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title: HuggingEnvs
emoji: π€
colorFrom: yellow
colorTo: purple
sdk: static
pinned: false
license: mit
---

[](https://github.com/adithya-s-k/HuggingEnvs)
[](https://huggingface.co/spaces/AdithyaSK/rl-environments-guide)
[](https://huggingface.co/spaces/AdithyaSK/rl-environments-101-slides)
# π€ HuggingEnvs: Open RL Environments
HuggingEnvs is a home for **end-to-end RL environment recipes**, built to make it easier to **explore, reproduce, train, and evaluate agent systems**.
Explore complete and reproducible environment projects from us and the community, including:
* π **Open RL environments**
* π§© **End-to-end environment recipes**
* π» **Complete implementations**
* π¦ **Models, datasets, and artifacts**
* π§ͺ **Training and evaluation setups**
* π **Demos and Spaces**
* π **Tutorials and guides**
All the reproducible code β environments, rollouts, training configs, notebooks, article and slide sources β lives in one repo: **[github.com/adithya-s-k/HuggingEnvs](https://github.com/adithya-s-k/HuggingEnvs)**. The artifacts those produce live here on the Hub.
# HuggingEnvs Projects
A growing collection of open projects, environments, resources, and artifacts.
| Project | What it is | Explore |
| :------------------------- | :----------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------ |
| **HuggingEnvs Academy** | Articles, guides, tutorials, slides, and hands-on resources for learning how to build RL environments and agent systems. | [Explore β](https://huggingface.co/collections/HuggingEnvs/huggingenvs-academy) |
| **Data Agent** | Training SLMs for data science with multi-harness RL environments. | [Explore β](https://huggingface.co/collections/HuggingEnvs/data-agent) |
# Articles & Talks
| | What it covers | Read / Watch |
| :--- | :--- | :--- |
| π **The Ultimate Guide to RL Environments** | Building and scaling RL environments in the LLM era β how frameworks are built, how rewards are wired, how they scale to thousands of concurrent sessions. | [Read β](https://huggingface.co/spaces/AdithyaSK/rl-environments-guide) |
| ποΈ **RL Environments 101** | From "what is an env?" to training your own: RL fundamentals β environment anatomy β OpenEnv β training with TRL. | [Watch β](https://huggingface.co/spaces/AdithyaSK/rl-environments-101-slides) |
| π **Scaling RL for LLMs** | RL environments and RL training β what an environment is, how reward hacking happens, how to train against your own. AMD AI Dev Day. | [Watch β](https://huggingface.co/spaces/AdithyaSK/scaling-rl-for-llms-amd-ai-dev-day) |
| π **Multi-Harness Training** | OpenEnv Γ Harbor β why an environment's failure model decides whether it can be trained against. | [Watch β](https://huggingface.co/spaces/AdithyaSK/multi-harness-training-slides) |
# Environments
Three reference environments, each implemented across six frameworks β `openenv`, `ors`, `nemo_gym`, `verifiers`, `skyrl_gym`, `gem`. Same logic, six dialects. [Source β](https://github.com/adithya-s-k/HuggingEnvs/tree/main/00-environments-101)
| Environment | Tools | OpenEnv | ORS | NeMo Gym |
| :--- | :--: | :--- | :--- | :--- |
| **Jupyter agent** β real code execution in an E2B sandbox | 4 | [Space](https://huggingface.co/spaces/AdithyaSK/jupyter-agent-openenv) | [Space](https://huggingface.co/spaces/AdithyaSK/jupyter-agent-ors) | [Space](https://huggingface.co/spaces/AdithyaSK/jupyter-agent-nemo-gym) |
| **Wordle** β multi-turn, pure Python, no backend | 1 | [Space](https://huggingface.co/spaces/AdithyaSK/wordle-openenv) | [Space](https://huggingface.co/spaces/AdithyaSK/wordle-ors) | [Space](https://huggingface.co/spaces/AdithyaSK/wordle-nemo-gym) |
| **Desktop** β computer-use, vision-driven Linux desktop | 19 | [Space](https://huggingface.co/spaces/AdithyaSK/desktop-openenv) | [Space](https://huggingface.co/spaces/AdithyaSK/desktop-ors) | β |
# Build your own
Five agent skills turn a plain-English description into a runnable RL environment across four frameworks β works with Claude Code, Cursor, Codex, OpenCode, Gemini CLI and others.
```bash
npx skills add adithya-s-k/HuggingEnvs
```
**We're looking for new end-to-end recipes** β a task, an environment, a training run, and honest results. [Contributing guide β](https://github.com/adithya-s-k/HuggingEnvs/blob/main/CONTRIBUTING.md)
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