open-edge-platform/skills

physicalai-runtime-loading-exported-policies

Loads and validates policies exported from Physical AI Studio for Runtime deployment.

First seen Aug 19, 2026

Installation

$ npx skills add open-edge-platform/skills --skill physicalai-runtime-loading-exported-policies

Summary

  • Loads and validates policies exported from Physical AI Studio for Runtime deployment.
  • Use when working on InferenceModel, InferenceModel.from_pretrained, manifest.json, adapter auto-detection (onnx, openvino), backend/device kwargs, Hugging Face Hub policy packages, or the Runtime side of the export/load contract that Studio produces with physicalai export.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 2
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

LicenseApache-2.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,225 B
  • docs SUMMARY.md 411 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 14 installs

SKILL.md

Loading Exported Policies

Runtime loads Studio export directories (or Hub snapshots that mirror them) through InferenceModel in src/physicalai/inference/model.py. Manifest parsing lives in src/physicalai/inference/manifest.py; backends register in src/physicalai/inference/adapters/registry.py (onnx → .onnx, openvino → .xml). Hub downloads use src/physicalai/inference/utils/_hub.py.

Workflow

  1. Identify the artifact: local export directory or Hub repoid, expected backend, and whether the user needs selectaction vs predictactionchunk.

- Done when: load path and API entry point are chosen before editing code.

  1. Load with auto-detection first (local):

``python from physicalai.inference import InferenceModel model = InferenceModel("./exports/act_policy") ``

- Done when: model constructs without explicit backend= when artifacts match a registered extension.

  1. Hub load when the package is published:

``python model = InferenceModel.from_pretrained("OpenVINO/act-fp16-ov", revision="<commit-sha>") ``

- Done when: revision is pinned for reproducibility when security or CI matters.

  1. Explicit backend only when auto-detection is ambiguous:

``python model = InferenceModel("./exports/act_policy", backend="openvino", device="CPU") ``

  1. Validate structure against references/export-load-contract.md and backend notes (references/onnx.md, references/openvino.md).

- Done when: manifest, model file, and processor artifacts resolve under the export directory.

  1. Smoke inference without owning robot timing:

``python model.reset() action = model.select_action(observation) ``

- Done when: one forward pass succeeds on representative observation keys/shapes. For hardware loops, hand off to physicalai-runtime-running-policy-on-robot.

Validation loop

uv run pytest tests/unit/inference/test_model.py tests/unit/inference/test_manifest.py -q

For adapter changes, add or run targeted tests under tests/unit/inference/.

Required checks

  • Export directory contains backend model file(s) and manifest.json consistent with docs/reference/manifest-schema.md.
  • Metadata input/output/feature names align with preprocessors in the manifest.
  • Optional backends fail with clear install guidance (onnxruntime, OpenVINO).
  • Do not document a backend unless an adapter is registered in src/physicalai/inference/adapters/.
  • Hub loads must not log tokens; prefer pinned revision= for production docs.

References

  • references/export-load-contract.md — consumer-side contract (coordinate with Studio export skill).
  • references/onnx.md, references/openvino.md — adapter constraints.