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.
Tip
Just getting started? Check out Deep Agents — a higher-level package built on LangChain for agents that have built-in capabilites for common usage patterns such as planning, subagents, file system usage, and more.
Documentation: To learn more about LangChain, check out the docs.
If you're looking for more advanced customization or agent orchestration, check out LangGraph.js - our framework for building agents and controllable workflows.
For an equivalent Python library, check out LangChain.
To help you ship LangChain apps to production faster, check out LangSmith. LangSmith is a unified developer platform for building, testing, and monitoring LLM applications.
You can use npm, pnpm, or yarn to install LangChain.js
npm install -S langchain or pnpm install langchain or yarn add langchain
LangChain helps developers build applications powered by LLMs through a standard interface for agents, 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.
- Rapid prototyping. Quickly build and iterate on LLM applications with LangChain's modular, component-based architecture. Test different approaches and workflows without rebuilding from scratch, accelerating your development cycle.
- Production-ready features. Deploy reliable applications with built-in support for monitoring, evaluation, and debugging through integrations like LangSmith. Scale with confidence using battle-tested patterns and best practices.
- Vibrant community and ecosystem. Leverage a rich ecosystem of integrations, templates, and community-contributed components. Benefit from continuous improvements and stay up-to-date with the latest AI developments through an active open-source community.
- Flexible abstraction layers. Work at the level of abstraction that suits your needs - from high-level chains for quick starts to low-level components for fine-grained control. LangChain grows with your application's complexity.
- Deep Agents (JS) - Build agents that can plan, use subagents, and leverage file systems for complex tasks. A higher-level package built on top of LangChain.
- LangSmith - Unified developer platform for building, testing, and monitoring LLM applications. With LangSmith, you can debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and deploy agents with confidence.
- LangSmith Deployment — Deploy and scale agents with a purpose-built platform for long-running, stateful workflows
- 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.
- Integrations — Chat & embedding models, tools & toolkits, and more
LangChain.js is written in TypeScript and can be used in:
- Node.js (ESM and CommonJS) - 20.x, 22.x, 24.x
- Cloudflare Workers
- Vercel / Next.js (Browser, Serverless and Edge functions)
- Supabase Edge Functions
- Browser
- Deno
- Bun
- Getting started: Installation, setting up the environment, simple examples
- Learn: Learn about the core concepts of LangChain.
- LangChain Forum: Connect with the community and share all of your technical questions, ideas, and feedback.
- Chat LangChain: Ask questions & chat with our documentation.
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see CONTRIBUTING.md.
Please report any security issues or concerns following our security guidelines.