Merge branch 'main' into user/azouitine/2025-7-2-implement-pipeline

2026-05-30 10:21:24 +00:00 · 2025-08-06 14:15:01 +02:00
parent fd4ae3466b 88f7bf01c1
commit 20f2910b63
31 changed files with 1623 additions and 207 deletions
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -19,6 +19,11 @@ on:
    tags:
      - 'v*.*.*' # Trigger on tags like v0.1.0, v1.0.0

+# Sets up the environment variables
+env:
+  UV_VERSION: "0.8.0"
+  PYTHON_VERSION: "3.10"
+
 jobs:
  # This job builds the Python package and publishes it to PyPI
  build-and-publish:
@@ -50,6 +55,7 @@ jobs:
          VERSION_NUMBER=${VERSION#v}
          echo "tag_version=$VERSION_NUMBER" >> $GITHUB_OUTPUT
      - name: Check if version matches pyproject.toml
+        if: startsWith(github.ref, 'refs/tags/v') && !contains(github.ref, '-')
        # zizmor: ignore[template-injection]
        run: |
          TAG_VERSION=${{ steps.extract_info.outputs.tag_version }}
@@ -86,13 +92,29 @@ jobs:
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        # zizmor: ignore[template-injection]
-        run: gh release create ${{ github.ref_name }} --release-name "Release ${{ github.ref_name }}" --generate-notes ./dist/*
+        run: |
+          gh release create ${{ github.ref_name }} \
+            --title "Release ${{ github.ref_name }}" \
+            --generate-notes \
+            --draft=$([[ "${{ github.ref_name }}" == *-* ]] && echo true || echo false) \
+            --prerelease=$([[ "${{ github.ref_name }}" == *-* ]] && echo true || echo false) \
+            ./dist/*

-      - name: Publish to PyPI
-        if: startsWith(github.ref, 'refs/tags/v')
+      - name: Publish to TestPyPI for pre-releases
+        # True for tags like 'v0.2.0-rc1'
+        if: startsWith(github.ref, 'refs/tags/v') && contains(github.ref, '-')
        uses: pypa/gh-action-pypi-publish@v1.12.4 # zizmor: ignore[unpinned-uses, use-trusted-publishing]
        with:
-          password: ${{ secrets.PYPI_API_TOKEN }}
+          repository-url: https://test.pypi.org/legacy/
+          verbose: true
+          print-hash: true
+
+      - name: Publish to PyPI
+        if: startsWith(github.ref, 'refs/tags/v') && !contains(github.ref, '-')
+        uses: pypa/gh-action-pypi-publish@v1.12.4 # zizmor: ignore[unpinned-uses, use-trusted-publishing]
+        with:
+          verbose: true
+          print-hash: true

  # This job runs end-to-end tests on the release
  test-release:
@@ -119,15 +141,31 @@ jobs:
          enable-cache: true
          version: ${{ env.UV_VERSION }}
          python-version: ${{ env.PYTHON_VERSION }}
+      - name: Create uv virtual environment
+        run: uv venv
      - name: Install lerobot release
-        run: uv run pip install lerobot==${{ needs.build-and-publish.outputs.version }} # zizmor: ignore[template-injection]
-
+        # zizmor: ignore[template-injection]
+        run: |
+          VERSION="${{ needs.build-and-publish.outputs.version }}"
+          if [[ "$VERSION" == *-* ]]; then
+            BASE_VERSION="${VERSION%%-*}"
+            echo "Installing pre-release version $BASE_VERSION from TestPyPI..."
+            uv pip install \
+              --index-url https://test.pypi.org/simple/ \
+              --extra-index-url https://pypi.org/simple \
+              --index-strategy unsafe-best-match \
+               "lerobot[all]==$BASE_VERSION"
+          else
+            echo "Installing release version $VERSION from PyPI..."
+            uv pip install "lerobot[all]==$VERSION"
+          fi
      - name: Check lerobot version
-        run: uv run lerobot --version
+        run: uv run python -c "import lerobot; print(lerobot.__version__)"

      - name: Run end-to-end tests
        run: uv run make test-end-to-end


-# TODO(Steven): Publish draft/pre-release and to test pypi
+# TODO(Steven): Publish draft/pre-release and to test pypi weekly
+# TODO(Steven): Separate build and publish job
 # TODO(Steven): Tag documentation with the same version as the package
--- a/README.md
+++ b/README.md
@@ -1,25 +1,21 @@
 <p align="center">
-  <picture>
-    <source media="(prefers-color-scheme: dark)" srcset="media/lerobot-logo-thumbnail.png">
-    <source media="(prefers-color-scheme: light)" srcset="media/lerobot-logo-thumbnail.png">
-    <img alt="LeRobot, Hugging Face Robotics Library" src="media/lerobot-logo-thumbnail.png" style="max-width: 100%;">
-  </picture>
+  <img alt="LeRobot, Hugging Face Robotics Library" src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/lerobot-logo-thumbnail.png" width="100%">
  <br/>
  <br/>
 </p>

 <div align="center">

-[![Tests](https://github.com/huggingface/lerobot/actions/workflows/nightly-tests.yml/badge.svg?branch=main)](https://github.com/huggingface/lerobot/actions/workflows/nightly-tests.yml?query=branch%3Amain)
-[![Coverage](https://codecov.io/gh/huggingface/lerobot/branch/main/graph/badge.svg?token=TODO)](https://codecov.io/gh/huggingface/lerobot)
+[![Tests](https://github.com/huggingface/lerobot/actions/workflows/nightly.yml/badge.svg?branch=main)](https://github.com/huggingface/lerobot/actions/workflows/nighty.yml?query=branch%3Amain)
 [![Python versions](https://img.shields.io/pypi/pyversions/lerobot)](https://www.python.org/downloads/)
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/huggingface/lerobot/blob/main/LICENSE)
 [![Status](https://img.shields.io/pypi/status/lerobot)](https://pypi.org/project/lerobot/)
 [![Version](https://img.shields.io/pypi/v/lerobot)](https://pypi.org/project/lerobot/)
-[![Examples](https://img.shields.io/badge/Examples-green.svg)](https://github.com/huggingface/lerobot/tree/main/examples)
-[![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-v2.1%20adopted-ff69b4.svg)](https://github.com/huggingface/lerobot/blob/main/CODE_OF_CONDUCT.md)
+[![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-v2.1-ff69b4.svg)](https://github.com/huggingface/lerobot/blob/main/CODE_OF_CONDUCT.md)
 [![Discord](https://dcbadge.vercel.app/api/server/C5P34WJ68S?style=flat)](https://discord.gg/s3KuuzsPFb)

+<!-- [![Coverage](https://codecov.io/gh/huggingface/lerobot/branch/main/graph/badge.svg?token=TODO)](https://codecov.io/gh/huggingface/lerobot) -->
+
 </div>

 <h2 align="center">
@@ -29,10 +25,10 @@

 <div align="center">
  <img
-    src="media/hope_jr/hopejr.png?raw=true"
+    src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/hope_jr/hopejr.png"
    alt="HopeJR robot"
    title="HopeJR robot"
-    style="width: 60%;"
+    width="60%"
  />

  <p><strong>Meet HopeJR – A humanoid robot arm and hand for dexterous manipulation!</strong></p>
@@ -51,20 +47,12 @@
 </h2>

 <div align="center">
-  <div style="display: flex; gap: 1rem; justify-content: center; align-items: center;" >
-    <img
-      src="media/so101/so101.webp?raw=true"
-      alt="SO-101 follower arm"
-      title="SO-101 follower arm"
-      style="width: 40%;"
-    />
-    <img
-      src="media/so101/so101-leader.webp?raw=true"
-      alt="SO-101 leader arm"
-      title="SO-101 leader arm"
-      style="width: 40%;"
-    />
-  </div>
+  <table>
+    <tr>
+      <td align="center"><img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/so101/so101.webp" alt="SO-101 follower arm" title="SO-101 follower arm" width="90%"/></td>
+      <td align="center"><img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/so101/so101-leader.webp" alt="SO-101 leader arm" title="SO-101 leader arm" width="90%"/></td>
+    </tr>
+  </table>

  <p><strong>Meet the updated SO100, the SO-101 – Just €114 per arm!</strong></p>
  <p>Train it in minutes with a few simple moves on your laptop.</p>
@@ -76,7 +64,7 @@
  <p>Want to take it to the next level? Make your SO-101 mobile by building LeKiwi!</p>
  <p>Check out the <a href="https://huggingface.co/docs/lerobot/lekiwi">LeKiwi tutorial</a> and bring your robot to life on wheels.</p>

-  <img src="media/lekiwi/kiwi.webp?raw=true" alt="LeKiwi mobile robot" title="LeKiwi mobile robot" width="50%">
+  <img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/lekiwi/kiwi.webp" alt="LeKiwi mobile robot" title="LeKiwi mobile robot" width="50%">
 </div>

 <br/>
@@ -99,9 +87,9 @@

 <table>
  <tr>
-    <td><img src="media/gym/aloha_act.gif" width="100%" alt="ACT policy on ALOHA env"/></td>
-    <td><img src="media/gym/simxarm_tdmpc.gif" width="100%" alt="TDMPC policy on SimXArm env"/></td>
-    <td><img src="media/gym/pusht_diffusion.gif" width="100%" alt="Diffusion policy on PushT env"/></td>
+    <td><img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/gym/aloha_act.gif" width="100%" alt="ACT policy on ALOHA env"/></td>
+    <td><img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/gym/simxarm_tdmpc.gif" width="100%" alt="TDMPC policy on SimXArm env"/></td>
+    <td><img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/gym/pusht_diffusion.gif" width="100%" alt="Diffusion policy on PushT env"/></td>
  </tr>
  <tr>
    <td align="center">ACT policy on ALOHA env</td>
@@ -110,23 +98,11 @@
  </tr>
 </table>

-### Acknowledgment
-
- The LeRobot team 🤗 for building SmolVLA [Paper](https://arxiv.org/abs/2506.01844), [Blog](https://huggingface.co/blog/smolvla).
- Thanks to Tony Zhao, Zipeng Fu and colleagues for open sourcing ACT policy, ALOHA environments and datasets. Ours are adapted from [ALOHA](https://tonyzhaozh.github.io/aloha) and [Mobile ALOHA](https://mobile-aloha.github.io).
- Thanks to Cheng Chi, Zhenjia Xu and colleagues for open sourcing Diffusion policy, Pusht environment and datasets, as well as UMI datasets. Ours are adapted from [Diffusion Policy](https://diffusion-policy.cs.columbia.edu) and [UMI Gripper](https://umi-gripper.github.io).
- Thanks to Nicklas Hansen, Yunhai Feng and colleagues for open sourcing TDMPC policy, Simxarm environments and datasets. Ours are adapted from [TDMPC](https://github.com/nicklashansen/tdmpc) and [FOWM](https://www.yunhaifeng.com/FOWM).
- Thanks to Antonio Loquercio and Ashish Kumar for their early support.
- Thanks to [Seungjae (Jay) Lee](https://sjlee.cc/), [Mahi Shafiullah](https://mahis.life/) and colleagues for open sourcing [VQ-BeT](https://sjlee.cc/vq-bet/) policy and helping us adapt the codebase to our repository. The policy is adapted from [VQ-BeT repo](https://github.com/jayLEE0301/vq_bet_official).
-
 ## Installation

-Download our source code:
+LeRobot works with Python 3.10+ and PyTorch 2.2+.

-```bash
-git clone https://github.com/huggingface/lerobot.git
-cd lerobot
-```
+### Environment Setup

 Create a virtual environment with Python 3.10 and activate it, e.g. with [`miniconda`](https://docs.anaconda.com/free/miniconda/index.html):

@@ -151,7 +127,18 @@ conda install ffmpeg -c conda-forge
 >
 > - _[On Linux only]_ Install [ffmpeg build dependencies](https://trac.ffmpeg.org/wiki/CompilationGuide/Ubuntu#GettheDependencies) and [compile ffmpeg from source with libsvtav1](https://trac.ffmpeg.org/wiki/CompilationGuide/Ubuntu#libsvtav1), and make sure you use the corresponding ffmpeg binary to your install with `which ffmpeg`.

-Install 🤗 LeRobot:
+### Install LeRobot 🤗
+
+#### From Source
+
+First, clone the repository and navigate into the directory:
+
+```bash
+git clone https://github.com/huggingface/lerobot.git
+cd lerobot
+```
+
+Then, install the library in editable mode. This is useful if you plan to contribute to the code.

 ```bash
 pip install -e .
@@ -172,6 +159,34 @@ For instance, to install 🤗 LeRobot with aloha and pusht, use:
 pip install -e ".[aloha, pusht]"
 ```

+### Installation from PyPI
+
+**Core Library:**
+Install the base package with:
+
+```bash
+pip install lerobot
+```
+
+_This installs only the default dependencies._
+
+**Extra Features:**
+To install additional functionality, use one of the following:
+
+```bash
+pip install 'lerobot[all]'          # All available features
+pip install 'lerobot[aloha,pusht]'  # Specific features (Aloha & Pusht)
+pip install 'lerobot[feetech]'      # Feetech motor support
+```
+
+_Replace `[...]` with your desired features._
+
+**Available Tags:**
+For a full list of optional dependencies, see:
+https://pypi.org/project/lerobot/
+
+### Weights & Biases
+
 To use [Weights and Biases](https://docs.wandb.ai/quickstart) for experiment tracking, log in with

 ```bash
@@ -182,7 +197,7 @@ wandb login

 ### Visualize datasets

-Check out [example 1](./examples/1_load_lerobot_dataset.py) that illustrates how to use our dataset class which automatically downloads data from the Hugging Face hub.
+Check out [example 1](https://github.com/huggingface/lerobot/blob/main/examples/1_load_lerobot_dataset.py) that illustrates how to use our dataset class which automatically downloads data from the Hugging Face hub.

 You can also locally visualize episodes from a dataset on the hub by executing our script from the command line:

@@ -212,7 +227,7 @@ Our script can also visualize datasets stored on a distant server. See `python -

 A dataset in `LeRobotDataset` format is very simple to use. It can be loaded from a repository on the Hugging Face hub or a local folder simply with e.g. `dataset = LeRobotDataset("lerobot/aloha_static_coffee")` and can be indexed into like any Hugging Face and PyTorch dataset. For instance `dataset[0]` will retrieve a single temporal frame from the dataset containing observation(s) and an action as PyTorch tensors ready to be fed to a model.

-A specificity of `LeRobotDataset` is that, rather than retrieving a single frame by its index, we can retrieve several frames based on their temporal relationship with the indexed frame, by setting `delta_timestamps` to a list of relative times with respect to the indexed frame. For example, with `delta_timestamps = {"observation.image": [-1, -0.5, -0.2, 0]}` one can retrieve, for a given index, 4 frames: 3 "previous" frames 1 second, 0.5 seconds, and 0.2 seconds before the indexed frame, and the indexed frame itself (corresponding to the 0 entry). See example [1_load_lerobot_dataset.py](examples/1_load_lerobot_dataset.py) for more details on `delta_timestamps`.
+A specificity of `LeRobotDataset` is that, rather than retrieving a single frame by its index, we can retrieve several frames based on their temporal relationship with the indexed frame, by setting `delta_timestamps` to a list of relative times with respect to the indexed frame. For example, with `delta_timestamps = {"observation.image": [-1, -0.5, -0.2, 0]}` one can retrieve, for a given index, 4 frames: 3 "previous" frames 1 second, 0.5 seconds, and 0.2 seconds before the indexed frame, and the indexed frame itself (corresponding to the 0 entry). See example [1_load_lerobot_dataset.py](https://github.com/huggingface/lerobot/blob/main/examples/1_load_lerobot_dataset.py) for more details on `delta_timestamps`.

 Under the hood, the `LeRobotDataset` format makes use of several ways to serialize data which can be useful to understand if you plan to work more closely with this format. We tried to make a flexible yet simple dataset format that would cover most type of features and specificities present in reinforcement learning and robotics, in simulation and in real-world, with a focus on cameras and robot states but easily extended to other types of sensory inputs as long as they can be represented by a tensor.

@@ -256,7 +271,7 @@ Dataset can be uploaded/downloaded from the HuggingFace hub seamlessly. To work

 ### Evaluate a pretrained policy

-Check out [example 2](./examples/2_evaluate_pretrained_policy.py) that illustrates how to download a pretrained policy from Hugging Face hub, and run an evaluation on its corresponding environment.
+Check out [example 2](https://github.com/huggingface/lerobot/blob/main/examples/2_evaluate_pretrained_policy.py) that illustrates how to download a pretrained policy from Hugging Face hub, and run an evaluation on its corresponding environment.

 We also provide a more capable script to parallelize the evaluation over multiple environments during the same rollout. Here is an example with a pretrained model hosted on [lerobot/diffusion_pusht](https://huggingface.co/lerobot/diffusion_pusht):

@@ -280,13 +295,13 @@ See `python -m lerobot.scripts.eval --help` for more instructions.

 ### Train your own policy

-Check out [example 3](./examples/3_train_policy.py) that illustrates how to train a model using our core library in python, and [example 4](./examples/4_train_policy_with_script.md) that shows how to use our training script from command line.
+Check out [example 3](https://github.com/huggingface/lerobot/blob/main/examples/3_train_policy.py) that illustrates how to train a model using our core library in python, and [example 4](https://github.com/huggingface/lerobot/blob/main/examples/4_train_policy_with_script.md) that shows how to use our training script from command line.

 To use wandb for logging training and evaluation curves, make sure you've run `wandb login` as a one-time setup step. Then, when running the training command above, enable WandB in the configuration by adding `--wandb.enable=true`.

-A link to the wandb logs for the run will also show up in yellow in your terminal. Here is an example of what they look like in your browser. Please also check [here](./examples/4_train_policy_with_script.md#typical-logs-and-metrics) for the explanation of some commonly used metrics in logs.
+A link to the wandb logs for the run will also show up in yellow in your terminal. Here is an example of what they look like in your browser. Please also check [here](https://github.com/huggingface/lerobot/blob/main/examples/4_train_policy_with_script.md#typical-logs-and-metrics) for the explanation of some commonly used metrics in logs.

-![](media/wandb.png)
+\<img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/wandb.png" alt="WandB logs example"\>

 Note: For efficiency, during training every checkpoint is evaluated on a low number of episodes. You may use `--eval.n_episodes=500` to evaluate on more episodes than the default. Or, after training, you may want to re-evaluate your best checkpoints on more episodes or change the evaluation settings. See `python -m lerobot.scripts.eval --help` for more instructions.

@@ -305,26 +320,6 @@ reproduces SOTA results for Diffusion Policy on the PushT task.

 If you would like to contribute to 🤗 LeRobot, please check out our [contribution guide](https://github.com/huggingface/lerobot/blob/main/CONTRIBUTING.md).

-<!-- ### Add a new dataset
-
-To add a dataset to the hub, you need to login using a write-access token, which can be generated from the [Hugging Face settings](https://huggingface.co/settings/tokens):
-```bash
-huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
-```
-
-Then point to your raw dataset folder (e.g. `data/aloha_static_pingpong_test_raw`), and push your dataset to the hub with:
-```bash
-python lerobot/scripts/push_dataset_to_hub.py \
--raw-dir data/aloha_static_pingpong_test_raw \
--out-dir data \
--repo-id lerobot/aloha_static_pingpong_test \
--raw-format aloha_hdf5
-```
-
-See `python lerobot/scripts/push_dataset_to_hub.py --help` for more instructions.
-
-If your dataset format is not supported, implement your own in `lerobot/datasets/push_dataset_to_hub/${raw_format}_format.py` by copying examples like [pusht_zarr](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/pusht_zarr_format.py), [umi_zarr](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/umi_zarr_format.py), [aloha_hdf5](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/aloha_hdf5_format.py), or [xarm_pkl](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/xarm_pkl_format.py). -->
-
 ### Add a pretrained policy

 Once you have trained a policy you may upload it to the Hugging Face hub using a hub id that looks like `${hf_user}/${repo_name}` (e.g. [lerobot/diffusion_pusht](https://huggingface.co/lerobot/diffusion_pusht)).
@@ -341,34 +336,16 @@ To upload these to the hub, run the following:
 huggingface-cli upload ${hf_user}/${repo_name} path/to/pretrained_model
 ```

-See [eval.py](https://github.com/huggingface/lerobot/blob/main/lerobot/scripts/eval.py) for an example of how other people may use your policy.
+See [eval.py](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/eval.py) for an example of how other people may use your policy.

-### Improve your code with profiling
+### Acknowledgment

-An example of a code snippet to profile the evaluation of a policy:
-
-<!-- prettier-ignore-start -->
-```python
-from torch.profiler import profile, record_function, ProfilerActivity
-
-def trace_handler(prof):
-    prof.export_chrome_trace(f"tmp/trace_schedule_{prof.step_num}.json")
-
-with profile(
-    activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA],
-    schedule=torch.profiler.schedule(
-        wait=2,
-        warmup=2,
-        active=3,
-    ),
-    on_trace_ready=trace_handler
-) as prof:
-    with record_function("eval_policy"):
-        for i in range(num_episodes):
-            prof.step()
-            # insert code to profile, potentially whole body of eval_policy function
-```
-<!-- prettier-ignore-end -->
+- The LeRobot team 🤗 for building SmolVLA [Paper](https://arxiv.org/abs/2506.01844), [Blog](https://huggingface.co/blog/smolvla).
+- Thanks to Tony Zhao, Zipeng Fu and colleagues for open sourcing ACT policy, ALOHA environments and datasets. Ours are adapted from [ALOHA](https://tonyzhaozh.github.io/aloha) and [Mobile ALOHA](https://mobile-aloha.github.io).
+- Thanks to Cheng Chi, Zhenjia Xu and colleagues for open sourcing Diffusion policy, Pusht environment and datasets, as well as UMI datasets. Ours are adapted from [Diffusion Policy](https://diffusion-policy.cs.columbia.edu) and [UMI Gripper](https://umi-gripper.github.io).
+- Thanks to Nicklas Hansen, Yunhai Feng and colleagues for open sourcing TDMPC policy, Simxarm environments and datasets. Ours are adapted from [TDMPC](https://github.com/nicklashansen/tdmpc) and [FOWM](https://www.yunhaifeng.com/FOWM).
+- Thanks to Antonio Loquercio and Ashish Kumar for their early support.
+- Thanks to [Seungjae (Jay) Lee](https://sjlee.cc/), [Mahi Shafiullah](https://mahis.life/) and colleagues for open sourcing [VQ-BeT](https://sjlee.cc/vq-bet/) policy and helping us adapt the codebase to our repository. The policy is adapted from [VQ-BeT repo](https://github.com/jayLEE0301/vq_bet_official).

 ## Citation

@@ -376,83 +353,13 @@ If you want, you can cite this work with:

 ```bibtex
@misc{cadene2024lerobot,
-    author = {Cadene, Remi and Alibert, Simon and Soare, Alexander and Gallouedec, Quentin and Zouitine, Adil and Palma, Steven and Kooijmans, Pepijn and Aractingi, Michel and Shukor, Mustafa and Aubakirova, Dana and Russi, Martino and Capuano, Francesco and Pascale, Caroline and Choghari, Jade and Moss, Jess and Wolf, Thomas},
+    author = {Cadene, Remi and Alibert, Simon and Soare, Alexander and Gallouedec, Quentin and Zouitine, Adil and Palma, Steven and Kooijmans, Pepijn and Aractingi, Michel and Shukor, Mustafa and Aubakirova, Dana and Russi, Martino and Capuano, Francesco and Pascal, Caroline and Choghari, Jade and Moss, Jess and Wolf, Thomas},
    title = {LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch},
    howpublished = "\url{https://github.com/huggingface/lerobot}",
    year = {2024}
 }
 ```

-Additionally, if you are using any of the particular policy architecture, pretrained models, or datasets, it is recommended to cite the original authors of the work as they appear below:
-
- [SmolVLA](https://arxiv.org/abs/2506.01844)
-
-```bibtex
-@article{shukor2025smolvla,
-  title={SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics},
-  author={Shukor, Mustafa and Aubakirova, Dana and Capuano, Francesco and Kooijmans, Pepijn and Palma, Steven and Zouitine, Adil and Aractingi, Michel and Pascal, Caroline and Russi, Martino and Marafioti, Andres and Alibert, Simon and Cord, Matthieu and Wolf, Thomas and Cadene, Remi},
-  journal={arXiv preprint arXiv:2506.01844},
-  year={2025}
-}
-```
-
- [Diffusion Policy](https://diffusion-policy.cs.columbia.edu)
-
-```bibtex
-@article{chi2024diffusionpolicy,
-	author = {Cheng Chi and Zhenjia Xu and Siyuan Feng and Eric Cousineau and Yilun Du and Benjamin Burchfiel and Russ Tedrake and Shuran Song},
-	title ={Diffusion Policy: Visuomotor Policy Learning via Action Diffusion},
-	journal = {The International Journal of Robotics Research},
-	year = {2024},
-}
-```
-
- [ACT or ALOHA](https://tonyzhaozh.github.io/aloha)
-
-```bibtex
-@article{zhao2023learning,
-  title={Learning fine-grained bimanual manipulation with low-cost hardware},
-  author={Zhao, Tony Z and Kumar, Vikash and Levine, Sergey and Finn, Chelsea},
-  journal={arXiv preprint arXiv:2304.13705},
-  year={2023}
-}
-```
-
- [TDMPC](https://www.nicklashansen.com/td-mpc/)
-
-```bibtex
-@inproceedings{Hansen2022tdmpc,
-	title={Temporal Difference Learning for Model Predictive Control},
-	author={Nicklas Hansen and Xiaolong Wang and Hao Su},
-	booktitle={ICML},
-	year={2022}
-}
-```
-
- [VQ-BeT](https://sjlee.cc/vq-bet/)
-
-```bibtex
-@article{lee2024behavior,
-  title={Behavior generation with latent actions},
-  author={Lee, Seungjae and Wang, Yibin and Etukuru, Haritheja and Kim, H Jin and Shafiullah, Nur Muhammad Mahi and Pinto, Lerrel},
-  journal={arXiv preprint arXiv:2403.03181},
-  year={2024}
-}
-```
-
- [HIL-SERL](https://hil-serl.github.io/)
-
-```bibtex
-@Article{luo2024hilserl,
-title={Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning},
-author={Jianlan Luo and Charles Xu and Jeffrey Wu and Sergey Levine},
-year={2024},
-eprint={2410.21845},
-archivePrefix={arXiv},
-primaryClass={cs.RO}
-}
-```
-
 ## Star History

 [![Star History Chart](https://api.star-history.com/svg?repos=huggingface/lerobot&type=Timeline)](https://star-history.com/#huggingface/lerobot&Timeline)
--- a/docs-requirements.txt
+++ b/docs-requirements.txt
@@ -0,0 +1,3 @@
+# docs-requirements.txt
+hf-doc-builder @ git+https://github.com/huggingface/doc-builder.git@main
+watchdog>=6.0.0
--- a/docs/README.md
+++ b/docs/README.md
@@ -20,7 +20,7 @@ To generate the documentation, you first have to build it. Several packages are
 you can install them with the following command, at the root of the code repository:

 ```bash
-pip install -e ".[docs]"
+pip install -e . -r docs-requirements.txt
 ```

 You will also need `nodejs`. Please refer to their [installation page](https://nodejs.org/en/download)
--- a/docs/source/il_robots.mdx
+++ b/docs/source/il_robots.mdx
@@ -294,7 +294,7 @@ dataset.push_to_hub()

 #### Dataset upload

-Locally, your dataset is stored in this folder: `~/.cache/huggingface/lerobot/{repo-id}`. At the end of data recording, your dataset will be uploaded on your Hugging Face page (e.g. https://huggingface.co/datasets/cadene/so101_test) that you can obtain by running:
+Locally, your dataset is stored in this folder: `~/.cache/huggingface/lerobot/{repo-id}`. At the end of data recording, your dataset will be uploaded on your Hugging Face page (e.g. `https://huggingface.co/datasets/${HF_USER}/so101_test`) that you can obtain by running:

 ```bash
 echo https://huggingface.co/datasets/${HF_USER}/so101_test
@@ -428,7 +428,7 @@ Your robot should replicate movements similar to those you recorded. For example

 ## Train a policy

-To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](../src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
+To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:

 ```bash
 python -m lerobot.scripts.train \
@@ -444,7 +444,7 @@ python -m lerobot.scripts.train \
 Let's explain the command:

 1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/so101_test`.
-2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../src/lerobot/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor states, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
+2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor states, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
 3. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
 4. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.

--- a/docs/source/il_sim.mdx
+++ b/docs/source/il_sim.mdx
@@ -96,7 +96,7 @@ If you uploaded your dataset to the hub you can [visualize your dataset online](

 ## Train a policy

-To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](../src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
+To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:

 ```bash
 python -m lerobot.scripts.train \
@@ -111,7 +111,7 @@ python -m lerobot.scripts.train \
 Let's explain the command:

 1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/il_gym`.
-2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../src/lerobot/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor states, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
+2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor states, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
 3. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
 4. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.

--- a/docs/source/installation.mdx
+++ b/docs/source/installation.mdx
@@ -1,15 +1,6 @@
 # Installation

-## Install LeRobot
-
-Currently only available from source.
-
-Download our source code:
-
-```bash
-git clone https://github.com/huggingface/lerobot.git
-cd lerobot
-```
+## Environment Setup

 Create a virtual environment with Python 3.10, using [`Miniconda`](https://docs.anaconda.com/miniconda/install/#quick-command-line-install)

@@ -40,12 +31,49 @@ conda install ffmpeg -c conda-forge
 >
 > - _[On Linux only]_ If you want to bring your own ffmpeg: Install [ffmpeg build dependencies](https://trac.ffmpeg.org/wiki/CompilationGuide/Ubuntu#GettheDependencies) and [compile ffmpeg from source with libsvtav1](https://trac.ffmpeg.org/wiki/CompilationGuide/Ubuntu#libsvtav1), and make sure you use the corresponding ffmpeg binary to your install with `which ffmpeg`.

-Install 🤗 LeRobot:
+## Install LeRobot 🤗
+
+### From Source
+
+First, clone the repository and navigate into the directory:
+
+```bash
+git clone https://github.com/huggingface/lerobot.git
+cd lerobot
+```
+
+Then, install the library in editable mode. This is useful if you plan to contribute to the code.

 ```bash
 pip install -e .
 ```

+### Installation from PyPI
+
+**Core Library:**
+Install the base package with:
+
+```bash
+pip install lerobot
+```
+
+_This installs only the default dependencies._
+
+**Extra Features:**
+To install additional functionality, use one of the following:
+
+```bash
+pip install 'lerobot[all]'          # All available features
+pip install 'lerobot[aloha,pusht]'  # Specific features (Aloha & Pusht)
+pip install 'lerobot[feetech]'      # Feetech motor support
+```
+
+_Replace `[...]` with your desired features._
+
+**Available Tags:**
+For a full list of optional dependencies, see:
+https://pypi.org/project/lerobot/
+
 ### Troubleshooting

 If you encounter build errors, you may need to install additional dependencies: `cmake`, `build-essential`, and `ffmpeg libs`.
--- a/docs/source/policy_act_README.md
+++ b/docs/source/policy_act_README.md
@@ -0,0 +1,14 @@
+## Paper
+
+https://tonyzhaozh.github.io/aloha
+
+## Citation
+
+```bibtex
+@article{zhao2023learning,
+  title={Learning fine-grained bimanual manipulation with low-cost hardware},
+  author={Zhao, Tony Z and Kumar, Vikash and Levine, Sergey and Finn, Chelsea},
+  journal={arXiv preprint arXiv:2304.13705},
+  year={2023}
+}
+```
--- a/docs/source/policy_diffusion_README.md
+++ b/docs/source/policy_diffusion_README.md
@@ -0,0 +1,14 @@
+## Paper
+
+https://diffusion-policy.cs.columbia.edu
+
+## Citation
+
+```bibtex
+@article{chi2024diffusionpolicy,
+	author = {Cheng Chi and Zhenjia Xu and Siyuan Feng and Eric Cousineau and Yilun Du and Benjamin Burchfiel and Russ Tedrake and Shuran Song},
+	title ={Diffusion Policy: Visuomotor Policy Learning via Action Diffusion},
+	journal = {The International Journal of Robotics Research},
+	year = {2024},
+}
+```
--- a/docs/source/policy_smolvla_README.md
+++ b/docs/source/policy_smolvla_README.md
@@ -0,0 +1,14 @@
+## Paper
+
+https://arxiv.org/abs/2506.01844
+
+## Citation
+
+```bibtex
+@article{shukor2025smolvla,
+  title={SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics},
+  author={Shukor, Mustafa and Aubakirova, Dana and Capuano, Francesco and Kooijmans, Pepijn and Palma, Steven and Zouitine, Adil and Aractingi, Michel and Pascal, Caroline and Russi, Martino and Marafioti, Andres and Alibert, Simon and Cord, Matthieu and Wolf, Thomas and Cadene, Remi},
+  journal={arXiv preprint arXiv:2506.01844},
+  year={2025}
+}
+```
--- a/docs/source/policy_tdmpc_README.md
+++ b/docs/source/policy_tdmpc_README.md
@@ -0,0 +1,14 @@
+## Paper
+
+https://www.nicklashansen.com/td-mpc/
+
+## Citation
+
+```bibtex
+@inproceedings{Hansen2022tdmpc,
+	title={Temporal Difference Learning for Model Predictive Control},
+	author={Nicklas Hansen and Xiaolong Wang and Hao Su},
+	booktitle={ICML},
+	year={2022}
+}
+```
--- a/docs/source/policy_vqbet_README.md
+++ b/docs/source/policy_vqbet_README.md
@@ -0,0 +1,14 @@
+## Paper
+
+https://sjlee.cc/vq-bet/
+
+## Citation
+
+```bibtex
+@article{lee2024behavior,
+  title={Behavior generation with latent actions},
+  author={Lee, Seungjae and Wang, Yibin and Etukuru, Haritheja and Kim, H Jin and Shafiullah, Nur Muhammad Mahi and Pinto, Lerrel},
+  journal={arXiv preprint arXiv:2403.03181},
+  year={2024}
+}
+```
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,7 +25,7 @@ discord = "https://discord.gg/s3KuuzsPFb"

 [project]
 name = "lerobot"
-version = "0.2.0"
+version = "0.4.0"
 description = "🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch"
 readme = "README.md"
 license = { text = "Apache-2.0" }
@@ -125,7 +125,6 @@ hilserl = ["lerobot[transformers-dep]", "gym-hil>=0.1.9", "lerobot[grpcio-dep]",
 async = ["lerobot[grpcio-dep]", "matplotlib>=3.10.3"]

 # Development
-docs = ["hf-doc-builder @ git+https://github.com/huggingface/doc-builder.git@main", "watchdog >= 6.0.0"]
 dev = ["pre-commit>=3.7.0", "debugpy>=1.8.1", "lerobot[grpcio-dep]", "grpcio-tools==1.73.1"]
 test = ["pytest>=8.1.0", "pytest-timeout>=2.4.0", "pytest-cov>=5.0.0", "mock-serial>=0.0.1 ; sys_platform != 'win32'"]
 video_benchmark = ["scikit-image>=0.23.2", "pandas>=2.2.2"]
@@ -147,7 +146,6 @@ all = [
    "lerobot[smolvla]",
    "lerobot[hilserl]",
    "lerobot[async]",
-    "lerobot[docs]",
    "lerobot[dev]",
    "lerobot[test]",
    "lerobot[video_benchmark]",
--- a/requirements-macos.txt
+++ b/requirements-macos.txt
@@ -0,0 +1,625 @@
+# This file is autogenerated by pip-compile with Python 3.10
+# by the following command:
+#
+#    pip-compile --output-file=requirements-macos.txt requirements.in
+#
+-e .[all]
+    # via -[all]
+absl-py==2.3.1
+    # via
+    #   dm-control
+    #   dm-env
+    #   dm-tree
+    #   labmaze
+    #   mujoco
+accelerate==1.9.0
+    # via lerobot
+aiohappyeyeballs==2.6.1
+    # via aiohttp
+aiohttp==3.12.15
+    # via fsspec
+aiosignal==1.4.0
+    # via aiohttp
+annotated-types==0.7.0
+    # via pydantic
+asttokens==3.0.0
+    # via stack-data
+async-timeout==5.0.1
+    # via aiohttp
+attrs==25.3.0
+    # via
+    #   aiohttp
+    #   dm-tree
+    #   jsonlines
+    #   rerun-sdk
+av==15.0.0
+    # via lerobot
+blinker==1.9.0
+    # via flask
+certifi==2025.7.14
+    # via
+    #   requests
+    #   sentry-sdk
+cffi==1.17.1
+    # via pymunk
+cfgv==3.4.0
+    # via pre-commit
+charset-normalizer==3.4.2
+    # via requests
+click==8.2.1
+    # via
+    #   flask
+    #   wandb
+cloudpickle==3.1.1
+    # via gymnasium
+cmake==4.0.3
+    # via lerobot
+cmeel==0.57.3
+    # via
+    #   cmeel-assimp
+    #   cmeel-boost
+    #   cmeel-console-bridge
+    #   cmeel-octomap
+    #   cmeel-qhull
+    #   cmeel-tinyxml2
+    #   cmeel-urdfdom
+    #   cmeel-zlib
+    #   coal-library
+    #   eigenpy
+    #   eiquadprog
+    #   pin
+    #   placo
+    #   rhoban-cmeel-jsoncpp
+cmeel-assimp==5.4.3.1
+    # via coal-library
+cmeel-boost==1.87.0.1
+    # via
+    #   coal-library
+    #   eigenpy
+    #   eiquadprog
+    #   pin
+cmeel-console-bridge==1.0.2.3
+    # via cmeel-urdfdom
+cmeel-octomap==1.10.0
+    # via coal-library
+cmeel-qhull==8.0.2.1
+    # via coal-library
+cmeel-tinyxml2==10.0.0
+    # via cmeel-urdfdom
+cmeel-urdfdom==4.0.1
+    # via pin
+cmeel-zlib==1.3.1
+    # via cmeel-assimp
+coal-library==3.0.1
+    # via pin
+contourpy==1.3.2
+    # via matplotlib
+coverage[toml]==7.10.1
+    # via pytest-cov
+cycler==0.12.1
+    # via matplotlib
+datasets==3.6.0
+    # via lerobot
+debugpy==1.8.15
+    # via lerobot
+decorator==5.2.1
+    # via ipython
+deepdiff==8.5.0
+    # via lerobot
+diffusers==0.34.0
+    # via lerobot
+dill==0.3.8
+    # via
+    #   datasets
+    #   multiprocess
+distlib==0.4.0
+    # via virtualenv
+dm-control==1.0.14
+    # via gym-aloha
+dm-env==1.6
+    # via dm-control
+dm-tree==0.1.9
+    # via
+    #   dm-control
+    #   dm-env
+docopt==0.6.2
+    # via num2words
+draccus==0.10.0
+    # via lerobot
+dynamixel-sdk==3.7.31
+    # via lerobot
+eigenpy==3.10.3
+    # via coal-library
+einops==0.8.1
+    # via lerobot
+eiquadprog==1.2.9
+    # via placo
+exceptiongroup==1.3.0
+    # via
+    #   ipython
+    #   pytest
+executing==2.2.0
+    # via stack-data
+farama-notifications==0.0.4
+    # via gymnasium
+feetech-servo-sdk==1.0.0
+    # via lerobot
+filelock==3.18.0
+    # via
+    #   datasets
+    #   diffusers
+    #   huggingface-hub
+    #   torch
+    #   transformers
+    #   virtualenv
+flask==3.1.1
+    # via lerobot
+fonttools==4.59.0
+    # via matplotlib
+frozenlist==1.7.0
+    # via
+    #   aiohttp
+    #   aiosignal
+fsspec[http]==2025.3.0
+    # via
+    #   datasets
+    #   huggingface-hub
+    #   torch
+gitdb==4.0.12
+    # via gitpython
+gitpython==3.1.45
+    # via wandb
+glfw==2.9.0
+    # via
+    #   dm-control
+    #   mujoco
+grpcio==1.73.1
+    # via
+    #   grpcio-tools
+    #   lerobot
+grpcio-tools==1.73.1
+    # via lerobot
+gym-aloha==0.1.1
+    # via lerobot
+gym-hil==0.1.10
+    # via lerobot
+gym-pusht==0.1.5
+    # via lerobot
+gym-xarm==0.1.1
+    # via lerobot
+gymnasium==0.29.1
+    # via
+    #   gym-aloha
+    #   gym-hil
+    #   gym-pusht
+    #   gym-xarm
+    #   gymnasium-robotics
+    #   lerobot
+    #   pettingzoo
+gymnasium-robotics==1.2.4
+    # via gym-xarm
+hf-transfer==0.1.9
+    # via huggingface-hub
+hf-xet==1.1.5
+    # via huggingface-hub
+hidapi==0.14.0.post4
+    # via
+    #   gym-hil
+    #   lerobot
+huggingface-hub[cli,hf-transfer]==0.34.3
+    # via
+    #   accelerate
+    #   datasets
+    #   diffusers
+    #   lerobot
+    #   tokenizers
+    #   transformers
+identify==2.6.12
+    # via pre-commit
+idna==3.10
+    # via
+    #   requests
+    #   yarl
+imageio[ffmpeg]==2.37.0
+    # via
+    #   gym-aloha
+    #   gym-hil
+    #   gymnasium-robotics
+    #   lerobot
+    #   scikit-image
+imageio-ffmpeg==0.6.0
+    # via imageio
+importlib-metadata==8.7.0
+    # via diffusers
+iniconfig==2.1.0
+    # via pytest
+inquirerpy==0.3.4
+    # via huggingface-hub
+ipython==8.37.0
+    # via meshcat
+ischedule==1.2.7
+    # via placo
+itsdangerous==2.2.0
+    # via flask
+jedi==0.19.2
+    # via ipython
+jinja2==3.1.6
+    # via
+    #   flask
+    #   gymnasium-robotics
+    #   torch
+jsonlines==4.0.0
+    # via lerobot
+kiwisolver==1.4.8
+    # via matplotlib
+labmaze==1.0.6
+    # via dm-control
+lazy-loader==0.4
+    # via scikit-image
+lxml==6.0.0
+    # via dm-control
+markupsafe==3.0.2
+    # via
+    #   flask
+    #   jinja2
+    #   werkzeug
+matplotlib==3.10.5
+    # via lerobot
+matplotlib-inline==0.1.7
+    # via ipython
+mergedeep==1.3.4
+    # via draccus
+meshcat==0.3.2
+    # via placo
+mock-serial==0.0.1
+    # via lerobot
+mpmath==1.3.0
+    # via sympy
+mujoco==2.3.7
+    # via
+    #   dm-control
+    #   gym-aloha
+    #   gym-hil
+    #   gym-xarm
+    #   gymnasium-robotics
+multidict==6.6.3
+    # via
+    #   aiohttp
+    #   yarl
+multiprocess==0.70.16
+    # via datasets
+mypy-extensions==1.1.0
+    # via typing-inspect
+networkx==3.4.2
+    # via
+    #   scikit-image
+    #   torch
+nodeenv==1.9.1
+    # via pre-commit
+num2words==0.5.14
+    # via lerobot
+numpy==2.2.6
+    # via
+    #   accelerate
+    #   cmeel-boost
+    #   contourpy
+    #   datasets
+    #   diffusers
+    #   dm-control
+    #   dm-env
+    #   dm-tree
+    #   gymnasium
+    #   gymnasium-robotics
+    #   imageio
+    #   labmaze
+    #   matplotlib
+    #   meshcat
+    #   mujoco
+    #   opencv-python
+    #   opencv-python-headless
+    #   pandas
+    #   pettingzoo
+    #   rerun-sdk
+    #   scikit-image
+    #   scipy
+    #   shapely
+    #   tifffile
+    #   torchvision
+    #   transformers
+opencv-python==4.12.0.88
+    # via gym-pusht
+opencv-python-headless==4.12.0.88
+    # via lerobot
+orderly-set==5.5.0
+    # via deepdiff
+packaging==25.0
+    # via
+    #   accelerate
+    #   datasets
+    #   huggingface-hub
+    #   lazy-loader
+    #   lerobot
+    #   matplotlib
+    #   pytest
+    #   scikit-image
+    #   transformers
+    #   wandb
+pandas==2.3.1
+    # via
+    #   datasets
+    #   lerobot
+parso==0.8.4
+    # via jedi
+pettingzoo==1.24.3
+    # via gymnasium-robotics
+pexpect==4.9.0
+    # via ipython
+pfzy==0.3.4
+    # via inquirerpy
+pillow==11.3.0
+    # via
+    #   diffusers
+    #   imageio
+    #   matplotlib
+    #   meshcat
+    #   rerun-sdk
+    #   scikit-image
+    #   torchvision
+pin==3.4.0
+    # via placo
+placo==0.9.14
+    # via lerobot
+platformdirs==4.3.8
+    # via
+    #   virtualenv
+    #   wandb
+pluggy==1.6.0
+    # via
+    #   pytest
+    #   pytest-cov
+pre-commit==4.2.0
+    # via lerobot
+prompt-toolkit==3.0.51
+    # via
+    #   inquirerpy
+    #   ipython
+propcache==0.3.2
+    # via
+    #   aiohttp
+    #   yarl
+protobuf==6.31.0
+    # via
+    #   dm-control
+    #   grpcio-tools
+    #   lerobot
+    #   wandb
+psutil==7.0.0
+    # via
+    #   accelerate
+    #   imageio
+ptyprocess==0.7.0
+    # via pexpect
+pure-eval==0.2.3
+    # via stack-data
+pyarrow==21.0.0
+    # via
+    #   datasets
+    #   rerun-sdk
+pycparser==2.22
+    # via cffi
+pydantic==2.11.7
+    # via wandb
+pydantic-core==2.33.2
+    # via pydantic
+pygame==2.6.1
+    # via
+    #   gym-hil
+    #   gym-pusht
+    #   lerobot
+pygments==2.19.2
+    # via
+    #   ipython
+    #   pytest
+pymunk==6.11.1
+    # via
+    #   gym-pusht
+    #   lerobot
+pyngrok==7.2.12
+    # via meshcat
+pynput==1.8.1
+    # via
+    #   gym-hil
+    #   lerobot
+pyobjc-core==11.1
+    # via
+    #   pyobjc-framework-applicationservices
+    #   pyobjc-framework-cocoa
+    #   pyobjc-framework-coretext
+    #   pyobjc-framework-quartz
+pyobjc-framework-applicationservices==11.1
+    # via pynput
+pyobjc-framework-cocoa==11.1
+    # via
+    #   pyobjc-framework-applicationservices
+    #   pyobjc-framework-coretext
+    #   pyobjc-framework-quartz
+pyobjc-framework-coretext==11.1
+    # via pyobjc-framework-applicationservices
+pyobjc-framework-quartz==11.1
+    # via
+    #   pynput
+    #   pyobjc-framework-applicationservices
+    #   pyobjc-framework-coretext
+pyopengl==3.1.9
+    # via
+    #   dm-control
+    #   mujoco
+pyparsing==3.2.3
+    # via
+    #   dm-control
+    #   matplotlib
+pyrealsense2-macosx==2.54.2
+    # via lerobot
+pyserial==3.5
+    # via
+    #   dynamixel-sdk
+    #   feetech-servo-sdk
+    #   lerobot
+pytest==8.4.1
+    # via
+    #   lerobot
+    #   pytest-cov
+    #   pytest-timeout
+pytest-cov==6.2.1
+    # via lerobot
+pytest-timeout==2.4.0
+    # via lerobot
+python-dateutil==2.9.0.post0
+    # via
+    #   matplotlib
+    #   pandas
+pytz==2025.2
+    # via pandas
+pyyaml==6.0.2
+    # via
+    #   accelerate
+    #   datasets
+    #   draccus
+    #   huggingface-hub
+    #   pre-commit
+    #   pyngrok
+    #   pyyaml-include
+    #   transformers
+    #   wandb
+pyyaml-include==1.4.1
+    # via draccus
+pyzmq==27.0.0
+    # via
+    #   lerobot
+    #   meshcat
+regex==2025.7.34
+    # via
+    #   diffusers
+    #   transformers
+requests==2.32.4
+    # via
+    #   datasets
+    #   diffusers
+    #   dm-control
+    #   huggingface-hub
+    #   transformers
+    #   wandb
+rerun-sdk==0.22.1
+    # via lerobot
+rhoban-cmeel-jsoncpp==1.9.4.9
+    # via placo
+safetensors==0.5.3
+    # via
+    #   accelerate
+    #   diffusers
+    #   lerobot
+    #   transformers
+scikit-image==0.25.2
+    # via
+    #   gym-pusht
+    #   lerobot
+scipy==1.15.3
+    # via
+    #   dm-control
+    #   scikit-image
+sentry-sdk==2.34.1
+    # via wandb
+shapely==2.1.1
+    # via gym-pusht
+six==1.17.0
+    # via
+    #   pynput
+    #   python-dateutil
+smmap==5.0.2
+    # via gitdb
+stack-data==0.6.3
+    # via ipython
+sympy==1.14.0
+    # via torch
+termcolor==3.1.0
+    # via lerobot
+tifffile==2025.5.10
+    # via scikit-image
+tokenizers==0.21.4
+    # via transformers
+toml==0.10.2
+    # via draccus
+tomli==2.2.1
+    # via
+    #   cmeel
+    #   coverage
+    #   pytest
+torch==2.7.1
+    # via
+    #   accelerate
+    #   lerobot
+    #   torchvision
+torchcodec==0.5
+    # via lerobot
+torchvision==0.22.1
+    # via lerobot
+tornado==6.5.1
+    # via meshcat
+tqdm==4.67.1
+    # via
+    #   datasets
+    #   dm-control
+    #   huggingface-hub
+    #   transformers
+traitlets==5.14.3
+    # via
+    #   ipython
+    #   matplotlib-inline
+transformers==4.51.3
+    # via lerobot
+typing-extensions==4.14.1
+    # via
+    #   aiosignal
+    #   exceptiongroup
+    #   gymnasium
+    #   huggingface-hub
+    #   ipython
+    #   multidict
+    #   pydantic
+    #   pydantic-core
+    #   rerun-sdk
+    #   torch
+    #   typing-inspect
+    #   typing-inspection
+    #   wandb
+typing-inspect==0.9.0
+    # via draccus
+typing-inspection==0.4.1
+    # via pydantic
+tzdata==2025.2
+    # via pandas
+u-msgpack-python==2.8.0
+    # via meshcat
+urllib3==2.5.0
+    # via
+    #   requests
+    #   sentry-sdk
+virtualenv==20.32.0
+    # via pre-commit
+wandb==0.21.0
+    # via lerobot
+wcwidth==0.2.13
+    # via prompt-toolkit
+werkzeug==3.1.3
+    # via flask
+wrapt==1.17.2
+    # via dm-tree
+xxhash==3.5.0
+    # via datasets
+yarl==1.20.1
+    # via aiohttp
+zipp==3.23.0
+    # via importlib-metadata
+
+# The following packages are considered to be unsafe in a requirements file:
+# setuptools
--- a/requirements-ubuntu.txt
+++ b/requirements-ubuntu.txt
@@ -0,0 +1,650 @@
+#
+# This file is autogenerated by pip-compile with Python 3.10
+# by the following command:
+#
+#    pip-compile --output-file=requirements-ubuntu.txt requirements.in
+#
+-e .[all]
+    # via -[all]
+absl-py==2.3.1
+    # via
+    #   dm-control
+    #   dm-env
+    #   dm-tree
+    #   labmaze
+    #   mujoco
+accelerate==1.9.0
+    # via lerobot
+aiohappyeyeballs==2.6.1
+    # via aiohttp
+aiohttp==3.12.15
+    # via fsspec
+aiosignal==1.4.0
+    # via aiohttp
+annotated-types==0.7.0
+    # via pydantic
+asttokens==3.0.0
+    # via stack-data
+async-timeout==5.0.1
+    # via aiohttp
+attrs==25.3.0
+    # via
+    #   aiohttp
+    #   dm-tree
+    #   jsonlines
+    #   rerun-sdk
+av==15.0.0
+    # via lerobot
+blinker==1.9.0
+    # via flask
+certifi==2025.7.14
+    # via
+    #   requests
+    #   sentry-sdk
+cffi==1.17.1
+    # via pymunk
+cfgv==3.4.0
+    # via pre-commit
+charset-normalizer==3.4.2
+    # via requests
+click==8.2.1
+    # via
+    #   flask
+    #   wandb
+cloudpickle==3.1.1
+    # via gymnasium
+cmake==4.0.3
+    # via lerobot
+cmeel==0.57.3
+    # via
+    #   cmeel-assimp
+    #   cmeel-boost
+    #   cmeel-console-bridge
+    #   cmeel-octomap
+    #   cmeel-qhull
+    #   cmeel-tinyxml2
+    #   cmeel-urdfdom
+    #   cmeel-zlib
+    #   coal-library
+    #   eigenpy
+    #   eiquadprog
+    #   pin
+    #   placo
+    #   rhoban-cmeel-jsoncpp
+cmeel-assimp==5.4.3.1
+    # via coal-library
+cmeel-boost==1.87.0.1
+    # via
+    #   coal-library
+    #   eigenpy
+    #   eiquadprog
+    #   pin
+cmeel-console-bridge==1.0.2.3
+    # via cmeel-urdfdom
+cmeel-octomap==1.10.0
+    # via coal-library
+cmeel-qhull==8.0.2.1
+    # via coal-library
+cmeel-tinyxml2==10.0.0
+    # via cmeel-urdfdom
+cmeel-urdfdom==4.0.1
+    # via pin
+cmeel-zlib==1.3.1
+    # via cmeel-assimp
+coal-library==3.0.1
+    # via pin
+contourpy==1.3.2
+    # via matplotlib
+coverage[toml]==7.10.1
+    # via pytest-cov
+cycler==0.12.1
+    # via matplotlib
+datasets==3.6.0
+    # via lerobot
+debugpy==1.8.15
+    # via lerobot
+decorator==5.2.1
+    # via ipython
+deepdiff==8.5.0
+    # via lerobot
+diffusers==0.34.0
+    # via lerobot
+dill==0.3.8
+    # via
+    #   datasets
+    #   multiprocess
+distlib==0.4.0
+    # via virtualenv
+dm-control==1.0.14
+    # via gym-aloha
+dm-env==1.6
+    # via dm-control
+dm-tree==0.1.9
+    # via
+    #   dm-control
+    #   dm-env
+docopt==0.6.2
+    # via num2words
+draccus==0.10.0
+    # via lerobot
+dynamixel-sdk==3.7.31
+    # via lerobot
+eigenpy==3.10.3
+    # via coal-library
+einops==0.8.1
+    # via lerobot
+eiquadprog==1.2.9
+    # via placo
+evdev==1.9.2
+    # via pynput
+exceptiongroup==1.3.0
+    # via
+    #   ipython
+    #   pytest
+executing==2.2.0
+    # via stack-data
+farama-notifications==0.0.4
+    # via gymnasium
+feetech-servo-sdk==1.0.0
+    # via lerobot
+filelock==3.18.0
+    # via
+    #   datasets
+    #   diffusers
+    #   huggingface-hub
+    #   torch
+    #   transformers
+    #   virtualenv
+flask==3.1.1
+    # via lerobot
+fonttools==4.59.0
+    # via matplotlib
+frozenlist==1.7.0
+    # via
+    #   aiohttp
+    #   aiosignal
+fsspec[http]==2025.3.0
+    # via
+    #   datasets
+    #   huggingface-hub
+    #   torch
+gitdb==4.0.12
+    # via gitpython
+gitpython==3.1.45
+    # via wandb
+glfw==2.9.0
+    # via
+    #   dm-control
+    #   mujoco
+grpcio==1.73.1
+    # via
+    #   grpcio-tools
+    #   lerobot
+grpcio-tools==1.73.1
+    # via lerobot
+gym-aloha==0.1.1
+    # via lerobot
+gym-hil==0.1.10
+    # via lerobot
+gym-pusht==0.1.5
+    # via lerobot
+gym-xarm==0.1.1
+    # via lerobot
+gymnasium==0.29.1
+    # via
+    #   gym-aloha
+    #   gym-hil
+    #   gym-pusht
+    #   gym-xarm
+    #   gymnasium-robotics
+    #   lerobot
+    #   pettingzoo
+gymnasium-robotics==1.2.4
+    # via gym-xarm
+hf-transfer==0.1.9
+    # via huggingface-hub
+hf-xet==1.1.5
+    # via huggingface-hub
+hidapi==0.14.0.post4
+    # via
+    #   gym-hil
+    #   lerobot
+huggingface-hub[cli,hf-transfer]==0.34.3
+    # via
+    #   accelerate
+    #   datasets
+    #   diffusers
+    #   lerobot
+    #   tokenizers
+    #   transformers
+identify==2.6.12
+    # via pre-commit
+idna==3.10
+    # via
+    #   requests
+    #   yarl
+imageio[ffmpeg]==2.37.0
+    # via
+    #   gym-aloha
+    #   gym-hil
+    #   gymnasium-robotics
+    #   lerobot
+    #   scikit-image
+imageio-ffmpeg==0.6.0
+    # via imageio
+importlib-metadata==8.7.0
+    # via diffusers
+iniconfig==2.1.0
+    # via pytest
+inquirerpy==0.3.4
+    # via huggingface-hub
+ipython==8.37.0
+    # via meshcat
+ischedule==1.2.7
+    # via placo
+itsdangerous==2.2.0
+    # via flask
+jedi==0.19.2
+    # via ipython
+jinja2==3.1.6
+    # via
+    #   flask
+    #   gymnasium-robotics
+    #   torch
+jsonlines==4.0.0
+    # via lerobot
+kiwisolver==1.4.8
+    # via matplotlib
+labmaze==1.0.6
+    # via dm-control
+lazy-loader==0.4
+    # via scikit-image
+lxml==6.0.0
+    # via dm-control
+markupsafe==3.0.2
+    # via
+    #   flask
+    #   jinja2
+    #   werkzeug
+matplotlib==3.10.5
+    # via lerobot
+matplotlib-inline==0.1.7
+    # via ipython
+mergedeep==1.3.4
+    # via draccus
+meshcat==0.3.2
+    # via placo
+mock-serial==0.0.1
+    # via lerobot
+mpmath==1.3.0
+    # via sympy
+mujoco==2.3.7
+    # via
+    #   dm-control
+    #   gym-aloha
+    #   gym-hil
+    #   gym-xarm
+    #   gymnasium-robotics
+multidict==6.6.3
+    # via
+    #   aiohttp
+    #   yarl
+multiprocess==0.70.16
+    # via datasets
+mypy-extensions==1.1.0
+    # via typing-inspect
+networkx==3.4.2
+    # via
+    #   scikit-image
+    #   torch
+nodeenv==1.9.1
+    # via pre-commit
+num2words==0.5.14
+    # via lerobot
+numpy==2.2.6
+    # via
+    #   accelerate
+    #   cmeel-boost
+    #   contourpy
+    #   datasets
+    #   diffusers
+    #   dm-control
+    #   dm-env
+    #   dm-tree
+    #   gymnasium
+    #   gymnasium-robotics
+    #   imageio
+    #   labmaze
+    #   matplotlib
+    #   meshcat
+    #   mujoco
+    #   opencv-python
+    #   opencv-python-headless
+    #   pandas
+    #   pettingzoo
+    #   rerun-sdk
+    #   scikit-image
+    #   scipy
+    #   shapely
+    #   tifffile
+    #   torchvision
+    #   transformers
+nvidia-cublas-cu12==12.6.4.1
+    # via
+    #   nvidia-cudnn-cu12
+    #   nvidia-cusolver-cu12
+    #   torch
+nvidia-cuda-cupti-cu12==12.6.80
+    # via torch
+nvidia-cuda-nvrtc-cu12==12.6.77
+    # via torch
+nvidia-cuda-runtime-cu12==12.6.77
+    # via torch
+nvidia-cudnn-cu12==9.5.1.17
+    # via torch
+nvidia-cufft-cu12==11.3.0.4
+    # via torch
+nvidia-cufile-cu12==1.11.1.6
+    # via torch
+nvidia-curand-cu12==10.3.7.77
+    # via torch
+nvidia-cusolver-cu12==11.7.1.2
+    # via torch
+nvidia-cusparse-cu12==12.5.4.2
+    # via
+    #   nvidia-cusolver-cu12
+    #   torch
+nvidia-cusparselt-cu12==0.6.3
+    # via torch
+nvidia-nccl-cu12==2.26.2
+    # via torch
+nvidia-nvjitlink-cu12==12.6.85
+    # via
+    #   nvidia-cufft-cu12
+    #   nvidia-cusolver-cu12
+    #   nvidia-cusparse-cu12
+    #   torch
+nvidia-nvtx-cu12==12.6.77
+    # via torch
+opencv-python==4.12.0.88
+    # via gym-pusht
+opencv-python-headless==4.12.0.88
+    # via lerobot
+orderly-set==5.5.0
+    # via deepdiff
+packaging==25.0
+    # via
+    #   accelerate
+    #   datasets
+    #   huggingface-hub
+    #   lazy-loader
+    #   lerobot
+    #   matplotlib
+    #   pytest
+    #   scikit-image
+    #   transformers
+    #   wandb
+pandas==2.3.1
+    # via
+    #   datasets
+    #   lerobot
+parso==0.8.4
+    # via jedi
+pettingzoo==1.24.3
+    # via gymnasium-robotics
+pexpect==4.9.0
+    # via ipython
+pfzy==0.3.4
+    # via inquirerpy
+pillow==11.3.0
+    # via
+    #   diffusers
+    #   imageio
+    #   matplotlib
+    #   meshcat
+    #   rerun-sdk
+    #   scikit-image
+    #   torchvision
+pin==3.4.0
+    # via placo
+placo==0.9.14
+    # via lerobot
+platformdirs==4.3.8
+    # via
+    #   virtualenv
+    #   wandb
+pluggy==1.6.0
+    # via
+    #   pytest
+    #   pytest-cov
+pre-commit==4.2.0
+    # via lerobot
+prompt-toolkit==3.0.51
+    # via
+    #   inquirerpy
+    #   ipython
+propcache==0.3.2
+    # via
+    #   aiohttp
+    #   yarl
+protobuf==6.31.0
+    # via
+    #   dm-control
+    #   grpcio-tools
+    #   lerobot
+    #   wandb
+psutil==7.0.0
+    # via
+    #   accelerate
+    #   imageio
+ptyprocess==0.7.0
+    # via pexpect
+pure-eval==0.2.3
+    # via stack-data
+pyarrow==21.0.0
+    # via
+    #   datasets
+    #   rerun-sdk
+pycparser==2.22
+    # via cffi
+pydantic==2.11.7
+    # via wandb
+pydantic-core==2.33.2
+    # via pydantic
+pygame==2.6.1
+    # via
+    #   gym-hil
+    #   gym-pusht
+    #   lerobot
+pygments==2.19.2
+    # via
+    #   ipython
+    #   pytest
+pymunk==6.11.1
+    # via
+    #   gym-pusht
+    #   lerobot
+pyngrok==7.2.12
+    # via meshcat
+pynput==1.8.1
+    # via
+    #   gym-hil
+    #   lerobot
+pyopengl==3.1.9
+    # via
+    #   dm-control
+    #   mujoco
+pyparsing==3.2.3
+    # via
+    #   dm-control
+    #   matplotlib
+pyrealsense2==2.56.5.9235
+    # via lerobot
+pyserial==3.5
+    # via
+    #   dynamixel-sdk
+    #   feetech-servo-sdk
+    #   lerobot
+pytest==8.4.1
+    # via
+    #   lerobot
+    #   pytest-cov
+    #   pytest-timeout
+pytest-cov==6.2.1
+    # via lerobot
+pytest-timeout==2.4.0
+    # via lerobot
+python-dateutil==2.9.0.post0
+    # via
+    #   matplotlib
+    #   pandas
+python-xlib==0.33
+    # via pynput
+pytz==2025.2
+    # via pandas
+pyyaml==6.0.2
+    # via
+    #   accelerate
+    #   datasets
+    #   draccus
+    #   huggingface-hub
+    #   pre-commit
+    #   pyngrok
+    #   pyyaml-include
+    #   transformers
+    #   wandb
+pyyaml-include==1.4.1
+    # via draccus
+pyzmq==27.0.0
+    # via
+    #   lerobot
+    #   meshcat
+regex==2025.7.34
+    # via
+    #   diffusers
+    #   transformers
+requests==2.32.4
+    # via
+    #   datasets
+    #   diffusers
+    #   dm-control
+    #   huggingface-hub
+    #   transformers
+    #   wandb
+rerun-sdk==0.22.1
+    # via lerobot
+rhoban-cmeel-jsoncpp==1.9.4.9
+    # via placo
+safetensors==0.5.3
+    # via
+    #   accelerate
+    #   diffusers
+    #   lerobot
+    #   transformers
+scikit-image==0.25.2
+    # via
+    #   gym-pusht
+    #   lerobot
+scipy==1.15.3
+    # via
+    #   dm-control
+    #   scikit-image
+sentry-sdk==2.34.1
+    # via wandb
+shapely==2.1.1
+    # via gym-pusht
+six==1.17.0
+    # via
+    #   pynput
+    #   python-dateutil
+    #   python-xlib
+smmap==5.0.2
+    # via gitdb
+stack-data==0.6.3
+    # via ipython
+sympy==1.14.0
+    # via torch
+termcolor==3.1.0
+    # via lerobot
+tifffile==2025.5.10
+    # via scikit-image
+tokenizers==0.21.4
+    # via transformers
+toml==0.10.2
+    # via draccus
+tomli==2.2.1
+    # via
+    #   cmeel
+    #   coverage
+    #   pytest
+torch==2.7.1
+    # via
+    #   accelerate
+    #   lerobot
+    #   torchvision
+torchcodec==0.5
+    # via lerobot
+torchvision==0.22.1
+    # via lerobot
+tornado==6.5.1
+    # via meshcat
+tqdm==4.67.1
+    # via
+    #   datasets
+    #   dm-control
+    #   huggingface-hub
+    #   transformers
+traitlets==5.14.3
+    # via
+    #   ipython
+    #   matplotlib-inline
+transformers==4.51.3
+    # via lerobot
+triton==3.3.1
+    # via torch
+typing-extensions==4.14.1
+    # via
+    #   aiosignal
+    #   exceptiongroup
+    #   gymnasium
+    #   huggingface-hub
+    #   ipython
+    #   multidict
+    #   pydantic
+    #   pydantic-core
+    #   rerun-sdk
+    #   torch
+    #   typing-inspect
+    #   typing-inspection
+    #   wandb
+typing-inspect==0.9.0
+    # via draccus
+typing-inspection==0.4.1
+    # via pydantic
+tzdata==2025.2
+    # via pandas
+u-msgpack-python==2.8.0
+    # via meshcat
+urllib3==2.5.0
+    # via
+    #   requests
+    #   sentry-sdk
+virtualenv==20.32.0
+    # via pre-commit
+wandb==0.21.0
+    # via lerobot
+wcwidth==0.2.13
+    # via prompt-toolkit
+werkzeug==3.1.3
+    # via flask
+wrapt==1.17.2
+    # via dm-tree
+xxhash==3.5.0
+    # via datasets
+yarl==1.20.1
+    # via aiohttp
+zipp==3.23.0
+    # via importlib-metadata
+
+# The following packages are considered to be unsafe in a requirements file:
+# setuptools
--- a/requirements.in
+++ b/requirements.in
@@ -0,0 +1,9 @@
+# requirements.in
+
+# requirements-macos.txt was generated on macOS and is platform-specific (macOS 15.5 24F74 arm64).
+# Darwin MacBook-Pro.local 24.5.0 Darwin Kernel Version 24.5.0: Tue Apr 22 19:54:43 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T8132 arm64
+
+# requirements-ubuntu.txt was generated on Linux and is platform-specific (Ubuntu 24.04.2 LTS x86_64).
+# Linux mlerobot-linux 6.14.0-27-generic #27~24.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Jul 22 17:38:49 UTC 2 x86_64 x86_64 x86_64 GNU/Linux
+
+-e .[all]
--- a/src/lerobot/calibrate.py
+++ b/src/lerobot/calibrate.py
@@ -82,5 +82,9 @@ def calibrate(cfg: CalibrateConfig):
    device.disconnect()


-if __name__ == "__main__":
+def main():
    calibrate()
+
+
+if __name__ == "__main__":
+    main()
--- a/src/lerobot/configs/policies.py
+++ b/src/lerobot/configs/policies.py
@@ -27,6 +27,7 @@ from huggingface_hub.constants import CONFIG_NAME
 from huggingface_hub.errors import HfHubHTTPError

 from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
+from lerobot.constants import ACTION, OBS_STATE
 from lerobot.optim.optimizers import OptimizerConfig
 from lerobot.optim.schedulers import LRSchedulerConfig
 from lerobot.utils.hub import HubMixin
@@ -119,8 +120,8 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):

    @property
    def robot_state_feature(self) -> PolicyFeature | None:
-        for _, ft in self.input_features.items():
-            if ft.type is FeatureType.STATE:
+        for ft_name, ft in self.input_features.items():
+            if ft.type is FeatureType.STATE and ft_name == OBS_STATE:
                return ft
        return None

@@ -137,8 +138,8 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):

    @property
    def action_feature(self) -> PolicyFeature | None:
-        for _, ft in self.output_features.items():
-            if ft.type is FeatureType.ACTION:
+        for ft_name, ft in self.output_features.items():
+            if ft.type is FeatureType.ACTION and ft_name == ACTION:
                return ft
        return None

--- a/src/lerobot/find_cameras.py
+++ b/src/lerobot/find_cameras.py
@@ -286,7 +286,7 @@ def save_images_from_all_cameras(
            print(f"Image capture finished. Images saved to {output_dir}")


-if __name__ == "__main__":
+def main():
    parser = argparse.ArgumentParser(
        description="Unified camera utility script for listing cameras and capturing images."
    )
@@ -313,3 +313,7 @@ if __name__ == "__main__":
    )
    args = parser.parse_args()
    save_images_from_all_cameras(**vars(args))
+
+
+if __name__ == "__main__":
+    main()
--- a/src/lerobot/find_port.py
+++ b/src/lerobot/find_port.py
@@ -61,5 +61,9 @@ def find_port():
        raise OSError(f"Could not detect the port. More than one port was found ({ports_diff}).")


-if __name__ == "__main__":
+def main():
    find_port()
+
+
+if __name__ == "__main__":
+    main()
--- a/src/lerobot/policies/act/README.md
+++ b/src/lerobot/policies/act/README.md
@@ -0,0 +1 @@
+../../../../docs/source/policy_act_README.md
--- a/src/lerobot/policies/diffusion/README.md
+++ b/src/lerobot/policies/diffusion/README.md
@@ -0,0 +1 @@
+../../../../docs/source/policy_diffusion_README.md
--- a/src/lerobot/policies/smolvla/README.md
+++ b/src/lerobot/policies/smolvla/README.md
@@ -0,0 +1 @@
+../../../../docs/source/policy_smolvla_README.md
--- a/src/lerobot/policies/tdmpc/README.md
+++ b/src/lerobot/policies/tdmpc/README.md
@@ -0,0 +1 @@
+../../../../docs/source/policy_tdmpc_README.md
--- a/src/lerobot/policies/vqbet/README.md
+++ b/src/lerobot/policies/vqbet/README.md
@@ -0,0 +1 @@
+../../../../docs/source/policy_vqbet_README.md
--- a/src/lerobot/record.py
+++ b/src/lerobot/record.py
@@ -393,5 +393,9 @@ def record(cfg: RecordConfig) -> LeRobotDataset:
    return dataset


-if __name__ == "__main__":
+def main():
    record()
+
+
+if __name__ == "__main__":
+    main()
--- a/src/lerobot/replay.py
+++ b/src/lerobot/replay.py
@@ -112,5 +112,9 @@ def replay(cfg: ReplayConfig):
    robot.disconnect()


-if __name__ == "__main__":
+def main():
    replay()
+
+
+if __name__ == "__main__":
+    main()
--- a/src/lerobot/scripts/train.py
+++ b/src/lerobot/scripts/train.py
@@ -286,6 +286,10 @@ def train(cfg: TrainPipelineConfig):
        policy.push_model_to_hub(cfg)


-if __name__ == "__main__":
+def main():
    init_logging()
    train()
+
+
+if __name__ == "__main__":
+    main()
--- a/src/lerobot/setup_motors.py
+++ b/src/lerobot/setup_motors.py
@@ -80,5 +80,9 @@ def setup_motors(cfg: SetupConfig):
    device.setup_motors()


-if __name__ == "__main__":
+def main():
    setup_motors()
+
+
+if __name__ == "__main__":
+    main()
--- a/src/lerobot/teleoperate.py
+++ b/src/lerobot/teleoperate.py
@@ -153,5 +153,9 @@ def teleoperate(cfg: TeleoperateConfig):
        robot.disconnect()


-if __name__ == "__main__":
+def main():
    teleoperate()
+
+
+if __name__ == "__main__":
+    main()
--- a/tests/policies/test_policies.py
+++ b/tests/policies/test_policies.py
@@ -27,11 +27,13 @@ from lerobot import available_policies
 from lerobot.configs.default import DatasetConfig
 from lerobot.configs.train import TrainPipelineConfig
 from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
+from lerobot.constants import ACTION, OBS_STATE
 from lerobot.datasets.factory import make_dataset
 from lerobot.datasets.utils import cycle, dataset_to_policy_features
 from lerobot.envs.factory import make_env, make_env_config
 from lerobot.envs.utils import preprocess_observation
 from lerobot.optim.factory import make_optimizer_and_scheduler
+from lerobot.policies.act.configuration_act import ACTConfig
 from lerobot.policies.act.modeling_act import ACTTemporalEnsembler
 from lerobot.policies.factory import (
    get_policy_class,
@@ -363,6 +365,54 @@ def test_normalize(insert_temporal_dim):
    unnormalize(output_batch)


+@pytest.mark.parametrize("multikey", [True, False])
+def test_multikey_construction(multikey: bool):
+    """
+    Asserts that multiple keys with type State/Action are correctly processed by the policy constructor,
+    preventing erroneous creation of the policy object.
+    """
+    input_features = {
+        "observation.state": PolicyFeature(
+            type=FeatureType.STATE,
+            shape=(10,),
+        ),
+    }
+    output_features = {
+        "action": PolicyFeature(
+            type=FeatureType.ACTION,
+            shape=(5,),
+        ),
+    }
+
+    if multikey:
+        """Simulates the complete state/action is constructed from more granular multiple
+        keys, of the same type as the overall state/action"""
+        input_features = {}
+        input_features["observation.state.subset1"] = PolicyFeature(type=FeatureType.STATE, shape=(5,))
+        input_features["observation.state.subset2"] = PolicyFeature(type=FeatureType.STATE, shape=(5,))
+        input_features["observation.state"] = PolicyFeature(type=FeatureType.STATE, shape=(10,))
+
+        output_features = {}
+        output_features["action.first_three_motors"] = PolicyFeature(type=FeatureType.ACTION, shape=(3,))
+        output_features["action.last_two_motors"] = PolicyFeature(type=FeatureType.ACTION, shape=(2,))
+        output_features["action"] = PolicyFeature(
+            type=FeatureType.ACTION,
+            shape=(5,),
+        )
+
+    config = ACTConfig(input_features=input_features, output_features=output_features)
+
+    state_condition = config.robot_state_feature == input_features[OBS_STATE]
+    action_condition = config.action_feature == output_features[ACTION]
+
+    assert state_condition, (
+        f"Discrepancy detected. Robot state feature is {config.robot_state_feature} but policy expects {input_features[OBS_STATE]}"
+    )
+    assert action_condition, (
+        f"Discrepancy detected. Action feature is {config.action_feature} but policy expects {output_features[ACTION]}"
+    )
+
+
@pytest.mark.parametrize(
    "ds_repo_id, policy_name, policy_kwargs, file_name_extra",
    [
				`@@ -0,0 +1 @@`
				`../../../../docs/source/policy_act_README.md`
				`@@ -0,0 +1 @@`
				`../../../../docs/source/policy_diffusion_README.md`
				`@@ -0,0 +1 @@`
				`../../../../docs/source/policy_smolvla_README.md`
				`@@ -0,0 +1 @@`
				`../../../../docs/source/policy_tdmpc_README.md`
				`@@ -0,0 +1 @@`
				`../../../../docs/source/policy_vqbet_README.md`