Agent Lightning: Train agents with RL (no code changes needed)

Summary

Agent Lightning⚡ The absolute trainer to light up AI agents. Join our Discord community to connect with other users and contributors. ⚡ Core Features Turn your agent into an optimizable beast with ZERO CODE CHANGE (almost)! 💤 (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! 🤖 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. 🎯 optimize one or more agents in a multi-agent system. 🎯 Embraces Algorithms like Reinforcement Learning, Automatic Prompt Optimization, Supervised Fine-tuning and more. 🤗 Read more on our documentation website. ⚡ Installation pip install agentlightning Please refer to our installation guide for more details. To start using Agent-lightning, check out our documentation and examples. ⚡ Articles ⚡ Community Projects DeepWerewolf — A case study of agent RL training for the Chinese Werewolf game built with AgentScope and Agent Lightning. AgentFlow — 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. ⚡ Architecture Agent Lightning keeps the moving parts to a minimum so you can focus on your idea, not the plumbing. Your agent continues to run as usual; you can still use any agent framework you like; you drop in the lightweight agl.emit_xxx() helper, or let the tracer collect every prompt, tool call, and reward. Those events become structured spans that flow into the LightningStore, a central hub that keeps tasks, resources, and traces in sync. On the other side of the store sits the algorithm you choose, or write yourself. The algorithm reads spans, learns from them, and posts updated resources such as refined prompt templates or new ...