NVIDIA Isaac GR00T: GR00T policy server

Serve a configured GR00T checkpoint or the upstream dataset-replay alternative through the policy server protocol with an explicit embodiment tag.

isaac-groot-gr00t-eval-run-gr00t-server-py | Record version: source-b94d8f879bc83b97120cfcf3e3c9d7a506d93f633a036474c7f60db81792705d

Record JSON | Markdown | Pinned upstream source

Access

Fetch the pinned repository, verify this source checksum, and use upstream installation and invocation. This record does not install or execute code.

Hub preparation adapter: false. Follow the upstream setup and invocation contract.

Source and license

Repository: https://github.com/NVIDIA/Isaac-GR00T
Revision: dac54b313160c201c450f97df0fd74ebd379c892
Path: gr00t/eval/run_gr00t_server.py
Source SHA256: b94d8f879bc83b97120cfcf3e3c9d7a506d93f633a036474c7f60db81792705d
Original authors: NVIDIA CORPORATION & AFFILIATES
License: Apache-2.0
License scope: Only the 12 selected Python source files, each with explicit matching Apache-2.0 header. Preserve copyright and attribution, including source adaptation notices. Third-party code, datasets, simulators, robot firmware, services, model architecture components and weights retain separate terms.
License SHA256: 93363510f62ce25ad1a47605b0b06ab335edd82f1a444531c58dd30b6e5a5a0c
Hub commit: 1d6d9eb134e397d910265a8d6e7d8f257f9e8d7f

Artifact

{
  "kind": "workflow",
  "format": "python",
  "workflow_role": "policy-serving"
}

Requirements

{
  "python": "Root environment declares >=3.12,<3.13; per-workflow or robot-client environments may differ and must follow their pinned setup documents.",
  "packages": [
    "Pinned gr00t source checkout",
    "Upstream PyTorch/CUDA or TensorRT stack as selected",
    "Matching simulator or robot connector only for selected workflow"
  ],
  "display": "No environment has been installed. Training, inference, platform architecture and robot-client environments differ; setup text is a declaration.",
  "execution_domain": "computation",
  "source_imports": [
    "dataclasses",
    "gr00t.configs.data.embodiment_configs",
    "gr00t.data.embodiment_tags",
    "gr00t.data.types",
    "gr00t.policy.gr00t_policy",
    "gr00t.policy.replay_policy",
    "gr00t.policy.server_client",
    "importlib",
    "json",
    "os",
    "pathlib",
    "sys",
    "tyro"
  ],
  "notes": "These are upstream source/document declarations, not verified installed dependencies or operating capabilities.",
  "declared_requirements": {
    "gpu_notes": "Model-serving branch defaults to CUDA; upstream learned-policy inference guide declares >=16 GB VRAM and CUDA 12.6+ for the dGPU profile. The dataset-replay branch does not establish a GPU or learned-model requirement.",
    "checkpoint_or_model_access": "Either a configured checkpoint or the source's dataset-replay branch is selected. Checkpoint licensing remains separate from the source-code license; no model or dataset was acquired.",
    "python": "Root environment declares >=3.12,<3.13; per-workflow or robot-client environments may differ and must follow their pinned setup documents.",
    "external_service_or_network": "Upstream model/data retrieval, configured policy server and optional logging/robot connectivity depend on selection. No network service was invoked by this entrypoint during review.",
    "interpretation": "These are upstream source/document declarations, not verified installed dependencies or operating capabilities.",
    "model_license_scope": {
      "upstream_readme_license_section": "Code: Apache-2.0; model weights: NVIDIA Open Model License",
      "evidence_path": "README.md",
      "checkpoint_license_applicability": "not_reviewed",
      "weights_acquired": false,
      "scope": "Source declarations only; no checkpoint access or downstream licensing clearance is inferred."
    }
  }
}

Invocation

{
  "entrypoint": "python gr00t/eval/run_gr00t_server.py",
  "notes": "Read the pinned source and workflow setup. Model-serving branch defaults to CUDA; upstream learned-policy inference guide declares >=16 GB VRAM and CUDA 12.6+ for the dGPU profile. The dataset-replay branch does not establish a GPU or learned-model requirement. Either a configured checkpoint or the source's dataset-replay branch is selected. Checkpoint licensing remains separate from the source-code license; no model or dataset was acquired. No environment was resolved and no source was executed."
}

Explicit compatibility

[]

Missing environment fields remain unknown. Discovery labels do not establish robot compatibility.

Evidence

Level: source_reviewed; runtime verification: not_run.

Verified exact source, applicable license and author/setup document bytes at a full Git commit; parsed the Python AST and reviewed this guarded operational entrypoint and its explicit license notices. No upstream code, installation, robot command, dataset, mesh or checkpoint was executed or loaded.

Source review and contributor reports do not establish task completion. Preserve upstream attribution and licenses.