Cerebras

This post details the technical journey in transforming OpenHands from a SWE-Bench evaluation tool into a general-purpose RL training platform. Key contributions include a refactored evaluation workflow for dynamic loading of arbitrary Docker images and runtime metadata parsing, and a unified rollout architecture that maintains a persistent runtime context to eliminate container duplication overhead, reducing instance setup time by approximately 95%. These advancements enable multi-turn interaction support, fast rollout generation, sparse reward evaluation, and comprehensive trajectory logging for training code-repair agents via Reinforcement Learning.