Introduction

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 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.

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: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it.
• LangServe: Deploy LangChain chains as REST APIs.
• LangSmith: A developer platform that lets you debug, test, evaluate, and monitor LLM applications.

Tutorials​

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

These are the best ones to get started with:

• Build a Simple LLM Application
• Build a Chatbot
• Build an Agent
• Introduction to LangGraph

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 “How 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.

Ecosystem​

🦜🛠️ LangSmith​

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

🦜🕸️ LangGraph​

Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.

Additional resources​

Security​

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

Integrations​

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.

Contributing​

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