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 5dc959f51..6814f9c30 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 @@ -8,12 +8,17 @@ "dataType": "OpenAIModel", "id": "OpenAIModel-k39HS", "name": "text_output", - "output_types": ["Text"] + "output_types": [ + "Text" + ] }, "targetHandle": { "fieldName": "input_value", "id": "ChatOutput-njtka", - "inputTypes": ["Text", "Message"], + "inputTypes": [ + "Text", + "Message" + ], "type": "str" } }, @@ -33,12 +38,18 @@ "dataType": "Prompt", "id": "Prompt-uxBqP", "name": "prompt", - "output_types": ["Prompt"] + "output_types": [ + "Prompt" + ] }, "targetHandle": { "fieldName": "input_value", "id": "OpenAIModel-k39HS", - "inputTypes": ["Text", "Data", "Prompt"], + "inputTypes": [ + "Text", + "Data", + "Prompt" + ], "type": "str" } }, @@ -58,12 +69,19 @@ "dataType": "ChatInput", "id": "ChatInput-P3fgL", "name": "message", - "output_types": ["Message"] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "user_input", "id": "Prompt-uxBqP", - "inputTypes": ["Document", "Message", "Record", "Text"], + "inputTypes": [ + "Document", + "Message", + "Record", + "Text" + ], "type": "str" } }, @@ -84,10 +102,16 @@ "display_name": "Prompt", "id": "Prompt-uxBqP", "node": { - "base_classes": ["object", "str", "Text"], + "base_classes": [ + "object", + "str", + "Text" + ], "beta": false, "custom_fields": { - "template": ["user_input"] + "template": [ + "user_input" + ] }, "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", @@ -110,7 +134,9 @@ "method": "build_prompt", "name": "prompt", "selected": "Prompt", - "types": ["Prompt"], + "types": [ + "Prompt" + ], "value": "__UNDEFINED__" }, { @@ -119,7 +145,9 @@ "method": "format_prompt", "name": "text", "selected": "Text", - "types": ["Text"], + "types": [ + "Text" + ], "value": "__UNDEFINED__" } ], @@ -150,7 +178,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -171,7 +201,12 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Document", "Message", "Record", "Text"], + "input_types": [ + "Document", + "Message", + "Record", + "Text" + ], "list": false, "load_from_db": false, "multiline": true, @@ -209,7 +244,11 @@ "display_name": "OpenAI", "id": "OpenAIModel-k39HS", "node": { - "base_classes": ["object", "Text", "str"], + "base_classes": [ + "object", + "Text", + "str" + ], "beta": false, "custom_fields": { "input_value": null, @@ -247,7 +286,9 @@ "method": "text_response", "name": "text_output", "selected": "Text", - "types": ["Text"], + "types": [ + "Text" + ], "value": "__UNDEFINED__" }, { @@ -256,7 +297,9 @@ "method": "build_model", "name": "model_output", "selected": "BaseLanguageModel", - "types": ["BaseLanguageModel"], + "types": [ + "BaseLanguageModel" + ], "value": "__UNDEFINED__" } ], @@ -278,7 +321,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n return output\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n" }, "input_value": { "advanced": false, @@ -287,7 +330,11 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text", "Data", "Prompt"], + "input_types": [ + "Text", + "Data", + "Prompt" + ], "list": false, "load_from_db": false, "multiline": false, @@ -307,7 +354,9 @@ "fileTypes": [], "file_path": "", "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -327,7 +376,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -347,7 +398,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": true, "load_from_db": false, "multiline": false, @@ -365,7 +418,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "gpt-4o" }, "openai_api_base": { "advanced": true, @@ -374,7 +427,9 @@ "fileTypes": [], "file_path": "", "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -394,9 +449,11 @@ "fileTypes": [], "file_path": "", "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, - "load_from_db": false, + "load_from_db": true, "multiline": false, "name": "openai_api_key", "password": true, @@ -405,7 +462,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "OPENAI_API_KEY" }, "stream": { "advanced": true, @@ -414,7 +471,9 @@ "fileTypes": [], "file_path": "", "info": "Stream the response from the model. Streaming works only in Chat.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -425,7 +484,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": false }, "system_message": { "advanced": true, @@ -434,7 +493,9 @@ "fileTypes": [], "file_path": "", "info": "System message to pass to the model.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -454,7 +515,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -465,7 +528,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": 0.1 } } }, @@ -490,7 +553,12 @@ "data": { "id": "ChatOutput-njtka", "node": { - "base_classes": ["Record", "Text", "str", "object"], + "base_classes": [ + "Record", + "Text", + "str", + "object" + ], "beta": false, "custom_fields": { "input_value": null, @@ -509,22 +577,15 @@ "icon": "ChatOutput", "output_types": [], "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Text", - "types": ["Text"], - "value": "__UNDEFINED__" - }, { "cache": true, "display_name": "Message", "method": "message_response", "name": "message", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" } ], @@ -546,7 +607,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\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:\n self.message_response()\n self.status = result\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) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -555,7 +616,10 @@ "fileTypes": [], "file_path": "", "info": "Message to be passed as output.", - "input_types": ["Text", "Message"], + "input_types": [ + "Text", + "Message" + ], "list": false, "load_from_db": false, "multiline": true, @@ -575,12 +639,17 @@ "fileTypes": [], "file_path": "", "info": "Type of sender.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": true, "load_from_db": false, "multiline": false, "name": "sender", - "options": ["Machine", "User"], + "options": [ + "Machine", + "User" + ], "password": false, "placeholder": "", "required": false, @@ -596,7 +665,9 @@ "fileTypes": [], "file_path": "", "info": "Name of the sender.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -616,7 +687,9 @@ "fileTypes": [], "file_path": "", "info": "Session ID for the message.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -652,7 +725,12 @@ "data": { "id": "ChatInput-P3fgL", "node": { - "base_classes": ["object", "Record", "str", "Text"], + "base_classes": [ + "object", + "Record", + "str", + "Text" + ], "beta": false, "custom_fields": { "input_value": null, @@ -676,7 +754,9 @@ "method": "message_response", "name": "message", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" } ], @@ -698,7 +778,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -718,7 +798,7 @@ "show": true, "title_case": false, "type": "str", - "value": "Hello, world!" + "value": "" }, "sender": { "advanced": true, @@ -727,12 +807,17 @@ "fileTypes": [], "file_path": "", "info": "Type of sender.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": true, "load_from_db": false, "multiline": false, "name": "sender", - "options": ["Machine", "User"], + "options": [ + "Machine", + "User" + ], "password": false, "placeholder": "", "required": false, @@ -748,7 +833,9 @@ "fileTypes": [], "file_path": "", "info": "Name of the sender.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -768,7 +855,9 @@ "fileTypes": [], "file_path": "", "info": "Session ID for the message.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -812,4 +901,4 @@ "is_component": false, "last_tested_version": "1.0.0a4", "name": "Basic Prompting (Hello, World)" -} +} \ No newline at end of file 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 36a76085c..7e92c3d0b 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 @@ -372,15 +372,12 @@ "field_order": [], "frozen": false, "icon": "layout-template", - "output_types": [ - "Data" - ], + "output_types": [], "outputs": [ { "cache": true, "display_name": "Data", - "hidden": null, - "method": null, + "method": "fetch_content", "name": "data", "selected": "Data", "types": [ @@ -390,7 +387,7 @@ } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -407,31 +404,22 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any, Dict\n\nfrom langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import CustomComponent\nfrom langflow.schema import Data\n\n\nclass URLComponent(CustomComponent):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n def build_config(self) -> Dict[str, Any]:\n return {\n \"urls\": {\"display_name\": \"URL\"},\n }\n\n def build(\n self,\n urls: list[str],\n ) -> list[Data]:\n loader = WebBaseLoader(web_paths=[url for url in urls if url])\n docs = loader.load()\n data = self.to_data(docs)\n self.status = data\n return data\n" + "value": "from langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.inputs import StrInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n StrInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n value=\"\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def fetch_content(self) -> Data:\n urls = [url.strip() for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls)\n docs = loader.load()\n data = [Data(content=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n" }, "urls": { "advanced": false, - "display_name": "URL", + "display_name": "URLs", "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], + "info": "Enter one or more URLs, separated by commas.", "list": true, "load_from_db": false, - "multiline": false, "name": "urls", - "password": false, "placeholder": "", - "required": true, + "required": false, "show": true, "title_case": false, "type": "str", - "value": [ - "https://www.promptingguide.ai/techniques/prompt_chaining" - ] + "value": "" } } }, @@ -480,17 +468,6 @@ "icon": "ChatOutput", "output_types": [], "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Text", - "types": [ - "Text" - ], - "value": "__UNDEFINED__" - }, { "cache": true, "display_name": "Message", @@ -521,7 +498,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\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:\n self.message_response()\n self.status = result\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) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -570,7 +547,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "Machine" }, "sender_name": { "advanced": true, @@ -592,7 +569,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "AI" }, "session_id": { "advanced": true, @@ -711,7 +688,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n return output\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n" }, "input_value": { "advanced": false, @@ -808,7 +785,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "gpt-4o" }, "openai_api_base": { "advanced": true, @@ -843,7 +820,7 @@ "Text" ], "list": false, - "load_from_db": false, + "load_from_db": true, "multiline": false, "name": "openai_api_key", "password": true, @@ -852,7 +829,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "OPENAI_API_KEY" }, "stream": { "advanced": true, @@ -874,7 +851,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": false }, "system_message": { "advanced": true, @@ -918,7 +895,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": 0.1 } } }, @@ -957,15 +934,12 @@ "field_order": [], "frozen": false, "icon": "layout-template", - "output_types": [ - "Data" - ], + "output_types": [], "outputs": [ { "cache": true, "display_name": "Data", - "hidden": null, - "method": null, + "method": "fetch_content", "name": "data", "selected": "Data", "types": [ @@ -975,7 +949,7 @@ } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -992,31 +966,22 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any, Dict\n\nfrom langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import CustomComponent\nfrom langflow.schema import Data\n\n\nclass URLComponent(CustomComponent):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n def build_config(self) -> Dict[str, Any]:\n return {\n \"urls\": {\"display_name\": \"URL\"},\n }\n\n def build(\n self,\n urls: list[str],\n ) -> list[Data]:\n loader = WebBaseLoader(web_paths=[url for url in urls if url])\n docs = loader.load()\n data = self.to_data(docs)\n self.status = data\n return data\n" + "value": "from langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.inputs import StrInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n StrInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n value=\"\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def fetch_content(self) -> Data:\n urls = [url.strip() for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls)\n docs = loader.load()\n data = [Data(content=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n" }, "urls": { "advanced": false, - "display_name": "URL", + "display_name": "URLs", "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], + "info": "Enter one or more URLs, separated by commas.", "list": true, "load_from_db": false, - "multiline": false, "name": "urls", - "password": false, "placeholder": "", - "required": true, + "required": false, "show": true, "title_case": false, "type": "str", - "value": [ - "https://www.promptingguide.ai/introduction/basics" - ] + "value": "" } } }, 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 09fc19060..da9e2031d 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 @@ -1,999 +1,995 @@ { - "id": "cd558bbb-10b7-4c22-a7ad-3739f26b4bd7", - "data": { - "nodes": [ - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-9DNZG", - "node": { - "template": { - "Document": { - "field_type": "str", - "required": false, - "placeholder": "", - "list": false, - "show": true, - "multiline": true, - "value": "", - "fileTypes": [], - "file_path": "", - "password": false, - "name": "Document", - "display_name": "Document", - "advanced": false, - "input_types": [ - "Document", - "Message", - "Data", - "Text" - ], - "dynamic": false, - "info": "", - "load_from_db": false, - "title_case": false, - "type": "str" - }, - "Question": { - "field_type": "str", - "required": false, - "placeholder": "", - "list": false, - "show": true, - "multiline": true, - "value": "", - "fileTypes": [], - "file_path": "", - "password": false, - "name": "Question", - "display_name": "Question", - "advanced": false, - "input_types": [ - "Document", - "Message", - "Data", - "Text" - ], - "dynamic": false, - "info": "", - "load_from_db": false, - "title_case": false, - "type": "str" - }, - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.field_typing.prompt import Prompt\nfrom langflow.inputs import PromptInput\nfrom langflow.template import Output\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 inputs = [\n PromptInput(name=\"template\", 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, - "display_name": "Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "prompt", - "value": "Answer user's questions based on the document below:\n\n---\n\n{Document}\n\n---\n\nQuestion:\n{Question}\n\nAnswer:\n" - } - }, - "description": "Create a prompt template with dynamic variables.", - "icon": "prompts", - "is_input": null, - "is_output": null, - "is_composition": null, - "base_classes": [ - "object", - "str", - "Text" - ], - "name": "", - "display_name": "Prompt", - "documentation": "", - "custom_fields": { - "template": [ - "Document", - "Question" - ] - }, - "output_types": [], - "full_path": null, - "pinned": false, - "conditional_paths": [], - "frozen": false, - "outputs": [ - { - "types": [ - "Prompt" - ], - "selected": "Prompt", - "name": "prompt", - "hidden": false, - "display_name": "Prompt", - "method": "build_prompt", - "value": "__UNDEFINED__", - "cache": true - }, - { - "types": [ - "Text" - ], - "selected": "Text", - "name": "text", - "hidden": null, - "display_name": "Text", - "method": "format_prompt", - "value": "__UNDEFINED__", - "cache": true - } - ], - "field_order": [], - "beta": false, - "error": null - }, - "type": "Prompt" - }, - "dragging": false, - "height": 573, - "id": "Prompt-9DNZG", - "position": { - "x": 585.7906101139403, - "y": 117.52115876762832 - }, - "positionAbsolute": { - "x": 585.7906101139403, - "y": 117.52115876762832 - }, - "selected": false, - "type": "genericNode", - "width": 384 + "data": { + "edges": [ + { + "data": { + "sourceHandle": { + "dataType": "File", + "id": "File-BzIs2", + "name": "data", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "Document", + "id": "Prompt-9DNZG", + "inputTypes": [ + "Document", + "Message", + "Data", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-File-BzIs2{œdataTypeœ:œFileœ,œidœ:œFile-BzIs2œ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-Prompt-9DNZG{œfieldNameœ:œDocumentœ,œidœ:œPrompt-9DNZGœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}", + "source": "File-BzIs2", + "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-BzIs2œ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "Prompt-9DNZG", + "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-9DNZGœ, œinputTypesœ: [œDocumentœ, œMessageœ, œDataœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-27Usy", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "Question", + "id": "Prompt-9DNZG", + "inputTypes": [ + "Document", + "Message", + "Data", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-27Usy{œdataTypeœ:œChatInputœ,œidœ:œChatInput-27Usyœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-9DNZG{œfieldNameœ:œQuestionœ,œidœ:œPrompt-9DNZGœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-27Usy", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-27Usyœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-9DNZG", + "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-9DNZGœ, œinputTypesœ: [œDocumentœ, œMessageœ, œDataœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-9DNZG", + "name": "prompt", + "output_types": [ + "Prompt" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-8b6nG", + "inputTypes": [ + "Text", + "Data", + "Prompt" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-9DNZG{œdataTypeœ:œPromptœ,œidœ:œPrompt-9DNZGœ,œnameœ:œpromptœ,œoutput_typesœ:[œPromptœ]}-OpenAIModel-8b6nG{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-8b6nGœ,œinputTypesœ:[œTextœ,œDataœ,œPromptœ],œtypeœ:œstrœ}", + "source": "Prompt-9DNZG", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-9DNZGœ, œnameœ: œpromptœ, œoutput_typesœ: [œPromptœ]}", + "target": "OpenAIModel-8b6nG", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-8b6nGœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}" + }, + { + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-8b6nG", + "name": "text_output", + "output_types": [ + "Text" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-y4SCS", + "inputTypes": [ + "Text", + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-8b6nG{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-8b6nGœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œTextœ]}-ChatOutput-y4SCS{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-y4SCSœ,œinputTypesœ:[œTextœ,œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-8b6nG", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-8b6nGœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œTextœ]}", + "target": "ChatOutput-y4SCS", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-y4SCSœ, œinputTypesœ: [œTextœ, œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-9DNZG", + "node": { + "base_classes": [ + "object", + "str", + "Text" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "Document", + "Question" + ] }, - { - "data": { - "id": "ChatInput-27Usy", - "node": { - "base_classes": [ - "str", - "Record", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "ChatInput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__", - "hidden": false - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Message to be passed as input.", - "input_types": [], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "yo yo" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "sender", - "options": [ - "Machine", - "User" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Name of the sender.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "sender_name", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Session ID for the message.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "session_id", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "ChatInput" - }, - "dragging": false, - "height": 301, - "id": "ChatInput-27Usy", - "position": { - "x": -38.501719080514135, - "y": 379.81180230285355 - }, - "positionAbsolute": { - "x": -38.501719080514135, - "y": 379.81180230285355 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ChatOutput-y4SCS", - "node": { - "base_classes": [ - "str", - "Record", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Message to be passed as output.", - "input_types": [ - "Text", - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "sender", - "options": [ - "Machine", - "User" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Name of the sender.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "sender_name", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Session ID for the message.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "session_id", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 309, - "id": "ChatOutput-y4SCS", - "position": { - "x": 1733.3012915204283, - "y": 168.76098809939327 - }, - "positionAbsolute": { - "x": 1733.3012915204283, - "y": 168.76098809939327 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "id": "File-BzIs2", - "type": "genericNode", - "position": { - "x": -44.56084223565597, - "y": 39.0475820447775 - }, - "data": { - "type": "File", - "node": { - "template": { - "_type": "Component", - "path": { - "file_path": "cd558bbb-10b7-4c22-a7ad-3739f26b4bd7/Climate Prediction Updated.json", - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx" - ], - "list": false, - "required": false, - "placeholder": "", - "show": true, - "name": "path", - "display_name": "Path", - "advanced": false, - "dynamic": false, - "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", - "title_case": false, - "type": "file", - "value": "" - }, - "code": { - "type": "code", - "required": true, - "placeholder": "", - "list": false, - "show": true, - "multiline": true, - "value": "from pathlib import Path\nfrom langflow.custom import Component\nfrom langflow.inputs import FileInput, BoolInput\nfrom langflow.template import Output\nfrom langflow.schema import Data\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(Path(self.path))\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n", - "fileTypes": [], - "file_path": "", - "password": false, - "name": "code", - "advanced": true, - "dynamic": true, - "info": "", - "load_from_db": false, - "title_case": false - }, - "silent_errors": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": false, - "name": "silent_errors", - "display_name": "Silent Errors", - "advanced": true, - "dynamic": false, - "info": "If true, errors will not raise an exception.", - "title_case": false, - "type": "bool" - } - }, - "description": "A generic file loader.", - "icon": "file-text", - "base_classes": [ - "Data" - ], - "display_name": "File", - "documentation": "", - "custom_fields": {}, - "output_types": [], - "pinned": false, - "conditional_paths": [], - "frozen": false, - "outputs": [ - { - "types": [ - "Data" - ], - "selected": "Data", - "name": "data", - "display_name": "Data", - "method": "load_file", - "value": "__UNDEFINED__", - "cache": true - } - ], - "field_order": [ - "path", - "silent_errors" - ], - "beta": false, - "edited": true - }, - "id": "File-BzIs2", - "description": "A generic file loader.", - "display_name": "File" - }, - "selected": true, - "width": 384, - "height": 301, - "positionAbsolute": { - "x": -44.56084223565597, - "y": 39.0475820447775 - }, - "dragging": false - }, - { - "id": "OpenAIModel-8b6nG", - "type": "genericNode", - "position": { - "x": 1141.7303854551026, - "y": -51.19892217231286 - }, - "data": { - "type": "OpenAIModel", - "node": { - "template": { - "_type": "Component", - "code": { - "type": "code", - "required": true, - "placeholder": "", - "list": false, - "show": true, - "multiline": true, - "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n return output\n", - "fileTypes": [], - "file_path": "", - "password": false, - "name": "code", - "advanced": true, - "dynamic": true, - "info": "", - "load_from_db": false, - "title_case": false - }, - "input_value": { - "load_from_db": false, - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "input_value", - "display_name": "Input", - "advanced": false, - "input_types": [ - "Text", - "Data", - "Prompt" - ], - "dynamic": false, - "info": "", - "title_case": false, - "type": "str" - }, - "max_tokens": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "name": "max_tokens", - "display_name": "Max Tokens", - "advanced": true, - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "title_case": false, - "type": "int" - }, - "model_kwargs": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "name": "model_kwargs", - "display_name": "Model Kwargs", - "advanced": true, - "dynamic": false, - "info": "", - "title_case": false, - "type": "dict" - }, - "model_name": { - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "required": false, - "placeholder": "", - "show": true, - "value": "gpt-4o", - "name": "model_name", - "display_name": "Model Name", - "advanced": false, - "dynamic": false, - "info": "", - "title_case": false, - "type": "str" - }, - "openai_api_base": { - "load_from_db": false, - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "openai_api_base", - "display_name": "OpenAI API Base", - "advanced": true, - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.", - "title_case": false, - "type": "str" - }, - "openai_api_key": { - "load_from_db": true, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "openai_api_key", - "display_name": "OpenAI API Key", - "advanced": false, - "input_types": [ - "Text" - ], - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "title_case": false, - "password": true, - "type": "str" - }, - "stream": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": false, - "name": "stream", - "display_name": "Stream", - "advanced": true, - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "title_case": false, - "type": "bool" - }, - "system_message": { - "load_from_db": false, - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "system_message", - "display_name": "System Message", - "advanced": true, - "dynamic": false, - "info": "System message to pass to the model.", - "title_case": false, - "type": "str" - }, - "temperature": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": 0.1, - "name": "temperature", - "display_name": "Temperature", - "advanced": false, - "dynamic": false, - "info": "", - "title_case": false, - "type": "float" - } - }, - "description": "Generates text using OpenAI LLMs.", - "icon": "OpenAI", - "base_classes": [ - "BaseLanguageModel", - "Text" - ], - "display_name": "OpenAI", - "documentation": "", - "custom_fields": {}, - "output_types": [], - "pinned": false, - "conditional_paths": [], - "frozen": false, - "outputs": [ - { - "types": [ - "Text" - ], - "selected": "Text", - "name": "text_output", - "display_name": "Text", - "method": "text_response", - "value": "__UNDEFINED__", - "cache": true, - "hidden": false - }, - { - "types": [ - "BaseLanguageModel" - ], - "selected": "BaseLanguageModel", - "name": "model_output", - "display_name": "Language Model", - "method": "build_model", - "value": "__UNDEFINED__", - "cache": true - } - ], - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message" - ], - "beta": false - }, - "id": "OpenAIModel-8b6nG" - }, - "selected": false, - "width": 384, - "height": 623, - "positionAbsolute": { - "x": 1141.7303854551026, - "y": -51.19892217231286 - }, - "dragging": false + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "error": null, + "field_order": [], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "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__" + } + ], + "pinned": false, + "template": { + "Document": { + "advanced": false, + "display_name": "Document", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Document", + "Message", + "Data", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "Document", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "Question": { + "advanced": false, + "display_name": "Question", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Document", + "Message", + "Data", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "Question", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.field_typing.prompt import Prompt\nfrom langflow.inputs import PromptInput\nfrom langflow.template import Output\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 inputs = [\n PromptInput(name=\"template\", 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, + "display_name": "Template", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": false, + "name": "template", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "prompt", + "value": "Answer user's questions based on the document below:\n\n---\n\n{Document}\n\n---\n\nQuestion:\n{Question}\n\nAnswer:\n" + } } - ], - "edges": [ - { - "source": "File-BzIs2", - "sourceHandle": "{œdataTypeœ:œFileœ,œidœ:œFile-BzIs2œ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}", - "target": "Prompt-9DNZG", - "targetHandle": "{œfieldNameœ:œDocumentœ,œidœ:œPrompt-9DNZGœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}", - "data": { - "targetHandle": { - "fieldName": "Document", - "id": "Prompt-9DNZG", - "inputTypes": [ - "Document", - "Message", - "Data", - "Text" - ], - "type": "str" - }, - "sourceHandle": { - "dataType": "File", - "id": "File-BzIs2", - "name": "data", - "output_types": [ - "Data" - ] - } - }, - "id": "reactflow__edge-File-BzIs2{œdataTypeœ:œFileœ,œidœ:œFile-BzIs2œ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-Prompt-9DNZG{œfieldNameœ:œDocumentœ,œidœ:œPrompt-9DNZGœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}" + }, + "type": "Prompt" + }, + "dragging": false, + "height": 573, + "id": "Prompt-9DNZG", + "position": { + "x": 585.7906101139403, + "y": 117.52115876762832 + }, + "positionAbsolute": { + "x": 585.7906101139403, + "y": 117.52115876762832 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "ChatInput-27Usy", + "node": { + "base_classes": [ + "str", + "Record", + "Text", + "object" + ], + "beta": false, + "custom_fields": { + "input_value": null, + "return_record": null, + "sender": null, + "sender_name": null, + "session_id": null }, - { - "source": "ChatInput-27Usy", - "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-27Usyœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}", - "target": "Prompt-9DNZG", - "targetHandle": "{œfieldNameœ:œQuestionœ,œidœ:œPrompt-9DNZGœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}", - "data": { - "targetHandle": { - "fieldName": "Question", - "id": "Prompt-9DNZG", - "inputTypes": [ - "Document", - "Message", - "Data", - "Text" - ], - "type": "str" - }, - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-27Usy", - "name": "message", - "output_types": [ - "Message" - ] - } - }, - "id": "reactflow__edge-ChatInput-27Usy{œdataTypeœ:œChatInputœ,œidœ:œChatInput-27Usyœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-9DNZG{œfieldNameœ:œQuestionœ,œidœ:œPrompt-9DNZGœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}" - }, - { - "source": "Prompt-9DNZG", - "sourceHandle": "{œdataTypeœ:œPromptœ,œidœ:œPrompt-9DNZGœ,œnameœ:œpromptœ,œoutput_typesœ:[œPromptœ]}", - "target": "OpenAIModel-8b6nG", - "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-8b6nGœ,œinputTypesœ:[œTextœ,œDataœ,œPromptœ],œtypeœ:œstrœ}", - "data": { - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-8b6nG", - "inputTypes": [ - "Text", - "Data", - "Prompt" - ], - "type": "str" - }, - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-9DNZG", - "name": "prompt", - "output_types": [ - "Prompt" - ] - } - }, - "id": "reactflow__edge-Prompt-9DNZG{œdataTypeœ:œPromptœ,œidœ:œPrompt-9DNZGœ,œnameœ:œpromptœ,œoutput_typesœ:[œPromptœ]}-OpenAIModel-8b6nG{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-8b6nGœ,œinputTypesœ:[œTextœ,œDataœ,œPromptœ],œtypeœ:œstrœ}" - }, - { - "source": "OpenAIModel-8b6nG", - "sourceHandle": "{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-8b6nGœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œTextœ]}", - "target": "ChatOutput-y4SCS", - "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-y4SCSœ,œinputTypesœ:[œTextœ,œMessageœ],œtypeœ:œstrœ}", - "data": { - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-y4SCS", - "inputTypes": [ - "Text", - "Message" - ], - "type": "str" - }, - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-8b6nG", - "name": "text_output", - "output_types": [ - "Text" - ] - } - }, - "id": "reactflow__edge-OpenAIModel-8b6nG{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-8b6nGœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œTextœ]}-ChatOutput-y4SCS{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-y4SCSœ,œinputTypesœ:[œTextœ,œMessageœ],œtypeœ:œstrœ}" + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "ChatInput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Message to be passed as input.", + "input_types": [], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Type of sender.", + "input_types": [ + "Text" + ], + "list": true, + "load_from_db": false, + "multiline": false, + "name": "sender", + "options": [ + "Machine", + "User" + ], + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "User" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Name of the sender.", + "input_types": [ + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": false, + "name": "sender_name", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "User" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Session ID for the message.", + "input_types": [ + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": false, + "name": "session_id", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } } - ], - "viewport": { - "x": 198.5801484914205, - "y": 244.8736279905512, - "zoom": 0.5335671198494703 - } - }, - "description": "This flow integrates PDF reading with a language model to answer document-specific questions. Ideal for small-scale texts, it facilitates direct queries with immediate insights.", - "name": "Document QA", - "last_tested_version": "1.0.0a52", - "is_component": false + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 301, + "id": "ChatInput-27Usy", + "position": { + "x": -38.501719080514135, + "y": 379.81180230285355 + }, + "positionAbsolute": { + "x": -38.501719080514135, + "y": 379.81180230285355 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "ChatOutput-y4SCS", + "node": { + "base_classes": [ + "str", + "Record", + "Text", + "object" + ], + "beta": false, + "custom_fields": { + "input_value": null, + "return_record": null, + "sender": null, + "sender_name": null, + "session_id": null + }, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "ChatOutput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Message to be passed as output.", + "input_types": [ + "Text", + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Type of sender.", + "input_types": [ + "Text" + ], + "list": true, + "load_from_db": false, + "multiline": false, + "name": "sender", + "options": [ + "Machine", + "User" + ], + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Name of the sender.", + "input_types": [ + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": false, + "name": "sender_name", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "fileTypes": [], + "file_path": "", + "info": "Session ID for the message.", + "input_types": [ + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": false, + "name": "session_id", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 309, + "id": "ChatOutput-y4SCS", + "position": { + "x": 1733.3012915204283, + "y": 168.76098809939327 + }, + "positionAbsolute": { + "x": 1733.3012915204283, + "y": 168.76098809939327 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "A generic file loader.", + "display_name": "File", + "id": "File-BzIs2", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "A generic file loader.", + "display_name": "File", + "documentation": "", + "edited": true, + "field_order": [ + "path", + "silent_errors" + ], + "frozen": false, + "icon": "file-text", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "method": "load_file", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from pathlib import Path\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import Component\nfrom langflow.inputs import BoolInput, FileInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(self.path)\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n" + }, + "path": { + "advanced": false, + "display_name": "Path", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx" + ], + "file_path": "cd558bbb-10b7-4c22-a7ad-3739f26b4bd7/Climate Prediction Updated.json", + "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", + "list": false, + "name": "path", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "file", + "value": "" + }, + "silent_errors": { + "advanced": true, + "display_name": "Silent Errors", + "dynamic": false, + "info": "If true, errors will not raise an exception.", + "list": false, + "name": "silent_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + } + } + }, + "type": "File" + }, + "dragging": false, + "height": 301, + "id": "File-BzIs2", + "position": { + "x": -44.56084223565597, + "y": 39.0475820447775 + }, + "positionAbsolute": { + "x": -44.56084223565597, + "y": 39.0475820447775 + }, + "selected": true, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "OpenAIModel-8b6nG", + "node": { + "base_classes": [ + "BaseLanguageModel", + "Text" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "field_order": [ + "input_value", + "max_tokens", + "model_kwargs", + "model_name", + "openai_api_base", + "openai_api_key", + "temperature", + "stream", + "system_message" + ], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "method": "text_response", + "name": "text_output", + "selected": "Text", + "types": [ + "Text" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "BaseLanguageModel", + "types": [ + "BaseLanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n" + }, + "input_value": { + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Text", + "Data", + "Prompt" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict" + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "gpt-4o" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [ + "Text" + ], + "load_from_db": true, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "OPENAI_API_KEY" + }, + "stream": { + "advanced": true, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": 0.1 + } + } + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 623, + "id": "OpenAIModel-8b6nG", + "position": { + "x": 1141.7303854551026, + "y": -51.19892217231286 + }, + "positionAbsolute": { + "x": 1141.7303854551026, + "y": -51.19892217231286 + }, + "selected": false, + "type": "genericNode", + "width": 384 + } + ], + "viewport": { + "x": 198.5801484914205, + "y": 244.8736279905512, + "zoom": 0.5335671198494703 + } + }, + "description": "This flow integrates PDF reading with a language model to answer document-specific questions. Ideal for small-scale texts, it facilitates direct queries with immediate insights.", + "id": "cd558bbb-10b7-4c22-a7ad-3739f26b4bd7", + "is_component": false, + "last_tested_version": "1.0.0a52", + "name": "Document QA" } \ No newline at end of file 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 0066bcfa1..dc5fe03b8 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 @@ -217,7 +217,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -263,7 +263,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "User" }, "sender_name": { "advanced": true, @@ -285,7 +285,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "User" }, "session_id": { "advanced": true, @@ -355,17 +355,6 @@ "icon": "ChatOutput", "output_types": [], "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Text", - "types": [ - "Text" - ], - "value": "__UNDEFINED__" - }, { "cache": true, "display_name": "Message", @@ -396,7 +385,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\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:\n self.message_response()\n self.status = result\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) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -445,7 +434,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "Machine" }, "sender_name": { "advanced": true, @@ -467,7 +456,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "AI" }, "session_id": { "advanced": true, @@ -958,7 +947,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n return output\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n" }, "input_value": { "advanced": false, @@ -1055,7 +1044,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "gpt-4o" }, "openai_api_base": { "advanced": true, @@ -1090,7 +1079,7 @@ "Text" ], "list": false, - "load_from_db": false, + "load_from_db": true, "multiline": false, "name": "openai_api_key", "password": true, @@ -1099,7 +1088,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "OPENAI_API_KEY" }, "stream": { "advanced": true, @@ -1121,7 +1110,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": false }, "system_message": { "advanced": true, @@ -1165,7 +1154,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": 0.1 } } }, 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 f2bf96df0..88a175a9e 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 @@ -557,17 +557,6 @@ "icon": "ChatOutput", "output_types": [], "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Text", - "types": [ - "Text" - ], - "value": "__UNDEFINED__" - }, { "cache": true, "display_name": "Message", @@ -598,7 +587,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\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:\n self.message_response()\n self.status = result\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) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -647,7 +636,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "Machine" }, "sender_name": { "advanced": true, @@ -669,7 +658,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "AI" }, "session_id": { "advanced": true, @@ -736,17 +725,6 @@ "icon": "ChatOutput", "output_types": [], "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Text", - "types": [ - "Text" - ], - "value": "__UNDEFINED__" - }, { "cache": true, "display_name": "Message", @@ -777,7 +755,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\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:\n self.message_response()\n self.status = result\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) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -826,7 +804,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "Machine" }, "sender_name": { "advanced": true, @@ -848,7 +826,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "AI" }, "session_id": { "advanced": true, @@ -939,15 +917,15 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import StrInput\nfrom langflow.template import Output\n\n\nclass TextInput(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n type=str,\n display_name=\"Value\",\n info=\"Text or Data to be passed as input.\",\n input_types=[\"Data\", \"Text\"],\n ),\n StrInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n multiline=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n advanced=True,\n value=\"{text}\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Text:\n return self.build(input_value=self.input_value, data_template=self.data_template)\n" + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import MultilineInput, StrInput\nfrom langflow.template import Output\n\n\nclass TextInput(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n MultilineInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n advanced=True,\n value=\"{text}\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Text:\n return self.build(input_value=self.input_value, data_template=self.data_template)\n" }, "input_value": { "advanced": false, - "display_name": "Value", + "display_name": "Text", "dynamic": false, "fileTypes": [], "file_path": "", - "info": "Text or Data to be passed as input.", + "info": "Text to be passed as input.", "input_types": [ "Data", "Text" @@ -1172,7 +1150,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n return output\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n" }, "input_value": { "advanced": false, @@ -1269,7 +1247,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "gpt-4o" }, "openai_api_base": { "advanced": true, @@ -1304,7 +1282,7 @@ "Text" ], "list": false, - "load_from_db": false, + "load_from_db": true, "multiline": false, "name": "openai_api_key", "password": true, @@ -1313,7 +1291,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "OPENAI_API_KEY" }, "stream": { "advanced": true, @@ -1335,7 +1313,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": false }, "system_message": { "advanced": true, @@ -1379,7 +1357,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": 0.1 } } }, @@ -1589,7 +1567,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n return output\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n" }, "input_value": { "advanced": false, @@ -1686,7 +1664,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "gpt-4o" }, "openai_api_base": { "advanced": true, @@ -1721,7 +1699,7 @@ "Text" ], "list": false, - "load_from_db": false, + "load_from_db": true, "multiline": false, "name": "openai_api_key", "password": true, @@ -1730,7 +1708,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "OPENAI_API_KEY" }, "stream": { "advanced": true, @@ -1752,7 +1730,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": false }, "system_message": { "advanced": true, @@ -1796,7 +1774,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": 0.1 } } }, 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 a1a776895..7340fb242 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 @@ -356,7 +356,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\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=\"message_response\"),\n ]\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)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -402,7 +402,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "User" }, "sender_name": { "advanced": true, @@ -424,7 +424,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "User" }, "session_id": { "advanced": true, @@ -1187,7 +1187,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n return output\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n" }, "input_value": { "advanced": false, @@ -1284,7 +1284,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "gpt-4o" }, "openai_api_base": { "advanced": true, @@ -1319,7 +1319,7 @@ "Text" ], "list": false, - "load_from_db": false, + "load_from_db": true, "multiline": false, "name": "openai_api_key", "password": true, @@ -1328,7 +1328,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "OPENAI_API_KEY" }, "stream": { "advanced": true, @@ -1350,7 +1350,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": false }, "system_message": { "advanced": true, @@ -1394,7 +1394,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": 0.1 } } }, @@ -1612,17 +1612,6 @@ "icon": "ChatOutput", "output_types": [], "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Text", - "types": [ - "Text" - ], - "value": "__UNDEFINED__" - }, { "cache": true, "display_name": "Message", @@ -1653,7 +1642,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\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:\n self.message_response()\n self.status = result\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) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import 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 MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\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) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -1702,7 +1691,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "Machine" }, "sender_name": { "advanced": true, @@ -1724,7 +1713,7 @@ "show": true, "title_case": false, "type": "str", - "value": "" + "value": "AI" }, "session_id": { "advanced": true, @@ -1786,15 +1775,12 @@ "field_order": [], "frozen": false, "icon": "file-text", - "output_types": [ - "Data" - ], + "output_types": [], "outputs": [ { "cache": true, "display_name": "Data", - "hidden": null, - "method": null, + "method": "load_file", "name": "data", "selected": "Data", "types": [ @@ -1804,7 +1790,7 @@ } ], "template": { - "_type": "CustomComponent", + "_type": "Component", "code": { "advanced": true, "dynamic": true, @@ -1821,58 +1807,49 @@ "show": true, "title_case": false, "type": "code", - "value": "from pathlib import Path\nfrom typing import Any, Dict\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import CustomComponent\nfrom langflow.schema import Data\n\n\nclass FileComponent(CustomComponent):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n def build_config(self) -> Dict[str, Any]:\n return {\n \"path\": {\n \"display_name\": \"Path\",\n \"field_type\": \"file\",\n \"file_types\": TEXT_FILE_TYPES,\n \"info\": f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n },\n \"silent_errors\": {\n \"display_name\": \"Silent Errors\",\n \"advanced\": True,\n \"info\": \"If true, errors will not raise an exception.\",\n },\n }\n\n def load_file(self, path: str, silent_errors: bool = False) -> Data:\n resolved_path = self.resolve_path(path)\n path_obj = Path(resolved_path)\n extension = path_obj.suffix[1:].lower()\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n record = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = record if record else \"No data\"\n return record or Data()\n\n def build(\n self,\n path: str,\n silent_errors: bool = False,\n ) -> Data:\n record = self.load_file(path, silent_errors)\n self.status = record\n return record\n" + "value": "from pathlib import Path\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import Component\nfrom langflow.inputs import BoolInput, FileInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(self.path)\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n" }, "path": { "advanced": false, "display_name": "Path", "dynamic": false, "fileTypes": [ - ".txt", - ".md", - ".mdx", - ".csv", - ".json", - ".yaml", - ".yml", - ".xml", - ".html", - ".htm", - ".pdf", - ".docx", - ".py", - ".sh", - ".sql", - ".js", - ".ts", - ".tsx" + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx" ], - "file_path": "51e2b78a-199b-4054-9f32-e288eef6924c/Langflow conversation.pdf", + "file_path": "", "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", "list": false, - "load_from_db": false, - "multiline": false, "name": "path", - "password": false, "placeholder": "", - "required": true, + "required": false, "show": true, "title_case": false, - "type": "file", - "value": "" + "type": "file" }, "silent_errors": { "advanced": true, "display_name": "Silent Errors", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "If true, errors will not raise an exception.", "list": false, - "load_from_db": false, - "multiline": false, "name": "silent_errors", - "password": false, "placeholder": "", "required": false, "show": true, @@ -2130,7 +2107,7 @@ "Text" ], "list": false, - "load_from_db": true, + "load_from_db": false, "multiline": false, "name": "api_endpoint", "password": false, @@ -2496,7 +2473,7 @@ "Text" ], "list": false, - "load_from_db": true, + "load_from_db": false, "multiline": false, "name": "token", "password": true, @@ -2608,7 +2585,7 @@ "Text" ], "list": false, - "load_from_db": true, + "load_from_db": false, "multiline": false, "name": "api_endpoint", "password": false, @@ -2926,7 +2903,7 @@ "Text" ], "list": false, - "load_from_db": true, + "load_from_db": false, "multiline": false, "name": "token", "password": true,