chore: update repo and docs URLs after migration to huggingface org (#736)

sergiopaniego · web-flow · commit 653e9580f8ee · 2026-06-02T11:13:46.000+02:00
diff --git a/README.md b/README.md
@@ -4,8 +4,8 @@ An e2e framework for creating, deploying and using isolated execution environmen
 
 [![PyPI](https://img.shields.io/pypi/v/openenv?color=blue)](https://pypi.org/project/openenv/)
 [![Discord](https://img.shields.io/badge/Discord-OpenEnv-7289da?style=flat&logo=discord&logoColor=white)](https://discord.gg/YsTYBh6PD9)
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-pytorch/OpenEnv/blob/main/examples/OpenEnv_Tutorial.ipynb)
-[![Docs](https://img.shields.io/badge/Docs-Explore-blue?logo=readthedocs&logoColor=white)](https://meta-pytorch.org/OpenEnv/)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/OpenEnv/blob/main/examples/OpenEnv_Tutorial.ipynb)
+[![Docs](https://img.shields.io/badge/Docs-Explore-blue?logo=readthedocs&logoColor=white)](https://huggingface.github.io/OpenEnv/)
 
 ---
 
@@ -70,7 +70,7 @@ with EchoEnv(base_url="https://openenv-echo-env.hf.space").sync() as client:
     print(result.observation.result)
 ```
 
-For a detailed quick start, check out the [docs page](https://meta-pytorch.org/OpenEnv/auto_getting_started/index.html).
+For a detailed quick start, check out the [docs page](https://huggingface.github.io/OpenEnv/auto_getting_started/index.html).
 
 ## OpenEnv on partner platforms:
 
@@ -102,11 +102,11 @@ OpenEnv is openly governed by a technical committee that includes Hugging Face,
 
 Below is a list of active and historical RFCs for OpenEnv. RFCs are proposals for major changes or features. Please review and contribute!
 
-- [RFC 001: Baseline API and Interface Specifications](https://github.com/meta-pytorch/OpenEnv/pull/26)
-- [RFC 002: Discoverability of environment tools by agents](https://github.com/meta-pytorch/OpenEnv/pull/32)
-- [RFC 003: Add MCP (Model Context Protocol) support](https://github.com/meta-pytorch/OpenEnv/pull/224)
-- [RFC 004: Add delayed rewards support for trajectory-based scoring](https://github.com/meta-pytorch/OpenEnv/pull/337)
-- [RFC 005: Agentic Harness Integration](https://github.com/meta-pytorch/OpenEnv/pull/387)
+- [RFC 001: Baseline API and Interface Specifications](https://github.com/huggingface/OpenEnv/pull/26)
+- [RFC 002: Discoverability of environment tools by agents](https://github.com/huggingface/OpenEnv/pull/32)
+- [RFC 003: Add MCP (Model Context Protocol) support](https://github.com/huggingface/OpenEnv/pull/224)
+- [RFC 004: Add delayed rewards support for trajectory-based scoring](https://github.com/huggingface/OpenEnv/pull/337)
+- [RFC 005: Agentic Harness Integration](https://github.com/huggingface/OpenEnv/pull/387)
 
 ## Architecture
 
@@ -304,7 +304,7 @@ For detailed options: `openenv init --help` and `openenv push --help`.
 
 ```bash
 # Clone the repository
-git clone https://github.com/meta-pytorch/OpenEnv.git
+git clone https://github.com/huggingface/OpenEnv.git
 cd OpenEnv
 
 # Install core package in editable mode
@@ -380,7 +380,7 @@ See the [Oumi example](https://github.com/oumi-ai/oumi/blob/main/notebooks/Oumi%
 | [Atari Environment](envs/atari_env/README.md) | Classic Arcade Learning Environment tasks for RL benchmarking. |
 | [FinRL Environment](envs/finrl_env/README.md) | Financial market simulations for algorithmic trading experiments. |
 
-> Browse the full catalog of community environments at [meta-pytorch.org/OpenEnv/environments](https://meta-pytorch.org/OpenEnv/environments.html).
+> Browse the full catalog of community environments at [huggingface.github.io/OpenEnv/environments](https://huggingface.github.io/OpenEnv/environments.html).
 
 ## Community Support & Acknowledgments
 This is an open and community-centric project, governed in public by a technical committee that includes Hugging Face, Unsloth, Reflection, and Meta PyTorch. If you would like to add your project or organization here, please open a pull request for maintainer review.
diff --git a/docs/README.md b/docs/README.md
@@ -154,7 +154,7 @@ The file `docs/source/_static/versions.json` lists all published versions. Each
   {
     "name": "main",
     "version": "main",
-    "url": "https://meta-pytorch.org/OpenEnv/",
+    "url": "https://huggingface.github.io/OpenEnv/",
     "preferred": true
   }
 ]
@@ -173,14 +173,14 @@ When cutting a release:
 
 1. Ensure `pyproject.toml` has the release version (e.g. `0.2.0`)
 2. Build with `make html-stable` — this produces docs tagged as version `0.2`
-3. Deploy the output to a versioned path (e.g. `https://meta-pytorch.org/OpenEnv/0.2/`)
+3. Deploy the output to a versioned path (e.g. `https://huggingface.github.io/OpenEnv/0.2/`)
 4. Add an entry to `docs/source/_static/versions.json`:
 
 ```json
 {
   "name": "0.2",
   "version": "0.2",
-  "url": "https://meta-pytorch.org/OpenEnv/0.2/"
+  "url": "https://huggingface.github.io/OpenEnv/0.2/"
 }
 ```
 
diff --git a/docs/source/_static/versions.json b/docs/source/_static/versions.json
@@ -2,7 +2,7 @@
   {
     "name": "main ",
     "version": "main",
-    "url": "https://meta-pytorch.org/OpenEnv/",
+    "url": "https://huggingface.github.io/OpenEnv/",
     "preferred": true
   }
 ]
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -99,7 +99,7 @@
     "icon_links": [
         {
             "name": "GitHub",
-            "url": "https://github.com/meta-pytorch/OpenEnv",
+            "url": "https://github.com/huggingface/OpenEnv",
             "icon": "fa-brands fa-github",
         },
     ],
@@ -134,9 +134,9 @@
     "theme_variables": theme_variables,
     "display_github": False,
     "github_url": "https://github.com",
-    "github_user": "meta-pytorch",
+    "github_user": "huggingface",
     "github_repo": "OpenEnv",
-    "feedback_url": "https://github.com/meta-pytorch/OpenEnv",
+    "feedback_url": "https://github.com/huggingface/OpenEnv",
     "github_version": "main",
     "doc_path": "docs/source",
     # Suppress the theme's PyTorch-wide sidebar blocks (PyTorch Libraries,
@@ -148,7 +148,7 @@
 }
 
 # Base URL for the site (used by sitemap and canonical URLs)
-html_baseurl = "https://meta-pytorch.org/OpenEnv/"
+html_baseurl = "https://huggingface.github.io/OpenEnv/"
 sitemap_locales = [None]
 sitemap_excludes = [
     "search.html",
diff --git a/docs/source/contributing.md b/docs/source/contributing.md
@@ -10,7 +10,7 @@ We welcome contributions from the community! OpenEnv is an open-source project a
 
 ### 🐛 Report Bugs
 
-Found a bug? Please [open an issue](https://github.com/meta-pytorch/OpenEnv/issues/new) with:
+Found a bug? Please [open an issue](https://github.com/huggingface/OpenEnv/issues/new) with:
 
 - A clear description of the problem
 - Steps to reproduce
@@ -19,7 +19,7 @@ Found a bug? Please [open an issue](https://github.com/meta-pytorch/OpenEnv/issu
 
 ### 💡 Suggest Features
 
-Have an idea? Open a [feature request](https://github.com/meta-pytorch/OpenEnv/issues/new) describing:
+Have an idea? Open a [feature request](https://github.com/huggingface/OpenEnv/issues/new) describing:
 
 - The problem you're trying to solve
 - Your proposed solution
@@ -76,7 +76,7 @@ OpenEnv is openly governed by a technical committee that includes Hugging Face,
 Unsloth, Reflection, and Meta PyTorch. The committee coordinates project
 direction, major technical decisions, RFCs, and release planning in public.
 
-Use the [OpenEnv repository](https://github.com/meta-pytorch/OpenEnv) to file
+Use the [OpenEnv repository](https://github.com/huggingface/OpenEnv) to file
 issues, discuss substantial changes, and submit pull requests.
 
 ## License
diff --git a/docs/source/getting_started/environment-builder.md b/docs/source/getting_started/environment-builder.md
@@ -62,7 +62,7 @@ A typical workflow looks like:
 
 - Python 3.11+ and [`uv`](https://github.com/astral-sh/uv) for dependency locking
 - Docker Desktop / Docker Engine
-- The OpenEnv library installed: `pip install https://github.com/meta-pytorch/OpenEnv.git`
+- The OpenEnv library installed: `pip install https://github.com/huggingface/OpenEnv.git`
 
 ## Step-by-Step Guide
 
@@ -441,4 +441,4 @@ finally:
 
 Your next steps are to:
 
-- [Try out the end-to-end tutorial](https://colab.research.google.com/github/meta-pytorch/OpenEnv/blob/main/examples/OpenEnv_Tutorial.ipynb)
+- [Try out the end-to-end tutorial](https://colab.research.google.com/github/huggingface/OpenEnv/blob/main/examples/OpenEnv_Tutorial.ipynb)
diff --git a/docs/source/guides/rewards.md b/docs/source/guides/rewards.md
@@ -88,6 +88,6 @@ Per-turn progress helps the agent explore, but the terminal outcome still domina
 ## Next Steps
 
 - [Rubrics tutorial](../tutorials/rubrics.md) — full API walkthrough with composable examples.
-- [RFC 004](https://github.com/meta-pytorch/OpenEnv/blob/main/rfcs/004-rubrics.md) — design rationale.
+- [RFC 004](https://github.com/huggingface/OpenEnv/blob/main/rfcs/004-rubrics.md) — design rationale.
 - [RL Framework Integration](rl-integration.md) — consume the reward signal in a training loop.
 - [Environment Anatomy](environment-anatomy.md) — where the rubric plugs in.
diff --git a/docs/source/guides/simulation-vs-production.md b/docs/source/guides/simulation-vs-production.md
@@ -223,5 +223,5 @@ That is not the model OpenEnv uses.
 
 - [Core API](../reference/core.md)
 - [Getting Started Tutorials](auto_getting_started/index)
-- [RFC 002: Environment Spec](https://github.com/meta-pytorch/OpenEnv/blob/main/rfcs/002-env-spec.md)
-- [RFC 005: Agentic Harnesses](https://github.com/meta-pytorch/OpenEnv/blob/main/rfcs/005-agentic-harnesses.md)
+- [RFC 002: Environment Spec](https://github.com/huggingface/OpenEnv/blob/main/rfcs/002-env-spec.md)
+- [RFC 005: Agentic Harnesses](https://github.com/huggingface/OpenEnv/blob/main/rfcs/005-agentic-harnesses.md)
diff --git a/docs/source/index.md b/docs/source/index.md
@@ -54,7 +54,7 @@ New to OpenEnv? Follow our recommended learning path:
 
 We welcome contributions from the community! OpenEnv is openly governed by a technical committee that includes Hugging Face, Unsloth, Reflection, and Meta PyTorch. The committee coordinates project direction, major technical decisions, RFCs, and release planning through the public repository.
 
-If you find a bug, have a feature request, or want to contribute a new environment, please open an issue or submit a pull request. The repository is hosted on GitHub at [meta-pytorch/OpenEnv](https://github.com/meta-pytorch/OpenEnv).
+If you find a bug, have a feature request, or want to contribute a new environment, please open an issue or submit a pull request. The repository is hosted on GitHub at [huggingface/OpenEnv](https://github.com/huggingface/OpenEnv).
 
 ```{warning}
 OpenEnv is currently in an experimental stage. You should expect bugs, incomplete features, and APIs that may change in future versions. The project welcomes bug fixes, but significant changes should be discussed before implementation so the technical committee and community can coordinate scope, compatibility, and release timing. Signal your intention to contribute in the issue tracker by filing a new issue or claiming an existing one.
diff --git a/docs/source/tutorials/browsergym-harness.md b/docs/source/tutorials/browsergym-harness.md
@@ -22,7 +22,7 @@ Install OpenEnv, TRL, and the BrowserGym environment package:
 
 ```bash
 pip install -U "trl[vllm]" peft trackio kernels
-pip install -U git+https://github.com/meta-pytorch/OpenEnv.git
+pip install -U git+https://github.com/huggingface/OpenEnv.git
 pip install -U "openenv-browsergym @ git+https://huggingface.co/spaces/openenv/browsergym_env"
 ```
 
@@ -124,6 +124,6 @@ BrowserGym episode per prompt, and returns `prompt_ids`, `completion_ids`,
 
 ## Full Example
 
-See [`examples/browsergym_harness.py`](https://github.com/meta-pytorch/OpenEnv/blob/main/examples/browsergym_harness.py)
+See [`examples/browsergym_harness.py`](https://github.com/huggingface/OpenEnv/blob/main/examples/browsergym_harness.py)
 for a complete TRL-oriented helper that includes action normalization and a
 ready-to-use `build_browsergym_rollout_func`.
diff --git a/docs/source/tutorials/end-to-end-walkthrough.md b/docs/source/tutorials/end-to-end-walkthrough.md
@@ -1,6 +1,6 @@
 # End-to-end OpenEnv walkthrough: train a reasoning agent with GRPO
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-pytorch/OpenEnv/blob/main/examples/end_to_end_walkthrough.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/OpenEnv/blob/main/examples/end_to_end_walkthrough.ipynb)
 
 In this tutorial you'll take a small open-weight model, an OpenEnv environment, and TRL, and run the full training pipeline end-to-end:
 
@@ -19,7 +19,7 @@ We pair **GRPO** with a **procedural** task on purpose. GRPO is a value-free RL
 ## What you'll use
 
 - **Model**: [`Qwen/Qwen3-1.7B`](https://huggingface.co/Qwen/Qwen3-1.7B) — fits a single A100 (40 GB) at the settings below and is large enough for GRPO to move the needle. For smaller GPUs, swap to [`Qwen/Qwen3-0.6B`](https://huggingface.co/Qwen/Qwen3-0.6B).
-- **Environment**: [`reasoning_gym_env`](https://github.com/meta-pytorch/OpenEnv/tree/main/envs/reasoning_gym_env), an OpenEnv wrapper around the [Reasoning Gym](https://github.com/open-thought/reasoning-gym) library. Each episode is a single Q→A.
+- **Environment**: [`reasoning_gym_env`](https://github.com/huggingface/OpenEnv/tree/main/envs/reasoning_gym_env), an OpenEnv wrapper around the [Reasoning Gym](https://github.com/open-thought/reasoning-gym) library. Each episode is a single Q→A.
 - **Dataset**: `chain_sum` from Reasoning Gym — chains of integer additions like `Compute 17 + 4 + 22 + 9`. Procedurally generated, so every rollout sees a fresh problem.
 - **Trainer**: [TRL `GRPOTrainer`](https://huggingface.co/docs/trl/main/en/grpo_trainer) with `environment_factory`.
 
@@ -201,7 +201,7 @@ dataset = Dataset.from_dict(
 
 ## 7. Set the GRPO config
 
-These settings mirror the [Wordle GRPO tutorial](https://meta-pytorch.org/OpenEnv/tutorials/wordle-grpo.html) and are tuned for a single A100 (40 GB). Bigger GPUs can raise `per_device_train_batch_size` and `num_generations`; smaller GPUs should drop to Qwen3-0.6B and shrink `max_completion_length`.
+These settings mirror the [Wordle GRPO tutorial](https://huggingface.github.io/OpenEnv/tutorials/wordle-grpo.html) and are tuned for a single A100 (40 GB). Bigger GPUs can raise `per_device_train_batch_size` and `num_generations`; smaller GPUs should drop to Qwen3-0.6B and shrink `max_completion_length`.
 
 ```python
 from trl import GRPOConfig
@@ -308,7 +308,7 @@ else:
 A delta of **+10 to +30 pp** is what you should expect at this difficulty; outside that range:
 
 - **Δ ≈ 0 pp, initial already high (≥90%)** — `DATASET_CONFIG` is too easy; the model already solves it before training. Bump `min_terms` / `min_digits`.
-- **Δ ≈ 0 pp, initial very low (≤20%)** — task is too hard for the base model to ever stumble onto a correct answer, so GRPO has no positive rollouts to learn from. Lower `min_terms` / `min_digits`. If the reward stays near zero even at minimum difficulty, the bottleneck is likely **format compliance** rather than task difficulty — the model never produces a valid `<tool_call>` so the env cannot score it. See the [SFT warm-up tutorial](https://meta-pytorch.org/OpenEnv/tutorials/sft-warmup.html) for how to fix this before returning to GRPO.
+- **Δ ≈ 0 pp, initial very low (≤20%)** — task is too hard for the base model to ever stumble onto a correct answer, so GRPO has no positive rollouts to learn from. Lower `min_terms` / `min_digits`. If the reward stays near zero even at minimum difficulty, the bottleneck is likely **format compliance** rather than task difficulty — the model never produces a valid `<tool_call>` so the env cannot score it. See the [SFT warm-up tutorial](https://huggingface.github.io/OpenEnv/tutorials/sft-warmup.html) for how to fix this before returning to GRPO.
 - **Δ negative** — you trained past saturation: once `reward` plateaus, the KL penalty starts pulling the policy back toward the reference. Reduce `max_steps` so training stops while it's still net-improving.
 
 ```{note}
@@ -320,6 +320,6 @@ This delta is measured *during training* — same prompt format, same env, same
 ## 11. Where to go next
 
 - **Swap the dataset.** `chain_sum` is one of ~100 datasets in [Reasoning Gym](https://github.com/open-thought/reasoning-gym) — try `simple_equations`, `letter_counting`, or `propositional_logic` by changing `DATASET_NAME` and re-running the same recipe.
-- **Try a different environment.** The same `environment_factory` shape works for any OpenEnv environment with a small tool surface — browse the [environment catalog](https://meta-pytorch.org/OpenEnv/environments.html) for ideas.
-- **Use SFT as a warm-start.** If format compliance is the bottleneck (initial reward near zero regardless of difficulty), the [SFT warm-up tutorial](https://meta-pytorch.org/OpenEnv/tutorials/sft-warmup.html) shows how to collect teacher rollouts, filter by reward, and fine-tune a student model — so GRPO starts with non-zero `reward_std` from the first batch.
-- **Read the other tutorials.** [Wordle GRPO](https://meta-pytorch.org/OpenEnv/tutorials/wordle-grpo.html) covers the multi-step variant; the full list is in the [tutorials index](https://meta-pytorch.org/OpenEnv/tutorials/index.html).
+- **Try a different environment.** The same `environment_factory` shape works for any OpenEnv environment with a small tool surface — browse the [environment catalog](https://huggingface.github.io/OpenEnv/environments.html) for ideas.
+- **Use SFT as a warm-start.** If format compliance is the bottleneck (initial reward near zero regardless of difficulty), the [SFT warm-up tutorial](https://huggingface.github.io/OpenEnv/tutorials/sft-warmup.html) shows how to collect teacher rollouts, filter by reward, and fine-tune a student model — so GRPO starts with non-zero `reward_std` from the first batch.
+- **Read the other tutorials.** [Wordle GRPO](https://huggingface.github.io/OpenEnv/tutorials/wordle-grpo.html) covers the multi-step variant; the full list is in the [tutorials index](https://huggingface.github.io/OpenEnv/tutorials/index.html).
diff --git a/docs/source/tutorials/evaluation-inspect.md b/docs/source/tutorials/evaluation-inspect.md
@@ -1,6 +1,6 @@
 # Evaluating agents with Inspect AI
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-pytorch/OpenEnv/blob/main/examples/evaluation_inspect.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/OpenEnv/blob/main/examples/evaluation_inspect.ipynb)
 
 After training a model in an OpenEnv environment, you need to measure how it
 actually performs on a held-out set of episodes. OpenEnv integrates with
@@ -37,7 +37,7 @@ Run via InspectAIHarness → EvalResult with structured scores
 
 ```bash
 pip install "inspect-ai>=0.3.0"
-pip install "openenv @ git+https://github.com/meta-pytorch/OpenEnv.git"
+pip install "openenv @ git+https://github.com/huggingface/OpenEnv.git"
 ```
 
 `inspect-ai` is an optional dependency — `InspectAIHarness` is importable
@@ -276,9 +276,9 @@ def my_env_solver(base_url: str):
 
 ## Next steps
 
-- [End-to-end walkthrough](https://meta-pytorch.org/OpenEnv/tutorials/end-to-end-walkthrough.html) — full GRPO training loop that produces a model you can evaluate with this tutorial
-- [SFT warm-up tutorial](https://meta-pytorch.org/OpenEnv/tutorials/sft-warmup.html) — collect rollouts, filter by reward, and fine-tune a student model before running GRPO
-- [Rubrics tutorial](https://meta-pytorch.org/OpenEnv/tutorials/rubrics.html) — define reward functions inside
+- [End-to-end walkthrough](https://huggingface.github.io/OpenEnv/tutorials/end-to-end-walkthrough.html) — full GRPO training loop that produces a model you can evaluate with this tutorial
+- [SFT warm-up tutorial](https://huggingface.github.io/OpenEnv/tutorials/sft-warmup.html) — collect rollouts, filter by reward, and fine-tune a student model before running GRPO
+- [Rubrics tutorial](https://huggingface.github.io/OpenEnv/tutorials/rubrics.html) — define reward functions inside
   the environment using composable rubrics
 - [Inspect AI documentation](https://inspect.aisi.org.uk/) — full reference
   for tasks, solvers, scorers, and the log viewer
diff --git a/docs/source/tutorials/index.md b/docs/source/tutorials/index.md
diff --git a/docs/source/tutorials/mcp-environment.md b/docs/source/tutorials/mcp-environment.md
diff --git a/docs/source/tutorials/openenv-tutorial.md b/docs/source/tutorials/openenv-tutorial.md
diff --git a/docs/source/tutorials/rubrics.md b/docs/source/tutorials/rubrics.md
diff --git a/docs/source/tutorials/sft-warmup.md b/docs/source/tutorials/sft-warmup.md
diff --git a/docs/source/tutorials/wordle-grpo.md b/docs/source/tutorials/wordle-grpo.md

Original file line number	Diff line number	Diff line change
@@ -154,7 +154,7 @@ The file `docs/source/_static/versions.json` lists all published versions. Each
`154`	`154`	`{`
`155`	`155`	`"name": "main",`
`156`	`156`	`"version": "main",`
`157`		`- "url": "https://meta-pytorch.org/OpenEnv/",`
	`157`	`+ "url": "https://huggingface.github.io/OpenEnv/",`
`158`	`158`	`"preferred": true`
`159`	`159`	`}`
`160`	`160`	`]`
`@@ -173,14 +173,14 @@ When cutting a release:`
`173`	`173`
`174`	`174`	1. Ensure `pyproject.toml` has the release version (e.g. `0.2.0`)
`175`	`175`	2. Build with `make html-stable` — this produces docs tagged as version `0.2`
`176`		-3. Deploy the output to a versioned path (e.g. `https://meta-pytorch.org/OpenEnv/0.2/`)
	`176`	+3. Deploy the output to a versioned path (e.g. `https://huggingface.github.io/OpenEnv/0.2/`)
`177`	`177`	4. Add an entry to `docs/source/_static/versions.json`:
`178`	`178`
`179`	`179`	```json
`180`	`180`	`{`
`181`	`181`	`"name": "0.2",`
`182`	`182`	`"version": "0.2",`
`183`		`- "url": "https://meta-pytorch.org/OpenEnv/0.2/"`
	`183`	`+ "url": "https://huggingface.github.io/OpenEnv/0.2/"`
`184`	`184`	`}`
`185`	`185`	```
`186`	`186`
Original file line number	Diff line number	Diff line change
`@@ -2,7 +2,7 @@`
`2`	`2`	`{`
`3`	`3`	`"name": "main ",`
`4`	`4`	`"version": "main",`
`5`		`- "url": "https://meta-pytorch.org/OpenEnv/",`
	`5`	`+ "url": "https://huggingface.github.io/OpenEnv/",`
`6`	`6`	`"preferred": true`
`7`	`7`	`}`
`8`	`8`	`]`