Files
Pepijn 5de7aa5a4f refactor(envs): move benchmark dispatch into EnvConfig subclasses (#3272)
* docs(benchmarks): add benchmark integration guide and standardize benchmark docs

Add a comprehensive guide for adding new benchmarks to LeRobot, and
refactor the existing LIBERO and Meta-World docs to follow the new
standardized template.

* refactor(envs): move dispatch logic from factory into EnvConfig subclasses

Replace hardcoded if/elif chains in factory.py with create_envs() and
get_env_processors() methods on EnvConfig. New benchmarks now only need
to register a config subclass — no factory.py edits required.

Net -23 lines: factory.py shrinks from ~200 to ~70 lines of logic.

* docs(benchmarks): clean up adding-benchmarks guide for clarity

Rewrite for simpler language, better structure, and easier navigation.
Move quick-reference table to the top, fold eval explanation into
architecture section, condense the doc template to a bulleted outline.

* fix link

* fix task count

* fix(tests): fix 3 failing dispatch tests

- test_registry_all_types: skip non-EnvConfig stubs (e.g. TestPluginConfig)
- test_processors_delegation: use None instead of abstract PreTrainedConfig
- test_custom_get_env_processors_override: use DataProcessorPipeline for isinstance check (PolicyProcessorPipeline is a subscripted generic)

* fix: enable SmolVLA eval on LIBERO with custom camera mappings

- Thread camera_name_mapping from LiberoEnv config through to gym envs
- Sync features_map with camera_name_mapping in LiberoEnv.__post_init__
- Fix render() to use first available camera instead of hardcoded "image"
- Handle non-dict final_info in rollout by falling back to info["is_success"]
- Add use_peft legacy field to SmolVLAConfig for checkpoint compat
- Add defaults to GR00TN15Config init=False fields for transformers 5.3

Made-with: Cursor

* fix: use direct AutoresetMode import for gymnasium compat

Made-with: Cursor

* fix: handle gymnasium < 1.0 without AutoresetMode

Made-with: Cursor

* refactor: revert policy changes, keep env-only camera mapping fixes

- Revert GR00T N1.5 default_factory/default changes (transformers compat)
- Revert SmolVLA use_peft legacy field
- Apply ruff formatting fixes
- camera_name_mapping stays entirely in env/eval layer (no policy changes)

Made-with: Cursor

* Update docs/source/env_processor.mdx

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* Update docs/source/env_processor.mdx

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* Update docs/source/env_processor.mdx

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* fix(eval): raise RuntimeError for unsupported final_info format (Gymnasium < 1.0)

Made-with: Cursor

* style: fix markdown code fences in env_processor.mdx

Made-with: Cursor

* docs: remove duplicate code blocks in env_processor.mdx

Made-with: Cursor

* style: revert quadruple backticks to triple (prettier compat)

* docs(env_processor): add EnvConfig subclass step and policy_cfg examples

- Add missing '### 2. Update Your EnvConfig Subclass' section with
  get_env_processors() snippet
- Update factory usage example to show policy_cfg parameter and
  keyword-argument style for both SmolVLA and ACT cases

* docs(env_processor): rename step 2 and fix policy_cfg examples

- Rename '### 2. Update the Factory' → '### 2. Update Your EnvConfig Subclass'
- Update factory usage examples to use keyword-argument style with
  policy_cfg parameter for both SmolVLA and ACT cases

---------

Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
2026-04-08 17:48:58 +02:00
..

Generating the documentation

To generate the documentation, you first have to build it. Several packages are necessary to build the doc, you can install them with the following command, at the root of the code repository:

pip install -e . -r docs-requirements.txt

You will also need nodejs. Please refer to their installation page


NOTE

You only need to generate the documentation to inspect it locally (if you're planning changes and want to check how they look before committing for instance). You don't have to git commit the built documentation.


Building the documentation

Once you have setup the doc-builder and additional packages, you can generate the documentation by typing the following command:

doc-builder build lerobot docs/source/ --build_dir ~/tmp/test-build

You can adapt the --build_dir to set any temporary folder that you prefer. This command will create it and generate the MDX files that will be rendered as the documentation on the main website. You can inspect them in your favorite Markdown editor.

Previewing the documentation

To preview the docs, first install the watchdog module with:

pip install watchdog

Then run the following command:

doc-builder preview lerobot docs/source/

The docs will be viewable at http://localhost:3000. You can also preview the docs once you have opened a PR. You will see a bot add a comment to a link where the documentation with your changes lives.


NOTE

The preview command only works with existing doc files. When you add a completely new file, you need to update _toctree.yml & restart preview command (ctrl-c to stop it & call doc-builder preview ... again).


Adding a new element to the navigation bar

Accepted files are Markdown (.md).

Create a file with its extension and put it in the source directory. You can then link it to the toc-tree by putting the filename without the extension in the _toctree.yml file.

Renaming section headers and moving sections

It helps to keep the old links working when renaming the section header and/or moving sections from one document to another. This is because the old links are likely to be used in Issues, Forums, and Social media and it'd make for a much more superior user experience if users reading those months later could still easily navigate to the originally intended information.

Therefore, we simply keep a little map of moved sections at the end of the document where the original section was. The key is to preserve the original anchor.

So if you renamed a section from: "Section A" to "Section B", then you can add at the end of the file:

Sections that were moved:

[ <a href="#section-b">Section A</a><a id="section-a"></a> ]

and of course, if you moved it to another file, then:

Sections that were moved:

[ <a href="../new-file#section-b">Section A</a><a id="section-a"></a> ]

Use the relative style to link to the new file so that the versioned docs continue to work.

For an example of a rich moved sections set please see the very end of the transformers Trainer doc.

Adding a new tutorial

Adding a new tutorial or section is done in two steps:

  • Add a new file under ./source. This file can either be ReStructuredText (.rst) or Markdown (.md).
  • Link that file in ./source/_toctree.yml on the correct toc-tree.

Make sure to put your new file under the proper section. If you have a doubt, feel free to ask in a Github Issue or PR.

Writing source documentation

Values that should be put in code should either be surrounded by backticks: `like so`. Note that argument names and objects like True, None or any strings should usually be put in code.

Writing a multi-line code block

Multi-line code blocks can be useful for displaying examples. They are done between two lines of three backticks as usual in Markdown:

```
# first line of code
# second line
# etc
```

Adding an image

Due to the rapidly growing repository, it is important to make sure that no files that would significantly weigh down the repository are added. This includes images, videos, and other non-text files. We prefer to leverage a hf.co hosted dataset like the ones hosted on hf-internal-testing in which to place these files and reference them by URL. We recommend putting them in the following dataset: huggingface/documentation-images. If an external contribution, feel free to add the images to your PR and ask a Hugging Face member to migrate your images to this dataset.