langchain

[!NOTE]
Looking for the JS/TS library? Check out LangChain.js.

LangChain is a framework for building LLM-powered applications. It helps you chain
together interoperable components and third-party integrations to simplify AI
application development — all while future-proofing decisions as the underlying
technology evolves.

pip install -U langchain

To learn more about LangChain, check out
the docs. If you’re looking for more
advanced customization or agent orchestration, check out
LangGraph, our framework for building
controllable agent workflows.

Why use LangChain?

LangChain helps developers build applications powered by LLMs through a standard
interface for models, embeddings, vector stores, and more.

Use LangChain for:

• Real-time data augmentation. Easily connect LLMs to diverse data sources and
  external / internal systems, drawing from LangChain’s vast library of integrations with
  model providers, tools, vector stores, retrievers, and more.
• Model interoperability. Swap models in and out as your engineering team
  experiments to find the best choice for your application’s needs. As the industry
  frontier evolves, adapt quickly — LangChain’s abstractions keep you moving without
  losing momentum.

LangChain’s ecosystem

While the LangChain framework can be used standalone, it also integrates seamlessly
with any LangChain product, giving developers a full suite of tools when building LLM
applications.

To improve your LLM application development, pair LangChain with:

• LangSmith - Helpful for agent evals and
  observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain
  visibility in production, and improve performance over time.
• LangGraph - Build agents that can
  reliably handle complex tasks with LangGraph, our low-level agent orchestration
  framework. LangGraph offers customizable architecture, long-term memory, and
  human-in-the-loop workflows — and is trusted in production by companies like LinkedIn,
  Uber, Klarna, and GitLab.
• LangGraph Platform - Deploy
  and scale agents effortlessly with a purpose-built deployment platform for long
  running, stateful workflows. Discover, reuse, configure, and share agents across
  teams — and iterate quickly with visual prototyping in
  LangGraph Studio.

Additional resources

• Tutorials: Simple walkthroughs with
  guided examples on getting started with LangChain.
• How-to Guides: Quick, actionable code
  snippets for topics such as tool calling, RAG use cases, and more.
• Conceptual Guides: Explanations of key
  concepts behind the LangChain framework.
• API Reference: Detailed reference on
  navigating base packages and integrations for LangChain.