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name: "any4lerobot" description: "Guides Any4LeRobot dataset conversions, LeRobot-to-RLDS export, and LeRobot v1.6-v3.0 format migrations with schema validation, version-aware environments, and safe publication boundaries." disable-model-invocation: true metadata: disco-role: operating license: MIT

Any4LeRobot

Any4LeRobot is a script-oriented toolbox for moving robotics datasets into and between LeRobot formats. Use this skill to plan a conversion from a documented source layout, select the matching route, validate schemas before writing, and keep Ray, Beam, simulator, video, and Hub side effects explicit.

Start here

1. Identify the source format, target format/version, local source root, output root, desired modalities, and whether publication is requested.
2. Read workflow selection and choose one focused route below. Load troubleshooting before changing dependencies or retrying a failed run.
3. Check repository provenance when working from a checkout or deciding whether the guidance needs refreshing.
4. Run the safe environment probe in scripts/check_environment.py before executing any converter. It reports core and optional import/API status but never downloads data or writes a dataset.
5. Build a no-write preflight: verify input layout, feature shapes/dtypes, version/API compatibility, distinct output path, backup/rollback plan, and resource budget. Start with local/debug execution; defer Hub publication.

This skill contains distilled guidance, not a dependency on the original checkout. Do not tell a future agent to run a source-repository script or checkout-relative convert.sh; use the route references and their commands as recipes, then verify the equivalent entry point in the selected environment.

Route map

User request or input	Read this route
Design an adapter, use local/Ray DataTrove execution, aggregate task outputs, resume, or publish	generic-conversion
Open X-Embodiment/RLDS/TFDS → LeRobot	openx-conversion
AgiBotWorld raw tree → LeRobot	agibot-conversion
RoboMIND benchmark/embodiment HDF5 → LeRobot	robomind-conversion
LIBERO HDF5 → LeRobot or LIBERO rerender planning	libero-conversion
RoboCasa HDF5, subset, depth/segmentation, or rerender planning	robocasa-conversion
LeRobot → RLDS/TFDS	rlds-export
LeRobot v1.6, v2.0, v2.1, or v3.0 migration	version-migration

Do not conflate the two RLDS directions: openx-conversion consumes an RLDS builder, while rlds-export produces one. Do not use version-migration to convert raw HDF5 or to repair missing modalities.

Environment contract

Any4LeRobot has no pyproject.toml, setup.py, or declared distribution. The usual baseline is a private Python 3.10/3.11 environment with a LeRobot writer compatible with the selected source script, NumPy, h5py, pyarrow/pandas, Pillow/OpenCV, tqdm, and the video codec stack. Add only what the route needs:

• datatrove for the shared pipeline; Ray/DataTrove Ray extras only for distributed execution.
• tensorflow and tensorflow-datasets for either RLDS direction; Apache Beam is optional and should be disabled for small/lossless exports.
• datasets, jsonlines, safetensors, and the exact historical LeRobot revision for version migration. Keep v2.x and v3.x environments separate.
• RoboCasa/robosuite or LIBERO plus their assets only for simulator rerendering; these are not required for ordinary HDF5 conversion and are not verified by this skill.

Verify the installed API rather than trusting a package import alone:

python -c "from lerobot.datasets.lerobot_dataset import LeRobotDataset, LeRobotDatasetMetadata; print('LeRobot API OK')"
python -c "import h5py, pyarrow, torch, torchcodec; print('core dependencies OK')"

The source snapshot mixes historical and current LeRobot import locations. In particular, a current release may not re-export LeRobotDataset from lerobot.datasets or provide lerobot.datasets.dataset_writer.py. Treat that as a compatibility stop gate; do not patch imports or metadata behavior by guesswork. Read the route-specific troubleshooting before selecting another revision.

Safety gates

• Never use the raw source tree as the output root. Inventory existing output and temporary paths first; several converters delete an existing destination.
• Never enable --push-to-hub, Hub deletion/tagging, Git-LFS moves, or public upload during the first local pass. Use a new staging root or test branch.
• Do not run Ray, Beam, simulator rendering, or large video/data conversions as an import or help check. Record external datasets, credentials, assets, and hardware as explicit prerequisites.
• Preserve source version, feature schemas, task text, and episode counts. A successful file open is not proof that all episodes or modalities are convertible.

Shared references

• Read workflow selection for route triggers, directionality, and the preflight record.
• Read troubleshooting for install/import, optional backend, schema, output, and publication failures.
• Run the environment probe for a no-write dependency/API status summary.
• Read provenance before refresh or when the repository commit differs from this generated baseline.