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 (Hello, world!).json index c874ee14a..683bb5b26 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 (Hello, world!).json @@ -7,7 +7,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-k39HS", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -23,7 +23,7 @@ }, "id": "reactflow__edge-OpenAIModel-k39HS{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-k39HSœ}-ChatOutput-njtka{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-njtkaœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "OpenAIModel-k39HS", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-k39HSœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-k39HSœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -36,7 +36,7 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-uxBqP", - "name": "Text", + "name": "prompt", "output_types": [ "Prompt" ] @@ -54,7 +54,7 @@ }, "id": "reactflow__edge-Prompt-uxBqP{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-uxBqPœ}-OpenAIModel-k39HS{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-k39HSœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "Prompt-uxBqP", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-uxBqPœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-uxBqPœ, œoutput_typesœ: [œPromptœ], œnameœ: œpromptœ}", "style": { "stroke": "#555" }, @@ -68,14 +68,16 @@ "dataType": "ChatInput", "id": "ChatInput-P3fgL", "name": "message", - "output_types": [] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "user_input", "id": "Prompt-uxBqP", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -84,12 +86,12 @@ }, "id": "reactflow__edge-ChatInput-P3fgL{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-P3fgLœ}-Prompt-uxBqP{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-uxBqPœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "ChatInput-P3fgL", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-P3fgLœ, œoutput_typesœ: [], œnameœ: œmessageœ}", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-P3fgLœ, œoutput_typesœ: [œMessageœ], œnameœ: œmessageœ}", "style": { "stroke": "#555" }, "target": "Prompt-uxBqP", - "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-uxBqPœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-uxBqPœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -123,22 +125,33 @@ "is_input": null, "is_output": null, "name": "", - "output_types": [ - "Prompt" - ], + "output_types": [], "outputs": [ { - "display_name": null, - "method": null, - "name": "Prompt", - "selected": null, + "cache": true, + "display_name": "Prompt", + "method": "build_prompt", + "name": "prompt", + "selected": "Prompt", "types": [ "Prompt" - ] + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "format_prompt", + "name": "text", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -155,7 +168,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import CustomComponent\nfrom langflow.field_typing import Input\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n \"code\": Input(advanced=True),\n }\n\n async def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Prompt:\n prompt = await Prompt.from_template_and_variables(template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" + "value": "from langflow.custom import Component\nfrom langflow.field_typing import Input, Output\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n }\n\n inputs = [\n Input(name=\"template\", type=Prompt, display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n Output(display_name=\"Text\", name=\"text\", method=\"format_prompt\"),\n ]\n\n async def format_prompt(self) -> str:\n prompt = await self.build_prompt()\n formatted_text = prompt.format_text()\n self.status = formatted_text\n return formatted_text\n\n async def build_prompt(\n self,\n ) -> Prompt:\n kwargs = {k: v for k, v in self._arguments.items() if k != \"template\"}\n prompt = await Prompt.from_template_and_variables(self.template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" }, "template": { "advanced": false, @@ -189,7 +202,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -269,13 +282,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -544,22 +559,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -580,11 +599,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Message\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"message\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n \"template\": self.record_template or \"\",\n }\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Text\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -743,22 +762,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -779,11 +802,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Message\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"text\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n },\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json index 7308c2a43..b59944358 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json @@ -7,7 +7,7 @@ "sourceHandle": { "dataType": "URL", "id": "URL-HYPkR", - "name": "Record", + "name": "record", "output_types": [ "Record" ] @@ -27,7 +27,7 @@ "id": "reactflow__edge-URL-HYPkR{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-HYPkRœ}-Prompt-Rse03{œfieldNameœ:œreference_2œ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "selected": false, "source": "URL-HYPkR", - "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-HYPkRœ, œoutput_typesœ: [œRecordœ], œnameœ: œRecordœ}", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-HYPkRœ, œoutput_typesœ: [œRecordœ], œnameœ: œrecordœ}", "style": { "stroke": "#555" }, @@ -40,7 +40,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-gi29P", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -56,7 +56,7 @@ }, "id": "reactflow__edge-OpenAIModel-gi29P{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-gi29Pœ}-ChatOutput-JPlxl{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-JPlxlœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "OpenAIModel-gi29P", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-gi29Pœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-gi29Pœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -69,7 +69,7 @@ "sourceHandle": { "dataType": "URL", "id": "URL-2cX90", - "name": "Record", + "name": "record", "output_types": [ "Record" ] @@ -88,7 +88,7 @@ }, "id": "reactflow__edge-URL-2cX90{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-2cX90œ}-Prompt-Rse03{œfieldNameœ:œreference_1œ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "URL-2cX90", - "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-2cX90œ, œoutput_typesœ: [œRecordœ], œnameœ: œRecordœ}", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-2cX90œ, œoutput_typesœ: [œRecordœ], œnameœ: œrecordœ}", "style": { "stroke": "#555" }, @@ -133,7 +133,7 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-Rse03", - "name": "Text", + "name": "prompt", "output_types": [ "Prompt" ] @@ -152,7 +152,7 @@ "id": "reactflow__edge-Prompt-Rse03{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-Rse03œ}-OpenAIModel-gi29P{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-gi29Pœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "selected": false, "source": "Prompt-Rse03", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-Rse03œ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-Rse03œ, œoutput_typesœ: [œPromptœ], œnameœ: œpromptœ}", "style": { "stroke": "#555" }, @@ -193,22 +193,33 @@ "is_input": null, "is_output": null, "name": "", - "output_types": [ - "Prompt" - ], + "output_types": [], "outputs": [ { - "display_name": null, - "method": null, - "name": "Prompt", - "selected": null, + "cache": true, + "display_name": "Prompt", + "method": "build_prompt", + "name": "prompt", + "selected": "Prompt", "types": [ "Prompt" - ] + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "format_prompt", + "name": "text", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -225,7 +236,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import CustomComponent\nfrom langflow.field_typing import Input\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n \"code\": Input(advanced=True),\n }\n\n async def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Prompt:\n prompt = await Prompt.from_template_and_variables(template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" + "value": "from langflow.custom import Component\nfrom langflow.field_typing import Input, Output\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n }\n\n inputs = [\n Input(name=\"template\", type=Prompt, display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n Output(display_name=\"Text\", name=\"text\", method=\"format_prompt\"),\n ]\n\n async def format_prompt(self) -> str:\n prompt = await self.build_prompt()\n formatted_text = prompt.format_text()\n self.status = formatted_text\n return formatted_text\n\n async def build_prompt(\n self,\n ) -> Prompt:\n kwargs = {k: v for k, v in self._arguments.items() if k != \"template\"}\n prompt = await Prompt.from_template_and_variables(self.template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" }, "instructions": { "advanced": false, @@ -369,13 +380,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Record", "method": null, - "name": "Record", - "selected": null, + "name": "record", + "selected": "Record", "types": [ "Record" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -470,22 +483,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -506,11 +523,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Message\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"message\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n \"template\": self.record_template or \"\",\n }\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Text\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -679,13 +696,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -948,13 +967,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Record", "method": null, - "name": "Record", - "selected": null, + "name": "record", + "selected": "Record", "types": [ "Record" - ] + ], + "value": "__UNDEFINED__" } ], "template": { diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json index d56409f3e..a2981ed94 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json @@ -8,14 +8,16 @@ "dataType": "ChatInput", "id": "ChatInput-MsSJ9", "name": "message", - "output_types": [] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "Question", "id": "Prompt-tHwPf", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -24,12 +26,12 @@ }, "id": "reactflow__edge-ChatInput-MsSJ9{œbaseClassesœ:[œstrœ,œRecordœ,œTextœ,œobjectœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-MsSJ9œ}-Prompt-tHwPf{œfieldNameœ:œQuestionœ,œidœ:œPrompt-tHwPfœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "ChatInput-MsSJ9", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-MsSJ9œ, œoutput_typesœ: [], œnameœ: œmessageœ}", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-MsSJ9œ, œoutput_typesœ: [œMessageœ], œnameœ: œmessageœ}", "style": { "stroke": "#555" }, "target": "Prompt-tHwPf", - "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-tHwPfœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-tHwPfœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -47,7 +49,7 @@ "id": "Prompt-tHwPf", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -61,7 +63,7 @@ "stroke": "#555" }, "target": "Prompt-tHwPf", - "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-tHwPfœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-tHwPfœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -69,7 +71,7 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-tHwPf", - "name": "Text", + "name": "prompt", "output_types": [ "Prompt" ] @@ -87,7 +89,7 @@ }, "id": "reactflow__edge-Prompt-tHwPf{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-tHwPfœ}-OpenAIModel-Bt067{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Bt067œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "Prompt-tHwPf", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-tHwPfœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-tHwPfœ, œoutput_typesœ: [œPromptœ], œnameœ: œpromptœ}", "style": { "stroke": "#555" }, @@ -100,7 +102,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-Bt067", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -116,7 +118,7 @@ }, "id": "reactflow__edge-OpenAIModel-Bt067{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Bt067œ}-ChatOutput-F5Awj{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-F5Awjœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "OpenAIModel-Bt067", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-Bt067œ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-Bt067œ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -156,18 +158,29 @@ "is_input": null, "is_output": null, "name": "", - "output_types": [ - "Prompt" - ], + "output_types": [], "outputs": [ { - "display_name": null, - "method": null, - "name": "Prompt", - "selected": null, + "cache": true, + "display_name": "Prompt", + "method": "build_prompt", + "name": "prompt", + "selected": "Prompt", "types": [ "Prompt" - ] + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "format_prompt", + "name": "text", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -181,7 +194,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -207,7 +220,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -223,7 +236,7 @@ "type": "str", "value": "" }, - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -240,7 +253,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import CustomComponent\nfrom langflow.field_typing import Input\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n \"code\": Input(advanced=True),\n }\n\n async def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Prompt:\n prompt = await Prompt.from_template_and_variables(template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" + "value": "from langflow.custom import Component\nfrom langflow.field_typing import Input, Output\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n }\n\n inputs = [\n Input(name=\"template\", type=Prompt, display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n Output(display_name=\"Text\", name=\"text\", method=\"format_prompt\"),\n ]\n\n async def format_prompt(self) -> str:\n prompt = await self.build_prompt()\n formatted_text = prompt.format_text()\n self.status = formatted_text\n return formatted_text\n\n async def build_prompt(\n self,\n ) -> Prompt:\n kwargs = {k: v for k, v in self._arguments.items() if k != \"template\"}\n prompt = await Prompt.from_template_and_variables(self.template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" }, "template": { "advanced": false, @@ -430,22 +443,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -466,11 +483,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Message\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"text\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n },\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -605,22 +622,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -641,11 +662,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Message\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"message\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n \"template\": self.record_template or \"\",\n }\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Text\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -819,13 +840,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json index d327c826b..c71815a0a 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json @@ -7,7 +7,7 @@ "sourceHandle": { "dataType": "MemoryComponent", "id": "MemoryComponent-cdA1J", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -17,7 +17,7 @@ "id": "Prompt-ODkUx", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -27,12 +27,12 @@ "id": "reactflow__edge-MemoryComponent-cdA1J{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-cdA1Jœ}-Prompt-ODkUx{œfieldNameœ:œcontextœ,œidœ:œPrompt-ODkUxœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "selected": false, "source": "MemoryComponent-cdA1J", - "sourceHandle": "{œdataTypeœ: œMemoryComponentœ, œidœ: œMemoryComponent-cdA1Jœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œMemoryComponentœ, œidœ: œMemoryComponent-cdA1Jœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, "target": "Prompt-ODkUx", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-ODkUxœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-ODkUxœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -41,14 +41,16 @@ "dataType": "ChatInput", "id": "ChatInput-t7F8v", "name": "message", - "output_types": [] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "user_message", "id": "Prompt-ODkUx", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -58,12 +60,12 @@ "id": "reactflow__edge-ChatInput-t7F8v{œbaseClassesœ:[œTextœ,œobjectœ,œRecordœ,œstrœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-t7F8vœ}-Prompt-ODkUx{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-ODkUxœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "selected": false, "source": "ChatInput-t7F8v", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-t7F8vœ, œoutput_typesœ: [], œnameœ: œmessageœ}", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-t7F8vœ, œoutput_typesœ: [œMessageœ], œnameœ: œmessageœ}", "style": { "stroke": "#555" }, "target": "Prompt-ODkUx", - "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-ODkUxœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-ODkUxœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -71,7 +73,7 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-ODkUx", - "name": "Text", + "name": "prompt", "output_types": [ "Prompt" ] @@ -89,7 +91,7 @@ }, "id": "reactflow__edge-Prompt-ODkUx{œbaseClassesœ:[œTextœ,œstrœ,œobjectœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-ODkUxœ}-OpenAIModel-9RykF{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-9RykFœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "Prompt-ODkUx", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-ODkUxœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-ODkUxœ, œoutput_typesœ: [œPromptœ], œnameœ: œpromptœ}", "style": { "stroke": "#555" }, @@ -102,7 +104,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-9RykF", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -118,7 +120,7 @@ }, "id": "reactflow__edge-OpenAIModel-9RykF{œbaseClassesœ:[œstrœ,œobjectœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-9RykFœ}-ChatOutput-P1jEe{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-P1jEeœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "OpenAIModel-9RykF", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-9RykFœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-9RykFœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -131,7 +133,7 @@ "sourceHandle": { "dataType": "MemoryComponent", "id": "MemoryComponent-cdA1J", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -148,7 +150,7 @@ }, "id": "reactflow__edge-MemoryComponent-cdA1J{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-cdA1Jœ}-TextOutput-vrs6T{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-vrs6Tœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "MemoryComponent-cdA1J", - "sourceHandle": "{œdataTypeœ: œMemoryComponentœ, œidœ: œMemoryComponent-cdA1Jœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œMemoryComponentœ, œidœ: œMemoryComponent-cdA1Jœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -185,22 +187,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -221,11 +227,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Message\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"text\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n },\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -360,22 +366,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -396,11 +406,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Message\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"message\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n \"template\": self.record_template or \"\",\n }\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Text\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -563,13 +573,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -779,22 +791,33 @@ "is_input": null, "is_output": null, "name": "", - "output_types": [ - "Prompt" - ], + "output_types": [], "outputs": [ { - "display_name": null, - "method": null, - "name": "Prompt", - "selected": null, + "cache": true, + "display_name": "Prompt", + "method": "build_prompt", + "name": "prompt", + "selected": "Prompt", "types": [ "Prompt" - ] + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "format_prompt", + "name": "text", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -811,7 +834,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import CustomComponent\nfrom langflow.field_typing import Input\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n \"code\": Input(advanced=True),\n }\n\n async def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Prompt:\n prompt = await Prompt.from_template_and_variables(template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" + "value": "from langflow.custom import Component\nfrom langflow.field_typing import Input, Output\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n }\n\n inputs = [\n Input(name=\"template\", type=Prompt, display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n Output(display_name=\"Text\", name=\"text\", method=\"format_prompt\"),\n ]\n\n async def format_prompt(self) -> str:\n prompt = await self.build_prompt()\n formatted_text = prompt.format_text()\n self.status = formatted_text\n return formatted_text\n\n async def build_prompt(\n self,\n ) -> Prompt:\n kwargs = {k: v for k, v in self._arguments.items() if k != \"template\"}\n prompt = await Prompt.from_template_and_variables(self.template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" }, "context": { "advanced": false, @@ -823,7 +846,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -871,7 +894,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -949,13 +972,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json index 21e3504d4..1c1186de2 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json @@ -8,14 +8,16 @@ "dataType": "TextInput", "id": "TextInput-sptaH", "name": "text", - "output_types": [] + "output_types": [ + "Text" + ] }, "targetHandle": { "fieldName": "document", "id": "Prompt-amqBu", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -24,12 +26,12 @@ }, "id": "reactflow__edge-TextInput-sptaH{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-sptaHœ}-Prompt-amqBu{œfieldNameœ:œdocumentœ,œidœ:œPrompt-amqBuœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "TextInput-sptaH", - "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-sptaHœ, œoutput_typesœ: [], œnameœ: œtextœ}", + "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-sptaHœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, "target": "Prompt-amqBu", - "targetHandle": "{œfieldNameœ: œdocumentœ, œidœ: œPrompt-amqBuœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œdocumentœ, œidœ: œPrompt-amqBuœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -37,9 +39,9 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-amqBu", - "name": "Text", + "name": "text", "output_types": [ - "Prompt" + "Text" ] }, "targetHandle": { @@ -54,7 +56,7 @@ }, "id": "reactflow__edge-Prompt-amqBu{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}-TextOutput-2MS4a{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-2MS4aœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "Prompt-amqBu", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-amqBuœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-amqBuœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -67,7 +69,7 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-amqBu", - "name": "Text", + "name": "prompt", "output_types": [ "Prompt" ] @@ -85,7 +87,7 @@ }, "id": "reactflow__edge-Prompt-amqBu{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}-OpenAIModel-uYXZJ{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-uYXZJœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "Prompt-amqBu", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-amqBuœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-amqBuœ, œoutput_typesœ: [œPromptœ], œnameœ: œpromptœ}", "style": { "stroke": "#555" }, @@ -98,7 +100,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-uYXZJ", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -108,7 +110,7 @@ "id": "Prompt-gTNiz", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -117,12 +119,12 @@ }, "id": "reactflow__edge-OpenAIModel-uYXZJ{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}-Prompt-gTNiz{œfieldNameœ:œsummaryœ,œidœ:œPrompt-gTNizœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "OpenAIModel-uYXZJ", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-uYXZJœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-uYXZJœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, "target": "Prompt-gTNiz", - "targetHandle": "{œfieldNameœ: œsummaryœ, œidœ: œPrompt-gTNizœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œsummaryœ, œidœ: œPrompt-gTNizœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -130,7 +132,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-uYXZJ", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -146,7 +148,7 @@ }, "id": "reactflow__edge-OpenAIModel-uYXZJ{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}-ChatOutput-EJkG3{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-EJkG3œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "OpenAIModel-uYXZJ", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-uYXZJœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-uYXZJœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -159,9 +161,9 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-gTNiz", - "name": "Text", + "name": "text", "output_types": [ - "Prompt" + "Text" ] }, "targetHandle": { @@ -176,7 +178,7 @@ }, "id": "reactflow__edge-Prompt-gTNiz{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}-TextOutput-MUDOR{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-MUDORœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "Prompt-gTNiz", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-gTNizœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-gTNizœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -189,7 +191,7 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-gTNiz", - "name": "Text", + "name": "prompt", "output_types": [ "Prompt" ] @@ -207,7 +209,7 @@ }, "id": "reactflow__edge-Prompt-gTNiz{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}-OpenAIModel-XawYB{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-XawYBœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "Prompt-gTNiz", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-gTNizœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-gTNizœ, œoutput_typesœ: [œPromptœ], œnameœ: œpromptœ}", "style": { "stroke": "#555" }, @@ -220,7 +222,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-XawYB", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -236,7 +238,7 @@ }, "id": "reactflow__edge-OpenAIModel-XawYB{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-XawYBœ}-ChatOutput-DNmvg{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-DNmvgœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "OpenAIModel-XawYB", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-XawYBœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-XawYBœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -275,22 +277,33 @@ "is_input": null, "is_output": null, "name": "", - "output_types": [ - "Prompt" - ], + "output_types": [], "outputs": [ { - "display_name": null, - "method": null, - "name": "Prompt", - "selected": null, + "cache": true, + "display_name": "Prompt", + "method": "build_prompt", + "name": "prompt", + "selected": "Prompt", "types": [ "Prompt" - ] + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "format_prompt", + "name": "text", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -307,7 +320,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import CustomComponent\nfrom langflow.field_typing import Input\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n \"code\": Input(advanced=True),\n }\n\n async def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Prompt:\n prompt = await Prompt.from_template_and_variables(template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" + "value": "from langflow.custom import Component\nfrom langflow.field_typing import Input, Output\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n }\n\n inputs = [\n Input(name=\"template\", type=Prompt, display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n Output(display_name=\"Text\", name=\"text\", method=\"format_prompt\"),\n ]\n\n async def format_prompt(self) -> str:\n prompt = await self.build_prompt()\n formatted_text = prompt.format_text()\n self.status = formatted_text\n return formatted_text\n\n async def build_prompt(\n self,\n ) -> Prompt:\n kwargs = {k: v for k, v in self._arguments.items() if k != \"template\"}\n prompt = await Prompt.from_template_and_variables(self.template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" }, "document": { "advanced": false, @@ -319,7 +332,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -406,22 +419,33 @@ "is_input": null, "is_output": null, "name": "", - "output_types": [ - "Prompt" - ], + "output_types": [], "outputs": [ { - "display_name": null, - "method": null, - "name": "Prompt", - "selected": null, + "cache": true, + "display_name": "Prompt", + "method": "build_prompt", + "name": "prompt", + "selected": "Prompt", "types": [ "Prompt" - ] + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "format_prompt", + "name": "text", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -438,7 +462,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import CustomComponent\nfrom langflow.field_typing import Input\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n \"code\": Input(advanced=True),\n }\n\n async def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Prompt:\n prompt = await Prompt.from_template_and_variables(template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" + "value": "from langflow.custom import Component\nfrom langflow.field_typing import Input, Output\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n }\n\n inputs = [\n Input(name=\"template\", type=Prompt, display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n Output(display_name=\"Text\", name=\"text\", method=\"format_prompt\"),\n ]\n\n async def format_prompt(self) -> str:\n prompt = await self.build_prompt()\n formatted_text = prompt.format_text()\n self.status = formatted_text\n return formatted_text\n\n async def build_prompt(\n self,\n ) -> Prompt:\n kwargs = {k: v for k, v in self._arguments.items() if k != \"template\"}\n prompt = await Prompt.from_template_and_variables(self.template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" }, "summary": { "advanced": false, @@ -450,7 +474,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -532,22 +556,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -568,11 +596,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Message\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"message\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n \"template\": self.record_template or \"\",\n }\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Text\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -728,22 +756,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -764,11 +796,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Message\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"message\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n \"template\": self.record_template or \"\",\n }\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Text\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -918,13 +950,15 @@ "output_types": [], "outputs": [ { + "cache": true, "display_name": "Text", "method": "text_response", "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -1162,13 +1196,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -1559,13 +1595,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { diff --git a/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json b/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json index 67af1468b..11a497cf3 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json @@ -17,7 +17,7 @@ "id": "Prompt-xeI6K", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -32,7 +32,7 @@ "stroke": "#555" }, "target": "Prompt-xeI6K", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-xeI6Kœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-xeI6Kœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -41,14 +41,16 @@ "dataType": "ChatInput", "id": "ChatInput-yxMKE", "name": "message", - "output_types": [] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "question", "id": "Prompt-xeI6K", "inputTypes": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -58,12 +60,12 @@ "id": "reactflow__edge-ChatInput-yxMKE{œbaseClassesœ:[œTextœ,œstrœ,œobjectœ,œRecordœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-yxMKEœ}-Prompt-xeI6K{œfieldNameœ:œquestionœ,œidœ:œPrompt-xeI6Kœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", "selected": false, "source": "ChatInput-yxMKE", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-yxMKEœ, œoutput_typesœ: [], œnameœ: œmessageœ}", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-yxMKEœ, œoutput_typesœ: [œMessageœ], œnameœ: œmessageœ}", "style": { "stroke": "#555" }, "target": "Prompt-xeI6K", - "targetHandle": "{œfieldNameœ: œquestionœ, œidœ: œPrompt-xeI6Kœ, œinputTypesœ: [œDocumentœ, œBaseOutputParserœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "targetHandle": "{œfieldNameœ: œquestionœ, œidœ: œPrompt-xeI6Kœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "stroke-gray-900 stroke-connection", @@ -71,7 +73,7 @@ "sourceHandle": { "dataType": "Prompt", "id": "Prompt-xeI6K", - "name": "Text", + "name": "prompt", "output_types": [ "Prompt" ] @@ -90,7 +92,7 @@ "id": "reactflow__edge-Prompt-xeI6K{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-xeI6Kœ}-OpenAIModel-EjXlN{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-EjXlNœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "selected": false, "source": "Prompt-xeI6K", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-xeI6Kœ, œoutput_typesœ: [œPromptœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-xeI6Kœ, œoutput_typesœ: [œPromptœ], œnameœ: œpromptœ}", "style": { "stroke": "#555" }, @@ -103,7 +105,7 @@ "sourceHandle": { "dataType": "OpenAIModel", "id": "OpenAIModel-EjXlN", - "name": "Text", + "name": "text", "output_types": [ "Text" ] @@ -120,7 +122,7 @@ "id": "reactflow__edge-OpenAIModel-EjXlN{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-EjXlNœ}-ChatOutput-Q39I8{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Q39I8œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "selected": false, "source": "OpenAIModel-EjXlN", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-EjXlNœ, œoutput_typesœ: [œTextœ], œnameœ: œTextœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-EjXlNœ, œoutput_typesœ: [œTextœ], œnameœ: œtextœ}", "style": { "stroke": "#555" }, @@ -133,7 +135,7 @@ "sourceHandle": { "dataType": "File", "id": "File-t0a6a", - "name": "Record", + "name": "record", "output_types": [ "Record" ] @@ -151,7 +153,7 @@ "id": "reactflow__edge-File-t0a6a{œbaseClassesœ:[œRecordœ],œdataTypeœ:œFileœ,œidœ:œFile-t0a6aœ}-RecursiveCharacterTextSplitter-tR9QM{œfieldNameœ:œinputsœ,œidœ:œRecursiveCharacterTextSplitter-tR9QMœ,œinputTypesœ:[œDocumentœ,œRecordœ],œtypeœ:œDocumentœ}", "selected": false, "source": "File-t0a6a", - "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-t0a6aœ, œoutput_typesœ: [œRecordœ], œnameœ: œRecordœ}", + "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-t0a6aœ, œoutput_typesœ: [œRecordœ], œnameœ: œrecordœ}", "style": { "stroke": "#555" }, @@ -164,7 +166,7 @@ "sourceHandle": { "dataType": "OpenAIEmbeddings", "id": "OpenAIEmbeddings-ZlOk1", - "name": "Embeddings", + "name": "embeddings", "output_types": [ "Embeddings" ] @@ -178,7 +180,7 @@ }, "id": "reactflow__edge-OpenAIEmbeddings-ZlOk1{œbaseClassesœ:[œEmbeddingsœ],œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-ZlOk1œ}-AstraDBSearch-41nRz{œfieldNameœ:œembeddingœ,œidœ:œAstraDBSearch-41nRzœ,œinputTypesœ:null,œtypeœ:œEmbeddingsœ}", "source": "OpenAIEmbeddings-ZlOk1", - "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-ZlOk1œ, œoutput_typesœ: [œEmbeddingsœ], œnameœ: œEmbeddingsœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-ZlOk1œ, œoutput_typesœ: [œEmbeddingsœ], œnameœ: œembeddingsœ}", "style": { "stroke": "#555" }, @@ -192,7 +194,9 @@ "dataType": "ChatInput", "id": "ChatInput-yxMKE", "name": "message", - "output_types": [] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "input_value", @@ -205,7 +209,7 @@ }, "id": "reactflow__edge-ChatInput-yxMKE{œbaseClassesœ:[œTextœ,œstrœ,œobjectœ,œRecordœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-yxMKEœ}-AstraDBSearch-41nRz{œfieldNameœ:œinput_valueœ,œidœ:œAstraDBSearch-41nRzœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", "source": "ChatInput-yxMKE", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-yxMKEœ, œoutput_typesœ: [], œnameœ: œmessageœ}", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-yxMKEœ, œoutput_typesœ: [œMessageœ], œnameœ: œmessageœ}", "style": { "stroke": "#555" }, @@ -218,7 +222,7 @@ "sourceHandle": { "dataType": "RecursiveCharacterTextSplitter", "id": "RecursiveCharacterTextSplitter-tR9QM", - "name": "Record", + "name": "record", "output_types": [ "Record" ] @@ -233,7 +237,7 @@ "id": "reactflow__edge-RecursiveCharacterTextSplitter-tR9QM{œbaseClassesœ:[œRecordœ],œdataTypeœ:œRecursiveCharacterTextSplitterœ,œidœ:œRecursiveCharacterTextSplitter-tR9QMœ}-AstraDB-eUCSS{œfieldNameœ:œinputsœ,œidœ:œAstraDB-eUCSSœ,œinputTypesœ:null,œtypeœ:œRecordœ}", "selected": false, "source": "RecursiveCharacterTextSplitter-tR9QM", - "sourceHandle": "{œdataTypeœ: œRecursiveCharacterTextSplitterœ, œidœ: œRecursiveCharacterTextSplitter-tR9QMœ, œoutput_typesœ: [œRecordœ], œnameœ: œRecordœ}", + "sourceHandle": "{œdataTypeœ: œRecursiveCharacterTextSplitterœ, œidœ: œRecursiveCharacterTextSplitter-tR9QMœ, œoutput_typesœ: [œRecordœ], œnameœ: œrecordœ}", "style": { "stroke": "#555" }, @@ -246,7 +250,7 @@ "sourceHandle": { "dataType": "OpenAIEmbeddings", "id": "OpenAIEmbeddings-9TPjc", - "name": "Embeddings", + "name": "embeddings", "output_types": [ "Embeddings" ] @@ -261,7 +265,7 @@ "id": "reactflow__edge-OpenAIEmbeddings-9TPjc{œbaseClassesœ:[œEmbeddingsœ],œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-9TPjcœ}-AstraDB-eUCSS{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-eUCSSœ,œinputTypesœ:null,œtypeœ:œEmbeddingsœ}", "selected": false, "source": "OpenAIEmbeddings-9TPjc", - "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-9TPjcœ, œoutput_typesœ: [œEmbeddingsœ], œnameœ: œEmbeddingsœ}", + "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-9TPjcœ, œoutput_typesœ: [œEmbeddingsœ], œnameœ: œembeddingsœ}", "style": { "stroke": "#555" }, @@ -274,7 +278,7 @@ "sourceHandle": { "dataType": "AstraDBSearch", "id": "AstraDBSearch-41nRz", - "name": "Record", + "name": "record", "output_types": [ "Record" ] @@ -291,7 +295,7 @@ }, "id": "reactflow__edge-AstraDBSearch-41nRz{œbaseClassesœ:[œRecordœ],œdataTypeœ:œAstraDBSearchœ,œidœ:œAstraDBSearch-41nRzœ}-TextOutput-BDknO{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-BDknOœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}", "source": "AstraDBSearch-41nRz", - "sourceHandle": "{œdataTypeœ: œAstraDBSearchœ, œidœ: œAstraDBSearch-41nRzœ, œoutput_typesœ: [œRecordœ], œnameœ: œRecordœ}", + "sourceHandle": "{œdataTypeœ: œAstraDBSearchœ, œidœ: œAstraDBSearch-41nRzœ, œoutput_typesœ: [œRecordœ], œnameœ: œrecordœ}", "style": { "stroke": "#555" }, @@ -328,22 +332,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -364,11 +372,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Message\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"text\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n },\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n Input(\n name=\"input_value\",\n type=str,\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n info=\"Message to be passed as input.\",\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"User\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -630,13 +638,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Embeddings", "method": null, - "name": "Embeddings", - "selected": null, + "name": "embeddings", + "selected": "Embeddings", "types": [ "Embeddings" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -1154,13 +1164,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Text", "method": null, - "name": "Text", - "selected": null, + "name": "text", + "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -1431,22 +1443,33 @@ "is_input": null, "is_output": null, "name": "", - "output_types": [ - "Prompt" - ], + "output_types": [], "outputs": [ { - "display_name": null, - "method": null, - "name": "Prompt", - "selected": null, + "cache": true, + "display_name": "Prompt", + "method": "build_prompt", + "name": "prompt", + "selected": "Prompt", "types": [ "Prompt" - ] + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Text", + "method": "format_prompt", + "name": "text", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -1463,7 +1486,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import CustomComponent\nfrom langflow.field_typing import Input\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n \"code\": Input(advanced=True),\n }\n\n async def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Prompt:\n prompt = await Prompt.from_template_and_variables(template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" + "value": "from langflow.custom import Component\nfrom langflow.field_typing import Input, Output\nfrom langflow.field_typing.prompt import Prompt\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": Input(display_name=\"Template\"),\n }\n\n inputs = [\n Input(name=\"template\", type=Prompt, display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n Output(display_name=\"Text\", name=\"text\", method=\"format_prompt\"),\n ]\n\n async def format_prompt(self) -> str:\n prompt = await self.build_prompt()\n formatted_text = prompt.format_text()\n self.status = formatted_text\n return formatted_text\n\n async def build_prompt(\n self,\n ) -> Prompt:\n kwargs = {k: v for k, v in self._arguments.items() if k != \"template\"}\n prompt = await Prompt.from_template_and_variables(self.template, kwargs)\n self.status = prompt.format_text()\n return prompt\n" }, "context": { "advanced": false, @@ -1475,7 +1498,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -1501,7 +1524,7 @@ "info": "", "input_types": [ "Document", - "BaseOutputParser", + "Message", "Record", "Text" ], @@ -1587,22 +1610,26 @@ "output_types": [], "outputs": [ { - "display_name": "Message", + "cache": true, + "display_name": "Text", "method": "text_response", - "name": "message", + "name": "text", "selected": "Text", "types": [ "Text" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": "Record", - "method": "record_response", - "name": "record", - "selected": "Record", + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", "types": [ - "Record" - ] + "Message" + ], + "value": "__UNDEFINED__" } ], "template": { @@ -1623,11 +1650,11 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Message\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"text_response\"),\n Output(display_name=\"Record\", name=\"record\", method=\"record_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Record, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def record_response(self) -> Record:\n record = Record(\n data={\n \"message\": self.input_value,\n \"sender\": self.sender,\n \"sender_name\": self.sender_name,\n \"session_id\": self.session_id,\n \"template\": self.record_template or \"\",\n }\n )\n if self.session_id and isinstance(record, (Record, str)):\n self.store_message(record, self.session_id, self.sender, self.sender_name)\n return record\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema.message import Message\nfrom langflow.template import Input, Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n Input(\n name=\"input_value\", type=str, display_name=\"Text\", multiline=True, info=\"Message to be passed as output.\"\n ),\n Input(\n name=\"sender\",\n type=str,\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n Input(name=\"sender_name\", type=str, display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\"),\n Input(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n Input(\n name=\"record_template\",\n type=str,\n display_name=\"Record Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def text_response(self) -> Text:\n result = self.input_value\n if self.session_id and isinstance(result, (Message, str)):\n self.store_message(result, self.session_id, self.sender, self.sender_name)\n return result\n\n def message_response(self) -> Message:\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 )\n if self.session_id and isinstance(message, (Message, str)):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, - "display_name": "Message", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", @@ -1782,13 +1809,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Record", "method": null, - "name": "Record", - "selected": null, + "name": "record", + "selected": "Record", "types": [ "Record" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -1912,13 +1941,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Record", "method": null, - "name": "Record", - "selected": null, + "name": "record", + "selected": "Record", "types": [ "Record" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -2090,13 +2121,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Record", "method": null, - "name": "Record", - "selected": null, + "name": "record", + "selected": "Record", "types": [ "Record" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -2553,22 +2586,26 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "VectorStore", "method": null, - "name": "VectorStore", - "selected": null, + "name": "vectorstore", + "selected": "VectorStore", "types": [ "VectorStore" - ] + ], + "value": "__UNDEFINED__" }, { - "display_name": null, + "cache": true, + "display_name": "BaseRetriever", "method": null, - "name": "BaseRetriever", - "selected": null, + "name": "baseretriever", + "selected": "BaseRetriever", "types": [ "BaseRetriever" - ] + ], + "value": "__UNDEFINED__" } ], "template": { @@ -2683,7 +2720,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import List, Optional, Union\n\nfrom langchain_astradb import AstraDBVectorStore\nfrom langchain_astradb.utils.astradb import SetupMode\nfrom langchain_core.retrievers import BaseRetriever\n\nfrom langflow.custom import CustomComponent\nfrom langflow.field_typing import Embeddings, VectorStore\nfrom langflow.schema import Record\n\n\nclass AstraDBVectorStoreComponent(CustomComponent):\n display_name = \"Astra DB\"\n description = \"Builds or loads an Astra DB Vector Store.\"\n icon = \"AstraDB\"\n field_order = [\"token\", \"api_endpoint\", \"collection_name\", \"inputs\", \"embedding\"]\n\n def build_config(self):\n return {\n \"inputs\": {\n \"display_name\": \"Inputs\",\n \"info\": \"Optional list of records to be processed and stored in the vector store.\",\n },\n \"embedding\": {\"display_name\": \"Embedding\", \"info\": \"Embedding to use\"},\n \"collection_name\": {\n \"display_name\": \"Collection Name\",\n \"info\": \"The name of the collection within Astra DB where the vectors will be stored.\",\n },\n \"token\": {\n \"display_name\": \"Token\",\n \"info\": \"Authentication token for accessing Astra DB.\",\n \"password\": True,\n },\n \"api_endpoint\": {\n \"display_name\": \"API Endpoint\",\n \"info\": \"API endpoint URL for the Astra DB service.\",\n },\n \"namespace\": {\n \"display_name\": \"Namespace\",\n \"info\": \"Optional namespace within Astra DB to use for the collection.\",\n \"advanced\": True,\n },\n \"metric\": {\n \"display_name\": \"Metric\",\n \"info\": \"Optional distance metric for vector comparisons in the vector store.\",\n \"advanced\": True,\n },\n \"batch_size\": {\n \"display_name\": \"Batch Size\",\n \"info\": \"Optional number of records to process in a single batch.\",\n \"advanced\": True,\n },\n \"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 \"bulk_insert_overwrite_concurrency\": {\n \"display_name\": \"Bulk Insert Overwrite Concurrency\",\n \"info\": \"Optional concurrency level for bulk insert operations that overwrite existing records.\",\n \"advanced\": True,\n },\n \"bulk_delete_concurrency\": {\n \"display_name\": \"Bulk Delete Concurrency\",\n \"info\": \"Optional concurrency level for bulk delete operations.\",\n \"advanced\": True,\n },\n \"setup_mode\": {\n \"display_name\": \"Setup Mode\",\n \"info\": \"Configuration mode for setting up the vector store, with options like “Sync”, “Async”, or “Off”.\",\n \"options\": [\"Sync\", \"Async\", \"Off\"],\n \"advanced\": True,\n },\n \"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 \"metadata_indexing_include\": {\n \"display_name\": \"Metadata Indexing Include\",\n \"info\": \"Optional list of metadata fields to include in the indexing.\",\n \"advanced\": True,\n },\n \"metadata_indexing_exclude\": {\n \"display_name\": \"Metadata Indexing Exclude\",\n \"info\": \"Optional list of metadata fields to exclude from the indexing.\",\n \"advanced\": True,\n },\n \"collection_indexing_policy\": {\n \"display_name\": \"Collection Indexing Policy\",\n \"info\": \"Optional dictionary defining the indexing policy for the collection.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n embedding: Embeddings,\n token: str,\n api_endpoint: str,\n collection_name: str,\n inputs: Optional[List[Record]] = None,\n namespace: Optional[str] = None,\n metric: Optional[str] = None,\n batch_size: Optional[int] = None,\n bulk_insert_batch_concurrency: Optional[int] = None,\n bulk_insert_overwrite_concurrency: Optional[int] = None,\n bulk_delete_concurrency: Optional[int] = None,\n setup_mode: str = \"Sync\",\n pre_delete_collection: bool = False,\n metadata_indexing_include: Optional[List[str]] = None,\n metadata_indexing_exclude: Optional[List[str]] = None,\n collection_indexing_policy: Optional[dict] = None,\n ) -> Union[VectorStore, BaseRetriever]:\n try:\n setup_mode_value = SetupMode[setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {setup_mode}\")\n if inputs:\n documents = [_input.to_lc_document() for _input in inputs]\n\n vector_store = AstraDBVectorStore.from_documents(\n documents=documents,\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n else:\n vector_store = AstraDBVectorStore(\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n\n return vector_store\n return vector_store\n" + "value": "from typing import List, Optional, Union\n\nfrom langchain_core.retrievers import BaseRetriever\n\nfrom langflow.custom import CustomComponent\nfrom langflow.field_typing import Embeddings, VectorStore\nfrom langflow.schema import Record\n\n\nclass AstraDBVectorStoreComponent(CustomComponent):\n display_name = \"Astra DB\"\n description = \"Builds or loads an Astra DB Vector Store.\"\n icon = \"AstraDB\"\n field_order = [\"token\", \"api_endpoint\", \"collection_name\", \"inputs\", \"embedding\"]\n\n def build_config(self):\n return {\n \"inputs\": {\n \"display_name\": \"Inputs\",\n \"info\": \"Optional list of records to be processed and stored in the vector store.\",\n },\n \"embedding\": {\"display_name\": \"Embedding\", \"info\": \"Embedding to use\"},\n \"collection_name\": {\n \"display_name\": \"Collection Name\",\n \"info\": \"The name of the collection within Astra DB where the vectors will be stored.\",\n },\n \"token\": {\n \"display_name\": \"Token\",\n \"info\": \"Authentication token for accessing Astra DB.\",\n \"password\": True,\n },\n \"api_endpoint\": {\n \"display_name\": \"API Endpoint\",\n \"info\": \"API endpoint URL for the Astra DB service.\",\n },\n \"namespace\": {\n \"display_name\": \"Namespace\",\n \"info\": \"Optional namespace within Astra DB to use for the collection.\",\n \"advanced\": True,\n },\n \"metric\": {\n \"display_name\": \"Metric\",\n \"info\": \"Optional distance metric for vector comparisons in the vector store.\",\n \"advanced\": True,\n },\n \"batch_size\": {\n \"display_name\": \"Batch Size\",\n \"info\": \"Optional number of records to process in a single batch.\",\n \"advanced\": True,\n },\n \"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 \"bulk_insert_overwrite_concurrency\": {\n \"display_name\": \"Bulk Insert Overwrite Concurrency\",\n \"info\": \"Optional concurrency level for bulk insert operations that overwrite existing records.\",\n \"advanced\": True,\n },\n \"bulk_delete_concurrency\": {\n \"display_name\": \"Bulk Delete Concurrency\",\n \"info\": \"Optional concurrency level for bulk delete operations.\",\n \"advanced\": True,\n },\n \"setup_mode\": {\n \"display_name\": \"Setup Mode\",\n \"info\": \"Configuration mode for setting up the vector store, with options like “Sync”, “Async”, or “Off”.\",\n \"options\": [\"Sync\", \"Async\", \"Off\"],\n \"advanced\": True,\n },\n \"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 \"metadata_indexing_include\": {\n \"display_name\": \"Metadata Indexing Include\",\n \"info\": \"Optional list of metadata fields to include in the indexing.\",\n \"advanced\": True,\n },\n \"metadata_indexing_exclude\": {\n \"display_name\": \"Metadata Indexing Exclude\",\n \"info\": \"Optional list of metadata fields to exclude from the indexing.\",\n \"advanced\": True,\n },\n \"collection_indexing_policy\": {\n \"display_name\": \"Collection Indexing Policy\",\n \"info\": \"Optional dictionary defining the indexing policy for the collection.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n embedding: Embeddings,\n token: str,\n api_endpoint: str,\n collection_name: str,\n inputs: Optional[List[Record]] = None,\n namespace: Optional[str] = None,\n metric: Optional[str] = None,\n batch_size: Optional[int] = None,\n bulk_insert_batch_concurrency: Optional[int] = None,\n bulk_insert_overwrite_concurrency: Optional[int] = None,\n bulk_delete_concurrency: Optional[int] = None,\n setup_mode: str = \"Sync\",\n pre_delete_collection: bool = False,\n metadata_indexing_include: Optional[List[str]] = None,\n metadata_indexing_exclude: Optional[List[str]] = None,\n collection_indexing_policy: Optional[dict] = None,\n ) -> Union[VectorStore, BaseRetriever]:\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError:\n raise ImportError(\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n\n try:\n setup_mode_value = SetupMode[setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {setup_mode}\")\n if inputs:\n documents = [_input.to_lc_document() for _input in inputs]\n\n vector_store = AstraDBVectorStore.from_documents(\n documents=documents,\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n else:\n vector_store = AstraDBVectorStore(\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n\n return vector_store\n return vector_store\n" }, "collection_indexing_policy": { "advanced": true, @@ -2975,13 +3012,15 @@ ], "outputs": [ { - "display_name": null, + "cache": true, + "display_name": "Embeddings", "method": null, - "name": "Embeddings", - "selected": null, + "name": "embeddings", + "selected": "Embeddings", "types": [ "Embeddings" - ] + ], + "value": "__UNDEFINED__" } ], "template": { diff --git a/src/frontend/src/CustomNodes/GenericNode/components/outputModal/components/switchOutputView/index.tsx b/src/frontend/src/CustomNodes/GenericNode/components/outputModal/components/switchOutputView/index.tsx index 468f573a0..6c22e3ffa 100644 --- a/src/frontend/src/CustomNodes/GenericNode/components/outputModal/components/switchOutputView/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/components/outputModal/components/switchOutputView/index.tsx @@ -25,7 +25,7 @@ export default function SwitchOutputView(nodeId): JSX.Element { const resultType = results?.type; let resultMessage = results?.message; const RECORD_TYPES = ["record", "object", "array", "message"]; - if (resultMessage.raw) { + if (resultMessage?.raw) { resultMessage = resultMessage.raw; } return (