Train Search Agents

AReaL is an asynchronous, distributed reinforcement-learning system for training LLMs and agent applications. It includes workflows for reasoning, coding, search, and multi-turn agents, with SGLang and vLLM inference backends.

AI Frameworks | Python · reinforcement-learning · LLM training