AIエージェント
NeMo-Agent-Toolkit
NVIDIA's toolkit for connecting, profiling and optimizing teams of AI agents — across any framework
★ 2.7k スターApache-2.0
ガイドを見る →agent-lightningは、microsoftが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: microsoft/agent-lightning）。GitHubスターは18,595、フォークは1,661で、MITライセンスの下で公開されています。GitHubでの最終更新は2026年9月29日です。
Microsoft's trainer for AI agents - reinforcement learning for almost any agent framework
Choose an existing agent workload - the repo includes a full coding-agent training example.
Training setups are run from a source checkout.
Use uv sync and the provided setup script to prepare the training stack for your CUDA version.
Start from an included example, collect trajectories, and launch a training run.
Designed to train agents built with popular frameworks without rewriting them around the trainer.
Applies RL (with veRL integration scripts) to multi-step agent trajectories.
Ships an end-to-end example that trains a coding agent on SWE-bench-style tasks with data cleaning and reward-hacking prevention.
Keeps the training architecture to three lightweight components per the README.
The README reports measured gains for its examples (for example SWE-bench Verified improvements in the coding-agent pipeline).
Includes additional examples and a catalog of community projects built on it.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/microsoft/agent-lightning.git
cd agent-lightningThe README's example installation targets a CUDA machine and uses uv plus the veRL setup script.
uv sync
bash scripts/setup_verl.sh 0.8.0 cu130 # example versions - see README installationOpen the examples in the repo (including the coding-agent training example) and adapt one to your agent.
# Browse the Examples section linked from the README and run one pipelineIt is maintained by Microsoft (Microsoft Research) as an open-source project on GitHub.
Yes - Agent Lightning is MIT licensed and free to use.
Training needs models to train and roll out: you bring your own model endpoints or local weights and the GPU capacity; the framework itself sells no API.
Compared with fine-tuning libraries like TRL, Agent Lightning is specialized for agents - trajectory-based training designed to wrap existing agent frameworks rather than single-turn LLM training.
Clone the repo, run uv sync, follow the installation guide for your CUDA setup, and run one of the included examples.
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