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Agent Lightning
Agent Lightning is an open-source reinforcement learning framework for training artificial intelligence agents with existing systems.
Agent Lightning is an open-source framework designed for training artificial intelligence agents using reinforcement learning. It keeps the architecture simple with three components: a trainer running verl and vLLM, an API gateway that proxies model requests and captures training data, and a rollout controller that runs agents locally or as Kubernetes jobs. Agents interact with models through a proxy without modifications, keeping tools and environments in the loop. The system targets researchers and developers wanting to optimize agent performance across domains like math reasoning, search, and coding tasks. Supported technologies include verl, vLLM, Kubernetes, and various language models.
Agent Lightning at a glance
Key features
- Run training with approximately 3500 lines of code
- Interact with models through a proxy with zero changes
- Support native Kubernetes jobs for running agents
- Capture training data via API gateway
- Integrate with verl and vLLM
- Support local and Kubernetes runners
- Provide end-to-end coding agent training pipelines
Use it for
- Train coding agents to improve software engineering benchmarks
- Optimize multi-turn retrieval and reasoning agents
- Execute interactive science and math reasoning tasks
- Train agents with computer and code execution tools
Alternatives to Agent Lightning
- rLLM — Enables reinforcement learning training for AI agents with minimal code changes.
- ART — Enhances LLM agent performance and reliability using reinforcement learning techniques.
- OpenRLHF — High-performance distributed architecture and unified agent-based execution
- VoltAgent — Offers open-source flexibility with built-in supervisor agent orchestration and RAG.
- RLinf — Scalable open-source framework supporting real-world robots and simulators.
- NeMo Molt — It scales fully-async agentic RL to frontier MoE scale with a small PyTorch stack.
- OmniAgent — It evolves skills in real-time and dynamically hardens security during task execution.
- MLflow — Complete observability and evaluation for production AI apps.
- Agent Skills — Encodes senior-engineer workflows and quality gates into 24 skills.
- AReaL — Bridges foundation model training with modern agent-based applications.
- OpenCode — Works with 75+ model providers, local models, and existing subscriptions
- Klavis — Provides live environments for training agents with verifiable reward data.
All Agent Lightning alternatives