microsoft--agent-lightning/docs/index.md

# Agent Lightning

Agent Lightning is the absolute trainer to light up AI agents.

[Join our Discord community](https://discord.gg/RYk7CdvDR7) to connect with other users and contributors.

## Features

- Turn your agent into an optimizable beast with **ZERO CODE CHANGE** (almost)! 💤
- Build with **ANY** agent framework (LangChain, OpenAI Agent SDK, AutoGen, CrewAI, Microsoft Agent Framework...); or even WITHOUT agent framework (Python OpenAI). You name it! 🤖
- **Selectively** optimize one or more agents in a multi-agent system. 🎯
- Embraces **Algorithms** like Reinforcement Learning, Automatic Prompt Optimization, Supervised Fine-tuning and more. 🤗

## How to Read this Documentation

This documentation is organized into the following parts:

- [Installation](tutorials/installation.md) - Get started with Agent Lightning
- How-to Recipes (e.g., [Train SQL Agent with RL](how-to/train-sql-agent.md)) - Practical examples of training agents and customizing algorithms.
- Learning More (e.g., [Debugging](tutorials/debug.md)) - Guides on specific topics like debugging or parallelization.
- Algorithm Zoo (e.g., [APO](algorithm-zoo/apo.md)) - References for built-in algorithms.
- Deep Dive (e.g., [Bird's Eye View](deep-dive/birds-eye-view.md)) - For a deeper understanding of what Agent-lightning is doing under the hood.
- API References (e.g., [Agent](reference/agent.md)) - References for the Agent-lightning Python API.

## Resources

- 11/4/2025 [Tuning ANY AI agent with Tinker ✕ Agent-lightning](https://medium.com/@yugez/tuning-any-ai-agent-with-tinker-agent-lightning-part-1-1d8c9a397f0e) Medium. See also [Part 2](https://medium.com/@yugez/tuning-any-ai-agent-with-tinker-agent-lightning-part-2-332c5437f0dc).
- 10/22/2025 [No More Retokenization Drift: Returning Token IDs via the OpenAI Compatible API Matters in Agent RL](https://blog.vllm.ai/2025/10/22/agent-lightning.html) vLLM blog. See also [Zhihu writeup](https://zhuanlan.zhihu.com/p/1965067274642785725).
- 8/11/2025 [Training AI Agents to Write and Self-correct SQL with Reinforcement Learning](https://medium.com/@yugez/training-ai-agents-to-write-and-self-correct-sql-with-reinforcement-learning-571ed31281ad) Medium.
- 8/5/2025 [Agent Lightning: Train ANY AI Agents with Reinforcement Learning](https://arxiv.org/abs/2508.03680) arXiv paper.
- 7/26/2025 [We discovered an approach to train any AI agent with RL, with (almost) zero code changes.](https://www.reddit.com/r/LocalLLaMA/comments/1m9m670/we_discovered_an_approach_to_train_any_ai_agent/) Reddit.
- 6/6/2025 [Agent Lightning - Microsoft Research](https://www.microsoft.com/en-us/research/project/agent-lightning/) Project page.

## Community Projects

- [DeepWerewolf](https://github.com/af-74413592/DeepWerewolf) — A case study of agent RL training for the Chinese Werewolf game built with AgentScope and Agent Lightning.
- [AgentFlow](https://agentflow.stanford.edu/) — A modular multi-agent framework that combines planner, executor, verifier, and generator agents with the Flow-GRPO algorithm to tackle long-horizon, sparse-reward tasks.
- [Youtu-Agent](https://github.com/TencentCloudADP/Youtu-agent) — Youtu-Agent lets you build and train your agent with ease. Built with [a modified branch](https://github.com/microsoft/agent-lightning/tree/contrib/youtu-agent-lightning) of Agent Lightning, Youtu-Agent has verified up to 128 GPUs RL training on maths/code and search capabilities with steady convergence. Also check [the recipe](https://github.com/TencentCloudADP/youtu-agent/tree/rl/agl) and their blog [*Stop Wrestling with Your Agent RL: How Youtu-Agent Achieved Stable, 128-GPU Scaling Without Breaking a Sweat*](https://spotted-coconut-df8.notion.site/Stop-Wrestling-with-Your-Agent-RL-How-Youtu-Agent-Achieved-Stable-128-GPU-Scaling-Without-Breaking-2ca5e8f089ba80539a98c582b65e0233).


## Citation

If you find Agent Lightning useful in your research or projects, please cite our paper:

```bibtex
@misc{luo2025agentlightningtrainai,
      title={Agent Lightning: Train ANY AI Agents with Reinforcement Learning},
      author={Xufang Luo and Yuge Zhang and Zhiyuan He and Zilong Wang and Siyun Zhao and Dongsheng Li and Luna K. Qiu and Yuqing Yang},
      year={2025},
      eprint={2508.03680},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2508.03680},
}
```

## License

See the [LICENSE](https://github.com/microsoft/agent-lightning/blob/main/LICENSE) file for details.