AReaL

About

AReaL is a large-scale asynchronous reinforcement learning system that connects foundation model training to agent-based applications, letting researchers run RL on LLM agents without building the distributed training plumbing themselves. It is Apache 2.0 licensed and ships documentation, benchmarks, examples, notebooks, and a Dockerfile, so a training run can be reproduced rather than reassembled from scratch.