langchain-ai

    langchain-ai/langchain

    🦜🔗 The platform for reliable agents.

    ai
    ai-agents
    llm
    agents
    anthropic
    chatgpt
    deepagents
    enterprise
    framework
    gemini
    generative-ai
    langchain
    langgraph
    multiagent
    open-source
    openai
    pydantic
    python
    rag
    Python
    MIT
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    Updated 2/27/2026
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    About langchain

    LangChain Logo

    The platform for reliable agents.

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    LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.

    pip install langchain
    

    Documentation: To learn more about LangChain, check out the docs.

    If you're looking for more advanced customization or agent orchestration, check out LangGraph, our framework for building controllable agent workflows.

    [!NOTE] Looking for the JS/TS library? Check out LangChain.js.

    Why use LangChain?

    LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.

    Use LangChain for:

    • Real-time data augmentation. Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChain’s vast library of integrations with model providers, tools, vector stores, retrievers, and more.
    • Model interoperability. Swap models in and out as your engineering team experiments to find the best choice for your application’s needs. As the industry frontier evolves, adapt quickly — LangChain’s abstractions keep you moving without losing momentum.

    LangChain’s ecosystem

    While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.

    To improve your LLM application development, pair LangChain with:

    • LangSmith - Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
    • LangGraph - Build agents that can reliably handle complex tasks with LangGraph, our low-level agent orchestration framework. LangGraph offers customizable architecture, long-term memory, and human-in-the-loop workflows — and is trusted in production by companies like LinkedIn, Uber, Klarna, and GitLab.
    • LangGraph Platform - Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in LangGraph Studio.

    Additional resources

    • Learn: Use cases, conceptual overviews, and more.
    • API Reference: Detailed reference on navigating base packages and integrations for LangChain.
    • Contributing Guide: Learn how to contribute to LangChain and find good first issues.
    • LangChain Forum: Connect with the community and share all of your technical questions, ideas, and feedback.
    • Chat LangChain: Ask questions & chat with our documentation.

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