LangChain
The most widely adopted framework for building LLM-powered applications - 100K+ GitHub stars, supports every major LLM and vector store.
LangChain is the leading open-source framework for building applications powered by large language models. It provides composable building blocks for chaining LLM calls, connecting models to external tools, building RAG (retrieval-augmented generation) pipelines, and orchestrating multi-step agents. LangChain supports 50+ LLM providers and 100+ vector stores, and includes LangGraph for building stateful multi-agent workflows and LangSmith for tracing, debugging, and evaluating LLM applications in production. As of 2026, LangChain has 100,000+ GitHub stars and is the dependency of choice for teams building production LLM systems.
Key Features
- Composable chains - connect LLM calls, prompts, parsers, and tools into reusable pipelines
- RAG pipeline toolkit - document loading, chunking, embedding, retrieval, and re-ranking
- LangGraph - build stateful multi-agent workflows with cycles and branching logic
- LangSmith - trace, debug, evaluate, and monitor LLM application calls in production
- 50+ LLM provider integrations - OpenAI, Anthropic, Google, Mistral, Ollama, and more
- 100+ vector store integrations - Pinecone, Weaviate, Chroma, pgvector, and more
Use Cases
- Engineering teams building RAG applications that answer questions over internal documents
- Developers creating multi-step AI agents that call APIs, query databases, and take actions
- ML teams monitoring and evaluating LLM outputs in production with LangSmith
- Startups prototyping LLM-powered products with pre-built integrations for every major model
Pros
- Largest ecosystem of any LLM framework - most questions and patterns have documented solutions
- LangGraph enables complex stateful agent workflows that simple chain-based frameworks cannot handle
- LangSmith turns LLM debugging from guesswork into observable, traceable data
Cons
- Abstraction layers can obscure what is actually happening in prompts and model calls
- Framework updates sometimes break existing chains - keeping dependencies current requires maintenance
- LangSmith is the primary paid product and required for production-grade observability
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