LangChain - Langflow

import Icon from "@site/src/components/icon";

<Icon name="Blocks" aria-hidden="true" /> Bundles contain custom components that support specific third-party integrations with Langflow.

This page describes the components that are available in the LangChain bundle.

CSV Agent

:::warning Security Setting allow_dangerous_code to true allows the agent to execute arbitrary, LLM-generated Python code at runtime on the Langflow server. This code can do anything that Python can do, so use this option only with trusted data and in a secure environment. For more information, see CVE-2024-21513. :::

This component is based on the Agent core component.

This component creates a CSV agent from a CSV file and LLM. For more information, see the LangChain CSV agent documentation.

CSV Agent parameters

Name	Type	Description
allow_dangerous_code	Input parameter.	Default: `false`. Set to `true` to allow the agent to execute arbitrary Python code. For more information, see the CSV Agent security warning.
llm	LanguageModel	Input parameter. The language model to use for the agent.
path	File	Input parameter. The path to the CSV file.
agent_type	String	Input parameter. The type of agent to create.
agent	AgentExecutor	Output parameter. The CSV agent instance.

OpenAI Tools Agent

This component is based on the Agent core component.

This component creates an OpenAI Tools Agent. For more information, see the LangChain OpenAI agent documentation.

OpenAI Tools Agent parameters

Name	Type	Description
llm	LanguageModel	Input parameter. The language model to use.
tools	List of Tools	Input parameter. The tools to give the agent access to.
system_prompt	String	Input parameter. The system prompt to provide context to the agent.
input_value	String	Input parameter. The user's input to the agent.
memory	Memory	Input parameter. The memory for the agent to use for context persistence.
max_iterations	Integer	Input parameter. The maximum number of iterations to allow the agent to execute.
verbose	Boolean	Input parameter. This determines whether to print out the agent's intermediate steps.
handle_parsing_errors	Boolean	Input parameter. This determines whether to handle parsing errors in the agent.
agent	AgentExecutor	Output parameter. The OpenAI Tools agent instance.
output	String	Output parameter. The output from executing the agent on the input.

OpenAPI Agent

This component is based on the Agent core component.

This component creates an agent for interacting with OpenAPI services. For more information, see the LangChain OpenAPI toolkit documentation.

OpenAPI Agent parameters

Name	Type	Description
llm	LanguageModel	Input parameter. The language model to use.
openapi_spec	String	Input parameter. The OpenAPI specification for the service.
base_url	String	Input parameter. The base URL for the API.
headers	Dict	Input parameter. The optional headers for API requests.
agent_executor_kwargs	Dict	Input parameter. The optional parameters for the agent executor.
agent	AgentExecutor	Output parameter.The OpenAPI agent instance.

Prompt Hub

This component fetches prompts from the LangChain Hub.

Like the Prompt Template core component, additional fields are added to the component for each variable in the prompt. For example, the default prompt efriis/my-first-prompt adds fields for profession and question.

Prompt Hub parameters

Name	Display Name	Description
langchain_api_key	Your LangChain API Key	Input parameter. The LangChain API Key to use.
langchain_hub_prompt	LangChain Hub Prompt	Input parameter. The LangChain Hub prompt to use.
prompt	Build Prompt	Output parameter. The built prompt message returned by the `build_prompt` method.

SQL Agent

This component is based on the Agent core component.

This component creates an agent for interacting with SQL databases. For more information, see the LangChain SQL agent documentation.

SQL Agent parameters

Name	Type	Description
llm	LanguageModel	Input parameter. The language model to use.
database	Database	Input parameter. The SQL database connection.
top_k	Integer	Input parameter. The number of results to return from a SELECT query.
use_tools	Boolean	Input parameter. This determines whether to use tools for query execution.
return_intermediate_steps	Boolean	Input parameter. This determines whether to return the agent's intermediate steps.
max_iterations	Integer	Input parameter. The maximum number of iterations to run the agent.
max_execution_time	Integer	Input parameter. The maximum execution time in seconds.
early_stopping_method	String	Input parameter. The method to use for early stopping.
verbose	Boolean	Input parameter. This determines whether to print the agent's thoughts.
agent	AgentExecutor	Output parameter. The SQL agent instance.

SQL Database

The LangChain SQL Database component establishes a connection to an SQL database.

This component is different from the SQL Database core component, which executes SQL queries on SQLAlchemy-compatible databases.

Text Splitters

The LangChain bundle includes the following text splitter components:

Character Text Splitter
Language Recursive Text Splitter
Natural Language Text Splitter
Recursive Character Text Splitter
Semantic Text Splitter

Tool Calling Agent

This component is based on the Agent core component.

This component creates an agent for structured tool calling with various language models. For more information, see the LangChain tool calling documentation.

Tool Calling Agent parameters

Name	Type	Description
llm	LanguageModel	Input parameter. The language model to use.
tools	List[Tool]	Input parameter. The list of tools available to the agent.
system_message	String	Input parameter. The system message to use for the agent.
return_intermediate_steps	Boolean	Input parameter. This determines whether to return the agent's intermediate steps.
max_iterations	Integer	Input parameter. The maximum number of iterations to run the agent.
max_execution_time	Integer	Input parameter. The maximum execution time in seconds.
early_stopping_method	String	Input parameter. The method to use for early stopping.
verbose	Boolean	Input parameter. This determines whether to print the agent's thoughts.
agent	AgentExecutor	Output parameter. The tool calling agent instance.

XML Agent

This component is based on the Agent core component.

This component creates an XML Agent using LangChain. The agent uses XML formatting for tool instructions to the LLM. For more information, see the LangChain XML Agent documentation.

XML Agent parameters

Name	Type	Description
llm	LanguageModel	Input parameter. The language model to use for the agent.
user_prompt	String	Input parameter. The custom prompt template for the agent with XML formatting instructions.
tools	List[Tool]	Input parameter. The list of tools available to the agent.
agent	AgentExecutor	Output parameter. The XML Agent instance.

Other LangChain components

Other components in the LangChain bundle include the following:

Fake Embeddings
HTML Link Extractor
Runnable Executor
Spider Web Crawler & Scraper

Legacy LangChain components

import PartialLegacy from '@site/docs/_partial-legacy.mdx';

The following LangChain components are in legacy status:

Conversation Chain
LLM Checker Chain
LLM Math Chain
Natural Language to SQL
Retrieval QA
Self Query Retriever
JSON Agent
Vector Store Info/Agent
VectorStoreRouterAgent

To replace these components, consider other components in the LangChain bundle or general Langflow components, such as the Agent component or the SQL Database component.