Spaces:
No application file
No application file
File size: 80,862 Bytes
2c9d2c6 |
1 |
{"id":"644602ad-47aa-4412-a33b-e6ae0a3d329d","data":{"nodes":[{"id":"ChatInput-Y41Qu","type":"genericNode","position":{"x":171.02045128257828,"y":-354.99633691780747},"data":{"type":"ChatInput","node":{"template":{"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Interaction Panel.\"\n icon = \"ChatInput\"\n\n def build_config(self):\n build_config = super().build_config()\n build_config[\"input_value\"] = {\n \"input_types\": [],\n \"display_name\": \"Message\",\n \"multiline\": True,\n }\n\n return build_config\n\n def build(\n self,\n sender: Optional[str] = \"User\",\n sender_name: Optional[str] = \"User\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n ) -> Union[Text, Record]:\n return super().build_no_record(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n )\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"input_value":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":true,"fileTypes":[],"file_path":"","password":false,"name":"input_value","display_name":"Message","advanced":false,"input_types":[],"dynamic":false,"info":"","load_from_db":false,"title_case":false,"value":"Quantos anos tem a associação APETI?"},"return_record":{"type":"bool","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"return_record","display_name":"Return Record","advanced":true,"dynamic":false,"info":"Return the message as a record containing the sender, sender_name, and session_id.","load_from_db":false,"title_case":false},"sender":{"type":"str","required":false,"placeholder":"","list":true,"show":true,"multiline":false,"value":"User","fileTypes":[],"file_path":"","password":false,"options":["Machine","User"],"name":"sender","display_name":"Sender Type","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"sender_name":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":"","fileTypes":[],"file_path":"","password":false,"name":"sender_name","display_name":"Sender Name","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"session_id":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"session_id","display_name":"Session ID","advanced":true,"dynamic":false,"info":"If provided, the message will be stored in the memory.","load_from_db":false,"title_case":false,"input_types":["Text"]},"_type":"CustomComponent"},"description":"Get chat inputs from the Interaction Panel.","icon":"ChatInput","base_classes":["object","Record","str","Text"],"display_name":"Chat Input","documentation":"","custom_fields":{"sender":null,"sender_name":null,"input_value":null,"session_id":null,"return_record":null},"output_types":["Text","Record"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"ChatInput-Y41Qu"},"selected":false,"width":384,"height":374,"positionAbsolute":{"x":171.02045128257828,"y":-354.99633691780747},"dragging":false},{"id":"Prompt-HDiQE","type":"genericNode","position":{"x":960.8000935808013,"y":-527.291849619816},"data":{"type":"Prompt","node":{"template":{"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from langchain_core.prompts import PromptTemplate\n\nfrom langflow.field_typing import Prompt, TemplateField, Text\nfrom langflow.interface.custom.custom_component import CustomComponent\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": TemplateField(display_name=\"Template\"),\n \"code\": TemplateField(advanced=True),\n }\n\n def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Text:\n from langflow.base.prompts.utils import dict_values_to_string\n\n prompt_template = PromptTemplate.from_template(Text(template))\n kwargs = dict_values_to_string(kwargs)\n kwargs = {k: \"\\n\".join(v) if isinstance(v, list) else v for k, v in kwargs.items()}\n try:\n formated_prompt = prompt_template.format(**kwargs)\n except Exception as exc:\n raise ValueError(f\"Error formatting prompt: {exc}\") from exc\n self.status = f'Prompt:\\n\"{formated_prompt}\"'\n return formated_prompt\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"template":{"type":"prompt","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":"Kindly provide a response to the user's inquiry, adhering to the provided context and message history. Please ensure the following rules are followed:\n\nAvoid repetition of information already stated in the context or message history.\nMaintain clarity and conciseness in your response.\nEnsure relevance to the user's question.\n\nContext: {context}\n\nMessage History:\n{history}\n\nUser's Question: {question}","fileTypes":[],"file_path":"","password":false,"name":"template","display_name":"Template","advanced":false,"input_types":["Text"],"dynamic":false,"info":"","load_from_db":false,"title_case":false},"_type":"CustomComponent","context":{"field_type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":true,"value":"","fileTypes":[],"file_path":"","password":false,"name":"context","display_name":"context","advanced":false,"input_types":["Document","BaseOutputParser","Record","Text"],"dynamic":false,"info":"","load_from_db":false,"title_case":false,"type":"str"},"history":{"field_type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":true,"value":"","fileTypes":[],"file_path":"","password":false,"name":"history","display_name":"history","advanced":false,"input_types":["Document","BaseOutputParser","Record","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","BaseOutputParser","Record","Text"],"dynamic":false,"info":"","load_from_db":false,"title_case":false,"type":"str"}},"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":["context","history","question"]},"output_types":["Text"],"full_path":null,"field_formatters":{},"frozen":false,"field_order":[],"beta":false,"error":null},"id":"Prompt-HDiQE","description":"Create a prompt template with dynamic variables.","display_name":"Prompt"},"selected":false,"width":384,"height":569,"positionAbsolute":{"x":960.8000935808013,"y":-527.291849619816},"dragging":false},{"id":"TextInput-tjpk3","type":"genericNode","position":{"x":-400.53202626838544,"y":-776.716579927136},"data":{"type":"TextInput","node":{"template":{"input_value":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":"Guilherme","fileTypes":[],"file_path":"","password":false,"name":"input_value","display_name":"Value","advanced":false,"input_types":["Record","Text"],"dynamic":false,"info":"Text or Record to be passed as input.","load_from_db":false,"title_case":false},"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextInput(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Interaction Panel.\"\n icon = \"type\"\n\n def build_config(self):\n return {\n \"input_value\": {\n \"display_name\": \"Value\",\n \"input_types\": [\"Record\", \"Text\"],\n \"info\": \"Text or Record to be passed as input.\",\n },\n \"record_template\": {\n \"display_name\": \"Record Template\",\n \"multiline\": True,\n \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Optional[Text] = \"\",\n record_template: Optional[str] = \"\",\n ) -> Text:\n return super().build(input_value=input_value, record_template=record_template)\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"record_template":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":true,"value":"","fileTypes":[],"file_path":"","password":false,"name":"record_template","display_name":"Record Template","advanced":true,"dynamic":false,"info":"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.","load_from_db":false,"title_case":false,"input_types":["Text"]},"_type":"CustomComponent"},"description":"Get text inputs from the Interaction Panel.","icon":"type","base_classes":["object","str","Text"],"display_name":"Name","documentation":"","custom_fields":{"input_value":null,"record_template":null},"output_types":["Text"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"TextInput-tjpk3"},"selected":false,"width":384,"height":288,"positionAbsolute":{"x":-400.53202626838544,"y":-776.716579927136},"dragging":false},{"id":"MemoryComponent-696A3","type":"genericNode","position":{"x":191.49773786184448,"y":-1031.8358279900226},"data":{"type":"MemoryComponent","node":{"template":{"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Optional\n\nfrom langflow.field_typing import Text\nfrom langflow.helpers.record import records_to_text\nfrom langflow.interface.custom.custom_component import CustomComponent\nfrom langflow.memory import get_messages\n\n\nclass MemoryComponent(CustomComponent):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages given a specific Session ID.\"\n beta: bool = True\n icon = \"history\"\n\n def build_config(self):\n return {\n \"sender\": {\n \"options\": [\"Machine\", \"User\", \"Machine and User\"],\n \"display_name\": \"Sender Type\",\n },\n \"sender_name\": {\"display_name\": \"Sender Name\", \"advanced\": True},\n \"n_messages\": {\n \"display_name\": \"Number of Messages\",\n \"info\": \"Number of messages to retrieve.\",\n },\n \"session_id\": {\n \"display_name\": \"Session ID\",\n \"info\": \"Session ID of the chat history.\",\n \"input_types\": [\"Text\"],\n },\n \"order\": {\n \"options\": [\"Ascending\", \"Descending\"],\n \"display_name\": \"Order\",\n \"info\": \"Order of the messages.\",\n \"advanced\": True,\n },\n \"record_template\": {\n \"display_name\": \"Record Template\",\n \"multiline\": True,\n \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n sender: Optional[str] = \"Machine and User\",\n sender_name: Optional[str] = None,\n session_id: Optional[str] = None,\n n_messages: int = 5,\n order: Optional[str] = \"Descending\",\n record_template: Optional[str] = \"{sender_name}: {text}\",\n ) -> Text:\n order = \"DESC\" if order == \"Descending\" else \"ASC\"\n if sender == \"Machine and User\":\n sender = None\n messages = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n messages_str = records_to_text(template=record_template or \"\", records=messages)\n self.status = messages_str\n return messages_str\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"n_messages":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":"5","fileTypes":[],"file_path":"","password":false,"name":"n_messages","display_name":"Number of Messages","advanced":false,"dynamic":false,"info":"Number of messages to retrieve.","load_from_db":false,"title_case":false},"order":{"type":"str","required":false,"placeholder":"","list":true,"show":true,"multiline":false,"value":"Descending","fileTypes":[],"file_path":"","password":false,"options":["Ascending","Descending"],"name":"order","display_name":"Order","advanced":true,"dynamic":false,"info":"Order of the messages.","load_from_db":false,"title_case":false,"input_types":["Text"]},"record_template":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":true,"value":"{sender_name}: {text}","fileTypes":[],"file_path":"","password":false,"name":"record_template","display_name":"Record Template","advanced":true,"dynamic":false,"info":"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.","load_from_db":false,"title_case":false,"input_types":["Text"]},"sender":{"type":"str","required":false,"placeholder":"","list":true,"show":true,"multiline":false,"value":"Machine and User","fileTypes":[],"file_path":"","password":false,"options":["Machine","User","Machine and User"],"name":"sender","display_name":"Sender Type","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"sender_name":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"sender_name","display_name":"Sender Name","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"session_id":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"session_id","display_name":"Session ID","advanced":false,"input_types":["Text"],"dynamic":false,"info":"Session ID of the chat history.","load_from_db":false,"title_case":false},"_type":"CustomComponent"},"description":"Retrieves stored chat messages given a specific Session ID.","icon":"history","base_classes":["object","str","Text"],"display_name":"Chat Memory","documentation":"","custom_fields":{"sender":null,"sender_name":null,"session_id":null,"n_messages":null,"order":null,"record_template":null},"output_types":["Text"],"field_formatters":{},"frozen":false,"field_order":[],"beta":true},"id":"MemoryComponent-696A3"},"selected":false,"width":384,"height":487,"positionAbsolute":{"x":191.49773786184448,"y":-1031.8358279900226},"dragging":false},{"id":"OpenAIModel-Aegqx","type":"genericNode","position":{"x":1692.6578105392912,"y":-569.5634342846232},"data":{"type":"OpenAIModel","node":{"template":{"input_value":{"type":"str","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"input_value","display_name":"Input","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\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,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"max_tokens":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":256,"fileTypes":[],"file_path":"","password":false,"name":"max_tokens","display_name":"Max Tokens","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"model_kwargs":{"type":"NestedDict","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":{},"fileTypes":[],"file_path":"","password":false,"name":"model_kwargs","display_name":"Model Kwargs","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"model_name":{"type":"str","required":true,"placeholder":"","list":true,"show":true,"multiline":false,"value":"gpt-3.5-turbo-1106","fileTypes":[],"file_path":"","password":false,"options":["gpt-4-turbo-2024-04-09","gpt-4-turbo-preview","gpt-3.5-turbo","gpt-4-0125-preview","gpt-4-1106-preview","gpt-4-vision-preview","gpt-3.5-turbo-0125","gpt-3.5-turbo-1106"],"name":"model_name","display_name":"Model Name","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"openai_api_base":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"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.","load_from_db":false,"title_case":false,"input_types":["Text"]},"openai_api_key":{"type":"str","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":true,"name":"openai_api_key","display_name":"OpenAI API Key","advanced":false,"dynamic":false,"info":"The OpenAI API Key to use for the OpenAI model.","load_from_db":true,"title_case":false,"input_types":["Text"],"value":"openai"},"stream":{"type":"bool","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"stream","display_name":"Stream","advanced":true,"dynamic":false,"info":"Stream the response from the model. Streaming works only in Chat.","load_from_db":false,"title_case":false},"system_message":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"system_message","display_name":"System Message","advanced":true,"dynamic":false,"info":"System message to pass to the model.","load_from_db":false,"title_case":false,"input_types":["Text"]},"temperature":{"type":"float","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"value":0.1,"fileTypes":[],"file_path":"","password":false,"name":"temperature","display_name":"Temperature","advanced":false,"dynamic":false,"info":"","rangeSpec":{"step_type":"float","min":-1,"max":1,"step":0.1},"load_from_db":false,"title_case":false},"_type":"CustomComponent"},"description":"Generates text using OpenAI LLMs.","icon":"OpenAI","base_classes":["object","str","Text"],"display_name":"OpenAI","documentation":"","custom_fields":{"input_value":null,"openai_api_key":null,"temperature":null,"model_name":null,"max_tokens":null,"model_kwargs":null,"openai_api_base":null,"stream":null,"system_message":null},"output_types":["Text"],"field_formatters":{},"frozen":false,"field_order":["max_tokens","model_kwargs","model_name","openai_api_base","openai_api_key","temperature","input_value","system_message","stream"],"beta":false},"id":"OpenAIModel-Aegqx"},"selected":false,"width":384,"height":561,"positionAbsolute":{"x":1692.6578105392912,"y":-569.5634342846232},"dragging":false},{"id":"ChatOutput-zm53k","type":"genericNode","position":{"x":2285.1766367569053,"y":-225.63227541784434},"data":{"type":"ChatOutput","node":{"template":{"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build_with_record(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template or \"\",\n )\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"input_value":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":true,"fileTypes":[],"file_path":"","password":false,"name":"input_value","display_name":"Message","advanced":false,"input_types":["Text"],"dynamic":false,"info":"","load_from_db":false,"title_case":false},"record_template":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":true,"value":"{text}","fileTypes":[],"file_path":"","password":false,"name":"record_template","display_name":"Record Template","advanced":true,"dynamic":false,"info":"In case of Message being a Record, this template will be used to convert it to text.","load_from_db":false,"title_case":false,"input_types":["Text"]},"return_record":{"type":"bool","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"return_record","display_name":"Return Record","advanced":true,"dynamic":false,"info":"Return the message as a record containing the sender, sender_name, and session_id.","load_from_db":false,"title_case":false},"sender":{"type":"str","required":false,"placeholder":"","list":true,"show":true,"multiline":false,"value":"Machine","fileTypes":[],"file_path":"","password":false,"options":["Machine","User"],"name":"sender","display_name":"Sender Type","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"sender_name":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":"AI","fileTypes":[],"file_path":"","password":false,"name":"sender_name","display_name":"Sender Name","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"session_id":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"session_id","display_name":"Session ID","advanced":true,"dynamic":false,"info":"If provided, the message will be stored in the memory.","load_from_db":false,"title_case":false,"input_types":["Text"]},"_type":"CustomComponent"},"description":"Display a chat message in the Interaction Panel.","icon":"ChatOutput","base_classes":["object","Record","str","Text"],"display_name":"Chat Output","documentation":"","custom_fields":{"sender":null,"sender_name":null,"input_value":null,"session_id":null,"return_record":null,"record_template":null},"output_types":["Text","Record"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"ChatOutput-zm53k"},"selected":false,"width":384,"height":382,"positionAbsolute":{"x":2285.1766367569053,"y":-225.63227541784434},"dragging":false},{"id":"URL-EsRFY","type":"genericNode","position":{"x":-744.1864590480818,"y":235.9890415194996},"data":{"type":"URL","node":{"template":{"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Any, Dict\n\nfrom langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.interface.custom.custom_component import CustomComponent\nfrom langflow.schema import Record\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[Record]:\n loader = WebBaseLoader(web_paths=urls)\n docs = loader.load()\n records = self.to_records(docs)\n self.status = records\n return records\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"urls":{"type":"str","required":true,"placeholder":"","list":true,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"urls","display_name":"URL","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"],"value":["https://www.apeti.org.br/"]},"_type":"CustomComponent"},"description":"Fetch content from one or more URLs.","icon":"layout-template","base_classes":["Record"],"display_name":"URL","documentation":"","custom_fields":{"urls":null},"output_types":["Record"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"URL-EsRFY"},"selected":false,"width":384,"height":280,"positionAbsolute":{"x":-744.1864590480818,"y":235.9890415194996},"dragging":false},{"id":"Chroma-08O1S","type":"genericNode","position":{"x":306.5775813362719,"y":907.4438125820202},"data":{"type":"Chroma","node":{"template":{"embedding":{"type":"Embeddings","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"embedding","display_name":"Embedding","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"inputs":{"type":"Record","required":false,"placeholder":"","list":true,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"inputs","display_name":"Input","advanced":false,"input_types":["Document","Record"],"dynamic":false,"info":"","load_from_db":false,"title_case":false},"chroma_server_cors_allow_origins":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_cors_allow_origins","display_name":"Server CORS Allow Origins","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"chroma_server_grpc_port":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_grpc_port","display_name":"Server gRPC Port","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"chroma_server_host":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_host","display_name":"Server Host","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"chroma_server_port":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_port","display_name":"Server Port","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"chroma_server_ssl_enabled":{"type":"bool","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_ssl_enabled","display_name":"Server SSL Enabled","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import List, Optional, Union\n\nimport chromadb # type: ignore\nfrom langchain.embeddings.base import Embeddings\nfrom langchain.schema import BaseRetriever\nfrom langchain_community.vectorstores import VectorStore\nfrom langchain_community.vectorstores.chroma import Chroma\n\nfrom langflow.interface.custom.custom_component import CustomComponent\nfrom langflow.schema.schema import Record\n\n\nclass ChromaComponent(CustomComponent):\n \"\"\"\n A custom component for implementing a Vector Store using Chroma.\n \"\"\"\n\n display_name: str = \"Chroma\"\n description: str = \"Implementation of Vector Store using Chroma\"\n documentation = \"https://python.langchain.com/docs/integrations/vectorstores/chroma\"\n icon = \"Chroma\"\n\n def build_config(self):\n \"\"\"\n Builds the configuration for the component.\n\n Returns:\n - dict: A dictionary containing the configuration options for the component.\n \"\"\"\n return {\n \"collection_name\": {\"display_name\": \"Collection Name\", \"value\": \"langflow\"},\n \"index_directory\": {\"display_name\": \"Persist Directory\"},\n \"code\": {\"advanced\": True, \"display_name\": \"Code\"},\n \"inputs\": {\"display_name\": \"Input\", \"input_types\": [\"Document\", \"Record\"]},\n \"embedding\": {\"display_name\": \"Embedding\"},\n \"chroma_server_cors_allow_origins\": {\n \"display_name\": \"Server CORS Allow Origins\",\n \"advanced\": True,\n },\n \"chroma_server_host\": {\"display_name\": \"Server Host\", \"advanced\": True},\n \"chroma_server_port\": {\"display_name\": \"Server Port\", \"advanced\": True},\n \"chroma_server_grpc_port\": {\n \"display_name\": \"Server gRPC Port\",\n \"advanced\": True,\n },\n \"chroma_server_ssl_enabled\": {\n \"display_name\": \"Server SSL Enabled\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n collection_name: str,\n embedding: Embeddings,\n chroma_server_ssl_enabled: bool,\n index_directory: Optional[str] = None,\n inputs: Optional[List[Record]] = None,\n chroma_server_cors_allow_origins: Optional[str] = None,\n chroma_server_host: Optional[str] = None,\n chroma_server_port: Optional[int] = None,\n chroma_server_grpc_port: Optional[int] = None,\n ) -> Union[VectorStore, BaseRetriever]:\n \"\"\"\n Builds the Vector Store or BaseRetriever object.\n\n Args:\n - collection_name (str): The name of the collection.\n - index_directory (Optional[str]): The directory to persist the Vector Store to.\n - chroma_server_ssl_enabled (bool): Whether to enable SSL for the Chroma server.\n - embedding (Optional[Embeddings]): The embeddings to use for the Vector Store.\n - documents (Optional[Document]): The documents to use for the Vector Store.\n - chroma_server_cors_allow_origins (Optional[str]): The CORS allow origins for the Chroma server.\n - chroma_server_host (Optional[str]): The host for the Chroma server.\n - chroma_server_port (Optional[int]): The port for the Chroma server.\n - chroma_server_grpc_port (Optional[int]): The gRPC port for the Chroma server.\n\n Returns:\n - Union[VectorStore, BaseRetriever]: The Vector Store or BaseRetriever object.\n \"\"\"\n\n # Chroma settings\n chroma_settings = None\n\n if chroma_server_host is not None:\n chroma_settings = chromadb.config.Settings(\n chroma_server_cors_allow_origins=chroma_server_cors_allow_origins or None,\n chroma_server_host=chroma_server_host,\n chroma_server_port=chroma_server_port or None,\n chroma_server_grpc_port=chroma_server_grpc_port or None,\n chroma_server_ssl_enabled=chroma_server_ssl_enabled,\n )\n\n # If documents, then we need to create a Chroma instance using .from_documents\n\n # Check index_directory and expand it if it is a relative path\n if index_directory is not None:\n index_directory = self.resolve_path(index_directory)\n\n documents = []\n for _input in inputs or []:\n if isinstance(_input, Record):\n documents.append(_input.to_lc_document())\n else:\n documents.append(_input)\n if documents is not None and embedding is not None:\n if len(documents) == 0:\n raise ValueError(\"If documents are provided, there must be at least one document.\")\n chroma = Chroma.from_documents(\n documents=documents, # type: ignore\n persist_directory=index_directory,\n collection_name=collection_name,\n embedding=embedding,\n client_settings=chroma_settings,\n )\n else:\n chroma = Chroma(\n persist_directory=index_directory,\n client_settings=chroma_settings,\n embedding_function=embedding,\n )\n return chroma\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"collection_name":{"type":"str","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"value":"langflow","fileTypes":[],"file_path":"","password":false,"name":"collection_name","display_name":"Collection Name","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"index_directory":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"index_directory","display_name":"Persist Directory","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"_type":"CustomComponent"},"description":"Implementation of Vector Store using Chroma","icon":"Chroma","base_classes":["BaseRetriever","Generic","object","Runnable","RunnableSerializable","Serializable","VectorStore"],"display_name":"Chroma","documentation":"https://python.langchain.com/docs/integrations/vectorstores/chroma","custom_fields":{"collection_name":null,"embedding":null,"chroma_server_ssl_enabled":null,"index_directory":null,"inputs":null,"chroma_server_cors_allow_origins":null,"chroma_server_host":null,"chroma_server_port":null,"chroma_server_grpc_port":null},"output_types":["VectorStore","BaseRetriever"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"Chroma-08O1S"},"selected":false,"width":384,"height":478,"positionAbsolute":{"x":306.5775813362719,"y":907.4438125820202},"dragging":false},{"id":"OpenAIEmbeddings-fzHCU","type":"genericNode","position":{"x":-491.48021192043234,"y":859.9937334513055},"data":{"type":"OpenAIEmbeddings","node":{"template":{"allowed_special":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":[],"fileTypes":[],"file_path":"","password":false,"name":"allowed_special","display_name":"Allowed Special","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"chunk_size":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":1000,"fileTypes":[],"file_path":"","password":false,"name":"chunk_size","display_name":"Chunk Size","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"client":{"type":"Any","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"client","display_name":"Client","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Any, Dict, List, Optional\n\nfrom langchain_openai.embeddings.base import OpenAIEmbeddings\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.field_typing import Embeddings, NestedDict\nfrom langflow.interface.custom.custom_component import CustomComponent\n\n\nclass OpenAIEmbeddingsComponent(CustomComponent):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n\n def build_config(self):\n return {\n \"allowed_special\": {\n \"display_name\": \"Allowed Special\",\n \"advanced\": True,\n \"field_type\": \"str\",\n \"is_list\": True,\n },\n \"default_headers\": {\n \"display_name\": \"Default Headers\",\n \"advanced\": True,\n \"field_type\": \"dict\",\n },\n \"default_query\": {\n \"display_name\": \"Default Query\",\n \"advanced\": True,\n \"field_type\": \"NestedDict\",\n },\n \"disallowed_special\": {\n \"display_name\": \"Disallowed Special\",\n \"advanced\": True,\n \"field_type\": \"str\",\n \"is_list\": True,\n },\n \"chunk_size\": {\"display_name\": \"Chunk Size\", \"advanced\": True},\n \"client\": {\"display_name\": \"Client\", \"advanced\": True},\n \"deployment\": {\"display_name\": \"Deployment\", \"advanced\": True},\n \"embedding_ctx_length\": {\n \"display_name\": \"Embedding Context Length\",\n \"advanced\": True,\n },\n \"max_retries\": {\"display_name\": \"Max Retries\", \"advanced\": True},\n \"model\": {\n \"display_name\": \"Model\",\n \"advanced\": False,\n \"options\": [\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n },\n \"model_kwargs\": {\"display_name\": \"Model Kwargs\", \"advanced\": True},\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"password\": True,\n \"advanced\": True,\n },\n \"openai_api_key\": {\"display_name\": \"OpenAI API Key\", \"password\": True},\n \"openai_api_type\": {\n \"display_name\": \"OpenAI API Type\",\n \"advanced\": True,\n \"password\": True,\n },\n \"openai_api_version\": {\n \"display_name\": \"OpenAI API Version\",\n \"advanced\": True,\n },\n \"openai_organization\": {\n \"display_name\": \"OpenAI Organization\",\n \"advanced\": True,\n },\n \"openai_proxy\": {\"display_name\": \"OpenAI Proxy\", \"advanced\": True},\n \"request_timeout\": {\"display_name\": \"Request Timeout\", \"advanced\": True},\n \"show_progress_bar\": {\n \"display_name\": \"Show Progress Bar\",\n \"advanced\": True,\n },\n \"skip_empty\": {\"display_name\": \"Skip Empty\", \"advanced\": True},\n \"tiktoken_model_name\": {\n \"display_name\": \"TikToken Model Name\",\n \"advanced\": True,\n },\n \"tiktoken_enable\": {\"display_name\": \"TikToken Enable\", \"advanced\": True},\n }\n\n def build(\n self,\n openai_api_key: str,\n default_headers: Optional[Dict[str, str]] = None,\n default_query: Optional[NestedDict] = {},\n allowed_special: List[str] = [],\n disallowed_special: List[str] = [\"all\"],\n chunk_size: int = 1000,\n client: Optional[Any] = None,\n deployment: str = \"text-embedding-ada-002\",\n embedding_ctx_length: int = 8191,\n max_retries: int = 6,\n model: str = \"text-embedding-ada-002\",\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n openai_api_type: Optional[str] = None,\n openai_api_version: Optional[str] = None,\n openai_organization: Optional[str] = None,\n openai_proxy: Optional[str] = None,\n request_timeout: Optional[float] = None,\n show_progress_bar: bool = False,\n skip_empty: bool = False,\n tiktoken_enable: bool = True,\n tiktoken_model_name: Optional[str] = None,\n ) -> Embeddings:\n # This is to avoid errors with Vector Stores (e.g Chroma)\n if disallowed_special == [\"all\"]:\n disallowed_special = \"all\" # type: ignore\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n return OpenAIEmbeddings(\n tiktoken_enabled=tiktoken_enable,\n default_headers=default_headers,\n default_query=default_query,\n allowed_special=set(allowed_special),\n disallowed_special=\"all\",\n chunk_size=chunk_size,\n client=client,\n deployment=deployment,\n embedding_ctx_length=embedding_ctx_length,\n max_retries=max_retries,\n model=model,\n model_kwargs=model_kwargs,\n base_url=openai_api_base,\n api_key=api_key,\n openai_api_type=openai_api_type,\n api_version=openai_api_version,\n organization=openai_organization,\n openai_proxy=openai_proxy,\n timeout=request_timeout,\n show_progress_bar=show_progress_bar,\n skip_empty=skip_empty,\n tiktoken_model_name=tiktoken_model_name,\n )\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"default_headers":{"type":"dict","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"default_headers","display_name":"Default Headers","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"default_query":{"type":"NestedDict","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":{},"fileTypes":[],"file_path":"","password":false,"name":"default_query","display_name":"Default Query","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"deployment":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":"text-embedding-ada-002","fileTypes":[],"file_path":"","password":false,"name":"deployment","display_name":"Deployment","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"disallowed_special":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":["all"],"fileTypes":[],"file_path":"","password":false,"name":"disallowed_special","display_name":"Disallowed Special","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"embedding_ctx_length":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":8191,"fileTypes":[],"file_path":"","password":false,"name":"embedding_ctx_length","display_name":"Embedding Context Length","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"max_retries":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":6,"fileTypes":[],"file_path":"","password":false,"name":"max_retries","display_name":"Max Retries","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"model":{"type":"str","required":false,"placeholder":"","list":true,"show":true,"multiline":false,"value":"text-embedding-ada-002","fileTypes":[],"file_path":"","password":false,"options":["text-embedding-3-small","text-embedding-3-large","text-embedding-ada-002"],"name":"model","display_name":"Model","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"model_kwargs":{"type":"NestedDict","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":{},"fileTypes":[],"file_path":"","password":false,"name":"model_kwargs","display_name":"Model Kwargs","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"openai_api_base":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":true,"name":"openai_api_base","display_name":"OpenAI API Base","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"],"value":""},"openai_api_key":{"type":"str","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":true,"name":"openai_api_key","display_name":"OpenAI API Key","advanced":false,"dynamic":false,"info":"","load_from_db":true,"title_case":false,"input_types":["Text"],"value":"openai"},"openai_api_type":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":true,"name":"openai_api_type","display_name":"OpenAI API Type","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"],"value":""},"openai_api_version":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"openai_api_version","display_name":"OpenAI API Version","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"openai_organization":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"openai_organization","display_name":"OpenAI Organization","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"openai_proxy":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"openai_proxy","display_name":"OpenAI Proxy","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"request_timeout":{"type":"float","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"request_timeout","display_name":"Request Timeout","advanced":true,"dynamic":false,"info":"","rangeSpec":{"step_type":"float","min":-1,"max":1,"step":0.1},"load_from_db":false,"title_case":false},"show_progress_bar":{"type":"bool","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"show_progress_bar","display_name":"Show Progress Bar","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"skip_empty":{"type":"bool","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"skip_empty","display_name":"Skip Empty","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"tiktoken_enable":{"type":"bool","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":true,"fileTypes":[],"file_path":"","password":false,"name":"tiktoken_enable","display_name":"TikToken Enable","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"tiktoken_model_name":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"tiktoken_model_name","display_name":"TikToken Model Name","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"_type":"CustomComponent"},"description":"Generate embeddings using OpenAI models.","base_classes":["Embeddings"],"display_name":"OpenAI Embeddings","documentation":"","custom_fields":{"openai_api_key":null,"default_headers":null,"default_query":null,"allowed_special":null,"disallowed_special":null,"chunk_size":null,"client":null,"deployment":null,"embedding_ctx_length":null,"max_retries":null,"model":null,"model_kwargs":null,"openai_api_base":null,"openai_api_type":null,"openai_api_version":null,"openai_organization":null,"openai_proxy":null,"request_timeout":null,"show_progress_bar":null,"skip_empty":null,"tiktoken_enable":null,"tiktoken_model_name":null},"output_types":["Embeddings"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"OpenAIEmbeddings-fzHCU"},"selected":false,"width":384,"height":382,"positionAbsolute":{"x":-491.48021192043234,"y":859.9937334513055},"dragging":false},{"id":"SplitText-xGTH7","type":"genericNode","position":{"x":-161.87531465226044,"y":120.00833754062234},"data":{"type":"SplitText","node":{"template":{"inputs":{"type":"str","required":true,"placeholder":"","list":true,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"inputs","display_name":"Inputs","advanced":false,"input_types":["Record","Text"],"dynamic":false,"info":"Texts to split.","load_from_db":false,"title_case":false},"chunk_overlap":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":200,"fileTypes":[],"file_path":"","password":false,"name":"chunk_overlap","display_name":"Chunk Overlap","advanced":false,"dynamic":false,"info":"The amount of character overlap between chunks.","load_from_db":false,"title_case":false},"chunk_size":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":"500","fileTypes":[],"file_path":"","password":false,"name":"chunk_size","display_name":"Max Chunk Size","advanced":false,"dynamic":false,"info":"The maximum length (in number of characters) of each chunk.","load_from_db":false,"title_case":false},"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import Optional, Union\n\nfrom langchain.text_splitter import CharacterTextSplitter, RecursiveCharacterTextSplitter\nfrom langchain_core.documents import Document\n\nfrom langflow.field_typing import Text\nfrom langflow.interface.custom.custom_component import CustomComponent\nfrom langflow.schema import Record\nfrom langflow.utils.util import unescape_string\n\n\nclass SplitTextComponent(CustomComponent):\n display_name: str = \"Split Text\"\n description: str = \"Split text into chunks of a specified length.\"\n\n def build_config(self):\n return {\n \"inputs\": {\n \"display_name\": \"Inputs\",\n \"info\": \"Texts to split.\",\n \"input_types\": [\"Record\", \"Text\"],\n },\n \"separators\": {\n \"display_name\": \"Separators\",\n \"info\": 'The characters to split on. Defaults to [\" \"].',\n \"is_list\": True,\n },\n \"chunk_size\": {\n \"display_name\": \"Max Chunk Size\",\n \"info\": \"The maximum length (in number of characters) of each chunk.\",\n \"field_type\": \"int\",\n \"value\": 1000,\n },\n \"chunk_overlap\": {\n \"display_name\": \"Chunk Overlap\",\n \"info\": \"The amount of character overlap between chunks.\",\n \"field_type\": \"int\",\n \"value\": 200,\n },\n \"recursive\": {\n \"display_name\": \"Recursive\",\n },\n \"code\": {\"show\": False},\n }\n\n def build(\n self,\n inputs: list[Text],\n separators: Optional[list[str]] = [\" \"],\n chunk_size: Optional[int] = 1000,\n chunk_overlap: Optional[int] = 200,\n recursive: bool = False,\n ) -> list[Record]:\n if separators is None:\n separators = []\n separators = [unescape_string(x) for x in separators]\n\n # Make sure chunk_size and chunk_overlap are ints\n if isinstance(chunk_size, str):\n chunk_size = int(chunk_size)\n if isinstance(chunk_overlap, str):\n chunk_overlap = int(chunk_overlap)\n splitter: Optional[Union[CharacterTextSplitter, RecursiveCharacterTextSplitter]] = None\n if recursive:\n splitter = RecursiveCharacterTextSplitter(\n separators=separators,\n chunk_size=chunk_size,\n chunk_overlap=chunk_overlap,\n )\n\n else:\n splitter = CharacterTextSplitter(\n separator=separators[0],\n chunk_size=chunk_size,\n chunk_overlap=chunk_overlap,\n )\n\n documents = []\n for _input in inputs:\n if isinstance(_input, Record):\n documents.append(_input.to_lc_document())\n else:\n documents.append(Document(page_content=_input))\n\n records = self.to_records(splitter.split_documents(documents))\n self.status = records\n return records\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"recursive":{"type":"bool","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"recursive","display_name":"Recursive","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"separators":{"type":"str","required":false,"placeholder":"","list":true,"show":true,"multiline":false,"value":[" "],"fileTypes":[],"file_path":"","password":false,"name":"separators","display_name":"Separators","advanced":false,"dynamic":false,"info":"The characters to split on. Defaults to [\" \"].","load_from_db":false,"title_case":false,"input_types":["Text"]},"_type":"CustomComponent"},"description":"Split text into chunks of a specified length.","base_classes":["Record"],"display_name":"Split Text","documentation":"","custom_fields":{"inputs":null,"separators":null,"chunk_size":null,"chunk_overlap":null,"recursive":null},"output_types":["Record"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"SplitText-xGTH7"},"selected":false,"width":384,"height":612,"positionAbsolute":{"x":-161.87531465226044,"y":120.00833754062234},"dragging":false},{"id":"ChromaSearch-BQCkw","type":"genericNode","position":{"x":741.8704299709141,"y":303.86308777737054},"data":{"type":"ChromaSearch","node":{"template":{"embedding":{"type":"Embeddings","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"embedding","display_name":"Embedding","advanced":false,"dynamic":false,"info":"Embedding model to vectorize inputs (make sure to use same as index)","load_from_db":false,"title_case":false},"input_value":{"type":"str","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"input_value","display_name":"Input","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"chroma_server_cors_allow_origins":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_cors_allow_origins","display_name":"Server CORS Allow Origins","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"chroma_server_grpc_port":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_grpc_port","display_name":"Server gRPC Port","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"chroma_server_host":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_host","display_name":"Server Host","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"chroma_server_port":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_port","display_name":"Server Port","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"chroma_server_ssl_enabled":{"type":"bool","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"value":false,"fileTypes":[],"file_path":"","password":false,"name":"chroma_server_ssl_enabled","display_name":"Server SSL Enabled","advanced":true,"dynamic":false,"info":"","load_from_db":false,"title_case":false},"code":{"type":"code","required":true,"placeholder":"","list":false,"show":true,"multiline":true,"value":"from typing import List, Optional\n\nimport chromadb # type: ignore\nfrom langchain_community.vectorstores.chroma import Chroma\n\nfrom langflow.components.vectorstores.base.model import LCVectorStoreComponent\nfrom langflow.field_typing import Embeddings, Text\nfrom langflow.schema import Record\n\n\nclass ChromaSearchComponent(LCVectorStoreComponent):\n display_name: str = \"Chroma Search\"\n description: str = \"Search a Chroma collection for similar documents.\"\n icon = \"Chroma\"\n\n def build_config(self):\n \"\"\"\n Builds the configuration for the component.\n\n Returns:\n - dict: A dictionary containing the configuration options for the component.\n \"\"\"\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"search_type\": {\n \"display_name\": \"Search Type\",\n \"options\": [\"Similarity\", \"MMR\"],\n },\n \"collection_name\": {\"display_name\": \"Collection Name\", \"value\": \"langflow\"},\n # \"persist\": {\"display_name\": \"Persist\"},\n \"index_directory\": {\"display_name\": \"Index Directory\"},\n \"code\": {\"show\": False, \"display_name\": \"Code\"},\n \"embedding\": {\n \"display_name\": \"Embedding\",\n \"info\": \"Embedding model to vectorize inputs (make sure to use same as index)\",\n },\n \"chroma_server_cors_allow_origins\": {\n \"display_name\": \"Server CORS Allow Origins\",\n \"advanced\": True,\n },\n \"chroma_server_host\": {\"display_name\": \"Server Host\", \"advanced\": True},\n \"chroma_server_port\": {\"display_name\": \"Server Port\", \"advanced\": True},\n \"chroma_server_grpc_port\": {\n \"display_name\": \"Server gRPC Port\",\n \"advanced\": True,\n },\n \"chroma_server_ssl_enabled\": {\n \"display_name\": \"Server SSL Enabled\",\n \"advanced\": True,\n },\n \"number_of_results\": {\n \"display_name\": \"Number of Results\",\n \"info\": \"Number of results to return.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n search_type: str,\n collection_name: str,\n embedding: Embeddings,\n chroma_server_ssl_enabled: bool,\n number_of_results: int = 4,\n index_directory: Optional[str] = None,\n chroma_server_cors_allow_origins: Optional[str] = None,\n chroma_server_host: Optional[str] = None,\n chroma_server_port: Optional[int] = None,\n chroma_server_grpc_port: Optional[int] = None,\n ) -> List[Record]:\n \"\"\"\n Builds the Vector Store or BaseRetriever object.\n\n Args:\n - collection_name (str): The name of the collection.\n - persist_directory (Optional[str]): The directory to persist the Vector Store to.\n - chroma_server_ssl_enabled (bool): Whether to enable SSL for the Chroma server.\n - persist (bool): Whether to persist the Vector Store or not.\n - embedding (Optional[Embeddings]): The embeddings to use for the Vector Store.\n - documents (Optional[Document]): The documents to use for the Vector Store.\n - chroma_server_cors_allow_origins (Optional[str]): The CORS allow origins for the Chroma server.\n - chroma_server_host (Optional[str]): The host for the Chroma server.\n - chroma_server_port (Optional[int]): The port for the Chroma server.\n - chroma_server_grpc_port (Optional[int]): The gRPC port for the Chroma server.\n\n Returns:\n - Union[VectorStore, BaseRetriever]: The Vector Store or BaseRetriever object.\n \"\"\"\n\n # Chroma settings\n chroma_settings = None\n\n if chroma_server_host is not None:\n chroma_settings = chromadb.config.Settings(\n chroma_server_cors_allow_origins=chroma_server_cors_allow_origins or None,\n chroma_server_host=chroma_server_host,\n chroma_server_port=chroma_server_port or None,\n chroma_server_grpc_port=chroma_server_grpc_port or None,\n chroma_server_ssl_enabled=chroma_server_ssl_enabled,\n )\n if index_directory:\n index_directory = self.resolve_path(index_directory)\n vector_store = Chroma(\n embedding_function=embedding,\n collection_name=collection_name,\n persist_directory=index_directory,\n client_settings=chroma_settings,\n )\n\n return self.search_with_vector_store(input_value, search_type, vector_store, k=number_of_results)\n","fileTypes":[],"file_path":"","password":false,"name":"code","advanced":true,"dynamic":true,"info":"","load_from_db":false,"title_case":false},"collection_name":{"type":"str","required":true,"placeholder":"","list":false,"show":true,"multiline":false,"value":"langflow","fileTypes":[],"file_path":"","password":false,"name":"collection_name","display_name":"Collection Name","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"index_directory":{"type":"str","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"name":"index_directory","display_name":"Index Directory","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"]},"number_of_results":{"type":"int","required":false,"placeholder":"","list":false,"show":true,"multiline":false,"value":4,"fileTypes":[],"file_path":"","password":false,"name":"number_of_results","display_name":"Number of Results","advanced":true,"dynamic":false,"info":"Number of results to return.","load_from_db":false,"title_case":false},"search_type":{"type":"str","required":true,"placeholder":"","list":true,"show":true,"multiline":false,"fileTypes":[],"file_path":"","password":false,"options":["Similarity","MMR"],"name":"search_type","display_name":"Search Type","advanced":false,"dynamic":false,"info":"","load_from_db":false,"title_case":false,"input_types":["Text"],"value":"Similarity"},"_type":"CustomComponent"},"description":"Search a Chroma collection for similar documents.","icon":"Chroma","base_classes":["Record"],"display_name":"Chroma Search","documentation":"","custom_fields":{"input_value":null,"search_type":null,"collection_name":null,"embedding":null,"chroma_server_ssl_enabled":null,"number_of_results":null,"index_directory":null,"chroma_server_cors_allow_origins":null,"chroma_server_host":null,"chroma_server_port":null,"chroma_server_grpc_port":null},"output_types":["Record"],"field_formatters":{},"frozen":false,"field_order":[],"beta":false},"id":"ChromaSearch-BQCkw"},"selected":false,"width":384,"height":617,"positionAbsolute":{"x":741.8704299709141,"y":303.86308777737054},"dragging":false}],"edges":[{"source":"TextInput-tjpk3","sourceHandle":"{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-tjpk3œ}","target":"ChatInput-Y41Qu","targetHandle":"{œfieldNameœ:œsender_nameœ,œidœ:œChatInput-Y41Quœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"sender_name","id":"ChatInput-Y41Qu","inputTypes":["Text"],"type":"str"},"sourceHandle":{"baseClasses":["object","str","Text"],"dataType":"TextInput","id":"TextInput-tjpk3"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-TextInput-tjpk3{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-tjpk3œ}-ChatInput-Y41Qu{œfieldNameœ:œsender_nameœ,œidœ:œChatInput-Y41Quœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"},{"source":"ChatInput-Y41Qu","sourceHandle":"{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-Y41Quœ}","target":"Prompt-HDiQE","targetHandle":"{œfieldNameœ:œquestionœ,œidœ:œPrompt-HDiQEœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"question","id":"Prompt-HDiQE","inputTypes":["Document","BaseOutputParser","Record","Text"],"type":"str"},"sourceHandle":{"baseClasses":["object","Record","str","Text"],"dataType":"ChatInput","id":"ChatInput-Y41Qu"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-ChatInput-Y41Qu{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-Y41Quœ}-Prompt-HDiQE{œfieldNameœ:œquestionœ,œidœ:œPrompt-HDiQEœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"},{"source":"TextInput-tjpk3","sourceHandle":"{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-tjpk3œ}","target":"MemoryComponent-696A3","targetHandle":"{œfieldNameœ:œsession_idœ,œidœ:œMemoryComponent-696A3œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"session_id","id":"MemoryComponent-696A3","inputTypes":["Text"],"type":"str"},"sourceHandle":{"baseClasses":["object","str","Text"],"dataType":"TextInput","id":"TextInput-tjpk3"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-TextInput-tjpk3{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-tjpk3œ}-MemoryComponent-696A3{œfieldNameœ:œsession_idœ,œidœ:œMemoryComponent-696A3œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"},{"source":"MemoryComponent-696A3","sourceHandle":"{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-696A3œ}","target":"Prompt-HDiQE","targetHandle":"{œfieldNameœ:œhistoryœ,œidœ:œPrompt-HDiQEœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"history","id":"Prompt-HDiQE","inputTypes":["Document","BaseOutputParser","Record","Text"],"type":"str"},"sourceHandle":{"baseClasses":["object","str","Text"],"dataType":"MemoryComponent","id":"MemoryComponent-696A3"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-MemoryComponent-696A3{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-696A3œ}-Prompt-HDiQE{œfieldNameœ:œhistoryœ,œidœ:œPrompt-HDiQEœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"},{"source":"Prompt-HDiQE","sourceHandle":"{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-HDiQEœ}","target":"OpenAIModel-Aegqx","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Aegqxœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"input_value","id":"OpenAIModel-Aegqx","inputTypes":["Text"],"type":"str"},"sourceHandle":{"baseClasses":["object","str","Text"],"dataType":"Prompt","id":"Prompt-HDiQE"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-Prompt-HDiQE{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-HDiQEœ}-OpenAIModel-Aegqx{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Aegqxœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"},{"source":"OpenAIModel-Aegqx","sourceHandle":"{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Aegqxœ}","target":"ChatOutput-zm53k","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-zm53kœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"input_value","id":"ChatOutput-zm53k","inputTypes":["Text"],"type":"str"},"sourceHandle":{"baseClasses":["object","str","Text"],"dataType":"OpenAIModel","id":"OpenAIModel-Aegqx"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-OpenAIModel-Aegqx{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Aegqxœ}-ChatOutput-zm53k{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-zm53kœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"},{"source":"OpenAIEmbeddings-fzHCU","sourceHandle":"{œbaseClassesœ:[œEmbeddingsœ],œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-fzHCUœ}","target":"Chroma-08O1S","targetHandle":"{œfieldNameœ:œembeddingœ,œidœ:œChroma-08O1Sœ,œinputTypesœ:null,œtypeœ:œEmbeddingsœ}","data":{"targetHandle":{"fieldName":"embedding","id":"Chroma-08O1S","inputTypes":null,"type":"Embeddings"},"sourceHandle":{"baseClasses":["Embeddings"],"dataType":"OpenAIEmbeddings","id":"OpenAIEmbeddings-fzHCU"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-OpenAIEmbeddings-fzHCU{œbaseClassesœ:[œEmbeddingsœ],œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-fzHCUœ}-Chroma-08O1S{œfieldNameœ:œembeddingœ,œidœ:œChroma-08O1Sœ,œinputTypesœ:null,œtypeœ:œEmbeddingsœ}"},{"source":"URL-EsRFY","sourceHandle":"{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-EsRFYœ}","target":"SplitText-xGTH7","targetHandle":"{œfieldNameœ:œinputsœ,œidœ:œSplitText-xGTH7œ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"inputs","id":"SplitText-xGTH7","inputTypes":["Record","Text"],"type":"str"},"sourceHandle":{"baseClasses":["Record"],"dataType":"URL","id":"URL-EsRFY"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-URL-EsRFY{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-EsRFYœ}-SplitText-xGTH7{œfieldNameœ:œinputsœ,œidœ:œSplitText-xGTH7œ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}"},{"source":"SplitText-xGTH7","sourceHandle":"{œbaseClassesœ:[œRecordœ],œdataTypeœ:œSplitTextœ,œidœ:œSplitText-xGTH7œ}","target":"Chroma-08O1S","targetHandle":"{œfieldNameœ:œinputsœ,œidœ:œChroma-08O1Sœ,œinputTypesœ:[œDocumentœ,œRecordœ],œtypeœ:œRecordœ}","data":{"targetHandle":{"fieldName":"inputs","id":"Chroma-08O1S","inputTypes":["Document","Record"],"type":"Record"},"sourceHandle":{"baseClasses":["Record"],"dataType":"SplitText","id":"SplitText-xGTH7"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-SplitText-xGTH7{œbaseClassesœ:[œRecordœ],œdataTypeœ:œSplitTextœ,œidœ:œSplitText-xGTH7œ}-Chroma-08O1S{œfieldNameœ:œinputsœ,œidœ:œChroma-08O1Sœ,œinputTypesœ:[œDocumentœ,œRecordœ],œtypeœ:œRecordœ}"},{"source":"ChatInput-Y41Qu","sourceHandle":"{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-Y41Quœ}","target":"ChromaSearch-BQCkw","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œChromaSearch-BQCkwœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"input_value","id":"ChromaSearch-BQCkw","inputTypes":["Text"],"type":"str"},"sourceHandle":{"baseClasses":["object","Record","str","Text"],"dataType":"ChatInput","id":"ChatInput-Y41Qu"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-ChatInput-Y41Qu{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-Y41Quœ}-ChromaSearch-BQCkw{œfieldNameœ:œinput_valueœ,œidœ:œChromaSearch-BQCkwœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"},{"source":"OpenAIEmbeddings-fzHCU","sourceHandle":"{œbaseClassesœ:[œEmbeddingsœ],œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-fzHCUœ}","target":"ChromaSearch-BQCkw","targetHandle":"{œfieldNameœ:œembeddingœ,œidœ:œChromaSearch-BQCkwœ,œinputTypesœ:null,œtypeœ:œEmbeddingsœ}","data":{"targetHandle":{"fieldName":"embedding","id":"ChromaSearch-BQCkw","inputTypes":null,"type":"Embeddings"},"sourceHandle":{"baseClasses":["Embeddings"],"dataType":"OpenAIEmbeddings","id":"OpenAIEmbeddings-fzHCU"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-OpenAIEmbeddings-fzHCU{œbaseClassesœ:[œEmbeddingsœ],œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-fzHCUœ}-ChromaSearch-BQCkw{œfieldNameœ:œembeddingœ,œidœ:œChromaSearch-BQCkwœ,œinputTypesœ:null,œtypeœ:œEmbeddingsœ}"},{"source":"ChromaSearch-BQCkw","sourceHandle":"{œbaseClassesœ:[œRecordœ],œdataTypeœ:œChromaSearchœ,œidœ:œChromaSearch-BQCkwœ}","target":"Prompt-HDiQE","targetHandle":"{œfieldNameœ:œcontextœ,œidœ:œPrompt-HDiQEœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}","data":{"targetHandle":{"fieldName":"context","id":"Prompt-HDiQE","inputTypes":["Document","BaseOutputParser","Record","Text"],"type":"str"},"sourceHandle":{"baseClasses":["Record"],"dataType":"ChromaSearch","id":"ChromaSearch-BQCkw"}},"style":{"stroke":"#555"},"className":"stroke-gray-900 stroke-connection","id":"reactflow__edge-ChromaSearch-BQCkw{œbaseClassesœ:[œRecordœ],œdataTypeœ:œChromaSearchœ,œidœ:œChromaSearch-BQCkwœ}-Prompt-HDiQE{œfieldNameœ:œcontextœ,œidœ:œPrompt-HDiQEœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"}],"viewport":{"x":-255.80051440114948,"y":385.7809054521003,"zoom":0.42337265618126585}},"description":"RAG Based LLM using URL","name":"RAG Based LLM","last_tested_version":"1.0.0a33","is_component":false} |