개요
OpenEnv는 Gymnasium과 유사한 API를 통해 에이전트 실행 환경과 상호작용하는 표준을 제공합니다. 여기에는 환경 생성 도구와 배포용 명령줄 인터페이스가 포함되어 있으며, 격리되고 안전하며 사용하기 쉬운 RL 후훈련 환경을 지원합니다.
README 미리보기
# OpenEnv: Agentic Execution Environments\n\nAn e2e framework for creating, deploying and using isolated execution environments for agentic RL training, built using Gymnasium style simple APIs.\n\n\n \n \n \n \n \n \n\n\n---\n\n**Featured Example:** Train LLMs to play BlackJack using [torchforge](https://meta-pytorch.org/torchforge/) (PyTorch's agentic RL framework): [`examples/grpo_blackjack/`](examples/grpo_blackjack/)\n\n**Zero to Hero Tutorial:** End to end tutorial from our [GPU Mode](tutorial/README.md) lecture and other hackathons.\n\n## Quick Start\n\nInstall the OpenEnv package:\n\n```bash\npip install openenv\n```\n\nInstall an environment client (e.g., Echo):\n\n```bash\npip install git+https://huggingface.co/spaces/openenv/echo_env\n```\n\nThen use the environment:\n\n```python\nimport asyncio\nfrom echo_env import CallToolAction, EchoEnv\n\nasync def main():\n # Connect to a running Space (async context manager)\n async with EchoEnv(base_url="https://openenv-echo-env.hf.space") as client:\n # Reset the environment\n result = await client.reset()\n print(result.observation.echoed_message) # "Echo environment ready!"\n\n # Send messages\n result = await client.step(\n CallToolAction(\n tool_name="echo_message",\n arguments={"message": "Hello, World!"},\n )\n )\n print(result.observation.result) # "Hello, World!"\n print(result.reward)\n\nasyncio.run(main())\n```\n\n**Synchronous usage** is also supported via the `.sync()` wrapper:\n\n```python\nfrom echo_env import CallToolAction, EchoEnv\n\n# Use .sync() for synchronous context manager\nwith EchoEnv(base_url="https://openenv-echo-env.hf.space").sync() as client:\n result = client.reset()\n result = client.step(\n CallToolAction(\n tool_name="echo_message",\n arguments={"message": "Hello, World!"},\n )\n )\n print(result.obse