LangChain

The agent engineering platform.</h3>
</div>

<div align="center">
  <a href="https://opensource.org/licenses/MIT" target="_blank"><img src="https://img.shields.io/pypi/l/langchain" alt="PyPI - License"></a>
  <a href="https://pypistats.org/packages/langchain" target="_blank"><img src="https://img.shields.io/pepy/dt/langchain" alt="PyPI - Downloads"></a>
  <a href="https://pypi.org/project/langchain/#history" target="_blank"><img src="https://img.shields.io/pypi/v/langchain?label=%20" alt="Version"></a>
  <a href="https://x.com/langchain_oss" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain_oss.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
</div>

<br>

LangChain is a framework for building agents and 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](http://docs.langchain.com/oss/python/deepagents/)** — a higher-level package built on LangChain for agents that have built-in capabilities for common usage patterns such as planning, subagents, file system usage, and more.

## Quickstart

```bash
uv add langchain
```

```python
from langchain.chat_models import init_chat_model

model = init_chat_model("openai:gpt-5.5")
result = model.invoke("Hello, world!")
```

If you're looking for more advanced customization or agent orchestration, check out [LangGraph](https://github.com/langchain-ai/langgraph), our framework for building controllable agent workflows.

For an equivalent JS/TS library, check out [LangChain.js](https://github.com/langchain-ai/langchainjs).

> [!TIP]
> For developing