LangChain Documentation

LangChain

LangChain's official documentation is the authoritative guide for anyone implementing agents with the framework, with clear APIs and practical examples.

September 13, 2026

Developers building agent systems with LangChain

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About

LangChain's official documentation covers the complete framework for building language model agents, including core abstractions, tool integration, memory systems, and agent execution patterns. It provides API references, conceptual guides, and practical examples for implementing ReAct, tool-calling, and multi-step reasoning workflows.

Who is it for

Python developers building production AI agents. Suitable for those with prior LLM familiarity who want to understand LangChain's agent-building patterns and APIs.

LangChain's definitive agent reference

As the official documentation from LangChain's maintainers, it reflects the current state of the framework and is kept in sync with releases. It covers agent architectures, tool binding, and state management with real code examples.

What you learn

How to design and structure agent systems using LangChain's Agent interface

Integration patterns for binding tools and APIs to language models

State management and memory strategies for multi-turn agent workflows

Debugging, testing, and deployment best practices for production agents

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