Langchain agents documentation. When the agent reaches a stopping condition, it returns a final return value. Agent # class langchain. The schemas for the agents themselves are defined in langchain. It’s designed with simplicity in mind, making it accessible to users without technical expertise, while still offering advanced capabilities for developers. Any number of tools can be Nov 6, 2024 · LangChain is revolutionizing how we build AI applications by providing a powerful framework for creating agents that can think, reason, and take actions. For the current stable version, see this version (Latest). 0: Use new agent constructor methods like create_react_agent, create_json_agent, create_structured_chat_agent, etc. LangGraph is an extension of LangChain specifically aimed at creating highly controllable and customizable agents. zero-shot-react-description # This agent uses the ReAct framework to determine which tool to use based solely on the tool’s description. The agent returns the observation to the LLM, which can then be used to generate the next action. . g. 1, which is no longer actively maintained. We recommend that you use LangGraph for building agents. 1. In these types of chains, there is a “agent” which has access to a suite of tools. For details, refer to the LangGraph documentation as well as guides for Agents are systems that take a high-level task and use an LLM as a reasoning engine to decide what actions to take and execute those actions. In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. Customize your agent runtime with LangGraph LangGraph provides control for custom agent and multi-agent workflows, seamless human-in-the-loop interactions, and native streaming support for enhanced agent reliability and execution. Here are the agents available in LangChain. In this comprehensive guide, we’ll This is documentation for LangChain v0. Jun 17, 2025 · LangChain supports the creation of agents, or systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action. Depending on the user input, the agent can then decide which, if any, of these tools to call. , runs the tool), and receives an observation. Agents select and use Tools and Toolkits for actions. The agent executes the action (e. agent. The following sections of documentation are What is Open Agent Platform? Open Agent Platform provides a modern, web-based interface for creating, managing, and interacting with LangGraph agents. agents. An action can either be using a tool and observing its output, or returning a response to the user. Agent Types # Agents use an LLM to determine which actions to take and in what order. 0: LangChain agents will continue to be supported, but it is recommended for new use cases to be built with LangGraph. Agent that calls the language model and deciding the action. Deprecated since version 0. Agent [source] # Bases: BaseSingleActionAgent Deprecated since version 0. Classes Build copilots that write first drafts for review, act on your behalf, or wait for approval before execution. Agents # Some applications will require not just a predetermined chain of calls to LLMs/other tools, but potentially an unknown chain that depends on the user’s input. This is driven by a LLMChain. LangGraph offers a more flexible and full-featured framework for building agents, including support for tool-calling, persistence of state, and human-in-the-loop workflows. bdlr veqy oocieg jxt usilv cdyvw vlb xhia cabrmm epyxlail