The LangChain Framework
LangChain simplifies every stage of the LLM application lifecycle, from development to productionization to deployment.
A framework for developing applications powered by large language models (LLMs)
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LangChain simplifies every stage of the LLM application lifecycle, from development to productionization to deployment.
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.
Create composable chains with LangChain Expression Language, providing flexibility and reusability.
Learn more →Build stateful agents with first-class streaming and human-in-the-loop support for complex applications.
Learn more →Use LangSmith to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence.
A developer platform that lets you debug, test, evaluate, and monitor LLM applications. Track improvements, identify issues, and gain insights to optimize your applications.
Learn more →Turn your LangGraph applications into production-ready APIs and Assistants with LangGraph Cloud.
Deploy your LangGraph applications as production-ready APIs and Assistants, making them accessible to users and other services.
Learn more →The framework consists of the following open-source libraries:
Base abstractions and LangChain Expression Language that form the foundation of LangChain.
Third party integrations enabling connections to external services and tools.
Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
Deploy LangChain chains as REST APIs for easy integration with other services.
A developer platform that lets you debug, test, evaluate, and monitor LLM applications.
Note: These docs focus on the Python LangChain library. Head here for docs on the JavaScript LangChain library.
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.
Learn how to create a basic application powered by large language models.
Start Learning →Create your own conversational AI assistant using LangChain's components.
Start Learning →Develop intelligent agents that can perform tasks and make decisions autonomously.
Start Learning →Learn how to use LangGraph to build stateful, multi-actor applications with LLMs.
Start Learning →Short answers to "How do I….?" types of questions. These guides help you quickly accomplish common tasks.
View How-to guides →Check out LangGraph-specific how-tos here.
Introductions to all the key parts of LangChain you'll need to know! High level explanations of all LangChain concepts.
View Conceptual guide →For a deeper dive into LangGraph concepts, check out this page.
Full documentation of all classes and methods in the LangChain Python packages.
View API reference →Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.
Learn more →Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
Learn more →See what changed in v0.3, learn how to migrate legacy code, read up on versioning policies, and more.
View Versions →Read up on security best practices to make sure you're developing safely with LangChain.
View Security Guidelines →LangChain is part of a rich ecosystem of tools that integrate with our framework and build on top of it.
View Integrations →Check out the developer's guide for guidelines on contributing and help getting your dev environment set up.
Learn How to Contribute →