisons in the vector store.", - "name": "metric", - "options": [ - "cosine", - "dot_product", - "euclidean" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "cosine" - }, - "namespace": { - "advanced": true, - "display_name": "Namespace", - "dynamic": false, - "info": "Optional namespace within Astra DB to use for the collection.", - "list": false, - "load_from_db": false, - "name": "namespace", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "number_of_results": { - "advanced": true, - "display_name": "Number of Results", - "dynamic": false, - "info": "Number of results to return.", - "list": false, - "name": "number_of_results", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 4 - }, - "pre_delete_collection": { - "advanced": true, - "display_name": "Pre Delete Collection", - "dynamic": false, - "info": "Boolean flag to determine whether to delete the collection before creating a new one.", - "list": false, - "name": "pre_delete_collection", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "search_filter": { - "advanced": true, - "display_name": "Search Metadata Filter", - "dynamic": false, - "info": "Optional dictionary of filters to apply to the search query.", - "list": true, - "name": "search_filter", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "search_input": { - "advanced": false, - "display_name": "Search Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "search_input", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "search_score_threshold": { - "advanced": true, - "display_name": "Search Score Threshold", - "dynamic": false, - "info": "Minimum similarity score threshold for search results. (when using 'Similarity with score threshold')", - "list": false, - "name": "search_score_threshold", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0 - }, - "search_type": { - "advanced": true, - "display_name": "Search Type", - "dynamic": false, - "info": "Search type to use", - "name": "search_type", - "options": [ - "Similarity", - "Similarity with score threshold", - "MMR (Max Marginal Relevance)" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Similarity" - }, - "setup_mode": { - "advanced": true, - "display_name": "Setup Mode", - "dynamic": false, - "info": "Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.", - "name": "setup_mode", - "options": [ - "Sync", - "Off" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Sync" - }, - "token": { - "advanced": false, - "display_name": "Astra DB Application Token", - "dynamic": false, - "info": "Authentication token for accessing Astra DB.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "token", - "password": true, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "str", - "value": "ASTRA_DB_APPLICATION_TOKEN" - } - } - }, - "type": "AstraVectorStoreComponent" - }, - "dragging": false, - "height": 837, - "id": "AstraVectorStoreComponent-0WT85", - "position": { - "x": 1246.0381406498648, - "y": 333.25157075413966 - }, - "positionAbsolute": { - "x": 1246.0381406498648, - "y": 333.25157075413966 - }, - "selected": false, - "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Convert Data into plain text following a specified template.", "display_name": "Parse Data", - "id": "ParseData-f6Jhl", + "id": "ParseData-pqaC7", "node": { "base_classes": [ "Message" @@ -1057,6 +579,7 @@ "frozen": false, "icon": "braces", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -1154,25 +677,25 @@ "type": "ParseData" }, "dragging": false, - "height": 369, - "id": "ParseData-f6Jhl", + "height": 302, + "id": "ParseData-pqaC7", "position": { - "x": 1854.1518317915907, - "y": 459.3386924128532 + "x": 1606.0595305373527, + "y": 751.4473696960695 }, "positionAbsolute": { - "x": 1854.1518317915907, - "y": 459.3386924128532 + "x": 1606.0595305373527, + "y": 751.4473696960695 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-oJ8Eh", + "id": "Prompt-uqDcR", "node": { "base_classes": [ "Message" @@ -1189,13 +712,20 @@ "display_name": "Prompt", "documentation": "", "edited": false, + "error": null, "field_order": [ "template" ], "frozen": false, + "full_path": null, "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, + "name": "", "output_types": [], "outputs": [ { @@ -1247,7 +777,6 @@ "load_from_db": false, "multiline": true, "name": "context", - "password": false, "placeholder": "", "required": false, "show": true, @@ -1271,7 +800,6 @@ "load_from_db": false, "multiline": true, "name": "question", - "password": false, "placeholder": "", "required": false, "show": true, @@ -1295,288 +823,31 @@ "type": "prompt", "value": "{context}\n\n---\n\nGiven the context above, answer the question as best as possible.\n\nQuestion: {question}\n\nAnswer: " } - } + }, + "tool_mode": false }, "type": "Prompt" }, "dragging": false, - "height": 497, - "id": "Prompt-oJ8Eh", + "height": 433, + "id": "Prompt-uqDcR", "position": { - "x": 2486.0988668404975, - "y": 496.5120474157301 + "x": 1977.9097981422992, + "y": 640.5656416923846 }, "positionAbsolute": { - "x": 2486.0988668404975, - "y": 496.5120474157301 + "x": 1977.9097981422992, + "y": 640.5656416923846 }, "selected": false, "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Display a chat message in the Playground. \n💡 Click the ▶️ to run the flow", - "display_name": "Chat Output", - "id": "ChatOutput-oPZbw", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground. \n💡 Click the ▶️ to run the flow", - "display_name": "Chat Output", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "should_store_message", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "MessagesSquare", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "background_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Background Color", - "dynamic": false, - "info": "The background color of the icon.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "background_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "chat_icon": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Icon", - "dynamic": false, - "info": "The icon of the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "chat_icon", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "should_store_message": { - "advanced": true, - "display_name": "Store Messages", - "dynamic": false, - "info": "Store the message in the history.", - "list": false, - "name": "should_store_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "text_color": { - "_input_type": "MessageTextInput", - "advanced": true, - "display_name": "Text Color", - "dynamic": false, - "info": "The text color of the name", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "text_color", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 297, - "id": "ChatOutput-oPZbw", - "position": { - "x": 3769.242086248817, - "y": 585.3403837062634 - }, - "positionAbsolute": { - "x": 3769.242086248817, - "y": 585.3403837062634 - }, - "selected": false, - "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { "description": "Split text into chunks based on specified criteria.", "display_name": "Split Text", - "id": "SplitText-Kl7VQ", + "id": "SplitText-QakmY", "node": { "base_classes": [ "Data" @@ -1597,6 +868,7 @@ "frozen": false, "icon": "scissors-line-dashed", "legacy": false, + "lf_version": "1.0.19.post2", "metadata": {}, "output_types": [], "outputs": [ @@ -1706,25 +978,2760 @@ "type": "SplitText" }, "dragging": false, - "height": 541, - "id": "SplitText-Kl7VQ", + "height": 475, + "id": "SplitText-QakmY", "position": { - "x": 2044.2799160989089, - "y": 1185.3130355818519 + "x": 1683.4543896546102, + "y": 1350.7871623588553 }, "positionAbsolute": { - "x": 2044.2799160989089, - "y": 1185.3130355818519 + "x": 1683.4543896546102, + "y": 1350.7871623588553 }, "selected": false, "type": "genericNode", - "width": 384 + "width": 320 }, { "data": { - "description": "💡 Load a PDF file from your local machine.", - "display_name": "File", - "id": "File-JZzdd", + "id": "note-i0pUr", + "node": { + "description": "## 📄 Load Data Flow\n\n**Purpose**: This flow is designed to ingest local files and store their contents as vectors in the database.\n\n**Steps to Use:**\n\n1. **Upload File**: Use the \"File\" component to upload your data file. Ensure the file format is supported (e.g., `txt`, `pdf`).\n2. **Text Splitting**: The \"Split Text\" component will automatically segment your document into smaller, manageable chunks for efficient processing.\n3. **Generate Embeddings**: OpenAI models will convert text chunks into vector representations that can be indexed in Astra DB.\n4. **Store Vectors**: The \"Astra DB\" component completes the process by saving these vectors, making them ready for retrieval and search operations.\n\n**Quick Tips**:\n- Always ensure your files are correctly formatted and free of errors before uploading.\n- Monitor the component indicators to confirm data processing and storage status.\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 445, + "id": "note-i0pUr", + "position": { + "x": 806.5400894704665, + "y": 1410.461680629912 + }, + "positionAbsolute": { + "x": 806.5400894704665, + "y": 1410.461680629912 + }, + "resizing": false, + "selected": false, + "style": { + "height": 445, + "width": 493 + }, + "type": "noteNode", + "width": 493 + }, + { + "data": { + "id": "note-9DvF2", + "node": { + "description": "# Vector Store RAG Overview\n\n\nThis Vector Store RAG workflow combines data ingestion and retrieval into a unified process, allowing you to manage and query your data efficiently.\n\n**Components**:\n- **📄 Load Data**: Prepares data for vector database storage.\n - File ingestion\n - Text chunking\n - Embedding generation\n - Storage in Astra DB\n\n- **✨ Retriever**: Provides intelligent search and retrieval from the vector database.\n - User query input\n - Database search\n - Enhanced response generation using AI models\n\n**Workflow Instructions**:\n1. Initiate the **Load Data** flow to input your document into the vector database.\n2. Use the **Retriever** flow to conduct queries and obtain comprehensive responses based on your stored data.\n3. Adjust settings like API keys and collection names as needed for your specific use case.\n\n**Benefits**:\n- Streamlines data management with a single interface.\n- Fast, scalable vector-based search capabilities.\n- Integrates cutting-edge AI technology for rich, context-aware outputs.\n", + "display_name": "Read Me", + "documentation": "", + "template": { + "backgroundColor": "indigo" + } + }, + "type": "note" + }, + "dragging": false, + "height": 798, + "id": "note-9DvF2", + "position": { + "x": 134.64227176140844, + "y": 307.10406179806375 + }, + "positionAbsolute": { + "x": 134.64227176140844, + "y": 307.10406179806375 + }, + "resizing": false, + "selected": false, + "style": { + "height": 798, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "id": "note-RC6pg", + "node": { + "description": "## Astra DB Setup\n\n**Important Setup Information:**\n\nTo use the Astra DB component in this workflow, you'll need to obtain an Astra DB key. Follow these steps to set up your access:\n\n1. **Create an Account**: Visit [DataStax Accounts](https://accounts.datastax.com) and create an account if you don't already have one.\n2. **Generate a Key**: Once logged in, navigate to the \"Astra DB\" section to create a new application token. This token will serve as your authentication key for API access.\n3. **Configure Endpoint**: Note the API endpoint URL provided by Astra DB. This is essential for connecting your vector database to the workflow.\n4. **Input Token**: Enter the generated token and API endpoint URL in the appropriate fields in the Astra DB component within the workflow.\n\n", + "display_name": "", + "documentation": "", + "template": { + "backgroundColor": "blue" + } + }, + "type": "note" + }, + "dragging": false, + "height": 358, + "id": "note-RC6pg", + "position": { + "x": 1180.1117634200216, + "y": -2.4324300661269547 + }, + "positionAbsolute": { + "x": 1180.1117634200216, + "y": -2.4324300661269547 + }, + "resizing": false, + "selected": false, + "style": { + "height": 358, + "width": 412 + }, + "type": "noteNode", + "width": 412 + }, + { + "data": { + "id": "OpenAIModel-H0ANr", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "system_message", + "stream", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "required_inputs": [], + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "required_inputs": [], + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "_input_type": "BoolInput", + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + }, + "tool_mode": false + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 543, + "id": "OpenAIModel-H0ANr", + "position": { + "x": 2360.1432368563187, + "y": 571.6712358167248 + }, + "positionAbsolute": { + "x": 2360.1432368563187, + "y": 571.6712358167248 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-a4EPO", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-a4EPO", + "position": { + "x": 2734.385670401691, + "y": 808.2967893015561 + }, + "positionAbsolute": { + "x": 2734.385670401691, + "y": 808.2967893015561 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "AstraDB-3buPx", + "node": { + "base_classes": [ + "Data", + "Retriever" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB", + "documentation": "https://docs.langflow.org/starter-projects-vector-store-rag", + "edited": false, + "field_order": [ + "token", + "api_endpoint", + "collection_name", + "search_input", + "ingest_data", + "namespace", + "embedding_service", + "embedding", + "metric", + "batch_size", + "bulk_insert_batch_concurrency", + "bulk_insert_overwrite_concurrency", + "bulk_delete_concurrency", + "setup_mode", + "pre_delete_collection", + "metadata_indexing_include", + "metadata_indexing_exclude", + "collection_indexing_policy", + "number_of_results", + "search_type", + "search_score_threshold", + "search_filter" + ], + "frozen": false, + "icon": "AstraDB", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Retriever", + "method": "build_base_retriever", + "name": "base_retriever", + "required_inputs": [], + "selected": "Retriever", + "types": [ + "Retriever" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Search Results", + "method": "search_documents", + "name": "search_results", + "required_inputs": [ + "api_endpoint", + "collection_name", + "token" + ], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_endpoint": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "API Endpoint", + "dynamic": false, + "info": "API endpoint URL for the Astra DB service.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_endpoint", + "password": true, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "str", + "value": "ASTRA_DB_API_ENDPOINT" + }, + "batch_size": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Batch Size", + "dynamic": false, + "info": "Optional number of data to process in a single batch.", + "list": false, + "name": "batch_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "bulk_delete_concurrency": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Bulk Delete Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk delete operations.", + "list": false, + "name": "bulk_delete_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "bulk_insert_batch_concurrency": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Bulk Insert Batch Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations.", + "list": false, + "name": "bulk_insert_batch_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "bulk_insert_overwrite_concurrency": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Bulk Insert Overwrite Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", + "list": false, + "name": "bulk_insert_overwrite_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import os\n\nimport orjson\nfrom astrapy.admin import parse_api_endpoint\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n VECTORIZE_PROVIDERS_MAPPING = {\n \"Azure OpenAI\": [\"azureOpenAI\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"NVIDIA\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n }\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n ),\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n is_list=True,\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n is_list=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n if field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n self.del_fields(build_config, [\"embedding\"])\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=self.VECTORIZE_PROVIDERS_MAPPING.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n new_parameter = HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding\": new_parameter})\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n model_options = self.VECTORIZE_PROVIDERS_MAPPING[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n is_list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n is_list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_value = self.VECTORIZE_PROVIDERS_MAPPING.get(self.embedding_provider, [None])[0] or kwargs.get(\n \"embedding_provider\"\n )\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or kwargs.get(\"z_04_authentication\", {}))}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Fetch values from kwargs if any self.* attributes are None\n dict_options = vectorize_options or self.build_vectorize_options()\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n try:\n vector_store = AstraDBVectorStore(\n collection_name=self.collection_name,\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.namespace or None,\n environment=parse_api_endpoint(self.api_endpoint).environment if self.api_endpoint else None,\n metric=self.metric or None,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n args = {\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n\n if self.search_filter:\n clean_filter = {k: v for k, v in self.search_filter.items() if k and v}\n if len(clean_filter) > 0:\n args[\"filter\"] = clean_filter\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n if not vector_store:\n vector_store = self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n search_type = self._map_search_type()\n search_args = self._build_search_args()\n\n docs = vector_store.search(query=self.search_input, search_type=search_type, **search_args)\n except Exception as e:\n msg = f\"Error performing search in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n self.log(\"No search input provided. Skipping search.\")\n return []\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" + }, + "collection_indexing_policy": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Collection Indexing Policy", + "dynamic": false, + "info": "Optional JSON string for the \"indexing\" field of the collection. See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option", + "list": false, + "load_from_db": false, + "name": "collection_indexing_policy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "collection_name": { + "_input_type": "StrInput", + "advanced": false, + "display_name": "Collection Name", + "dynamic": false, + "info": "The name of the collection within Astra DB where the vectors will be stored.", + "list": false, + "load_from_db": false, + "name": "collection_name", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "embedding": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Embedding Model", + "dynamic": false, + "info": "Allows an embedding model configuration.", + "input_types": [ + "Embeddings" + ], + "list": false, + "name": "embedding", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "embedding_choice": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Embedding Model or Astra Vectorize", + "dynamic": false, + "info": "Determines whether to use Astra Vectorize for the collection.", + "name": "embedding_choice", + "options": [ + "Embedding Model", + "Astra Vectorize" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Embedding Model" + }, + "ingest_data": { + "_input_type": "DataInput", + "advanced": false, + "display_name": "Ingest Data", + "dynamic": false, + "info": "", + "input_types": [ + "Data" + ], + "list": true, + "name": "ingest_data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "metadata_indexing_exclude": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Metadata Indexing Exclude", + "dynamic": false, + "info": "Optional list of metadata fields to exclude from the indexing.", + "list": true, + "load_from_db": false, + "name": "metadata_indexing_exclude", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "metadata_indexing_include": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Metadata Indexing Include", + "dynamic": false, + "info": "Optional list of metadata fields to include in the indexing.", + "list": true, + "load_from_db": false, + "name": "metadata_indexing_include", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "metric": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Metric", + "dynamic": false, + "info": "Optional distance metric for vector comparisons in the vector store.", + "name": "metric", + "options": [ + "cosine", + "dot_product", + "euclidean" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "cosine" + }, + "namespace": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Namespace", + "dynamic": false, + "info": "Optional namespace within Astra DB to use for the collection.", + "list": false, + "load_from_db": false, + "name": "namespace", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "number_of_results": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Results", + "dynamic": false, + "info": "Number of results to return.", + "list": false, + "name": "number_of_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 4 + }, + "pre_delete_collection": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Pre Delete Collection", + "dynamic": false, + "info": "Boolean flag to determine whether to delete the collection before creating a new one.", + "list": false, + "name": "pre_delete_collection", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "search_filter": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Search Metadata Filter", + "dynamic": false, + "info": "Optional dictionary of filters to apply to the search query.", + "list": true, + "name": "search_filter", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "search_input": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Search Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "search_input", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "search_score_threshold": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Search Score Threshold", + "dynamic": false, + "info": "Minimum similarity score threshold for search results. (when using 'Similarity with score threshold')", + "list": false, + "name": "search_score_threshold", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0 + }, + "search_type": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Type", + "dynamic": false, + "info": "Search type to use", + "name": "search_type", + "options": [ + "Similarity", + "Similarity with score threshold", + "MMR (Max Marginal Relevance)" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Similarity" + }, + "setup_mode": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Setup Mode", + "dynamic": false, + "info": "Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.", + "name": "setup_mode", + "options": [ + "Sync", + "Off" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Sync" + }, + "token": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "Astra DB Application Token", + "dynamic": false, + "info": "Authentication token for accessing Astra DB.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "token", + "password": true, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "str", + "value": "ASTRA_DB_APPLICATION_TOKEN" + } + }, + "tool_mode": false + }, + "type": "AstraDB" + }, + "dragging": false, + "height": 749, + "id": "AstraDB-3buPx", + "position": { + "x": 1225.8151138573664, + "y": 369.2727294042354 + }, + "positionAbsolute": { + "x": 1225.8151138573664, + "y": 369.2727294042354 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "OpenAIEmbeddings-CeoV9", + "node": { + "base_classes": [ + "Embeddings" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generate embeddings using OpenAI models.", + "display_name": "OpenAI Embeddings", + "documentation": "", + "edited": false, + "field_order": [ + "default_headers", + "default_query", + "chunk_size", + "client", + "deployment", + "embedding_ctx_length", + "max_retries", + "model", + "model_kwargs", + "openai_api_key", + "openai_api_base", + "openai_api_type", + "openai_api_version", + "openai_organization", + "openai_proxy", + "request_timeout", + "show_progress_bar", + "skip_empty", + "tiktoken_model_name", + "tiktoken_enable", + "dimensions" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Embeddings", + "method": "build_embeddings", + "name": "embeddings", + "required_inputs": [], + "selected": "Embeddings", + "types": [ + "Embeddings" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "chunk_size": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Chunk Size", + "dynamic": false, + "info": "", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1000 + }, + "client": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Client", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "client", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_openai import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.base.models.openai_constants import OPENAI_EMBEDDING_MODEL_NAMES\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n name = \"OpenAIEmbeddings\"\n\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=OPENAI_EMBEDDING_MODEL_NAMES,\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\", value=\"OPENAI_API_KEY\"),\n MessageTextInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n MessageTextInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n IntInput(\n name=\"dimensions\",\n display_name=\"Dimensions\",\n info=\"The number of dimensions the resulting output embeddings should have. \"\n \"Only supported by certain models.\",\n advanced=True,\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n client=self.client or None,\n model=self.model,\n dimensions=self.dimensions or None,\n deployment=self.deployment or None,\n api_version=self.openai_api_version or None,\n base_url=self.openai_api_base or None,\n openai_api_type=self.openai_api_type or None,\n openai_proxy=self.openai_proxy or None,\n embedding_ctx_length=self.embedding_ctx_length,\n api_key=self.openai_api_key or None,\n organization=self.openai_organization or None,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n max_retries=self.max_retries,\n timeout=self.request_timeout or None,\n tiktoken_enabled=self.tiktoken_enable,\n tiktoken_model_name=self.tiktoken_model_name or None,\n show_progress_bar=self.show_progress_bar,\n model_kwargs=self.model_kwargs,\n skip_empty=self.skip_empty,\n default_headers=self.default_headers or None,\n default_query=self.default_query or None,\n )\n" + }, + "default_headers": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Default Headers", + "dynamic": false, + "info": "Default headers to use for the API request.", + "list": false, + "name": "default_headers", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "default_query": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Default Query", + "dynamic": false, + "info": "Default query parameters to use for the API request.", + "list": false, + "name": "default_query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "deployment": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Deployment", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "deployment", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "dimensions": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Dimensions", + "dynamic": false, + "info": "The number of dimensions the resulting output embeddings should have. Only supported by certain models.", + "list": false, + "name": "dimensions", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "embedding_ctx_length": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Embedding Context Length", + "dynamic": false, + "info": "", + "list": false, + "name": "embedding_ctx_length", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1536 + }, + "max_retries": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Retries", + "dynamic": false, + "info": "", + "list": false, + "name": "max_retries", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 3 + }, + "model": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model", + "dynamic": false, + "info": "", + "name": "model", + "options": [ + "text-embedding-3-small", + "text-embedding-3-large", + "text-embedding-ada-002" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "text-embedding-3-small" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "openai_api_base": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "openai_api_type": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI API Type", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_type", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_api_version": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI API Version", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_version", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_organization": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI Organization", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_organization", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_proxy": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI Proxy", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_proxy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "request_timeout": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Request Timeout", + "dynamic": false, + "info": "", + "list": false, + "name": "request_timeout", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": "" + }, + "show_progress_bar": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Show Progress Bar", + "dynamic": false, + "info": "", + "list": false, + "name": "show_progress_bar", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "skip_empty": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Skip Empty", + "dynamic": false, + "info": "", + "list": false, + "name": "skip_empty", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "tiktoken_enable": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "TikToken Enable", + "dynamic": false, + "info": "If False, you must have transformers installed.", + "list": false, + "name": "tiktoken_enable", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "tiktoken_model_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "TikToken Model Name", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "tiktoken_model_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "OpenAIEmbeddings" + }, + "dragging": false, + "height": 322, + "id": "OpenAIEmbeddings-CeoV9", + "position": { + "x": 825.435626932521, + "y": 739.6327999745448 + }, + "positionAbsolute": { + "x": 825.435626932521, + "y": 739.6327999745448 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "AstraDB-laybz", + "node": { + "base_classes": [ + "Data", + "Retriever" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB", + "documentation": "https://docs.langflow.org/starter-projects-vector-store-rag", + "edited": false, + "field_order": [ + "token", + "api_endpoint", + "collection_name", + "search_input", + "ingest_data", + "namespace", + "embedding_service", + "embedding", + "metric", + "batch_size", + "bulk_insert_batch_concurrency", + "bulk_insert_overwrite_concurrency", + "bulk_delete_concurrency", + "setup_mode", + "pre_delete_collection", + "metadata_indexing_include", + "metadata_indexing_exclude", + "collection_indexing_policy", + "number_of_results", + "search_type", + "search_score_threshold", + "search_filter" + ], + "frozen": false, + "icon": "AstraDB", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Retriever", + "method": "build_base_retriever", + "name": "base_retriever", + "required_inputs": [], + "selected": "Retriever", + "types": [ + "Retriever" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Search Results", + "method": "search_documents", + "name": "search_results", + "required_inputs": [ + "api_endpoint", + "collection_name", + "token" + ], + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "api_endpoint": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "API Endpoint", + "dynamic": false, + "info": "API endpoint URL for the Astra DB service.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_endpoint", + "password": true, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "str", + "value": "ASTRA_DB_API_ENDPOINT" + }, + "batch_size": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Batch Size", + "dynamic": false, + "info": "Optional number of data to process in a single batch.", + "list": false, + "name": "batch_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "bulk_delete_concurrency": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Bulk Delete Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk delete operations.", + "list": false, + "name": "bulk_delete_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "bulk_insert_batch_concurrency": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Bulk Insert Batch Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations.", + "list": false, + "name": "bulk_insert_batch_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "bulk_insert_overwrite_concurrency": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Bulk Insert Overwrite Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", + "list": false, + "name": "bulk_insert_overwrite_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import os\n\nimport orjson\nfrom astrapy.admin import parse_api_endpoint\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n VECTORIZE_PROVIDERS_MAPPING = {\n \"Azure OpenAI\": [\"azureOpenAI\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"NVIDIA\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n }\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n ),\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n is_list=True,\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n is_list=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n if field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n self.del_fields(build_config, [\"embedding\"])\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=self.VECTORIZE_PROVIDERS_MAPPING.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n new_parameter = HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding\": new_parameter})\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n model_options = self.VECTORIZE_PROVIDERS_MAPPING[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n is_list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n is_list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_value = self.VECTORIZE_PROVIDERS_MAPPING.get(self.embedding_provider, [None])[0] or kwargs.get(\n \"embedding_provider\"\n )\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or kwargs.get(\"z_04_authentication\", {}))}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Fetch values from kwargs if any self.* attributes are None\n dict_options = vectorize_options or self.build_vectorize_options()\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n try:\n vector_store = AstraDBVectorStore(\n collection_name=self.collection_name,\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.namespace or None,\n environment=parse_api_endpoint(self.api_endpoint).environment if self.api_endpoint else None,\n metric=self.metric or None,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n args = {\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n\n if self.search_filter:\n clean_filter = {k: v for k, v in self.search_filter.items() if k and v}\n if len(clean_filter) > 0:\n args[\"filter\"] = clean_filter\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n if not vector_store:\n vector_store = self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n search_type = self._map_search_type()\n search_args = self._build_search_args()\n\n docs = vector_store.search(query=self.search_input, search_type=search_type, **search_args)\n except Exception as e:\n msg = f\"Error performing search in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n self.log(\"No search input provided. Skipping search.\")\n return []\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" + }, + "collection_indexing_policy": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Collection Indexing Policy", + "dynamic": false, + "info": "Optional JSON string for the \"indexing\" field of the collection. See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option", + "list": false, + "load_from_db": false, + "name": "collection_indexing_policy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "collection_name": { + "_input_type": "StrInput", + "advanced": false, + "display_name": "Collection Name", + "dynamic": false, + "info": "The name of the collection within Astra DB where the vectors will be stored.", + "list": false, + "load_from_db": false, + "name": "collection_name", + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "test" + }, + "embedding": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Embedding Model", + "dynamic": false, + "info": "Allows an embedding model configuration.", + "input_types": [ + "Embeddings" + ], + "list": false, + "name": "embedding", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "embedding_choice": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Embedding Model or Astra Vectorize", + "dynamic": false, + "info": "Determines whether to use Astra Vectorize for the collection.", + "name": "embedding_choice", + "options": [ + "Embedding Model", + "Astra Vectorize" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Embedding Model" + }, + "ingest_data": { + "_input_type": "DataInput", + "advanced": false, + "display_name": "Ingest Data", + "dynamic": false, + "info": "", + "input_types": [ + "Data" + ], + "list": true, + "name": "ingest_data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "metadata_indexing_exclude": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Metadata Indexing Exclude", + "dynamic": false, + "info": "Optional list of metadata fields to exclude from the indexing.", + "list": true, + "load_from_db": false, + "name": "metadata_indexing_exclude", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "metadata_indexing_include": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Metadata Indexing Include", + "dynamic": false, + "info": "Optional list of metadata fields to include in the indexing.", + "list": true, + "load_from_db": false, + "name": "metadata_indexing_include", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "metric": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Metric", + "dynamic": false, + "info": "Optional distance metric for vector comparisons in the vector store.", + "name": "metric", + "options": [ + "cosine", + "dot_product", + "euclidean" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "cosine" + }, + "namespace": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "Namespace", + "dynamic": false, + "info": "Optional namespace within Astra DB to use for the collection.", + "list": false, + "load_from_db": false, + "name": "namespace", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "number_of_results": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Results", + "dynamic": false, + "info": "Number of results to return.", + "list": false, + "name": "number_of_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 4 + }, + "pre_delete_collection": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Pre Delete Collection", + "dynamic": false, + "info": "Boolean flag to determine whether to delete the collection before creating a new one.", + "list": false, + "name": "pre_delete_collection", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "search_filter": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Search Metadata Filter", + "dynamic": false, + "info": "Optional dictionary of filters to apply to the search query.", + "list": true, + "name": "search_filter", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "search_input": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Search Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "search_input", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "search_score_threshold": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Search Score Threshold", + "dynamic": false, + "info": "Minimum similarity score threshold for search results. (when using 'Similarity with score threshold')", + "list": false, + "name": "search_score_threshold", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0 + }, + "search_type": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Search Type", + "dynamic": false, + "info": "Search type to use", + "name": "search_type", + "options": [ + "Similarity", + "Similarity with score threshold", + "MMR (Max Marginal Relevance)" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Similarity" + }, + "setup_mode": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Setup Mode", + "dynamic": false, + "info": "Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.", + "name": "setup_mode", + "options": [ + "Sync", + "Off" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Sync" + }, + "token": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "Astra DB Application Token", + "dynamic": false, + "info": "Authentication token for accessing Astra DB.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "token", + "password": true, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "str", + "value": "ASTRA_DB_APPLICATION_TOKEN" + } + }, + "tool_mode": false + }, + "type": "AstraDB" + }, + "dragging": false, + "height": 749, + "id": "AstraDB-laybz", + "position": { + "x": 2090.491421890006, + "y": 1351.6194724621473 + }, + "positionAbsolute": { + "x": 2090.491421890006, + "y": 1351.6194724621473 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "OpenAIEmbeddings-ANgku", + "node": { + "base_classes": [ + "Embeddings" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generate embeddings using OpenAI models.", + "display_name": "OpenAI Embeddings", + "documentation": "", + "edited": false, + "field_order": [ + "default_headers", + "default_query", + "chunk_size", + "client", + "deployment", + "embedding_ctx_length", + "max_retries", + "model", + "model_kwargs", + "openai_api_key", + "openai_api_base", + "openai_api_type", + "openai_api_version", + "openai_organization", + "openai_proxy", + "request_timeout", + "show_progress_bar", + "skip_empty", + "tiktoken_model_name", + "tiktoken_enable", + "dimensions" + ], + "frozen": false, + "icon": "OpenAI", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Embeddings", + "method": "build_embeddings", + "name": "embeddings", + "required_inputs": [], + "selected": "Embeddings", + "types": [ + "Embeddings" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "chunk_size": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Chunk Size", + "dynamic": false, + "info": "", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1000 + }, + "client": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Client", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "client", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_openai import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.base.models.openai_constants import OPENAI_EMBEDDING_MODEL_NAMES\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n name = \"OpenAIEmbeddings\"\n\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=OPENAI_EMBEDDING_MODEL_NAMES,\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\", value=\"OPENAI_API_KEY\"),\n MessageTextInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n MessageTextInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n IntInput(\n name=\"dimensions\",\n display_name=\"Dimensions\",\n info=\"The number of dimensions the resulting output embeddings should have. \"\n \"Only supported by certain models.\",\n advanced=True,\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n client=self.client or None,\n model=self.model,\n dimensions=self.dimensions or None,\n deployment=self.deployment or None,\n api_version=self.openai_api_version or None,\n base_url=self.openai_api_base or None,\n openai_api_type=self.openai_api_type or None,\n openai_proxy=self.openai_proxy or None,\n embedding_ctx_length=self.embedding_ctx_length,\n api_key=self.openai_api_key or None,\n organization=self.openai_organization or None,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n max_retries=self.max_retries,\n timeout=self.request_timeout or None,\n tiktoken_enabled=self.tiktoken_enable,\n tiktoken_model_name=self.tiktoken_model_name or None,\n show_progress_bar=self.show_progress_bar,\n model_kwargs=self.model_kwargs,\n skip_empty=self.skip_empty,\n default_headers=self.default_headers or None,\n default_query=self.default_query or None,\n )\n" + }, + "default_headers": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Default Headers", + "dynamic": false, + "info": "Default headers to use for the API request.", + "list": false, + "name": "default_headers", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "default_query": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Default Query", + "dynamic": false, + "info": "Default query parameters to use for the API request.", + "list": false, + "name": "default_query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "deployment": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Deployment", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "deployment", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "dimensions": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Dimensions", + "dynamic": false, + "info": "The number of dimensions the resulting output embeddings should have. Only supported by certain models.", + "list": false, + "name": "dimensions", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "embedding_ctx_length": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Embedding Context Length", + "dynamic": false, + "info": "", + "list": false, + "name": "embedding_ctx_length", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1536 + }, + "max_retries": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Retries", + "dynamic": false, + "info": "", + "list": false, + "name": "max_retries", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 3 + }, + "model": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model", + "dynamic": false, + "info": "", + "name": "model", + "options": [ + "text-embedding-3-small", + "text-embedding-3-large", + "text-embedding-ada-002" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "text-embedding-3-small" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "openai_api_base": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "openai_api_type": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI API Type", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_type", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_api_version": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI API Version", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_version", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_organization": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI Organization", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_organization", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_proxy": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "OpenAI Proxy", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "openai_proxy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "request_timeout": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Request Timeout", + "dynamic": false, + "info": "", + "list": false, + "name": "request_timeout", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": "" + }, + "show_progress_bar": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Show Progress Bar", + "dynamic": false, + "info": "", + "list": false, + "name": "show_progress_bar", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "skip_empty": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Skip Empty", + "dynamic": false, + "info": "", + "list": false, + "name": "skip_empty", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "tiktoken_enable": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "TikToken Enable", + "dynamic": false, + "info": "If False, you must have transformers installed.", + "list": false, + "name": "tiktoken_enable", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "tiktoken_model_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "TikToken Model Name", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "tiktoken_model_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "OpenAIEmbeddings" + }, + "dragging": false, + "height": 322, + "id": "OpenAIEmbeddings-ANgku", + "position": { + "x": 1690.9220896443658, + "y": 1866.483269483266 + }, + "positionAbsolute": { + "x": 1690.9220896443658, + "y": 1866.483269483266 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "File-FJIuH", "node": { "base_classes": [ "Data" @@ -1732,13 +3739,15 @@ "beta": false, "conditional_paths": [], "custom_fields": {}, - "description": "💡 Load a PDF file from your local machine.", + "description": "Load a file to be used in your project.", "display_name": "File", "documentation": "", "edited": false, "field_order": [ "path", - "silent_errors" + "silent_errors", + "use_multithreading", + "concurrency_multithreading" ], "frozen": false, "icon": "file-text", @@ -1796,6 +3805,7 @@ "value": 4 }, "path": { + "_input_type": "FileInput", "advanced": false, "display_name": "Path", "dynamic": false, @@ -1833,6 +3843,7 @@ "value": "" }, "silent_errors": { + "_input_type": "BoolInput", "advanced": true, "display_name": "Silent Errors", "dynamic": false, @@ -1863,1866 +3874,44 @@ "type": "bool", "value": false } - } + }, + "tool_mode": false }, "type": "File" }, "dragging": false, - "height": 297, - "id": "File-JZzdd", + "height": 232, + "id": "File-FJIuH", "position": { - "x": 1418.981990122179, - "y": 1539.3825691184466 + "x": 1318.9043936921921, + "y": 1486.3263312921847 }, "positionAbsolute": { - "x": 1418.981990122179, - "y": 1539.3825691184466 + "x": 1318.9043936921921, + "y": 1486.3263312921847 }, "selected": false, "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "💡 Select a Database and a Collection, or create new ones. Click ▶️ **Play** to load your data.*If you're using OS Langflow, Paste your Astra DB Application Token here.*", - "display_name": "Astra DB", - "edited": false, - "id": "AstraVectorStoreComponent-EUhWZ", - "node": { - "base_classes": [ - "Data", - "Retriever" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "💡 Select a Database and a Collection, or create new ones. Click ▶️ **Play** to load your data.*If you're using OS Langflow, Paste your Astra DB Application Token here.*", - "display_name": "Astra DB", - "documentation": "https://docs.langflow.org/starter-projects-vector-store-rag", - "edited": false, - "field_order": [ - "collection_name", - "token", - "api_endpoint", - "search_input", - "ingest_data", - "namespace", - "metric", - "batch_size", - "bulk_insert_batch_concurrency", - "bulk_insert_overwrite_concurrency", - "bulk_delete_concurrency", - "setup_mode", - "pre_delete_collection", - "metadata_indexing_include", - "embedding", - "metadata_indexing_exclude", - "collection_indexing_policy", - "number_of_results", - "search_type", - "search_score_threshold", - "search_filter" - ], - "frozen": false, - "icon": "AstraDB", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Retriever", - "method": "build_base_retriever", - "name": "base_retriever", - "required_inputs": [], - "selected": "Retriever", - "types": [ - "Retriever" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Search Results", - "method": "search_documents", - "name": "search_results", - "required_inputs": [ - "api_endpoint", - "collection_name", - "token" - ], - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_endpoint": { - "advanced": false, - "display_name": "API Endpoint", - "dynamic": false, - "info": "API endpoint URL for the Astra DB service.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_endpoint", - "password": true, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "str", - "value": "ASTRA_DB_API_ENDPOINT" - }, - "batch_size": { - "advanced": true, - "display_name": "Batch Size", - "dynamic": false, - "info": "Optional number of data to process in a single batch.", - "list": false, - "name": "batch_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "bulk_delete_concurrency": { - "advanced": true, - "display_name": "Bulk Delete Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk delete operations.", - "list": false, - "name": "bulk_delete_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "bulk_insert_batch_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Batch Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations.", - "list": false, - "name": "bulk_insert_batch_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "bulk_insert_overwrite_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Overwrite Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", - "list": false, - "name": "bulk_insert_overwrite_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import os\n\nimport orjson\nfrom astrapy.admin import parse_api_endpoint\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n VECTORIZE_PROVIDERS_MAPPING = {\n \"Azure OpenAI\": [\"azureOpenAI\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"NVIDIA\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n }\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n ),\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n is_list=True,\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n is_list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n is_list=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n if field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n self.del_fields(build_config, [\"embedding\"])\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=self.VECTORIZE_PROVIDERS_MAPPING.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n new_parameter = HandleInput(\n name=\"embedding\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding\": new_parameter})\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n model_options = self.VECTORIZE_PROVIDERS_MAPPING[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n is_list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n is_list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_value = self.VECTORIZE_PROVIDERS_MAPPING.get(self.embedding_provider, [None])[0] or kwargs.get(\n \"embedding_provider\"\n )\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or kwargs.get(\"z_04_authentication\", {}))}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Fetch values from kwargs if any self.* attributes are None\n dict_options = vectorize_options or self.build_vectorize_options()\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n try:\n vector_store = AstraDBVectorStore(\n collection_name=self.collection_name,\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.namespace or None,\n environment=parse_api_endpoint(self.api_endpoint).environment if self.api_endpoint else None,\n metric=self.metric or None,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n args = {\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n\n if self.search_filter:\n clean_filter = {k: v for k, v in self.search_filter.items() if k and v}\n if len(clean_filter) > 0:\n args[\"filter\"] = clean_filter\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n if not vector_store:\n vector_store = self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n search_type = self._map_search_type()\n search_args = self._build_search_args()\n\n docs = vector_store.search(query=self.search_input, search_type=search_type, **search_args)\n except Exception as e:\n msg = f\"Error performing search in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n self.log(\"No search input provided. Skipping search.\")\n return []\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" - }, - "collection_indexing_policy": { - "advanced": true, - "display_name": "Collection Indexing Policy", - "dynamic": false, - "info": "Optional JSON string for the \"indexing\" field of the collection. See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option", - "list": false, - "load_from_db": false, - "name": "collection_indexing_policy", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "collection_name": { - "advanced": false, - "display_name": "Collection Name", - "dynamic": false, - "info": "The name of the collection within Astra DB where the vectors will be stored.", - "list": false, - "load_from_db": false, - "name": "collection_name", - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "langflow" - }, - "embedding": { - "advanced": false, - "display_name": "Embedding Model", - "dynamic": false, - "info": "Allows an embedding model configuration.", - "input_types": [ - "Embeddings" - ], - "list": false, - "name": "embedding", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "embedding_choice": { - "_input_type": "DropdownInput", - "advanced": false, - "combobox": false, - "display_name": "Embedding Model or Astra Vectorize", - "dynamic": false, - "info": "Determines whether to use Astra Vectorize for the collection.", - "name": "embedding_choice", - "options": [ - "Embedding Model", - "Astra Vectorize" - ], - "placeholder": "", - "real_time_refresh": true, - "required": false, - "show": true, - "title_case": false, - "tool_mode": false, - "trace_as_metadata": true, - "type": "str", - "value": "Embedding Model" - }, - "ingest_data": { - "advanced": false, - "display_name": "Ingest Data", - "dynamic": false, - "info": "", - "input_types": [ - "Data" - ], - "list": true, - "name": "ingest_data", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "metadata_indexing_exclude": { - "advanced": true, - "display_name": "Metadata Indexing Exclude", - "dynamic": false, - "info": "Optional list of metadata fields to exclude from the indexing.", - "list": true, - "load_from_db": false, - "name": "metadata_indexing_exclude", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "metadata_indexing_include": { - "advanced": true, - "display_name": "Metadata Indexing Include", - "dynamic": false, - "info": "Optional list of metadata fields to include in the indexing.", - "list": true, - "load_from_db": false, - "name": "metadata_indexing_include", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "metric": { - "advanced": true, - "display_name": "Metric", - "dynamic": false, - "info": "Optional distance metric for vector comparisons in the vector store.", - "name": "metric", - "options": [ - "cosine", - "dot_product", - "euclidean" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "cosine" - }, - "namespace": { - "advanced": true, - "display_name": "Namespace", - "dynamic": false, - "info": "Optional namespace within Astra DB to use for the collection.", - "list": false, - "load_from_db": false, - "name": "namespace", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "number_of_results": { - "advanced": true, - "display_name": "Number of Results", - "dynamic": false, - "info": "Number of results to return.", - "list": false, - "name": "number_of_results", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 4 - }, - "pre_delete_collection": { - "advanced": true, - "display_name": "Pre Delete Collection", - "dynamic": false, - "info": "Boolean flag to determine whether to delete the collection before creating a new one.", - "list": false, - "name": "pre_delete_collection", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "search_filter": { - "advanced": true, - "display_name": "Search Metadata Filter", - "dynamic": false, - "info": "Optional dictionary of filters to apply to the search query.", - "list": true, - "name": "search_filter", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "search_input": { - "advanced": false, - "display_name": "Search Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "search_input", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "search_score_threshold": { - "advanced": true, - "display_name": "Search Score Threshold", - "dynamic": false, - "info": "Minimum similarity score threshold for search results. (when using 'Similarity with score threshold')", - "list": false, - "name": "search_score_threshold", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0 - }, - "search_type": { - "advanced": true, - "display_name": "Search Type", - "dynamic": false, - "info": "Search type to use", - "name": "search_type", - "options": [ - "Similarity", - "Similarity with score threshold", - "MMR (Max Marginal Relevance)" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Similarity" - }, - "setup_mode": { - "advanced": true, - "display_name": "Setup Mode", - "dynamic": false, - "info": "Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.", - "name": "setup_mode", - "options": [ - "Sync", - "Off" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Sync" - }, - "token": { - "advanced": false, - "display_name": "Astra DB Application Token", - "dynamic": false, - "info": "Authentication token for accessing Astra DB.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "token", - "password": true, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "str", - "value": "ASTRA_DB_APPLICATION_TOKEN" - } - } - }, - "type": "AstraVectorStoreComponent" - }, - "dragging": false, - "height": 837, - "id": "AstraVectorStoreComponent-EUhWZ", - "position": { - "x": 2678.506138892635, - "y": 1267.3353646037478 - }, - "positionAbsolute": { - "x": 2678.506138892635, - "y": 1267.3353646037478 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "💡 Paste your [OpenAI API key](https://platform.openai.com/) key here.", - "display_name": "OpenAI Embeddings", - "id": "OpenAIEmbeddings-Mf9md", - "node": { - "base_classes": [ - "Embeddings" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "💡 Paste your [OpenAI API key](https://platform.openai.com/) key here.", - "display_name": "OpenAI Embeddings", - "documentation": "", - "edited": false, - "field_order": [ - "default_headers", - "default_query", - "chunk_size", - "client", - "deployment", - "embedding_ctx_length", - "max_retries", - "model", - "model_kwargs", - "openai_api_base", - "openai_api_key", - "openai_api_type", - "openai_api_version", - "openai_organization", - "openai_proxy", - "request_timeout", - "show_progress_bar", - "skip_empty", - "tiktoken_model_name", - "tiktoken_enable", - "dimensions" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Embeddings", - "method": "build_embeddings", - "name": "embeddings", - "required_inputs": [], - "selected": "Embeddings", - "types": [ - "Embeddings" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "chunk_size": { - "advanced": true, - "display_name": "Chunk Size", - "dynamic": false, - "info": "", - "list": false, - "name": "chunk_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1000 - }, - "client": { - "advanced": true, - "display_name": "Client", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "client", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langchain_openai import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.base.models.openai_constants import OPENAI_EMBEDDING_MODEL_NAMES\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n name = \"OpenAIEmbeddings\"\n\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=OPENAI_EMBEDDING_MODEL_NAMES,\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\", value=\"OPENAI_API_KEY\"),\n MessageTextInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n MessageTextInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n IntInput(\n name=\"dimensions\",\n display_name=\"Dimensions\",\n info=\"The number of dimensions the resulting output embeddings should have. \"\n \"Only supported by certain models.\",\n advanced=True,\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n client=self.client or None,\n model=self.model,\n dimensions=self.dimensions or None,\n deployment=self.deployment or None,\n api_version=self.openai_api_version or None,\n base_url=self.openai_api_base or None,\n openai_api_type=self.openai_api_type or None,\n openai_proxy=self.openai_proxy or None,\n embedding_ctx_length=self.embedding_ctx_length,\n api_key=self.openai_api_key or None,\n organization=self.openai_organization or None,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n max_retries=self.max_retries,\n timeout=self.request_timeout or None,\n tiktoken_enabled=self.tiktoken_enable,\n tiktoken_model_name=self.tiktoken_model_name or None,\n show_progress_bar=self.show_progress_bar,\n model_kwargs=self.model_kwargs,\n skip_empty=self.skip_empty,\n default_headers=self.default_headers or None,\n default_query=self.default_query or None,\n )\n" - }, - "default_headers": { - "advanced": true, - "display_name": "Default Headers", - "dynamic": false, - "info": "Default headers to use for the API request.", - "list": false, - "name": "default_headers", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "default_query": { - "advanced": true, - "display_name": "Default Query", - "dynamic": false, - "info": "Default query parameters to use for the API request.", - "list": false, - "name": "default_query", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "deployment": { - "advanced": true, - "display_name": "Deployment", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "deployment", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "dimensions": { - "advanced": true, - "display_name": "Dimensions", - "dynamic": false, - "info": "The number of dimensions the resulting output embeddings should have. Only supported by certain models.", - "list": false, - "name": "dimensions", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "embedding_ctx_length": { - "advanced": true, - "display_name": "Embedding Context Length", - "dynamic": false, - "info": "", - "list": false, - "name": "embedding_ctx_length", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1536 - }, - "max_retries": { - "advanced": true, - "display_name": "Max Retries", - "dynamic": false, - "info": "", - "list": false, - "name": "max_retries", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 3 - }, - "model": { - "advanced": false, - "display_name": "Model", - "dynamic": false, - "info": "", - "name": "model", - "options": [ - "text-embedding-3-small", - "text-embedding-3-large", - "text-embedding-ada-002" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "text-embedding-3-small" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "load_from_db": false, - "name": "openai_api_base", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "openai_api_type": { - "advanced": true, - "display_name": "OpenAI API Type", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "load_from_db": false, - "name": "openai_api_type", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_version": { - "advanced": true, - "display_name": "OpenAI API Version", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "openai_api_version", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "openai_organization": { - "advanced": true, - "display_name": "OpenAI Organization", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "openai_organization", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "openai_proxy": { - "advanced": true, - "display_name": "OpenAI Proxy", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "openai_proxy", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "request_timeout": { - "advanced": true, - "display_name": "Request Timeout", - "dynamic": false, - "info": "", - "list": false, - "name": "request_timeout", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": "" - }, - "show_progress_bar": { - "advanced": true, - "display_name": "Show Progress Bar", - "dynamic": false, - "info": "", - "list": false, - "name": "show_progress_bar", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "skip_empty": { - "advanced": true, - "display_name": "Skip Empty", - "dynamic": false, - "info": "", - "list": false, - "name": "skip_empty", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "tiktoken_enable": { - "advanced": true, - "display_name": "TikToken Enable", - "dynamic": false, - "info": "If False, you must have transformers installed.", - "list": false, - "name": "tiktoken_enable", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": true - }, - "tiktoken_model_name": { - "advanced": true, - "display_name": "TikToken Model Name", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "tiktoken_model_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "OpenAIEmbeddings" - }, - "dragging": false, - "height": 383, - "id": "OpenAIEmbeddings-Mf9md", - "position": { - "x": 2044.683126356786, - "y": 1785.2283494456522 - }, - "positionAbsolute": { - "x": 2044.683126356786, - "y": 1785.2283494456522 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "💡 Paste your [OpenAI API key](https://platform.openai.com/) key here.", - "display_name": "OpenAI Embeddings", - "id": "OpenAIEmbeddings-q2lBh", - "node": { - "base_classes": [ - "Embeddings" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "💡 Paste your [OpenAI API key](https://platform.openai.com/) key here.", - "display_name": "OpenAI Embeddings", - "documentation": "", - "edited": false, - "field_order": [ - "default_headers", - "default_query", - "chunk_size", - "client", - "deployment", - "embedding_ctx_length", - "max_retries", - "model", - "model_kwargs", - "openai_api_base", - "openai_api_key", - "openai_api_type", - "openai_api_version", - "openai_organization", - "openai_proxy", - "request_timeout", - "show_progress_bar", - "skip_empty", - "tiktoken_model_name", - "tiktoken_enable", - "dimensions" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Embeddings", - "method": "build_embeddings", - "name": "embeddings", - "required_inputs": [], - "selected": "Embeddings", - "types": [ - "Embeddings" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "chunk_size": { - "advanced": true, - "display_name": "Chunk Size", - "dynamic": false, - "info": "", - "list": false, - "name": "chunk_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1000 - }, - "client": { - "advanced": true, - "display_name": "Client", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "client", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langchain_openai import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.base.models.openai_constants import OPENAI_EMBEDDING_MODEL_NAMES\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n name = \"OpenAIEmbeddings\"\n\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=OPENAI_EMBEDDING_MODEL_NAMES,\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\", value=\"OPENAI_API_KEY\"),\n MessageTextInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n MessageTextInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n IntInput(\n name=\"dimensions\",\n display_name=\"Dimensions\",\n info=\"The number of dimensions the resulting output embeddings should have. \"\n \"Only supported by certain models.\",\n advanced=True,\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n client=self.client or None,\n model=self.model,\n dimensions=self.dimensions or None,\n deployment=self.deployment or None,\n api_version=self.openai_api_version or None,\n base_url=self.openai_api_base or None,\n openai_api_type=self.openai_api_type or None,\n openai_proxy=self.openai_proxy or None,\n embedding_ctx_length=self.embedding_ctx_length,\n api_key=self.openai_api_key or None,\n organization=self.openai_organization or None,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n max_retries=self.max_retries,\n timeout=self.request_timeout or None,\n tiktoken_enabled=self.tiktoken_enable,\n tiktoken_model_name=self.tiktoken_model_name or None,\n show_progress_bar=self.show_progress_bar,\n model_kwargs=self.model_kwargs,\n skip_empty=self.skip_empty,\n default_headers=self.default_headers or None,\n default_query=self.default_query or None,\n )\n" - }, - "default_headers": { - "advanced": true, - "display_name": "Default Headers", - "dynamic": false, - "info": "Default headers to use for the API request.", - "list": false, - "name": "default_headers", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "default_query": { - "advanced": true, - "display_name": "Default Query", - "dynamic": false, - "info": "Default query parameters to use for the API request.", - "list": false, - "name": "default_query", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "deployment": { - "advanced": true, - "display_name": "Deployment", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "deployment", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "dimensions": { - "advanced": true, - "display_name": "Dimensions", - "dynamic": false, - "info": "The number of dimensions the resulting output embeddings should have. Only supported by certain models.", - "list": false, - "name": "dimensions", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "embedding_ctx_length": { - "advanced": true, - "display_name": "Embedding Context Length", - "dynamic": false, - "info": "", - "list": false, - "name": "embedding_ctx_length", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1536 - }, - "max_retries": { - "advanced": true, - "display_name": "Max Retries", - "dynamic": false, - "info": "", - "list": false, - "name": "max_retries", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 3 - }, - "model": { - "advanced": false, - "display_name": "Model", - "dynamic": false, - "info": "", - "name": "model", - "options": [ - "text-embedding-3-small", - 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], - "load_from_db": true, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "openai_api_type": { - "advanced": true, - "display_name": "OpenAI API Type", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "load_from_db": false, - "name": "openai_api_type", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_version": { - "advanced": true, - "display_name": "OpenAI API Version", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "openai_api_version", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "openai_organization": { - "advanced": true, - "display_name": "OpenAI Organization", - 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"display_name": "TikToken Model Name", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "tiktoken_model_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "OpenAIEmbeddings" - }, - "dragging": false, - "height": 383, - "id": "OpenAIEmbeddings-q2lBh", - "position": { - "x": 628.9252513328779, - "y": 648.6750537749285 - }, - "positionAbsolute": { - "x": 628.9252513328779, - "y": 648.6750537749285 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "💡 Paste your [OpenAI API key](https://platform.openai.com/) key here.", - "display_name": "OpenAI", - "id": "OpenAIModel-3v8LQ", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "💡 Paste your [OpenAI API key](https://platform.openai.com/) key here.", - "display_name": "OpenAI", - "documentation": "", - "edited": false, - "field_order": [ - "input_value", - "system_message", - "stream", - "max_tokens", - "model_kwargs", - "json_mode", - "output_schema", - "model_name", - "openai_api_base", - "api_key", - "temperature", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "legacy": false, - "metadata": {}, - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "required_inputs": [], - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "required_inputs": [], - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [ - "Message" - ], - "load_from_db": true, - "name": "api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "json_mode": { - "advanced": true, - "display_name": "JSON Mode", - "dynamic": false, - "info": "If True, it will output JSON regardless of passing a schema.", - "list": false, - "name": "json_mode", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "Additional keyword arguments to pass to the model.", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "load_from_db": false, - "name": "model_name", - "options": [ - "gpt-4o-mini", - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-4", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 595, - "id": "OpenAIModel-3v8LQ", - "position": { - "x": 3138.7638747868177, - "y": 413.0859233500825 - }, - "positionAbsolute": { - "x": 3138.7638747868177, - "y": 413.0859233500825 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "note-LkhtD", - "node": { - "description": "### 📄 Load Data\n\nRun this first! Loads data from a local file and embeds it into the vector database.", - "display_name": "", - "documentation": "", - "template": { - "backgroundColor": "indigo" - } - }, - "type": "note" - }, - "dragging": false, - "height": 356, - "id": "note-LkhtD", - "position": { - "x": 877.5400894704665, - "y": 1501.740726540235 - }, - "positionAbsolute": { - "x": 877.5400894704665, - "y": 1501.740726540235 - }, - "resizing": false, - "selected": false, - "style": { - "height": 356, - "width": 422 - }, - "type": "noteNode", - "width": 422 - }, - { - "data": { - "id": "note-SqVp4", - "node": { - "description": "## Vector Store RAG README\n\nLoad your data into a vector database with one flow, and use your data as chat context in another flow. \n\n**Look out for the** '💡' **emoji for tips in components.**\n\n#### 2 distinct flows:\n- **📄Load Data:** Run this first! Loads data from a local file and embeds it into the vector database.\n- **✨Retriever:** Retrieves data from the vector database based on your query.", - "display_name": "Read Me", - "documentation": "", - "template": { - "backgroundColor": "indigo" - } - }, - "type": "note" - }, - "dragging": false, - "height": 535, - "id": "note-SqVp4", - "position": { - "x": -210.5780262142282, - "y": 338.8484570142142 - }, - "positionAbsolute": { - "x": -210.5780262142282, - "y": 338.8484570142142 - }, - "resizing": false, - "selected": false, - "style": { - "height": 535, - "width": 600 - }, - "type": "noteNode", - "width": 600 - }, - { - "data": { - "id": "note-Rywlz", - "node": { - "description": "### ✨ Retriever \n\n Retrieves data from the vector database based on your query.", - "display_name": "", - "documentation": "", - "template": { - "backgroundColor": "indigo" - } - }, - "type": "note" - }, - "dragging": false, - "height": 358, - "id": "note-Rywlz", - "position": { - "x": 1246.270583789109, - "y": -99.85991506747081 - }, - "positionAbsolute": { - "x": 1246.270583789109, - "y": -99.85991506747081 - }, - "resizing": false, - "selected": false, - "style": { - "height": 358, - "width": 412 - }, - "type": "noteNode", - "width": 412 + "width": 320 } ], "viewport": { - "x": 342.7396252506155, - "y": 81.92958175685953, - "zoom": 0.28537669697335505 + "x": -298.6563130974548, + "y": -137.6024801797489, + "zoom": 0.5239796558908366 } }, "description": "Visit https://docs.langflow.org/starter-projects-vector-store-rag for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", "endpoint_name": null, "icon": "Database", - "id": "87aff7ff-7c7f-4965-a5b1-155b18ae43de", + "id": "c63bc197-85d6-4f39-87dc-2bc35523ec4e", "is_component": false, - "last_tested_version": "1.0.18", + "last_tested_version": "1.0.19.post2", "name": "Vector Store RAG", "tags": [ "openai", "astradb", - "chatbots", - "rag" + "rag", + "q-a" ] } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/YouTube Transcript Q&A.json b/src/backend/base/langflow/initial_setup/starter_projects/YouTube Transcript Q&A.json new file mode 100644 index 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"YouTubeTranscriptsComponent", + "id": "YouTubeTranscriptsComponent-n8Z9Y", + "name": "transcripts_tool", + "output_types": [ + "Tool" + ] + }, + "targetHandle": { + "fieldName": "tools", + "id": "Agent-EGSx3", + "inputTypes": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "type": "other" + } + }, + "id": "reactflow__edge-YouTubeTranscriptsComponent-n8Z9Y{œdataTypeœ:œYouTubeTranscriptsComponentœ,œidœ:œYouTubeTranscriptsComponent-n8Z9Yœ,œnameœ:œtranscripts_toolœ,œoutput_typesœ:[œToolœ]}-Agent-EGSx3{œfieldNameœ:œtoolsœ,œidœ:œAgent-EGSx3œ,œinputTypesœ:[œToolœ,œBaseToolœ,œStructuredToolœ],œtypeœ:œotherœ}", + "source": "YouTubeTranscriptsComponent-n8Z9Y", + "sourceHandle": "{œdataTypeœ: œYouTubeTranscriptsComponentœ, œidœ: œYouTubeTranscriptsComponent-n8Z9Yœ, œnameœ: œtranscripts_toolœ, œoutput_typesœ: [œToolœ]}", + "target": "Agent-EGSx3", + "targetHandle": "{œfieldNameœ: œtoolsœ, œidœ: œAgent-EGSx3œ, œinputTypesœ: [œToolœ, œBaseToolœ, œStructuredToolœ], œtypeœ: œotherœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "id": "Agent-EGSx3", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Define the agent's instructions, then enter a task to complete using tools.", + "display_name": "Agent", + "documentation": "", + "edited": false, + "field_order": [ + "agent_llm", + "max_tokens", + "model_kwargs", + "json_mode", + "output_schema", + "model_name", + "openai_api_base", + "api_key", + "temperature", + "seed", + "output_parser", + "system_prompt", + "tools", + "input_value", + "handle_parsing_errors", + "verbose", + "max_iterations", + "agent_description", + "memory", + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template", + "add_current_date_tool" + ], + "frozen": false, + "icon": "bot", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Response", + "method": "message_response", + "name": "response", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_current_date_tool": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Add tool Current Date", + "dynamic": false, + "info": "If true, will add a tool to the agent that returns the current date.", + "list": false, + "name": "add_current_date_tool", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "agent_description": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Agent Description", + "dynamic": false, + "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "agent_description", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "A helpful assistant with access to the following tools:" + }, + "agent_llm": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Provider", + "dynamic": false, + "info": "The provider of the language model that the agent will use to generate responses.", + "input_types": [], + "name": "agent_llm", + "options": [ + "Amazon Bedrock", + "Anthropic", + "Azure OpenAI", + "Groq", + "NVIDIA", + "OpenAI", + "Custom" + ], + "placeholder": "", + "real_time_refresh": true, + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "OpenAI" + }, + "api_key": { + "_input_type": "SecretStrInput", + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Message" + ], + "load_from_db": true, + "name": "api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.components.memories.memory import MemoryComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix), display_name\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n if field_name == \"agent_llm\":\n # Define provider configurations as (fields_to_add, fields_to_delete)\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n\n return build_config\n" + }, + "handle_parsing_errors": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Handle Parse Errors", + "dynamic": false, + "info": "Should the Agent fix errors when reading user input for better processing?", + "list": false, + "name": "handle_parsing_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "input_value": { + "_input_type": "MessageTextInput", + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "The input provided by the user for the agent to process.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": true, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "json_mode": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "JSON Mode", + "dynamic": false, + "info": "If True, it will output JSON regardless of passing a schema.", + "list": false, + "name": "json_mode", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "max_iterations": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Iterations", + "dynamic": false, + "info": "The maximum number of attempts the agent can make to complete its task before it stops.", + "list": false, + "name": "max_iterations", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 15 + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "range_spec": { + "max": 128000, + "min": 0, + "step": 0.1, + "step_type": "float" + }, + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "memory": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "External Memory", + "dynamic": false, + "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", + "input_types": [ + "BaseChatMessageHistory" + ], + "list": false, + "name": "memory", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "model_kwargs": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "Additional keyword arguments to pass to the model.", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o-mini", + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-4", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-4o-mini" + }, + "n_messages": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 100 + }, + "openai_api_base": { + "_input_type": "StrInput", + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "order": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Ascending" + }, + "output_parser": { + "_input_type": "HandleInput", + "advanced": true, + "display_name": "Output Parser", + "dynamic": false, + "info": "The parser to use to parse the output of the model", + "input_types": [ + "OutputParser" + ], + "list": false, + "name": "output_parser", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "output_schema": { + "_input_type": "DictInput", + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Filter by sender type.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Filter by sender name.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "system_prompt": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Agent Instructions", + "dynamic": false, + "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "system_prompt", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "You are an AI assistant capable of fetching and analyzing YouTube video transcripts to answer user questions. You have access to a YouTube Transcripts tool that can extract spoken content from YouTube videos.\n\n\n1. First, attempt to fetch the transcript using the following settings:\n \n YouTube_Transcripts(\n url=\"{{VIDEO_URL}}\",\n transcript_format=\"text\",\n language=\"\",\n translation=\"\"\n )\n \n\n2. If you receive an error indicating that only a specific language is available (e.g., \"only pt is available\"), retry the function call with the correct language setting:\n \n YouTube_Transcripts(\n url=\"{{VIDEO_URL}}\",\n transcript_format=\"text\",\n language=\"[specified_language_code]\",\n translation=\"\"\n )\n \n\n3. Once you have successfully retrieved the transcript, analyze its content to answer the user's question.\n\n4. If you need to refer to specific parts of the video, you can make an additional call to get chunked transcripts:\n \n YouTube_Transcripts(\n url=\"{{VIDEO_URL}}\",\n transcript_format=\"chunks\",\n chunk_size_seconds=60,\n language=\"[language_used_in_successful_call]\",\n translation=\"\"\n )\n \n\nWhen answering the user's question:\n- Provide a clear and concise answer based on the information in the transcript.\n- If the question cannot be answered using the transcript alone, state this clearly and explain why.\n- If you need to quote the transcript, use quotation marks and provide context.\n- If referring to specific timestamps, mention them in your answer (only if you've retrieved chunked transcripts).\n\nRemember, your primary goal is to accurately answer the user's question using the information available in the video transcript. If you encounter any issues or if the question cannot be answered based on the transcript, explain this clearly in your response." + }, + "temperature": { + "_input_type": "FloatInput", + "advanced": true, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + }, + "template": { + "_input_type": "MultilineInput", + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{sender_name}: {text}" + }, + "tools": { + "_input_type": "HandleInput", + "advanced": false, + "display_name": "Tools", + "dynamic": false, + "info": "These are the tools that the agent can use to help with tasks.", + "input_types": [ + "Tool", + "BaseTool", + "StructuredTool" + ], + "list": true, + "name": "tools", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "verbose": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Verbose", + "dynamic": false, + "info": "", + "list": false, + "name": "verbose", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + } + }, + "tool_mode": false + }, + "type": "Agent" + }, + "dragging": false, + "height": 650, + "id": "Agent-EGSx3", + "position": { + "x": -631.1849833420482, + "y": -1088.2379740335518 + }, + "positionAbsolute": { + "x": -631.1849833420482, + "y": -1088.2379740335518 + }, + "selected": true, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "ChatInput-B1nYa", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "files", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "files": { + "_input_type": "FileInput", + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "can you see the transcript from this video and tell me what this is about? https://www.youtube.com/watch?v=UkV79sJAvz8" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 234, + "id": "ChatInput-B1nYa", + "position": { + "x": -996.5201766752447, + "y": -667.1593168473087 + }, + "positionAbsolute": { + "x": -996.5201766752447, + "y": -667.1593168473087 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "id": "ChatOutput-zUzVK", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": false, + "field_order": [ + "input_value", + "should_store_message", + "sender", + "sender_name", + "session_id", + "data_template", + "background_color", + "chat_icon", + "text_color" + ], + "frozen": false, + "icon": "MessagesSquare", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "background_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Background Color", + "dynamic": false, + "info": "The background color of the icon.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "background_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "chat_icon": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Icon", + "dynamic": false, + "info": "The icon of the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "chat_icon", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, _id: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if _id:\n source_dict[\"id\"] = _id\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(_source_id, _display_name, _source)\n message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" + }, + "data_template": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "_input_type": "MessageInput", + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "should_store_message": { + "_input_type": "BoolInput", + "advanced": true, + "display_name": "Store Messages", + "dynamic": false, + "info": "Store the message in the history.", + "list": false, + "name": "should_store_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": true + }, + "text_color": { + "_input_type": "MessageTextInput", + "advanced": true, + "display_name": "Text Color", + "dynamic": false, + "info": "The text color of the name", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "text_color", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 234, + "id": "ChatOutput-zUzVK", + "position": { + "x": -261.7796479132812, + "y": -677.0769470644535 + }, + "positionAbsolute": { + "x": -261.7796479132812, + "y": -677.0769470644535 + }, + "selected": false, + "type": "genericNode", + "width": 320 + }, + { + "data": { + "id": "note-f5vkx", + "node": { + "description": "# YouTube Transcript Q&A\nA quick way to ask questions about YouTube video content through transcript analysis!\n\n## Instructions\n1. **Input Your Query**\n - Paste YouTube video URL\n - Add your question about the content\n - Format: \"What is this video about? [URL]\"\n\n2. **Get Analysis**\n - System extracts video transcript\n - AI processes your question\n - Provides detailed answer from content\n\n3. **Additional Features**\n - Handles multiple languages\n - Can reference specific timestamps\n - Supports follow-up questions\n\n4. **Best Practices**\n - Ensure video has captions/subtitles\n - Ask specific questions\n - For timing details, mention timestamps\n\n5. **Common Uses**\n - Content summaries\n - Finding specific information\n - Understanding key points\n - Fact checking video claims\n\nRemember: Quality depends on available transcripts! 🎥💬", + "display_name": "", + "documentation": "", + "template": {} + }, + "type": "note" + }, + "dragging": false, + "height": 800, + "id": "note-f5vkx", + "position": { + "x": -1627.783352547462, + "y": -1212.3239149398214 + }, + "positionAbsolute": { + "x": -1627.783352547462, + "y": -1212.3239149398214 + }, + "resizing": false, + "selected": false, + "style": { + "height": 800, + "width": 600 + }, + "type": "noteNode", + "width": 600 + }, + { + "data": { + "id": "YouTubeTranscriptsComponent-n8Z9Y", + "node": { + "base_classes": [ + "Data", + "Tool" + ], + "beta": false, + "category": "tools", + "conditional_paths": [], + "custom_fields": {}, + "description": "Extracts spoken content from YouTube videos as transcripts.", + "display_name": "YouTube Transcripts", + "documentation": "", + "edited": false, + "field_order": [ + "url", + "transcript_format", + "chunk_size_seconds", + "language", + "translation" + ], + "frozen": false, + "icon": "YouTube", + "key": "YouTubeTranscriptsComponent", + "legacy": false, + "lf_version": "1.0.19.post2", + "metadata": {}, + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "build_youtube_transcripts", + "name": "transcripts", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Tool", + "method": "build_youtube_tool", + "name": "transcripts_tool", + "selected": "Tool", + "types": [ + "Tool" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "chunk_size_seconds": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Chunk Size (seconds)", + "dynamic": false, + "info": "The size of each transcript chunk in seconds. Only applicable when 'Transcript Format' is set to 'chunks'.", + "list": false, + "name": "chunk_size_seconds", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 60 + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain.tools import StructuredTool\nfrom langchain_community.document_loaders import YoutubeLoader\nfrom langchain_community.document_loaders.youtube import TranscriptFormat\nfrom langchain_core.tools import ToolException\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import DropdownInput, IntInput, MultilineInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\n\nclass YoutubeApiSchema(BaseModel):\n \"\"\"Schema to define the input structure for the tool.\"\"\"\n\n url: str = Field(..., description=\"The YouTube URL to get transcripts from.\")\n transcript_format: TranscriptFormat = Field(\n TranscriptFormat.TEXT,\n description=\"The format of the transcripts. Either 'text' for a single \"\n \"text output or 'chunks' for timestamped chunks.\",\n )\n chunk_size_seconds: int = Field(\n 120,\n description=\"The size of each transcript chunk in seconds. Only \"\n \"applicable when 'Transcript Format' is set to 'chunks'.\",\n )\n language: str = Field(\n \"\",\n description=\"A comma-separated list of language codes in descending \" \"priority. Leave empty for default.\",\n )\n translation: str = Field(\n \"\", description=\"Translate the transcripts to the specified language. \" \"Leave empty for no translation.\"\n )\n\n\nclass YouTubeTranscriptsComponent(LCToolComponent):\n \"\"\"A component that extracts spoken content from YouTube videos as transcripts.\"\"\"\n\n display_name: str = \"YouTube Transcripts\"\n description: str = \"Extracts spoken content from YouTube videos as transcripts.\"\n icon: str = \"YouTube\"\n\n inputs = [\n MultilineInput(\n name=\"url\", display_name=\"Video URL\", info=\"Enter the YouTube video URL to get transcripts from.\"\n ),\n DropdownInput(\n name=\"transcript_format\",\n display_name=\"Transcript Format\",\n options=[\"text\", \"chunks\"],\n value=\"text\",\n info=\"The format of the transcripts. Either 'text' for a single output \"\n \"or 'chunks' for timestamped chunks.\",\n ),\n IntInput(\n name=\"chunk_size_seconds\",\n display_name=\"Chunk Size (seconds)\",\n value=60,\n advanced=True,\n info=\"The size of each transcript chunk in seconds. Only applicable when \"\n \"'Transcript Format' is set to 'chunks'.\",\n ),\n MultilineInput(\n name=\"language\",\n display_name=\"Language\",\n info=\"A comma-separated list of language codes in descending priority. \" \"Leave empty for default.\",\n ),\n DropdownInput(\n name=\"translation\",\n display_name=\"Translation Language\",\n advanced=True,\n options=[\"\", \"en\", \"es\", \"fr\", \"de\", \"it\", \"pt\", \"ru\", \"ja\", \"ko\", \"hi\", \"ar\", \"id\"],\n info=\"Translate the transcripts to the specified language. \" \"Leave empty for no translation.\",\n ),\n ]\n\n outputs = [\n Output(name=\"transcripts\", display_name=\"Data\", method=\"build_youtube_transcripts\"),\n Output(name=\"transcripts_tool\", display_name=\"Tool\", method=\"build_youtube_tool\"),\n ]\n\n def build_youtube_transcripts(self) -> Data | list[Data]:\n \"\"\"Method to build transcripts from the provided YouTube URL.\n\n Returns:\n Data | list[Data]: The transcripts of the video, either as a single\n Data object or a list of Data objects.\n \"\"\"\n try:\n loader = YoutubeLoader.from_youtube_url(\n self.url,\n transcript_format=TranscriptFormat.TEXT\n if self.transcript_format == \"text\"\n else TranscriptFormat.CHUNKS,\n chunk_size_seconds=self.chunk_size_seconds,\n language=self.language.split(\",\") if self.language else [\"en\"],\n translation=self.translation if self.translation else None,\n )\n\n transcripts = loader.load()\n\n if self.transcript_format == \"text\":\n # Extract only the page_content from the Document\n return Data(data={\"transcripts\": transcripts[0].page_content})\n # For chunks, extract page_content and metadata separately\n return [Data(data={\"content\": doc.page_content, \"metadata\": doc.metadata}) for doc in transcripts]\n\n except Exception as exc: # noqa: BLE001\n # Using a specific error type for the return value\n return Data(data={\"error\": f\"Failed to get YouTube transcripts: {exc!s}\"})\n\n def youtube_transcripts(\n self,\n url: str = \"\",\n transcript_format: TranscriptFormat = TranscriptFormat.TEXT,\n chunk_size_seconds: int = 120,\n language: str = \"\",\n translation: str = \"\",\n ) -> Data | list[Data]:\n \"\"\"Helper method to handle transcripts outside of component calls.\n\n Args:\n url: The YouTube URL to get transcripts from.\n transcript_format: Format of transcripts ('text' or 'chunks').\n chunk_size_seconds: Size of each transcript chunk in seconds.\n language: Comma-separated list of language codes.\n translation: Target language for translation.\n\n Returns:\n Data | list[Data]: Video transcripts as single Data or list of Data.\n \"\"\"\n try:\n if isinstance(transcript_format, str):\n transcript_format = TranscriptFormat(transcript_format)\n loader = YoutubeLoader.from_youtube_url(\n url,\n transcript_format=TranscriptFormat.TEXT\n if transcript_format == TranscriptFormat.TEXT\n else TranscriptFormat.CHUNKS,\n chunk_size_seconds=chunk_size_seconds,\n language=language.split(\",\") if language else [\"en\"],\n translation=translation if translation else None,\n )\n\n transcripts = loader.load()\n if transcript_format == TranscriptFormat.TEXT and len(transcripts) > 0:\n return Data(data={\"transcript\": transcripts[0].page_content})\n return [Data(data={\"content\": doc.page_content, \"metadata\": doc.metadata}) for doc in transcripts]\n except Exception as exc:\n msg = f\"Failed to get YouTube transcripts: {exc!s}\"\n raise ToolException(msg) from exc\n\n def build_youtube_tool(self) -> Tool:\n \"\"\"Method to build the transcripts tool.\n\n Returns:\n Tool: A structured tool that uses the transcripts method.\n\n Raises:\n RuntimeError: If tool creation fails.\n \"\"\"\n try:\n return StructuredTool.from_function(\n name=\"youtube_transcripts\",\n description=\"Get transcripts from YouTube videos.\",\n func=self.youtube_transcripts,\n args_schema=YoutubeApiSchema,\n )\n\n except Exception as exc:\n msg = f\"Failed to build the YouTube transcripts tool: {exc!s}\"\n raise RuntimeError(msg) from exc\n" + }, + "language": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Language", + "dynamic": false, + "info": "A comma-separated list of language codes in descending priority. Leave empty for default.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "language", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "transcript_format": { + "_input_type": "DropdownInput", + "advanced": false, + "combobox": false, + "display_name": "Transcript Format", + "dynamic": false, + "info": "The format of the transcripts. Either 'text' for a single output or 'chunks' for timestamped chunks.", + "name": "transcript_format", + "options": [ + "text", + "chunks" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "chunks" + }, + "translation": { + "_input_type": "DropdownInput", + "advanced": true, + "combobox": false, + "display_name": "Translation Language", + "dynamic": false, + "info": "Translate the transcripts to the specified language. Leave empty for no translation.", + "name": "translation", + "options": [ + "", + "en", + "es", + "fr", + "de", + "it", + "pt", + "ru", + "ja", + "ko", + "hi", + "ar", + "id" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "url": { + "_input_type": "MultilineInput", + "advanced": false, + "display_name": "Video URL", + "dynamic": false, + "info": "Enter the YouTube video URL to get transcripts from.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "url", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + }, + "tool_mode": false + }, + "type": "YouTubeTranscriptsComponent" + }, + "dragging": false, + "height": 475, + "id": "YouTubeTranscriptsComponent-n8Z9Y", + "position": { + "x": -996.7508450845454, + "y": -1169.8625689107164 + }, + "positionAbsolute": { + "x": -996.7508450845454, + "y": -1169.8625689107164 + }, + "selected": false, + "type": "genericNode", + "width": 320 + } + ], + "viewport": { + "x": 1337.7257173603357, + "y": 1096.2297230048744, + "zoom": 0.7807596345995297 + } + }, + "description": "Quickly get detailed answers to questions about YouTube videos by analyzing their transcripts.", + "endpoint_name": null, + "icon": "Youtube", + "id": "3b33c431-9b8b-4ba1-9372-04b785e590d3", + "is_component": false, + "last_tested_version": "1.0.19.post2", + "name": "YouTube Transcript Q&A", + "tags": [ + "agents", + "content-generation", + "rag", + "q-a" + ] +} \ No newline at end of file diff --git a/src/frontend/src/modals/templatesModal/components/GetStartedComponent/index.tsx b/src/frontend/src/modals/templatesModal/components/GetStartedComponent/index.tsx index a9f2ca5f0..8ac728470 100644 --- a/src/frontend/src/modals/templatesModal/components/GetStartedComponent/index.tsx +++ b/src/frontend/src/modals/templatesModal/components/GetStartedComponent/index.tsx @@ -19,8 +19,8 @@ export default function GetStartedComponent() { bgImage: memoryChatbot, bgHorizontalImage: memoryChatbotHorizontal, icon: "MessagesSquare", - category: "Prompting", - flow: examples.find((example) => example.name === "Memory Chatbot"), + category: "prompting", + flow: examples.find((example) => example.name === "Basic Prompting"), }, { bgImage: vectorRag, @@ -34,13 +34,13 @@ export default function GetStartedComponent() { bgHorizontalImage: multiAgentHorizontal, icon: "Bot", category: "Agents", - flow: examples.find((example) => example.name === "Dynamic Agent"), + flow: examples.find((example) => example.name === "Simple Agent"), }, ]; return (
- + Get started
diff --git a/src/frontend/src/modals/templatesModal/index.tsx b/src/frontend/src/modals/templatesModal/index.tsx index 76baf85d6..b14c4f350 100644 --- a/src/frontend/src/modals/templatesModal/index.tsx +++ b/src/frontend/src/modals/templatesModal/index.tsx @@ -31,6 +31,22 @@ export default function TemplatesModal({ { title: "All templates", icon: "LayoutPanelTop", id: "all-templates" }, ], }, + { + title: "Use Cases", + items: [ + { title: "Assistants", icon: "BotMessageSquare", id: "assistants" }, + { title: "Classification", icon: "Tags", id: "classification" }, + { title: "Coding", icon: "TerminalIcon", id: "coding" }, + { + title: "Content Generation", + icon: "Newspaper", + id: "content-generation", + }, + { title: "Q&A", icon: "Database", id: "q-a" }, + // { title: "Summarization", icon: "Bot", id: "summarization" }, + // { title: "Web Scraping", icon: "CodeXml", id: "web-scraping" }, + ], + }, { title: "Methodology", items: [ diff --git a/src/frontend/src/utils/styleUtils.ts b/src/frontend/src/utils/styleUtils.ts index ad41253d8..6942bae45 100644 --- a/src/frontend/src/utils/styleUtils.ts +++ b/src/frontend/src/utils/styleUtils.ts @@ -11,6 +11,7 @@ import { ZepMemoryIcon } from "@/icons/ZepMemory"; import { AthenaIcon } from "@/icons/athena/index"; import { freezeAllIcon } from "@/icons/freezeAll"; import { GlobeOkIcon } from "@/icons/globe-ok"; +import { TwitterLogoIcon } from "@radix-ui/react-icons"; import { AlertCircle, AlertTriangle, @@ -50,6 +51,7 @@ import { Clipboard, Code, Code2, + CodeXml, Cog, Combine, Command, @@ -74,6 +76,7 @@ import { File, FileClock, FileDown, + FileQuestion, FileSearch, FileSearch2, FileSliders, @@ -101,6 +104,7 @@ import { Home, Image, Info, + InstagramIcon, Key, Keyboard, Laptop2, @@ -109,6 +113,8 @@ import { LayoutPanelTop, Link, Link2, + List, + ListChecks, ListFilter, ListOrdered, Loader2, @@ -130,6 +136,8 @@ import { MoonIcon, MoreHorizontal, Network, + Newspaper, + NotebookPen, OctagonAlert, OptionIcon, Package2, @@ -143,6 +151,7 @@ import { Pen, Pencil, PencilLine, + PieChart, Pin, Plane, Play, @@ -177,6 +186,7 @@ import { Sparkles, Square, SquareArrowOutUpRight, + SquareCode, SquarePen, SquarePlay, StickyNote, @@ -184,10 +194,12 @@ import { Sun, SunIcon, Table, + Tags, TerminalIcon, TerminalSquare, TextCursorInput, TextSearch, + TextSearchIcon, ToyBrick, Trash2, Type, @@ -207,6 +219,7 @@ import { Wrench, X, XCircle, + Youtube, Zap, ZoomIn, ZoomOut, @@ -733,6 +746,7 @@ export const nodeIconsLucide: iconsType = { Hammer, GradientSave, Shield, + NotebookPen, Plus, Redo, Settings2, @@ -754,6 +768,10 @@ export const nodeIconsLucide: iconsType = { Eraser, Lock, LockOpen, + Newspaper, + Tags, + CodeXml, + PieChart, LucideSend, Sparkles, DownloadCloud, @@ -853,6 +871,14 @@ export const nodeIconsLucide: iconsType = { Image, CopyPlus, Pen, + TwitterLogoIcon, + InstagramIcon, + TextSearchIcon, + FileQuestion, + Youtube, + List, + SquareCode, + ListChecks, PanelRightOpen, CornerDownLeft, ChevronsDownUp,