🧪 AgentEnv Framework: RL Environment Builder

As AI agents become more capable, evaluating and training them has emerged as a new challenge. Open-sourced by Scale AI, this project provides a framework to help researchers and engineers efficiently build realistic environments for reinforcement learning (RL). It attempts to fill a gap in the current open-source ecosystem by balancing tooling, environment dynamism, and reproducibility. For teams working on training LLMs via reinforcement learning or running automated tests in complex sandboxes, this framework offers standardized infrastructure to reduce the overhead of building evaluation environments from scratch.