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.