LangChain overview

LangChain v1.x is now available!For a complete list of changes and instructions on how to upgrade your code, see therelease notes andmigration guide.If you encounter any issues or have feedback, pleaseopen an issue so we can improve. To view v0.x documentation,go to the archived content.

LangChain is the easiest way to start building agents and applications powered by LLMs. With under 10 lines of code, you can connect to OpenAI, Anthropic, Google, andmore. LangChain provides a pre-built agent architecture and model integrations to help you get started quickly and seamlessly incorporate LLMs into your agents and applications.We recommend you use LangChain if you want to quickly build agents and autonomous applications. UseLangGraph, our low-level agent orchestration framework and runtime, when you have more advanced needs that require a combination of deterministic and agentic workflows, heavy customization, and carefully controlled latency.LangChainagents are built on top of LangGraph in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. You do not need to know LangGraph for basic LangChain agent usage.

Install

pip install -U langchain# Requires Python 3.10+

Create an agent

# pip install -qU "langchain[anthropic]" to call the modelfrom langchain.agentsimport create_agentdef get_weather(city:str) ->str:    """Get weather for a given city."""    return f"It's always sunny in{city}!"agent= create_agent(    model="claude-sonnet-4-5-20250929",    tools=[get_weather],    system_prompt="You are a helpful assistant",)# Run the agentagent.invoke(    {"messages": [{"role":"user","content":"what is the weather in sf"}]})