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LangChain is a framework for developing applications powered by large language models (LLMs).

LangChain simplifies every stage of the LLM application lifecycle:

  • Development: Build your applications using LangChain's open-source building blocks, components, and third-party integrations. Use LangGraph.js to build stateful agents with first-class streaming and human-in-the-loop support.
  • Productionization: Use LangSmith to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence.
  • Deployment: Turn your LangGraph applications into production-ready APIs and Assistants with LangGraph Cloud (currently Python-only).
Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.

Concretely, the framework consists of the following open-source libraries:

  • @langchain/core: Base abstractions and LangChain Expression Language.
  • @langchain/community: Third party integrations.
    • Partner packages (e.g. @langchain/openai, @langchain/anthropic, etc.): Some integrations have been further split into their own lightweight packages that only depend on @langchain/core.
  • langchain: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
  • LangGraph.js: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
  • LangSmith: A developer platform that lets you debug, test, evaluate, and monitor LLM applications.

These docs focus on the JavaScript LangChain library. Head here for docs on the Python LangChain library.


If you're looking to build something specific or are more of a hands-on learner, check out our tutorials. This is the best place to get started.

These are the best ones to get started with:

Explore the full list of LangChain tutorials here, and check out other LangGraph tutorials here.

How-To Guides​

Here you'll find short answers to β€œHow do I….?” types of questions. These how-to guides don't cover topics in depth - you'll find that material in the Tutorials and the API Reference. However, these guides will help you quickly accomplish common tasks.

Check out LangGraph-specific how-tos here.

Conceptual Guide​

Introductions to all the key parts of LangChain you'll need to know! Here you'll find high level explanations of all LangChain concepts.

For a deeper dive into LangGraph concepts, check out this page.

API reference​

Head to the reference section for full documentation of all classes and methods in the LangChain Python packages.


πŸ¦œπŸ› οΈ LangSmith​

Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.

πŸ¦œπŸ•ΈοΈ LangGraph​

Build stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain primitives.

Additional resources​


Read up on our Security best practices to make sure you're developing safely with LangChain.


LangChain is part of a rich ecosystem of tools that integrate with our framework and build on top of it. Check out our growing list of integrations.


Check out the developer's guide for guidelines on contributing and help getting your dev environment set up.

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