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Fix Global Variables (#2430)

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* chore: update linting workflows to include dev branch in merge_group

* Update README.md

Add 1.0 banner

* Update README.md

* chore: update package versions in pyproject.toml files

* Added db value to every onChange on parameters

* Refactored global variables to find variables on the first render, and to execute just one onChange to update both values and db

* Changed group recursion function to include check for global variables already applied or outdated

* Removed already inserted component check for default fields on global variables

* Fixed import error

* Added required parameters to update node on drop

* Removed check for unused hardcoded name

* Added global variables handling on nodes when adding a flow

* Fixed maximum update depth when deleting used global variable

* Fixed type error on addNewVariableButton modal

* Fixed openai api key on starter flows

* Fixed values to get the .env values by default on the starter projects

* Formatted flows

* fix erros reported by mypy

* [autofix.ci] apply automated fixes

* 🐛 (prototypes/__init__.py): fix missing comma in the list of imported components to prevent syntax error

* chore: Fix type hinting in ConditionalRouterComponent

* [autofix.ci] apply automated fixes

---------

Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>
Co-authored-by: Rodrigo Nader <rodrigosilvanader@gmail.com>
Co-authored-by: italojohnny <italojohnnydosanjos@gmail.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
This commit is contained in:
Lucas Oliveira 2024-07-01 13:31:06 -03:00 • committed by Gabriel Luiz Freitas Almeida
commit b31c5e6b4a
26 changed files with 1036 additions and 885 deletions
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2
src/backend/base/langflow/components/embeddings/OpenAIEmbeddings.py
View file

@ -40,7 +40,7 @@ class OpenAIEmbeddingsComponent(LCEmbeddingsModel):
),
DictInput(name="model_kwargs", display_name="Model Kwargs", advanced=True),
SecretStrInput(name="openai_api_base", display_name="OpenAI API Base", advanced=True),
SecretStrInput(name="openai_api_key", display_name="OpenAI API Key"),
SecretStrInput(name="openai_api_key", display_name="OpenAI API Key", value="OPENAI_API_KEY"),
SecretStrInput(name="openai_api_type", display_name="OpenAI API Type", advanced=True),
MessageTextInput(name="openai_api_version", display_name="OpenAI API Version", advanced=True),
MessageTextInput(

101
src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json
View file

@ -2,10 +2,11 @@
"data": {
"edges": [
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "ChatInput",
"id": "ChatInput-pxptT",
"id": "ChatInput-Y6mi1",
"name": "message",
"output_types": [
"Message"
@ -13,7 +14,7 @@
},
"targetHandle": {
"fieldName": "user_input",
"id": "Prompt-1S5SU",
"id": "Prompt-Z4WYI",
"inputTypes": [
"Message",
"Text"
@ -21,17 +22,18 @@
"type": "str"
}
},
"id": "reactflow__edge-ChatInput-pxptT{œdataTypeœ:œChatInputœ,œidœ:œChatInput-pxptTœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-1S5SU{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-1S5SUœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ChatInput-pxptT",
"sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-pxptTœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-1S5SU",
"targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-1S5SUœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-ChatInput-Y6mi1{œdataTypeœ:œChatInputœ,œidœ:œChatInput-Y6mi1œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-Z4WYI{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-Z4WYIœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ChatInput-Y6mi1",
"sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-Y6mi1œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-Z4WYI",
"targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-Z4WYIœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
},
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "Prompt",
"id": "Prompt-1S5SU",
"id": "Prompt-Z4WYI",
"name": "prompt",
"output_types": [
"Message"
@ -39,24 +41,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "OpenAIModel-nJXWj",
"id": "OpenAIModel-26Eve",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "reactflow__edge-Prompt-1S5SU{œdataTypeœ:œPromptœ,œidœ:œPrompt-1S5SUœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-nJXWj{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-nJXWjœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-1S5SU",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-1S5SUœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-nJXWj",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-nJXWjœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-Prompt-Z4WYI{œdataTypeœ:œPromptœ,œidœ:œPrompt-Z4WYIœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-26Eve{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-26Eveœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-Z4WYI",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-Z4WYIœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-26Eve",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-26Eveœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
},
{
"data": {
"sourceHandle": {
"dataType": "OpenAIModel",
"id": "OpenAIModel-nJXWj",
"dataType": "OpenAIModelComponent",
"id": "OpenAIModel-26Eve",
"name": "text_output",
"output_types": [
"Message"
@ -64,24 +66,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "ChatOutput-XP4bj",
"id": "ChatOutput-cQnVI",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "reactflow__edge-OpenAIModel-nJXWj{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-nJXWjœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-XP4bj{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-XP4bjœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-nJXWj",
"sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-nJXWjœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-XP4bj",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-XP4bjœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-OpenAIModel-26Eve{œdataTypeœ:œOpenAIModelComponentœ,œidœ:œOpenAIModel-26Eveœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-cQnVI{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-cQnVIœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-26Eve",
"sourceHandle": "{œdataTypeœ: œOpenAIModelComponentœ, œidœ: œOpenAIModel-26Eveœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-cQnVI",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-cQnVIœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
}
],
"nodes": [
{
"data": {
"id": "ChatInput-pxptT",
"id": "ChatInput-Y6mi1",
"node": {
"base_classes": [
"Message"
@ -264,7 +266,7 @@
},
"dragging": false,
"height": 308,
"id": "ChatInput-pxptT",
"id": "ChatInput-Y6mi1",
"position": {
"x": -493.6459512396177,
"y": 1083.200545525551
@ -281,7 +283,7 @@
"data": {
"description": "Create a prompt template with dynamic variables.",
"display_name": "Prompt",
"id": "Prompt-1S5SU",
"id": "Prompt-Z4WYI",
"node": {
"base_classes": [
"Message"
@ -389,7 +391,7 @@
},
"dragging": false,
"height": 422,
"id": "Prompt-1S5SU",
"id": "Prompt-Z4WYI",
"position": {
"x": 56.354011530798516,
"y": 1157.2005405164796
@ -404,7 +406,10 @@
},
{
"data": {
"id": "OpenAIModel-nJXWj",
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"edited": false,
"id": "OpenAIModel-26Eve",
"node": {
"base_classes": [
"LanguageModel",
@ -416,11 +421,12 @@
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"documentation": "",
"edited": false,
"edited": true,
"field_order": [
"input_value",
"max_tokens",
"model_kwargs",
"json_mode",
"output_schema",
"model_name",
"openai_api_base",
@ -477,7 +483,7 @@
"show": true,
"title_case": false,
"type": "code",
"value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
"value": "import operator\nfrom functools import reduce\n\nfrom 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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n else:\n output = output.bind(response_format={\"type\": \"json_object\"}) # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
},
"input_value": {
"advanced": false,
@ -499,6 +505,21 @@
"type": "str",
"value": ""
},
"json_mode": {
"advanced": true,
"display_name": "JSON Mode",
"dynamic": false,
"info": "If True, it will output JSON regardless of passing a schema.",
"list": false,
"name": "json_mode",
"placeholder": "",
"required": false,
"show": true,
"title_case": false,
"trace_as_metadata": true,
"type": "bool",
"value": false
},
"max_tokens": {
"advanced": true,
"display_name": "Max Tokens",
@ -572,7 +593,7 @@
"dynamic": false,
"info": "The OpenAI API Key to use for the OpenAI model.",
"input_types": [],
"load_from_db": false,
"load_from_db": true,
"name": "openai_api_key",
"password": true,
"placeholder": "",
@ -580,7 +601,7 @@
"show": true,
"title_case": false,
"type": "str",
"value": ""
"value": "OPENAI_API_KEY"
},
"output_schema": {
"advanced": true,
@ -660,11 +681,11 @@
}
}
},
"type": "OpenAIModel"
"type": "OpenAIModelComponent"
},
"dragging": false,
"height": 621,
"id": "OpenAIModel-nJXWj",
"id": "OpenAIModel-26Eve",
"position": {
"x": 624.3539730827923,
"y": 1053.2005475562555
@ -679,7 +700,7 @@
},
{
"data": {
"id": "ChatOutput-XP4bj",
"id": "ChatOutput-cQnVI",
"node": {
"base_classes": [
"Message"
@ -839,7 +860,7 @@
},
"dragging": false,
"height": 308,
"id": "ChatOutput-XP4bj",
"id": "ChatOutput-cQnVI",
"position": {
"x": 1219.477374823274,
"y": 1200.950216973985
@ -854,15 +875,15 @@
}
],
"viewport": {
"x": 392.1085223509972,
"y": -327.49805229761307,
"zoom": 0.5000000676901589
"x": 366.93776265249005,
"y": -343.56726676261223,
"zoom": 0.5000000676901587
}
},
"description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ",
"endpoint_name": null,
"id": "f652abdc-7ef2-4e52-a00b-847b7aa32cee",
"id": "e533253b-818b-4b5a-9793-55ab83fffb07",
"is_component": false,
"last_tested_version": "1.0.0rc1",
"last_tested_version": "1.0.5",
"name": "Basic Prompting (Hello, World)"
}

133
src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json
View file

@ -2,10 +2,11 @@
"data": {
"edges": [
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "URL",
"id": "URL-k9NkE",
"id": "URL-rETJU",
"name": "data",
"output_types": [
"Data"
@ -13,24 +14,25 @@
},
"targetHandle": {
"fieldName": "data",
"id": "ParseData-EwWXd",
"id": "ParseData-AqSfN",
"inputTypes": [
"Data"
],
"type": "other"
}
},
"id": "reactflow__edge-URL-k9NkE{œdataTypeœ:œURLœ,œidœ:œURL-k9NkEœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-EwWXd{œfieldNameœ:œdataœ,œidœ:œParseData-EwWXdœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}",
"source": "URL-k9NkE",
"sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-k9NkEœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}",
"target": "ParseData-EwWXd",
"targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-EwWXdœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}"
"id": "reactflow__edge-URL-rETJU{œdataTypeœ:œURLœ,œidœ:œURL-rETJUœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-AqSfN{œfieldNameœ:œdataœ,œidœ:œParseData-AqSfNœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}",
"source": "URL-rETJU",
"sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-rETJUœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}",
"target": "ParseData-AqSfN",
"targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-AqSfNœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}"
},
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "ParseData",
"id": "ParseData-EwWXd",
"id": "ParseData-AqSfN",
"name": "text",
"output_types": [
"Message"
@ -38,7 +40,7 @@
},
"targetHandle": {
"fieldName": "references",
"id": "Prompt-B9Mq6",
"id": "Prompt-rizUK",
"inputTypes": [
"Message",
"Text"
@ -46,17 +48,18 @@
"type": "str"
}
},
"id": "reactflow__edge-ParseData-EwWXd{œdataTypeœ:œParseDataœ,œidœ:œParseData-EwWXdœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-B9Mq6{œfieldNameœ:œreferencesœ,œidœ:œPrompt-B9Mq6œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ParseData-EwWXd",
"sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-EwWXdœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-B9Mq6",
"targetHandle": "{œfieldNameœ: œreferencesœ, œidœ: œPrompt-B9Mq6œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-ParseData-AqSfN{œdataTypeœ:œParseDataœ,œidœ:œParseData-AqSfNœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-rizUK{œfieldNameœ:œreferencesœ,œidœ:œPrompt-rizUKœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ParseData-AqSfN",
"sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-AqSfNœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-rizUK",
"targetHandle": "{œfieldNameœ: œreferencesœ, œidœ: œPrompt-rizUKœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
},
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "TextInput",
"id": "TextInput-uf6ij",
"id": "TextInput-OffFR",
"name": "text",
"output_types": [
"Message"
@ -64,7 +67,7 @@
},
"targetHandle": {
"fieldName": "instructions",
"id": "Prompt-B9Mq6",
"id": "Prompt-rizUK",
"inputTypes": [
"Message",
"Text"
@ -72,17 +75,18 @@
"type": "str"
}
},
"id": "reactflow__edge-TextInput-uf6ij{œdataTypeœ:œTextInputœ,œidœ:œTextInput-uf6ijœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-B9Mq6{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-B9Mq6œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "TextInput-uf6ij",
"sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-uf6ijœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-B9Mq6",
"targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-B9Mq6œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-TextInput-OffFR{œdataTypeœ:œTextInputœ,œidœ:œTextInput-OffFRœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-rizUK{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-rizUKœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "TextInput-OffFR",
"sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-OffFRœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-rizUK",
"targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-rizUKœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
},
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "Prompt",
"id": "Prompt-B9Mq6",
"id": "Prompt-rizUK",
"name": "prompt",
"output_types": [
"Message"
@ -90,24 +94,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "OpenAIModel-X9ukk",
"id": "OpenAIModel-qmhKV",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "reactflow__edge-Prompt-B9Mq6{œdataTypeœ:œPromptœ,œidœ:œPrompt-B9Mq6œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-X9ukk{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-X9ukkœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-B9Mq6",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-B9Mq6œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-X9ukk",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-X9ukkœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-Prompt-rizUK{œdataTypeœ:œPromptœ,œidœ:œPrompt-rizUKœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-qmhKV{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-qmhKVœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-rizUK",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-rizUKœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-qmhKV",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-qmhKVœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
},
{
"data": {
"sourceHandle": {
"dataType": "OpenAIModel",
"id": "OpenAIModel-X9ukk",
"dataType": "OpenAIModelComponent",
"id": "OpenAIModel-qmhKV",
"name": "text_output",
"output_types": [
"Message"
@ -115,24 +119,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "ChatOutput-5r5Iw",
"id": "ChatOutput-W684s",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "reactflow__edge-OpenAIModel-X9ukk{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-X9ukkœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-5r5Iw{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-5r5Iwœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-X9ukk",
"sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-X9ukkœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-5r5Iw",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-5r5Iwœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-OpenAIModel-qmhKV{œdataTypeœ:œOpenAIModelComponentœ,œidœ:œOpenAIModel-qmhKVœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-W684s{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-W684sœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-qmhKV",
"sourceHandle": "{œdataTypeœ: œOpenAIModelComponentœ, œidœ: œOpenAIModel-qmhKVœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-W684s",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-W684sœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
}
],
"nodes": [
{
"data": {
"id": "URL-k9NkE",
"id": "URL-rETJU",
"node": {
"base_classes": [
"Data"
@ -214,7 +218,7 @@
},
"dragging": false,
"height": 358,
"id": "URL-k9NkE",
"id": "URL-rETJU",
"position": {
"x": 220.79156431407534,
"y": 498.8186168722667
@ -229,7 +233,7 @@
},
{
"data": {
"id": "ParseData-EwWXd",
"id": "ParseData-AqSfN",
"node": {
"base_classes": [
"Message"
@ -346,7 +350,7 @@
},
"dragging": false,
"height": 384,
"id": "ParseData-EwWXd",
"id": "ParseData-AqSfN",
"position": {
"x": 754.3607306709101,
"y": 736.8516961537598
@ -363,7 +367,7 @@
"data": {
"description": "Create a prompt template with dynamic variables.",
"display_name": "Prompt",
"id": "Prompt-B9Mq6",
"id": "Prompt-rizUK",
"node": {
"base_classes": [
"Message"
@ -496,7 +500,7 @@
},
"dragging": false,
"height": 515,
"id": "Prompt-B9Mq6",
"id": "Prompt-rizUK",
"position": {
"x": 1368.0633591447076,
"y": 467.19448061224284
@ -511,7 +515,7 @@
},
{
"data": {
"id": "TextInput-uf6ij",
"id": "TextInput-OffFR",
"node": {
"base_classes": [
"Message"
@ -590,7 +594,7 @@
},
"dragging": false,
"height": 308,
"id": "TextInput-uf6ij",
"id": "TextInput-OffFR",
"position": {
"x": 743.7338453293725,
"y": 301.58775454952183
@ -605,7 +609,10 @@
},
{
"data": {
"id": "OpenAIModel-X9ukk",
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"edited": false,
"id": "OpenAIModel-qmhKV",
"node": {
"base_classes": [
"LanguageModel",
@ -617,11 +624,12 @@
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"documentation": "",
"edited": false,
"edited": true,
"field_order": [
"input_value",
"max_tokens",
"model_kwargs",
"json_mode",
"output_schema",
"model_name",
"openai_api_base",
@ -678,7 +686,7 @@
"show": true,
"title_case": false,
"type": "code",
"value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
"value": "import operator\nfrom functools import reduce\n\nfrom 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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n else:\n output = output.bind(response_format={\"type\": \"json_object\"}) # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
},
"input_value": {
"advanced": false,
@ -700,6 +708,21 @@
"type": "str",
"value": ""
},
"json_mode": {
"advanced": true,
"display_name": "JSON Mode",
"dynamic": false,
"info": "If True, it will output JSON regardless of passing a schema.",
"list": false,
"name": "json_mode",
"placeholder": "",
"required": false,
"show": true,
"title_case": false,
"trace_as_metadata": true,
"type": "bool",
"value": false
},
"max_tokens": {
"advanced": true,
"display_name": "Max Tokens",
@ -773,7 +796,7 @@
"dynamic": false,
"info": "The OpenAI API Key to use for the OpenAI model.",
"input_types": [],
"load_from_db": false,
"load_from_db": true,
"name": "openai_api_key",
"password": true,
"placeholder": "",
@ -781,7 +804,7 @@
"show": true,
"title_case": false,
"type": "str",
"value": ""
"value": "OPENAI_API_KEY"
},
"output_schema": {
"advanced": true,
@ -861,11 +884,11 @@
}
}
},
"type": "OpenAIModel"
"type": "OpenAIModelComponent"
},
"dragging": false,
"height": 621,
"id": "OpenAIModel-X9ukk",
"id": "OpenAIModel-qmhKV",
"position": {
"x": 1899.407626221589,
"y": 395.9013619556682
@ -880,7 +903,7 @@
},
{
"data": {
"id": "ChatOutput-5r5Iw",
"id": "ChatOutput-W684s",
"node": {
"base_classes": [
"Message"
@ -1040,7 +1063,7 @@
},
"dragging": false,
"height": 308,
"id": "ChatOutput-5r5Iw",
"id": "ChatOutput-W684s",
"position": {
"x": 2449.3489426461606,
"y": 571.2449700910389
@ -1062,8 +1085,8 @@
},
"description": "This flow can be used to create a blog post following instructions from the user, using two other blogs as reference.",
"endpoint_name": null,
"id": "13da3150-95b9-4d81-9ad2-f635dcdce7ab",
"id": "da9999f8-9013-4bd9-8adb-653c94ebf08c",
"is_component": false,
"last_tested_version": "1.0.0rc1",
"last_tested_version": "1.0.5",
"name": "Blog Writer"
}

147
src/backend/base/langflow/initial_setup/starter_projects/Document QA.json
View file

@ -2,10 +2,11 @@
"data": {
"edges": [
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "File",
"id": "File-h46aK",
"id": "File-Q3Xrb",
"name": "data",
"output_types": [
"Data"
@ -13,24 +14,25 @@
},
"targetHandle": {
"fieldName": "data",
"id": "ParseData-sqVr1",
"id": "ParseData-1Y5jJ",
"inputTypes": [
"Data"
],
"type": "other"
}
},
"id": "reactflow__edge-File-h46aK{œdataTypeœ:œFileœ,œidœ:œFile-h46aKœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-sqVr1{œfieldNameœ:œdataœ,œidœ:œParseData-sqVr1œ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}",
"source": "File-h46aK",
"sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-h46aKœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}",
"target": "ParseData-sqVr1",
"targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-sqVr1œ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}"
"id": "reactflow__edge-File-Q3Xrb{œdataTypeœ:œFileœ,œidœ:œFile-Q3Xrbœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-1Y5jJ{œfieldNameœ:œdataœ,œidœ:œParseData-1Y5jJœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}",
"source": "File-Q3Xrb",
"sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-Q3Xrbœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}",
"target": "ParseData-1Y5jJ",
"targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-1Y5jJœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}"
},
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"data": {
"sourceHandle": {
"dataType": "ParseData",
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"id": "ParseData-1Y5jJ",
"name": "text",
"output_types": [
"Message"
@ -38,7 +40,7 @@
},
"targetHandle": {
"fieldName": "Document",
"id": "Prompt-mQ7w2",
"id": "Prompt-CMJEB",
"inputTypes": [
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@ -46,17 +48,18 @@
"type": "str"
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},
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"source": "ParseData-sqVr1",
"sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-sqVr1œ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-mQ7w2",
"targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-mQ7w2œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-ParseData-1Y5jJ{œdataTypeœ:œParseDataœ,œidœ:œParseData-1Y5jJœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-CMJEB{œfieldNameœ:œDocumentœ,œidœ:œPrompt-CMJEBœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ParseData-1Y5jJ",
"sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-1Y5jJœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-CMJEB",
"targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-CMJEBœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
},
{
"className": "",
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"dataType": "ChatInput",
"id": "ChatInput-cMXe0",
"id": "ChatInput-mc7sJ",
"name": "message",
"output_types": [
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@ -64,7 +67,7 @@
},
"targetHandle": {
"fieldName": "Question",
"id": "Prompt-mQ7w2",
"id": "Prompt-CMJEB",
"inputTypes": [
"Message",
"Text"
@ -72,17 +75,18 @@
"type": "str"
}
},
"id": "reactflow__edge-ChatInput-cMXe0{œdataTypeœ:œChatInputœ,œidœ:œChatInput-cMXe0œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-mQ7w2{œfieldNameœ:œQuestionœ,œidœ:œPrompt-mQ7w2œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ChatInput-cMXe0",
"sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-cMXe0œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-mQ7w2",
"targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-mQ7w2œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-ChatInput-mc7sJ{œdataTypeœ:œChatInputœ,œidœ:œChatInput-mc7sJœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-CMJEB{œfieldNameœ:œQuestionœ,œidœ:œPrompt-CMJEBœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ChatInput-mc7sJ",
"sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-mc7sJœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-CMJEB",
"targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-CMJEBœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
},
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "Prompt",
"id": "Prompt-mQ7w2",
"id": "Prompt-CMJEB",
"name": "prompt",
"output_types": [
"Message"
@ -90,24 +94,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "OpenAIModel-O0AGC",
"id": "OpenAIModel-U2g5u",
"inputTypes": [
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],
"type": "str"
}
},
"id": "reactflow__edge-Prompt-mQ7w2{œdataTypeœ:œPromptœ,œidœ:œPrompt-mQ7w2œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-O0AGC{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-O0AGCœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-mQ7w2",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-mQ7w2œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-O0AGC",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-O0AGCœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-Prompt-CMJEB{œdataTypeœ:œPromptœ,œidœ:œPrompt-CMJEBœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-U2g5u{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-U2g5uœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-CMJEB",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-CMJEBœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-U2g5u",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-U2g5uœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
},
{
"data": {
"sourceHandle": {
"dataType": "OpenAIModel",
"id": "OpenAIModel-O0AGC",
"dataType": "OpenAIModelComponent",
"id": "OpenAIModel-U2g5u",
"name": "text_output",
"output_types": [
"Message"
@ -115,24 +119,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "ChatOutput-efggd",
"id": "ChatOutput-yZjPO",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "reactflow__edge-OpenAIModel-O0AGC{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-O0AGCœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-efggd{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-efggdœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-O0AGC",
"sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-O0AGCœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-efggd",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-efggdœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-OpenAIModel-U2g5u{œdataTypeœ:œOpenAIModelComponentœ,œidœ:œOpenAIModel-U2g5uœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-yZjPO{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-yZjPOœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-U2g5u",
"sourceHandle": "{œdataTypeœ: œOpenAIModelComponentœ, œidœ: œOpenAIModel-U2g5uœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-yZjPO",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-yZjPOœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
}
],
"nodes": [
{
"data": {
"id": "File-h46aK",
"id": "File-Q3Xrb",
"node": {
"base_classes": [
"Data"
@ -243,7 +247,7 @@
},
"dragging": false,
"height": 300,
"id": "File-h46aK",
"id": "File-Q3Xrb",
"position": {
"x": -449.0807503257012,
"y": -253.5304920926106
@ -258,7 +262,7 @@
},
{
"data": {
"id": "ParseData-sqVr1",
"id": "ParseData-1Y5jJ",
"node": {
"base_classes": [
"Message"
@ -375,7 +379,7 @@
},
"dragging": false,
"height": 384,
"id": "ParseData-sqVr1",
"id": "ParseData-1Y5jJ",
"position": {
"x": 73.79471204296345,
"y": -186.9430114986888
@ -392,7 +396,7 @@
"data": {
"description": "Create a prompt template with dynamic variables.",
"display_name": "Prompt",
"id": "Prompt-mQ7w2",
"id": "Prompt-CMJEB",
"node": {
"base_classes": [
"Message"
@ -525,7 +529,7 @@
},
"dragging": false,
"height": 515,
"id": "Prompt-mQ7w2",
"id": "Prompt-CMJEB",
"position": {
"x": 637.3518652087848,
"y": 47.191730368560215
@ -540,7 +544,7 @@
},
{
"data": {
"id": "ChatInput-cMXe0",
"id": "ChatInput-mc7sJ",
"node": {
"base_classes": [
"Message"
@ -723,7 +727,7 @@
},
"dragging": false,
"height": 308,
"id": "ChatInput-cMXe0",
"id": "ChatInput-mc7sJ",
"position": {
"x": 50.08709924122684,
"y": 320.88186720121615
@ -738,7 +742,10 @@
},
{
"data": {
"id": "OpenAIModel-O0AGC",
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"edited": false,
"id": "OpenAIModel-U2g5u",
"node": {
"base_classes": [
"LanguageModel",
@ -750,11 +757,12 @@
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"documentation": "",
"edited": false,
"edited": true,
"field_order": [
"input_value",
"max_tokens",
"model_kwargs",
"json_mode",
"output_schema",
"model_name",
"openai_api_base",
@ -811,7 +819,7 @@
"show": true,
"title_case": false,
"type": "code",
"value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
"value": "import operator\nfrom functools import reduce\n\nfrom 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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n else:\n output = output.bind(response_format={\"type\": \"json_object\"}) # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
},
"input_value": {
"advanced": false,
@ -833,6 +841,21 @@
"type": "str",
"value": ""
},
"json_mode": {
"advanced": true,
"display_name": "JSON Mode",
"dynamic": false,
"info": "If True, it will output JSON regardless of passing a schema.",
"list": false,
"name": "json_mode",
"placeholder": "",
"required": false,
"show": true,
"title_case": false,
"trace_as_metadata": true,
"type": "bool",
"value": false
},
"max_tokens": {
"advanced": true,
"display_name": "Max Tokens",
@ -906,7 +929,7 @@
"dynamic": false,
"info": "The OpenAI API Key to use for the OpenAI model.",
"input_types": [],
"load_from_db": false,
"load_from_db": true,
"name": "openai_api_key",
"password": true,
"placeholder": "",
@ -914,7 +937,7 @@
"show": true,
"title_case": false,
"type": "str",
"value": ""
"value": "OPENAI_API_KEY"
},
"output_schema": {
"advanced": true,
@ -994,26 +1017,26 @@
}
}
},
"type": "OpenAIModel"
"type": "OpenAIModelComponent"
},
"dragging": false,
"height": 621,
"id": "OpenAIModel-O0AGC",
"id": "OpenAIModel-U2g5u",
"position": {
"x": 1227.3672858178775,
"y": 11.61201090144857
"x": 1249.1992451905348,
"y": 2.8792271523856243
},
"positionAbsolute": {
"x": 1227.3672858178775,
"y": 11.61201090144857
"x": 1249.1992451905348,
"y": 2.8792271523856243
},
"selected": false,
"selected": true,
"type": "genericNode",
"width": 384
},
{
"data": {
"id": "ChatOutput-efggd",
"id": "ChatOutput-yZjPO",
"node": {
"base_classes": [
"Message"
@ -1173,7 +1196,7 @@
},
"dragging": false,
"height": 308,
"id": "ChatOutput-efggd",
"id": "ChatOutput-yZjPO",
"position": {
"x": 1831.1359796346408,
"y": 139.5174517327903
@ -1188,15 +1211,15 @@
}
],
"viewport": {
"x": 249.03047748371796,
"y": 251.71203687916693,
"x": 252.03047748371796,
"y": 253.71203687916693,
"zoom": 0.4580440916596844
}
},
"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.",
"endpoint_name": null,
"id": "4b4cbf9e-34fe-4613-a460-3b7af89b7788",
"id": "483d5200-b59b-4afa-a71f-52fcfcde8fca",
"is_component": false,
"last_tested_version": "1.0.0rc1",
"last_tested_version": "1.0.5",
"name": "Document QA"
}

114
src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json
View file

@ -2,10 +2,11 @@
"data": {
"edges": [
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "Memory",
"id": "Memory-uy2TA",
"id": "Memory-VIq7F",
"name": "messages_text",
"output_types": [
"Message"
@ -13,7 +14,7 @@
},
"targetHandle": {
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"id": "Prompt-m9rUs",
"id": "Prompt-gEaWL",
"inputTypes": [
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@ -21,17 +22,18 @@
"type": "str"
}
},
"id": "reactflow__edge-Memory-uy2TA{œdataTypeœ:œMemoryœ,œidœ:œMemory-uy2TAœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-m9rUs{œfieldNameœ:œcontextœ,œidœ:œPrompt-m9rUsœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "Memory-uy2TA",
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"target": "Prompt-m9rUs",
"targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-m9rUsœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-Memory-VIq7F{œdataTypeœ:œMemoryœ,œidœ:œMemory-VIq7Fœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-gEaWL{œfieldNameœ:œcontextœ,œidœ:œPrompt-gEaWLœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "Memory-VIq7F",
"sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-VIq7Fœ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-gEaWL",
"targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-gEaWLœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
},
{
"className": "",
"data": {
"sourceHandle": {
"dataType": "ChatInput",
"id": "ChatInput-hSTqh",
"id": "ChatInput-gIy9N",
"name": "message",
"output_types": [
"Message"
@ -39,7 +41,7 @@
},
"targetHandle": {
"fieldName": "user_message",
"id": "Prompt-m9rUs",
"id": "Prompt-gEaWL",
"inputTypes": [
"Message",
"Text"
@ -47,17 +49,18 @@
"type": "str"
}
},
"id": "reactflow__edge-ChatInput-hSTqh{œdataTypeœ:œChatInputœ,œidœ:œChatInput-hSTqhœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-m9rUs{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-m9rUsœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ChatInput-hSTqh",
"sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-hSTqhœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-m9rUs",
"targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-m9rUsœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-ChatInput-gIy9N{œdataTypeœ:œChatInputœ,œidœ:œChatInput-gIy9Nœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-gEaWL{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-gEaWLœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}",
"source": "ChatInput-gIy9N",
"sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-gIy9Nœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
"target": "Prompt-gEaWL",
"targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-gEaWLœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}"
},
{
"className": "",
"data": {
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"dataType": "Prompt",
"id": "Prompt-m9rUs",
"id": "Prompt-gEaWL",
"name": "prompt",
"output_types": [
"Message"
@ -65,24 +68,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "OpenAIModel-WmUtU",
"id": "OpenAIModel-uNcAU",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "reactflow__edge-Prompt-m9rUs{œdataTypeœ:œPromptœ,œidœ:œPrompt-m9rUsœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-WmUtU{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-WmUtUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-m9rUs",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-m9rUsœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-WmUtU",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-WmUtUœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-Prompt-gEaWL{œdataTypeœ:œPromptœ,œidœ:œPrompt-gEaWLœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-uNcAU{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-uNcAUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "Prompt-gEaWL",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-gEaWLœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-uNcAU",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-uNcAUœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
},
{
"data": {
"sourceHandle": {
"dataType": "OpenAIModel",
"id": "OpenAIModel-WmUtU",
"dataType": "OpenAIModelComponent",
"id": "OpenAIModel-uNcAU",
"name": "text_output",
"output_types": [
"Message"
@ -90,24 +93,24 @@
},
"targetHandle": {
"fieldName": "input_value",
"id": "ChatOutput-LIvGN",
"id": "ChatOutput-KtSB9",
"inputTypes": [
"Message"
],
"type": "str"
}
},
"id": "reactflow__edge-OpenAIModel-WmUtU{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-WmUtUœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-LIvGN{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-LIvGNœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-WmUtU",
"sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-WmUtUœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-LIvGN",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-LIvGNœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
"id": "reactflow__edge-OpenAIModel-uNcAU{œdataTypeœ:œOpenAIModelComponentœ,œidœ:œOpenAIModel-uNcAUœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-KtSB9{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-KtSB9œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
"source": "OpenAIModel-uNcAU",
"sourceHandle": "{œdataTypeœ: œOpenAIModelComponentœ, œidœ: œOpenAIModel-uNcAUœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}",
"target": "ChatOutput-KtSB9",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-KtSB9œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
}
],
"nodes": [
{
"data": {
"id": "Memory-uy2TA",
"id": "Memory-VIq7F",
"node": {
"base_classes": [
"Data",
@ -296,7 +299,7 @@
},
"dragging": false,
"height": 266,
"id": "Memory-uy2TA",
"id": "Memory-VIq7F",
"position": {
"x": 1264.7588980556088,
"y": 506.6868269980502
@ -313,7 +316,7 @@
"data": {
"description": "Create a prompt template with dynamic variables.",
"display_name": "Prompt",
"id": "Prompt-m9rUs",
"id": "Prompt-gEaWL",
"node": {
"base_classes": [
"Message"
@ -446,7 +449,7 @@
},
"dragging": false,
"height": 515,
"id": "Prompt-m9rUs",
"id": "Prompt-gEaWL",
"position": {
"x": 1880.8227904110583,
"y": 625.8049209882275
@ -461,7 +464,7 @@
},
{
"data": {
"id": "ChatInput-hSTqh",
"id": "ChatInput-gIy9N",
"node": {
"base_classes": [
"Message"
@ -644,7 +647,7 @@
},
"dragging": false,
"height": 308,
"id": "ChatInput-hSTqh",
"id": "ChatInput-gIy9N",
"position": {
"x": 1275.9262193671882,
"y": 836.1228056896347
@ -659,7 +662,10 @@
},
{
"data": {
"id": "OpenAIModel-WmUtU",
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"edited": false,
"id": "OpenAIModel-uNcAU",
"node": {
"base_classes": [
"LanguageModel",
@ -671,11 +677,12 @@
"description": "Generates text using OpenAI LLMs.",
"display_name": "OpenAI",
"documentation": "",
"edited": false,
"edited": true,
"field_order": [
"input_value",
"max_tokens",
"model_kwargs",
"json_mode",
"output_schema",
"model_name",
"openai_api_base",
@ -732,7 +739,7 @@
"show": true,
"title_case": false,
"type": "code",
"value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
"value": "import operator\nfrom functools import reduce\n\nfrom 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 LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\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. You 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 IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n else:\n output = output.bind(response_format={\"type\": \"json_object\"}) # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"
},
"input_value": {
"advanced": false,
@ -754,6 +761,21 @@
"type": "str",
"value": ""
},
"json_mode": {
"advanced": true,
"display_name": "JSON Mode",
"dynamic": false,
"info": "If True, it will output JSON regardless of passing a schema.",
"list": false,
"name": "json_mode",
"placeholder": "",
"required": false,
"show": true,
"title_case": false,
"trace_as_metadata": true,
"type": "bool",
"value": false
},
"max_tokens": {
"advanced": true,
"display_name": "Max Tokens",
@ -827,7 +849,7 @@
"dynamic": false,
"info": "The OpenAI API Key to use for the OpenAI model.",
"input_types": [],
"load_from_db": false,
"load_from_db": true,
"name": "openai_api_key",
"password": true,
"placeholder": "",
@ -835,7 +857,7 @@
"show": true,
"title_case": false,
"type": "str",
"value": ""
"value": "OPENAI_API_KEY"
},
"output_schema": {
"advanced": true,
@ -915,11 +937,11 @@
}
}
},
"type": "OpenAIModel"
"type": "OpenAIModelComponent"
},
"dragging": false,
"height": 621,
"id": "OpenAIModel-WmUtU",
"id": "OpenAIModel-uNcAU",
"position": {
"x": 2428.0215346784357,
"y": 569.9683144303319
@ -934,7 +956,7 @@
},
{
"data": {
"id": "ChatOutput-LIvGN",
"id": "ChatOutput-KtSB9",
"node": {
"base_classes": [
"Message"
@ -1094,7 +1116,7 @@
},
"dragging": false,
"height": 308,
"id": "ChatOutput-LIvGN",
"id": "ChatOutput-KtSB9",
"position": {
"x": 2988.248820475989,
"y": 705.837390387878
@ -1116,8 +1138,8 @@
},
"description": "This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.",
"endpoint_name": null,
"id": "2a47bc35-69ca-4d8b-9895-2a7fab222b9f",
"id": "16c029a0-0d89-4c36-8a8c-e5410206df38",
"is_component": false,
"last_tested_version": "1.0.0rc1",
"last_tested_version": "1.0.5",
"name": "Memory Chatbot"
}

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src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json
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