embodied-ops

Reliable collection, evaluation, and artifact workflows for embodied AI.

embodied-ops contains the workflow primitives that sit above robot and policy adapters: episode decisions, sample-timing checks, deterministic evaluation plans, and transactional artifact publication. The package has no runtime dependencies and does not define a competing robot API.

Install

python -m pip install embodied-ops

Scope

Use the native interface of the framework that owns the hardware integration, such as LeRobot Robot and Teleoperator. ROS nodes, drivers, control leases, safety limits, datasets, policies, and process supervision remain in those framework or robot-specific packages.

Atomic artifacts

from pathlib import Path
from embodied_ops import OutputDirectoryTransaction

with OutputDirectoryTransaction(Path("runs/eval-001")) as transaction:
    assert transaction.path is not None
    (transaction.path / "metrics.json").write_text("{}\n")
    transaction.commit()

If the body fails or exits without commit(), the staging directory is removed and any previous complete output remains authoritative. Once publication succeeds, transaction.committed remains true even if removal of the displaced backup fails; that recovery state raises PublishedOutputCleanupError with both paths. Unfinished staging or backup siblings block reuse until they are inspected. For single files, create_only_output_file() provides the same build-then-publish flow without ever replacing an existing path.

Evaluation plans

from embodied_ops import EvaluationPlan

plan = EvaluationPlan(
    identifier="fruit-placement",
    task_ids=("apple_bowl", "mango_plate"),
    attempts_per_task=3,
)
for slot in plan.slots():
    print(slot.sequence, slot.total, slot.task_id)

Run metadata may persist slot.to_dict() and later reconstruct the same task/repetition position without depending on directory order.

Development

uv sync --dev
uv run pytest
uv run ruff check .
uv run ruff format --check .
uv build