Ship fast with proven patterns
Start with the `create_agent` abstraction to get started quickly, with middleware that enables step-by-step control and customization.
Build agents faster, your way
LangChain is the open, composable framework with pre-built agent architectures and standard integrations for any model or tool — so you can build agents that adapt as fast as the ecosystem evolves.
Why use LangChain?
Composable by design
LangChain’s standard interface lets you experiment with different providers, tools, and databases – creating DevEx parity when gaps exist.
Real-time data augmentation
Connect LLMs to live data sources, APIs, and internal systems. LangChain’s vast library of integrations – including model providers, tools, and vector stores – brings your data directly into your AI workflows.
Open and neutral
Evolve your stack without vendor lock-in. LangChain is open source with 1000+ integrations. Future proof your app by swapping in components without rewriting your entire application.
Instantly connect to your preferred LLM.
LangChain FAQs
Is LangChain open source?
Yes - LangChain is an MIT-licensed open-source library and is free to use.
What are the most common ways people use LangChain?
There are many different use cases for LangChain. Some common ones that we see include: chatbots and conversational interfaces, document Q&A and knowledge retrieval systems, and data extraction. LangChain excels when you need to connect LLMs to external data sources, APIs, or tools– anywhere you need maximum integration flexibility.
How do I use LangChain with LangSmith?
LangChain is an open source framework with pre-built agent architectures and as integrations to models, tools, and databases to start building agents quickly. The LangChain framework integrates seamlessly with LangSmith, our platform for agent observability, evaluation, and deployment — you can set just one environment variable to get started.
How is LangChain different from LangGraph?
Use LangChain to get started quickly on simple use cases. Use LangGraph when you need to build agents that can reliably handle complex tasks.
LangChain is often used to build standard agents like SQL queries and document analysis, customer support bots, and predictable linear workflows with minimal customization.
LangGraph is often used for multi-agent research with specialized roles, long-running processes, use cases requiring human-in-the-loop approvals, and custom architectures with advanced control flow.
Can I use LangChain in production?
Yes. We’ve released LangChain 1.0, which means we’ve committed to no breaking changes until 2.0. Companies like Rakuten, Cisco, and Moody’s use LangChain in production for business-critical workflows.
Ready to start shipping reliable agents faster?
Get started with tools from the LangChain product suite for every step of the agent development lifecycle.