langchain-ai / langchain

LangChain is the most widely-used framework for building LLM applications. It standardizes how you connect models, prompts, tools, and memory into reusable chains and agents.

🎯 Use Cases

• RAG Applications: Connect LLMs to vector stores and your own data.
• Tool-Using Agents: Give LLMs access to APIs, databases, and the web.
• Prompt Templating & Chaining: Compose multi-step prompt pipelines.

✨ Features

• Hundreds of integrations: LLMs, vector stores, document loaders, tools
• LCEL (LangChain Expression Language) for declarative chains
• Agents, memory, callbacks, and streaming primitives
• Tight integration with LangSmith for tracing and evaluation

👍 Pros

• Largest ecosystem and community in the LLM tooling space
• Excellent for prototyping — most integrations work out of the box
• LangSmith provides best-in-class observability

👎 Cons & Limitations

• API churn has historically been heavy between versions
• Many layers of abstraction can hide what's really happening