langchain
Framework for building LLM applications with agents, chains, RAG, and 500+ integrations.
- Supports multiple LLM providers (OpenAI, Anthropic, Google) with unified interface and easy provider swapping
- Implements ReAct agents with tool calling, structured outputs, and parallel tool execution for autonomous reasoning
- Includes RAG pipelines with document loaders, text splitters, vector stores (Chroma, Pinecone, FAISS), and retrieval chains
- Provides conversation memory management, streaming support, and LangSmith observability for production deployments
LangChain - Build LLM Applications with Agents & RAG
The most popular framework for building LLM-powered applications.
When to use LangChain
Use LangChain when:
- Building agents with tool calling and reasoning (ReAct pattern)
- Implementing RAG (retrieval-augmented generation) pipelines
- Need to swap LLM providers easily (OpenAI, Anthropic, Google)
- Creating chatbots with conversation memory
- Rapid prototyping of LLM applications
- Production deployments with LangSmith observability
Metrics:
- 119,000+ GitHub stars
- 272,000+ repositories use LangChain
- 500+ integrations (models, vector stores, tools)
- 3,800+ contributors
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