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| license: apache-2.0 | |
| sdk: static | |
| # OpenEnv: Agentic Execution Environments | |
| A community driven collection of OpenEnv-spec Environments composed of a **Hub** and a **Standardized spec** to ensure environment compatibility. | |
| <a href="https://berkeleyrdi.substack.com/p/agentic-ai-weekly-berkeley-rdi-january?utm_campaign=email-half-post&r=wg271&utm_source=substack&utm_medium=email" style="text-decoration: none; color: inherit; width: 100%; height: 120px; margin-bottom: 10px; margin-top: 10px;"> | |
| <div style="padding: 5px; padding-left: 20px; border-radius: 8px; background-image: linear-gradient(to bottom, coral, lightcoral); color: black; box-shadow: 1px 1px 3px rgba(0,0,0,0.1); border: 2px solid #3498db; height: 100%; transition: all 0.3s ease;" onmouseover="this.style.transform='scale(1.02)'; this.style.boxShadow='2px 2px 8px rgba(0,0,0,0.2)'; this.style.backgroundImage='linear-gradient(to bottom, #d6f0ff, #b8daff)';" onmouseout="this.style.transform='scale(1)'; this.style.boxShadow='1px 1px 3px rgba(0,0,0,0.1)'; this.style.backgroundImage='linear-gradient(to bottom, #e6f7ff, #cce5ff)';"> | |
| <p> Join the Hackathon! </p> | |
| <p>Additionally, we’re thrilled to announce a new AgentBeats custom track: the <strong><a href="https://drive.google.com/file/d/1NASall4R84xAhoDdcaMwwJ78Ao3B-EK4/view?usp=sharing" rel="">OpenEnv Challenge: SOTA Environments to Drive General Intelligence</a></strong>, sponsored by the <a href="https://pytorch.org/" rel="">PyTorch</a> team at <a href="https://www.meta.com/" rel="">Meta</a>, <a href="https://huggingface.co/" rel="">Hugging Face</a>, and <a href="https://unsloth.ai/" rel="">Unsloth</a>. Participants will compete to develop innovative, open-source RL environments that push the frontiers of agent learning, with a prize pool of <strong>$10K in Hugging Face credits</strong>, and the chance to be published on the <a href="https://pytorch.org/blog/" rel="">PyTorch blog</a></p> | |
| </div> | |
| </a> | |
| ## OpenEnv Spec | |
| An e2e framework for creating, deploying and using isolated execution environments for agentic RL training, built using Gymnasium style simple APIs. | |
| Repo: https://github.com/meta-pytorch/OpenEnv | |
| [Open In Colab](https://colab.research.google.com/github/meta-pytorch/OpenEnv/blob/main/examples/OpenEnv_Tutorial.ipynb) ← Try the Interactive Tutorial! | |
| ## Hugging Face x Meta-PyTorch | |
| Hugging Face, Meta-PyTorch and many other [supporters](https://github.com/meta-pytorch/OpenEnv?tab=readme-ov-file#community-support--acknowledgments) are committed to democratizing RL post training with environmnets. | |
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