Omniverse Cad To Simready
OpenAIOfficialCreated by OmniverseDistributed by OpenAI
- Skill
- Workflow
- Software development
- Apache-2.0
- Medium risk
- Has scripts
From the skill’s files
Taken from the skill’s own files (its description, section headings and stated usage). Not an AutoGineer summary, and not written by the author as one.
Coordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation, and optional package creation; deploy or verify Content Agents services first when property assignment is enabled; route single-stage work through nested references. Use this workflow skill when the user wants an end-to-end pipeline from a source asset to a SimReady asset or package. This skill coordinates existing conversion, authoring, validation, conformance, rendering, and packaging references directly. Do not replace the workflow with a single monolithic runner command.
What it does
- When to Use
- Prerequisites
- Minimum Viable Scope
- First Action
- Instructions
- Output Format
When to use it
- Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation, and…
- Use this workflow skill when the user wants an end-to-end pipeline from a source asset to a SimReady asset or package.
- This skill coordinates existing conversion, authoring, validation, conformance, rendering, and packaging references directly.
- This skill is documentation-driven and does not ship scripts/run.py.
- It should not depend on a repository checkout.
- When a stage needs deterministic execution, run the portable script from that stage reference's installed directory.
Advantages
The skill’s files do not state this.
Usage examples
The skill’s files do not state this.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/openai/omniverse-cad-to-simready/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip omniverse-cad-to-simready.zip -d .agents/skills
Documentation by Omniverse
CAD to SimReady
When to Use
Use this workflow skill when the user wants an end-to-end pipeline from a source asset to a SimReady asset or package. This skill coordinates existing conversion, authoring, validation, conformance, rendering, and packaging references directly. Do not replace the workflow with a single monolithic runner command.
This skill is documentation-driven and does not ship scripts/run.py. It
should not depend on a repository checkout. When a stage needs deterministic
execution, run the portable script from that stage reference's installed
directory. Shell is declared because this workflow invokes installed stage
reference scripts directly; it still must not grow a monolithic runner.
Prerequisites
Prefer running the
preflightreference first for deterministic setup. It installs or verifies local upstream checkouts, writes acad-to-simready-preflight.jsonmanifest, and exportsPHYSICAL_AI_PREFLIGHT_MANIFESTplusPHYSICAL_AI_REQUIRE_PREFLIGHT=1for downstream references.Python 3.12 and
uv(per repoREADME.md).NVIDIA_API_KEY from
https://build.nvidia.comwhen local Content Agents deployment will run. Already-running endpoints may instead use explicit endpoint variables plus usage tokens such asNGC_API_KEY,NVCF_API_KEY, orCONTENT_AGENTS_*_TOKEN.Docker, NVIDIA Container Toolkit, and an NVIDIA GPU for Content Agents and OVRTX stages.
Local upstream checkouts under
${PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT:-$HOME/.physical-ai-skill-hub/upstreams}when a downstream stage needs upstream scripts or specs.
Minimum Viable Scope
Conversion-only is a valid workflow request. When the user asks only to convert
or smoke-test source asset conversion, set property_assignment_intent=skip,
do not deploy Content Agents, run convert-to-usd, then run
validate-usd-minimum on the generated USD if conversion succeeds.
Do not imply that uv sync installs every source converter runtime. URDF,
MuJoCo/MJCF, and the repo Python dependencies are handled by the project
environment, but NVIDIA-backed source conversion requires an installed and
validated NVIDIA-Omniverse/usd-convert-cad checkout. If that runtime is
missing or does not support the source, preserve the blocked conversion report
and its install_hint instead of attempting an unrequested local build or
substituting another converter.
First Action
For any broad CAD/source-asset to SimReady request, assume
property_assignment_intent=run unless the user explicitly asks for
conversion-only, validation-only, or no material/physics assignment.
Before invoking converter, validation, Content Agents, OVRTX, packaging, or FET
helper scripts, run the preflight reference or verify an existing
PHYSICAL_AI_PREFLIGHT_MANIFEST. Treat preflight as the mandatory dependency
bootstrap step, not as workflow routing. If the user explicitly asks not to
deploy services or asks for conversion-only/validation-only, use
--skip-content-agents.
When PHYSICAL_AI_REQUIRE_PREFLIGHT=1 is set and a required component is not
ready in the manifest, downstream references must block with the preflight
guardrail instead of rediscovering upstreams or services directly.
When property_assignment_intent=run, the first operational action after
confirming the source path and resolving intent is to verify or deploy Content
Agents services. Do this before asset-context inspection, converter dependency
checks, conversion, validation, conformance, rendering, packaging, or upstream
source builds.
Use healthy existing endpoints when available. If OVRTX, Material, or Physics
endpoints are missing or unhealthy, run deploy-content-agents
first and do not continue until the shared standalone OVRTX renderer plus
independent Material and Physics service containers are healthy and exported
through CONTENT_AGENTS_*_BASE_URL. Deploy the Texture Agent too when texture
generation is requested.
If required deployment authentication is missing, ask the user for
NVIDIA_API_KEY and wait. If a provided endpoint requires usage auth, ask for
the appropriate usage token instead. If deployment cannot produce healthy
services, report Content Agents readiness as blocked instead of proceeding to
conversion.
Instructions
Confirm the source asset path exists, resolve
output_root, and classify the request as end-to-end, conversion-only, validation-only, or packaging.Resolve
property_assignment_intentbefore running any asset inspection, converter probe, conversion, validation, conformance, rendering, or packaging step.Run
preflightfor the selected workflow targets, unless a readyPHYSICAL_AI_PREFLIGHT_MANIFESTis already configured. Source the generated env file before running downstream scripts. Treat preflight as dependency setup only: it may use a provided--source-asset,--source-format, or--conversion-toolsvalue to scope dependency checks, butconvert-to-usdand the upstream converter references still decide actual conversion support.Verify or deploy Content Agents services first when
property_assignment_intent=run; block on missing authentication or unhealthy services instead of continuing.Read
references/workflow.mdandreferences/commands.md, then run only the stage references needed for the current request.Run
identify-asset-contexton the original source asset when web search is available or property assignment will run.Route the source through
convert-to-usd, or skip conversion for existing USD input and treat the source path as the current USD path.Run
validate-usd-minimumbefore expensive downstream work. Treat this as a viability gate only: record unit/profile issues such asmetersPerUnit != 1.0, but do not runsimready-conform-profile, FET001, or any other FET repair before Content Agents assignment when property assignment will run.Run Content Agents material, physics, and optional texture assignment on the converted/minimum-valid USD when requested or required.
Run
simready-conform-profileon the latest simulation USD path after property assignment and preserve every selected FET repair report.Run validation gates in order:
omni-asset-validate,omni-asset-validate-geometry,omni-asset-validate-physics, andsimready-validate.Rerun
simready-conform-profilewhensimready-validatereports a repairable requirement, then rerun profile validation on the newest authored USD.Run
ovrtx-render-servicewhen preview, thumbnail, or inspection images are requested. When package outputs are requested, runassemble-package-sourcenext to create the cleandeliverable/package source from the final USD and thumbnail, then runnv-core-package-sampleandnv-core-package-sample-validationon that deliverable folder only.Emit the consolidated workflow report with the final USD path, all stage reports, validation findings, rerun reasons, and next work.
Use the simready-conform-profile reference only after property assignment
when property_assignment_intent=run. It routes feature repair to upstream
SimReady Foundation FET skills such
as simready-foundation-conform-fet-000-core,
simready-foundation-conform-fet-001-minimal,
simready-foundation-conform-fet-004-simulate-multi-body-physics, and
simready-foundation-conform-fet-005-simulate-grasp-physics from branch
main.
If simready-validate reports a repairable requirement after the first
conformance pass, feed the structured requirement IDs back into
the simready-conform-profile reference before writing the final result. In
particular, GSP.001 is owned by upstream
simready-foundation-conform-fet-005-simulate-grasp-physics; run that skill when a
vision-capable agent can inspect visual evidence or explicit grasp points were
provided, otherwise record the FET005 step as blocked by missing vision/points
instead of treating it as an optional preview task.
For RB.MB.001, route the failure to
upstream simready-foundation-conform-fet-004-simulate-multi-body-physics. Do not assume
multiple visual prims are multiple rigid bodies; inspect
UsdPhysics.RigidBodyAPI applications. When the Physics Agent report shows
composed topology optimization or the USD has existing component colliders/part
roots and the profile validator reports FET004/RB.MB.001, FET004 should promote
those existing components into rigid bodies without creating geometry. Do not
mark the gate not applicable until after confirming there are fewer than two
reusable body candidates.
Output Format
Emit a consolidated workflow report in Markdown, and include JSON when the workflow writes structured artifacts. The report must include:
Overall status:
passed,blocked,failed, orneeds_rerun.Request summary: source asset path, detected source format, output root, selected SimReady profile/version, and property assignment intent.
Ordered stage results: stage reference, input artifact, output USD or USDZ path, report path, status, blocker reason, and rerun reason when applicable.
Content Agents readiness and property assignment results with service URLs, tokens, and credentials redacted.
Conformance and validation findings grouped by gate, requirement ID, selected FET repair reference, repair-loop attempt, and final disposition.
Final artifacts: final reported USD path, render preview path when requested, package root and package validation report when packaging ran, Markdown report path, JSON report path when present, and recommended next work.
Detailed References
Read only the references needed for the current request:
references/preflight/README.md: deterministic local setup, manifest/env contract, Linux and Windows wrappers, Content Agents deployment opt-out, and guardrail behavior.references/workflow.md: inputs, source routing, detailed workflow, validation policy, output report fields, approval points, and next steps.references/commands.md: concrete portable script command patterns for each stage.references/assemble-package-source/README.md: two-zone package source assembly, canonical root USD naming, thumbnail placement, and self-contained deliverable checks.
Publishing Layout Notes
Use skills/omniverse-cad-to-simready/ as the source of truth for this product
repo's skill. The .agents/skills symlink is a compatibility alias for local
agentskills.io-style discovery, and .codex/skills and .claude/skills are
agent-specific compatibility aliases.
Frontmatter keeps version and tools at top level for agentskills.io runtime
compatibility. NVCARPS discoverability fields live under metadata.
The nested references/ tree is intentional. It keeps one public catalog skill
while retaining script-bearing atomic stage references, upstream handoff notes,
and router documentation under the workflow. Do not flatten those references or
promote nested README references to sibling SKILL.md files unless the repo's
publishing model changes.
Limitations
This workflow coordinates existing conversion, property assignment, conformance, validation, rendering, and packaging skills; it does not replace them with a single monolithic runner command.
Stop at the first failing deployment, conversion, property-assignment, or conformance authoring gate unless the user explicitly asks for best-effort continuation.
Upstream
simready-foundation-conform-fet-005-simulate-grasp-physicsneeds visual review or explicit grasp points before it can author a meaningful grasp vector.
Troubleshooting
| Symptom | Cause | Fix |
|---|---|---|
| Downstream reference reports that cad-to-simready preflight has not prepared a component | PHYSICAL_AI_REQUIRE_PREFLIGHT=1 is set, but the manifest is missing or the required runtime/service is not ready | Run preflight/scripts/preflight.py, source the generated env file, or explicitly disable service deployment with --skip-content-agents only when Content Agents are out of scope. |
Workflow stops on GSP.001 and reports the failure as unclassified | Visual evidence or explicit grasp points were not provided to FET005 | Run upstream simready-foundation-conform-fet-005-simulate-grasp-physics only after a vision-capable agent has reviewed the asset, or pass explicit grasp points. Otherwise report the FET005 step as blocked, not failed. |
| Validation fails after a meaningful USD artifact already exists | Workflow stopped at the first validation finding | Continue remaining diagnostic gates and mark the result needs_rerun. Do not stop at validation findings once a USD artifact has been produced. |
| Property-assignment stage fails with a missing service endpoint | Content Agents service was not deployed before conversion | Run deploy-content-agents first. Do not start asset inspection, conversion, validation, conformance, rendering, or packaging before Content Agents readiness when property assignment will run. |
Material Agent reports that rendering produced 0 images after unit or profile repair | A FET repair, commonly FET001 unit normalization, was applied before Material Agent and changed the USD layering/scene state consumed by the service | Rerun assignment from the converted/minimum-valid USD: Material Agent first, then Physics Agent, then run simready-conform-profile and FET repairs on the latest service-authored USD. |
Material or Physics Agent local optimized path reports Permission denied: '/app/.build-resources/scene_optimizer_core/python' | Local Docker Scene Optimizer bundle permissions prevent the non-root service user from reading the packaged SO runtime | Repair the relevant local container with docker exec --user root content-material-agent-service chmod -R a+rX /app/.build-resources/scene_optimizer_core or docker exec --user root content-physics-agent-service chmod -R a+rX /app/.build-resources/scene_optimizer_core, then rerun the same optimized agent command. Do not treat the no-optimizer fallback as the root cause for instanced/prototype assets. |
RB.MB.001 fails even though the asset has many prims | The profile counts UsdPhysics.RigidBodyAPI prims, not visual or collider prims; Physics Agent may author one root rigid body | Route to upstream simready-foundation-conform-fet-004-simulate-multi-body-physics. First ensure Physics Agent used composed-topology optimization when applicable, then promote existing component colliders/part roots when the active profile reports FET004/RB.MB.001 and no geometry must be invented. |
Hard Rules
Prefer the preflight manifest for local upstream roots, converter executables, SimReady validation runtime, OVRTX endpoint, and Content Agents service URLs. When
PHYSICAL_AI_REQUIRE_PREFLIGHT=1is set, do not bypass the manifest with direct upstream discovery.Do not run asset inspection, converter probes, local upstream builds, conversion, validation, conformance, rendering, or packaging before Content Agents readiness when property assignment will run.
Use stage-specific installed reference scripts directly. Do not add or call a single
omniverse-cad-to-simreadyrunner command.For source conversion, delegate to the
convert-to-usdreference; do not substitute another converter for CAD or mesh formats.For property assignment, use Content Agents references as separate atomic steps: material first, then physics, then texture only when requested.
When property assignment will run, do not run
simready-conform-profileor any FET helper before Content Agents. Validate minimum USD first, then run Content Agents on that converted/minimum-valid USD, then apply FET repairs to the latest service-authored USD.When property assignment will run, do not run
simready-validateor any SimReady profile validation before Content Agents. The only validation gate allowed before service calls isvalidate-usd-minimum, which is a basic USD viability check.Stop at the first failing deployment, conversion, property-assignment, or conformance authoring gate unless the user explicitly asks for best-effort continuation.
Do not stop at validation findings after a meaningful USD artifact exists. Continue remaining diagnostic gates and mark the result
needs_rerun.Do not leave a
GSP.001profile failure as an unclassified final finding. Route it to upstreamsimready-foundation-conform-fet-005-simulate-grasp-physics; if the current agent cannot inspect renders or no explicit grasp points are available, report a blocked FET005 repair with the visual evidence path or missing input reason.Preserve every stage report and pass the concrete output USD path from each report into the next stage.
Files
- ATTRIBUTION.mdAdded by AutoGineer1.0 KiB
- BENCHMARK.md7.2 KiB
- LICENSEAdded by AutoGineer10.0 KiB
- SKILL.md17.5 KiB
- agents/openai.yaml427 B
- evals/evals.json4.0 KiB
- evals/files/minimal_mesh.stl157 B
- references/assemble-package-source/README.md3.5 KiB
- references/assemble-package-source/scripts/check_dependencies.pyScript1.1 KiB
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- references/assemble-package-source/scripts/run.pyScript17.6 KiB
- references/commands.md5.3 KiB
- references/content-agents/README.md18.6 KiB
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- references/content-agents/scripts/content_agent_client.pyScript71.2 KiB
- references/content-agents/scripts/content_agent_material_cleanup.pyScript10.7 KiB
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- references/content-agents/scripts/run.pyScript9.6 KiB
- references/convert-to-usd/README.md10.7 KiB
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- references/convert-to-usd/references/mujoco-usd-converter/scripts/check_dependencies.pyScript1.5 KiB
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- references/convert-to-usd/references/openusd-exchange-sdk-usdex/README.md4.7 KiB
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- references/nv-core-package-sample-validation/README.md5.2 KiB
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- references/omni-asset-validate-geometry/README.md3.5 KiB
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- references/omni-asset-validate-physics/README.md3.4 KiB
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- references/omni-asset-validate-physics/scripts/report_schema.json362 B
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- references/simready-conform-profile/references/FET_001_MINIMAL/README.md1.5 KiB
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- references/simready-conform-profile/references/FET_004_SIMULATE_MULTI_BODY_PHYSICS/README.md1.4 KiB
- references/simready-conform-profile/references/FET_004_SIMULATE_MULTI_BODY_PHYSICS/scripts/check_dependencies.py1.6 KiB
- references/simready-conform-profile/references/FET_004_SIMULATE_MULTI_BODY_PHYSICS/scripts/report_schema.json1.0 KiB
- references/simready-conform-profile/references/FET_004_SIMULATE_MULTI_BODY_PHYSICS/scripts/run.py13.3 KiB
- references/simready-conform-profile/references/FET_005_SIMULATE_GRASP_PHYSICS/README.md1.8 KiB
- references/simready-conform-profile/references/FET_005_SIMULATE_GRASP_PHYSICS/scripts/author_grasp_line.py11.2 KiB
- references/simready-conform-profile/scripts/check_dependencies.py1.9 KiB
- references/simready-conform-profile/scripts/report_schema.json466 B
- references/simready-conform-profile/scripts/run.py19.8 KiB
- references/simready-validate/README.md9.5 KiB
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- references/simready-validate/scripts/report_schema.json480 B
- references/simready-validate/scripts/run.py27.9 KiB
- references/validate-usd-minimum/README.md2.5 KiB
- references/validate-usd-minimum/scripts/check_dependencies.py1.7 KiB
- references/validate-usd-minimum/scripts/report_schema.json1.3 KiB
- references/validate-usd-minimum/scripts/run.py11.5 KiB
- references/workflow.md15.7 KiB
- shared/preflight_manifest.py6.0 KiB
- shared/script_utils.py11.7 KiB
- shared/simready_package.py33.6 KiB
- shared/simready_package_check_dependencies.py1.7 KiB
- shared/simready_package_report_schema.json702 B
- shared/usd_convert_cad_diagnostics.py3.2 KiB
- skill-card.md2.9 KiB
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references/content-agents/scripts/content_agent_client.py
#!/usr/bin/env python3
# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import argparse
from email.message import Message
import json
import os
from pathlib import Path
import shutil
import subprocess
import sys
import time
from typing import Any
from urllib.error import HTTPError, URLError
from urllib.parse import urljoin
from urllib.request import Request, urlopen
import uuid
sys.path.insert(0, str(Path(__file__).resolve().parents[3] / "shared"))
from script_utils import check_result as _check, emit_json_report
from content_agent_material_cleanup import cleanup_material_output
from preflight_manifest import load_preflight_manifest, preflight_required, preflight_status_check, ready_service_url
USD_EXTENSIONS = {".usd", ".usda", ".usdc", ".usdz"}
USD_LAYER_EXTENSIONS = {".usd", ".usda", ".usdc"}
TERMINAL_SUCCESS = {"completed", "complete", "succeeded", "success", "done"}
TERMINAL_FAILURE = {"failed", "failure", "cancelled", "canceled", "error"}
MATERIAL_ZERO_IMAGE_MARKERS = (
"rendering produced 0 images",
"build_dataset_usd",
)
PHYSICS_OPTIMIZER_FAILURE_MARKERS = (
"optimize_usd",
"scene optimizer",
"local backend unavailable",
"optimizer_endpoint",
"nvcf_optimizer_function_id",
)
SCENE_OPTIMIZER_PERMISSION_MARKERS = (
"permission denied",
"/app/.build-resources/scene_optimizer_core/python",
)
PHYSICS_SCENE_OPTIMIZER_CONTAINER_CANDIDATES = (
"content-physics-agent-service",
"pash-e2e-physics_agent_service",
"physics_agent_service",
)
MDL_UPLOAD_PREP_SNIPPET = r"""
import json
import shutil
import sys
from pathlib import Path
from pxr import Sdf, Usd
asset_path = Path(sys.argv[1]).resolve()
label = sys.argv[2] if len(sys.argv) > 2 else "content_agents"
info = {
"staged": False,
"path": str(asset_path),
"stripped_mdl_source_assets": 0,
"cleared_unresolved_service_asset_paths": 0,
"warning": None,
}
def is_unresolved_service_asset_path(path: str) -> bool:
lower = path.lower()
return ".usdz[" in lower and lower.startswith(
(
"/var/material-agent/sessions/",
"/var/physics-agent/sessions/",
"/var/texture-agent/sessions/",
)
)
stage = Usd.Stage.Open(str(asset_path))
if stage is None:
info["warning"] = f"Could not inspect {label} upload USD for MDL source assets"
print(json.dumps(info))
raise SystemExit(0)
mdl_attr_count = 0
service_asset_path_count = 0
for prim in stage.Traverse():
for attr in prim.GetAttributes():
try:
value = attr.Get()
except Exception:
continue
if not isinstance(value, Sdf.AssetPath):
continue
path = str(value.path)
if path.lower().endswith(".mdl"):
mdl_attr_count += 1
elif is_unresolved_service_asset_path(path):
service_asset_path_count += 1
if mdl_attr_count == 0 and service_asset_path_count == 0:
print(json.dumps(info))
raise SystemExit(0)
staged_path = asset_path.with_name(f"{asset_path.stem}_{label}_upload{asset_path.suffix.lower()}")
if staged_path.exists():
staged_path.unlink()
shutil.copy2(asset_path, staged_path)
staged = Usd.Stage.Open(str(staged_path))
if staged is None:
raise RuntimeError(f"Could not open staged {label} upload USD: {staged_path}")
stripped = 0
cleared_service_paths = 0
for prim in staged.Traverse():
for attr in prim.GetAttributes():
try:
value = attr.Get()
except Exception:
continue
if not isinstance(value, Sdf.AssetPath):
continue
path = str(value.path)
if path.lower().endswith(".mdl"):
attr.Clear()
stripped += 1
elif is_unresolved_service_asset_path(path):
attr.Clear()
cleared_service_paths += 1
if (stripped or cleared_service_paths) and not staged.GetRootLayer().Save():
raise RuntimeError(f"Could not save staged {label} upload USD: {staged_path}")
info.update(
{
"staged": True,
"path": str(staged_path.resolve()),
"stripped_mdl_source_assets": stripped,
"cleared_unresolved_service_asset_paths": cleared_service_paths,
"source_path": str(asset_path),
}
)
print(json.dumps(info))
"""
USD_TOPOLOGY_INSPECTION_SNIPPET = r"""
import json
import sys
from pathlib import Path
from pxr import Usd, UsdGeom
asset_path = Path(sys.argv[1]).resolve()
result = {
"inspected": False,
"reason": None,
"default_prim_path": None,
"mesh_count": 0,
"geom_subset_count": 0,
"mesh_with_geom_subset_count": 0,
"instance_count": 0,
"instance_proxy_count": 0,
"prototype_count": 0,
"has_composed_component_topology": False,
"component_topology_reasons": [],
}
stage = Usd.Stage.Open(str(asset_path))
if stage is None:
result["reason"] = "Could not open USD stage"
print(json.dumps(result))
raise SystemExit(0)
default_prim = stage.GetDefaultPrim()
if not default_prim:
result["reason"] = "Stage has no default prim"
print(json.dumps(result))
raise SystemExit(0)
result["inspected"] = True
result["default_prim_path"] = str(default_prim.GetPath())
try:
result["prototype_count"] = len(stage.GetPrototypes())
except Exception:
result["prototype_count"] = 0
mesh_paths_with_subsets = set()
for prim in Usd.PrimRange(default_prim):
if not prim.IsActive():
continue
if prim.IsA(UsdGeom.Mesh):
result["mesh_count"] += 1
if prim.IsInstance():
result["instance_count"] += 1
if prim.IsInstanceProxy():
result["instance_proxy_count"] += 1
is_geom_subset = prim.GetTypeName() == "GeomSubset"
try:
is_geom_subset = is_geom_subset or bool(UsdGeom.Subset(prim))
except Exception:
pass
if is_geom_subset:
result["geom_subset_count"] += 1
parent = prim.GetParent()
if parent and parent.IsA(UsdGeom.Mesh):
mesh_paths_with_subsets.add(str(parent.GetPath()))
result["mesh_with_geom_subset_count"] = len(mesh_paths_with_subsets)
if result["geom_subset_count"]:
result["component_topology_reasons"].append("geom_subsets")
if result["instance_count"] or result["instance_proxy_count"] or result["prototype_count"]:
result["component_topology_reasons"].append("instances_or_prototypes")
result["has_composed_component_topology"] = bool(result["component_topology_reasons"])
print(json.dumps(result))
"""
AGENTS: dict[str, dict[str, Any]] = {
"material-agent-client": {
"agent_key": "material",
"agent": "material-agent",
"default_env": ("CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL", "MATERIAL_AGENT_BASE_URL"),
"token_env": (
"CONTENT_AGENTS_MATERIAL_AGENT_TOKEN",
"MATERIAL_AGENT_TOKEN",
"CONTENT_AGENTS_TOKEN",
"NGC_API_KEY",
"NVCF_API_KEY",
),
"output_endpoint": "output",
"output_suffix": "_material.usd",
"output_label": "materialized_usd",
"optional_artifacts": (
("predictions", "predictions", ".jsonl", False),
("report", "report", ".html", False),
),
"next_step": "physics-agent-client",
},
"physics-agent-client": {
"agent_key": "physics",
"agent": "physics-agent",
"default_env": ("CONTENT_AGENTS_PHYSICS_AGENT_BASE_URL", "PHYSICS_AGENT_BASE_URL"),
"token_env": (
"CONTENT_AGENTS_PHYSICS_AGENT_TOKEN",
"PHYSICS_AGENT_TOKEN",
"CONTENT_AGENTS_TOKEN",
"NGC_API_KEY",
"NVCF_API_KEY",
),
"output_endpoint": "output-usd",
"output_suffix": "_physics.usd",
"output_label": "physics_usd",
"optional_artifacts": (
("predictions", "predictions", ".jsonl", False),
("dataset", "dataset", ".jsonl", False),
("report", "report", ".html", False),
),
"next_step": "simready-conform-profile",
},
"texture-agent-client": {
"agent_key": "texture",
"agent": "texture-agent",
"default_env": ("CONTENT_AGENTS_TEXTURE_AGENT_BASE_URL", "TEXTURE_AGENT_BASE_URL"),
"token_env": (
"CONTENT_AGENTS_TEXTURE_AGENT_TOKEN",
"TEXTURE_AGENT_TOKEN",
"CONTENT_AGENTS_TOKEN",
"NGC_API_KEY",
"NVCF_API_KEY",
),
"output_endpoint": "output",
"output_suffix": "_textured.usdz",
"output_label": "textured_usdz",
"optional_artifacts": (
("materials", "materials", ".json", False),
("textures", "textures", ".zip", False),
("renders", "renders", ".zip", False),
),
"next_step": "simready-conform-profile",
},
}
def _skill_name() -> str:
return Path(sys.argv[0]).resolve().parents[1].name
def _spec() -> dict[str, Any]:
skill_name = _skill_name()
if skill_name not in AGENTS:
raise RuntimeError(f"Unsupported Content Agents skill directory: {skill_name}")
return AGENTS[skill_name]
def _env_first(names: tuple[str, ...]) -> str | None:
for name in names:
value = os.getenv(name)
if value:
return value
return None
def _env_or_file_first(names: tuple[str, ...]) -> str | None:
for name in names:
value = os.getenv(name)
if value:
return value
file_value = os.getenv(f"{name}_FILE")
if not file_value:
continue
try:
token = Path(file_value).read_text(encoding="utf-8").strip()
except OSError:
continue
if token:
return token
return None
def _resolve_base_url(base_url: str | None, spec: dict[str, Any]) -> tuple[str | None, str | None]:
if base_url:
return base_url.rstrip("/"), "cli"
env_base_url = _env_first(spec["default_env"])
if env_base_url:
return env_base_url.rstrip("/"), "env_base_url"
manifest, _, _ = load_preflight_manifest()
manifest_base_url = ready_service_url(manifest, str(spec["agent_key"]))
if manifest_base_url:
return manifest_base_url.rstrip("/"), "preflight_manifest"
return None, None
def _headers(token: str | None, extra: dict[str, str] | None = None) -> dict[str, str]:
headers = dict(extra or {})
if token:
headers["Authorization"] = f"Bearer {token}"
return headers
def _http_request(
method: str,
url: str,
*,
token: str | None = None,
data: bytes | None = None,
headers: dict[str, str] | None = None,
timeout: int = 120,
) -> tuple[int, dict[str, str], bytes]:
request = Request(url, data=data, headers=_headers(token, headers), method=method)
try:
with urlopen(request, timeout=timeout) as response:
return response.status, dict(response.headers.items()), response.read()
except HTTPError as exc:
body = exc.read().decode("utf-8", errors="replace")
raise RuntimeError(f"HTTP {exc.code} from {url}: {body[:500]}") from exc
except URLError as exc:
raise RuntimeError(f"Could not reach {url}: {exc.reason}") from exc
except (TimeoutError, OSError) as exc:
raise RuntimeError(f"Could not reach {url}: {exc}") from exc
def _json_request(method: str, url: str, *, token: str | None, timeout: int) -> dict[str, Any]:
_, _, body = _http_request(method, url, token=token, timeout=timeout)
payload = json.loads(body.decode("utf-8"))
return payload if isinstance(payload, dict) else {"value": payload}
def _multipart_body(asset_path: Path, fields: dict[str, str]) -> tuple[bytes, str]:
boundary = f"----physical-ai-skill-{uuid.uuid4().hex}"
chunks: list[bytes] = []
for name, value in fields.items():
chunks.extend(
[
f"--{boundary}\r\n".encode("utf-8"),
f'Content-Disposition: form-data; name="{name}"\r\n\r\n'.encode("utf-8"),
str(value).encode("utf-8"),
b"\r\n",
]
)
chunks.extend(
[
f"--{boundary}\r\n".encode("utf-8"),
f'Content-Disposition: form-data; name="usd_file"; filename="{asset_path.name}"\r\n'.encode("utf-8"),
b"Content-Type: application/octet-stream\r\n\r\n",
asset_path.read_bytes(),
b"\r\n",
f"--{boundary}--\r\n".encode("utf-8"),
]
)
return b"".join(chunks), f"multipart/form-data; boundary={boundary}"
def _post_pipeline(asset_path: Path, base_url: str, token: str | None, fields: dict[str, str], timeout: int) -> str:
body, content_type = _multipart_body(asset_path, fields)
_, _, response_body = _http_request(
"POST",
urljoin(f"{base_url.rstrip('/')}/", "pipeline"),
token=token,
data=body,
headers={"Content-Type": content_type},
timeout=timeout,
)
payload = json.loads(response_body.decode("utf-8"))
session_id = payload.get("session_id")
if not session_id:
raise RuntimeError("Content Agents service did not return session_id")
return str(session_id)
def _layer_identifier(layer: Any) -> str:
return str(getattr(layer, "realPath", None) or getattr(layer, "identifier", "") or "")
def _prepare_upload_asset(asset_path: Path, output_directory: Path) -> tuple[Path, dict[str, Any]]:
upload_info: dict[str, Any] = {
"asset_path": str(asset_path),
"dependency_layers": [],
"dependency_assets": [],
"dependency_count": 0,
"inspection_error": None,
"packaging": "none",
"package_size_bytes": None,
"path": str(asset_path),
"unresolved_paths": [],
}
if asset_path.suffix.lower() == ".usdz":
upload_info["packaging"] = "already_usdz"
return asset_path, upload_info
try:
from pxr import UsdUtils
except Exception as exc:
upload_info["inspection_error"] = f"OpenUSD dependency inspection is unavailable: {exc}"
return asset_path, upload_info
try:
layers, assets, unresolved_paths = UsdUtils.ComputeAllDependencies(str(asset_path))
except Exception as exc:
upload_info["inspection_error"] = f"Could not inspect USD dependencies: {exc}"
return asset_path, upload_info
root_path = asset_path.resolve()
dependency_layers: list[str] = []
for layer in layers:
identifier = _layer_identifier(layer)
if not identifier:
continue
try:
if Path(identifier).resolve() == root_path:
continue
except OSError:
pass
dependency_layers.append(identifier)
dependency_assets = [str(asset) for asset in assets]
unresolved = [str(path) for path in unresolved_paths]
upload_info["dependency_layers"] = dependency_layers
upload_info["dependency_assets"] = dependency_assets
upload_info["unresolved_paths"] = unresolved
upload_info["dependency_count"] = len(dependency_layers) + len(dependency_assets)
if unresolved:
raise RuntimeError("Cannot package USD for Content Agents upload; unresolved dependencies: " + ", ".join(unresolved))
if upload_info["dependency_count"] == 0:
return asset_path, upload_info
output_directory.mkdir(parents=True, exist_ok=True)
package_path = output_directory / f"{asset_path.stem}_content_agents_upload.usdz"
if package_path.exists():
package_path.unlink()
ok = UsdUtils.CreateNewUsdzPackage(str(asset_path), str(package_path))
if not ok or not package_path.exists() or package_path.stat().st_size == 0:
raise RuntimeError(f"OpenUSD failed to package USD dependencies for Content Agents upload: {package_path}")
upload_info["packaging"] = "usdz"
upload_info["path"] = str(package_path.resolve())
upload_info["package_size_bytes"] = package_path.stat().st_size
return package_path, upload_info
def _is_unresolved_service_asset_path(path: str) -> bool:
lower = path.lower()
return ".usdz[" in lower and lower.startswith(
(
"/var/material-agent/sessions/",
"/var/physics-agent/sessions/",
"/var/texture-agent/sessions/",
)
)
def _stage_mdl_safe_upload_asset(asset_path: Path, label: str) -> tuple[Path, dict[str, Any]]:
info: dict[str, Any] = {
"staged": False,
"path": str(asset_path),
"stripped_mdl_source_assets": 0,
"cleared_unresolved_service_asset_paths": 0,
"warning": None,
}
if asset_path.suffix.lower() not in USD_LAYER_EXTENSIONS:
return asset_path, info
try:
from pxr import Sdf, Usd
except Exception as exc:
staged_path, external_info = _stage_mdl_safe_upload_asset_external(asset_path, label)
if external_info.get("staged") or not external_info.get("warning"):
return staged_path, external_info
info["warning"] = (
f"OpenUSD Python APIs are unavailable for {label} upload prep: {exc}. "
+ str(external_info.get("warning") or "No alternate OpenUSD Python runtime staged the upload.")
)
return asset_path, info
try:
stage = Usd.Stage.Open(str(asset_path))
except Exception as exc:
info["warning"] = f"Could not inspect {label} upload USD for MDL source assets: {exc}"
return asset_path, info
if stage is None:
info["warning"] = f"Could not inspect {label} upload USD for MDL source assets"
return asset_path, info
mdl_attrs: list[str] = []
service_asset_attrs: list[str] = []
for prim in stage.Traverse():
for attr in prim.GetAttributes():
try:
value = attr.Get()
except Exception:
continue
if not isinstance(value, Sdf.AssetPath):
continue
path = str(value.path)
if path.lower().endswith(".mdl"):
mdl_attrs.append(str(attr.GetPath()))
elif _is_unresolved_service_asset_path(path):
service_asset_attrs.append(str(attr.GetPath()))
if not mdl_attrs and not service_asset_attrs:
return asset_path, info
staged_path = asset_path.with_name(f"{asset_path.stem}_{label}_upload{asset_path.suffix.lower()}")
try:
if staged_path.exists():
staged_path.unlink()
shutil.copy2(asset_path, staged_path)
staged = Usd.Stage.Open(str(staged_path))
if staged is None:
raise RuntimeError(f"Could not open staged {label} upload USD: {staged_path}")
stripped = 0
cleared_service_paths = 0
for prim in staged.Traverse():
for attr in prim.GetAttributes():
try:
value = attr.Get()
except Exception:
continue
if not isinstance(value, Sdf.AssetPath):
continue
path = str(value.path)
if path.lower().endswith(".mdl"):
attr.Clear()
stripped += 1
elif _is_unresolved_service_asset_path(path):
attr.Clear()
cleared_service_paths += 1
if (stripped or cleared_service_paths) and not staged.GetRootLayer().Save():
raise RuntimeError(f"Could not save staged {label} upload USD: {staged_path}")
except Exception as exc:
staged_path.unlink(missing_ok=True)
info["warning"] = f"Could not stage {label} upload USD without MDL source assets: {exc}"
return asset_path, info
info.update(
{
"staged": True,
"path": str(staged_path.resolve()),
"stripped_mdl_source_assets": stripped,
"cleared_unresolved_service_asset_paths": cleared_service_paths,
"source_path": str(asset_path),
}
)
return staged_path, info
def _stage_mdl_safe_upload_asset_external(asset_path: Path, label: str) -> tuple[Path, dict[str, Any]]:
uv = shutil.which("uv")
info: dict[str, Any] = {
"staged": False,
"path": str(asset_path),
"stripped_mdl_source_assets": 0,
"warning": None,
}
if not uv:
info["warning"] = "uv was not found on PATH for alternate OpenUSD Python upload prep"
return asset_path, info
command = [uv, "run", "--python", "3.12", "python", "-c", MDL_UPLOAD_PREP_SNIPPET, str(asset_path), label]
try:
completed = subprocess.run(command, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=120, check=False)
except Exception as exc:
info["warning"] = f"Alternate OpenUSD Python upload prep failed to launch: {exc}"
return asset_path, info
if completed.returncode != 0:
detail = (completed.stderr or completed.stdout or "").strip()
info["warning"] = f"Alternate OpenUSD Python upload prep failed: {detail[:500]}"
return asset_path, info
try:
payload = json.loads(completed.stdout)
except json.JSONDecodeError as exc:
info["warning"] = f"Alternate OpenUSD Python upload prep returned invalid JSON: {exc}"
return asset_path, info
if not isinstance(payload, dict):
info["warning"] = "Alternate OpenUSD Python upload prep returned a non-object payload"
return asset_path, info
if payload.get("staged") and payload.get("path"):
return Path(str(payload["path"])), payload
return asset_path, payload
def _stage_physics_upload_asset(asset_path: Path) -> tuple[Path, dict[str, Any]]:
return _stage_mdl_safe_upload_asset(asset_path, "physics")
def _stage_material_upload_asset(asset_path: Path) -> tuple[Path, dict[str, Any]]:
return _stage_mdl_safe_upload_asset(asset_path, "material")
def _inspect_usd_topology_external(asset_path: Path) -> dict[str, Any]:
uv = shutil.which("uv")
if not uv:
return {"inspected": False, "reason": "uv was not found on PATH for alternate OpenUSD Python inspection"}
command = [uv, "run", "--python", "3.12", "python", "-c", USD_TOPOLOGY_INSPECTION_SNIPPET, str(asset_path)]
try:
completed = subprocess.run(command, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=120, check=False)
except Exception as exc:
return {"inspected": False, "reason": f"Alternate OpenUSD Python inspection failed to launch: {exc}"}
if completed.returncode != 0:
detail = (completed.stderr or completed.stdout or "").strip()
return {"inspected": False, "reason": f"Alternate OpenUSD Python inspection failed: {detail[:500]}"}
try:
payload = json.loads(completed.stdout)
except json.JSONDecodeError as exc:
return {"inspected": False, "reason": f"Alternate OpenUSD Python inspection returned invalid JSON: {exc}"}
return payload if isinstance(payload, dict) else {"inspected": False, "reason": "Alternate OpenUSD Python inspection returned a non-object payload"}
def _wait_for_status(
base_url: str,
token: str | None,
session_id: str,
*,
timeout: int,
poll_interval: float,
request_timeout: int,
) -> dict[str, Any]:
deadline = time.monotonic() + timeout
last_status: dict[str, Any] = {}
transient_errors: list[str] = []
status_url = urljoin(f"{base_url.rstrip('/')}/", f"pipeline/{session_id}/status")
while True:
try:
last_status = _json_request("GET", status_url, token=token, timeout=request_timeout)
except Exception as exc:
if not _is_transient_status_poll_error(exc):
raise
transient_errors.append(str(exc))
if time.monotonic() >= deadline:
raise TimeoutError(
f"Timed out waiting for Content Agents session {session_id}; "
f"last transient status poll error: {exc}"
) from exc
time.sleep(max(0.0, poll_interval))
continue
state = str(last_status.get("status", "")).lower()
if state in TERMINAL_SUCCESS or state in TERMINAL_FAILURE:
if transient_errors:
last_status["poll_warnings"] = transient_errors[-10:]
return last_status
if time.monotonic() >= deadline:
raise TimeoutError(f"Timed out waiting for Content Agents session {session_id}")
time.sleep(max(0.0, poll_interval))
def _is_transient_status_poll_error(exc: Exception) -> bool:
message = str(exc).lower()
if message.startswith("could not reach "):
return True
if message.startswith("http 5") or message.startswith("http 408") or message.startswith("http 429"):
return True
return any(
marker in message
for marker in (
"timed out",
"timeout",
"temporarily unavailable",
"connection reset",
"connection aborted",
"remote end closed connection",
"ssl",
)
)
def _is_transient_artifact_error(exc: Exception) -> bool:
message = str(exc).lower()
if message.startswith("http 404") and ("not available" in message or "not found" in message):
return True
if message.startswith("http 5") or message.startswith("http 408") or message.startswith("http 429"):
return True
return any(
marker in message
for marker in (
"timed out",
"timeout",
"temporarily unavailable",
"connection reset",
"connection aborted",
"remote end closed connection",
"ssl",
)
)
def _filename_from_content_disposition(value: str | None) -> str | None:
if not value:
return None
message = Message()
message["content-disposition"] = value
filename = message.get_filename()
return Path(filename).name if filename else None
def _download_artifact(
base_url: str,
token: str | None,
session_id: str,
artifact_name: str,
endpoint: str,
output_path: Path,
required: bool,
timeout: int,
*,
allow_response_usd_suffix: bool = False,
wait_timeout: float = 0.0,
poll_interval: float = 2.0,
) -> dict[str, Any]:
url = urljoin(f"{base_url.rstrip('/')}/", f"artifacts/{session_id}/{endpoint}")
deadline = time.monotonic() + max(0.0, wait_timeout)
attempts = 0
while True:
attempts += 1
try:
_, headers, body = _http_request("GET", url, token=token, timeout=timeout)
filename = _filename_from_content_disposition(
headers.get("Content-Disposition") or headers.get("content-disposition")
)
if allow_response_usd_suffix and filename:
suffix = Path(filename).suffix.lower()
if suffix in USD_EXTENSIONS:
output_path = output_path.with_suffix(suffix)
output_path.parent.mkdir(parents=True, exist_ok=True)
output_path.write_bytes(body)
return {
"name": artifact_name,
"url": url,
"path": str(output_path),
"required": required,
"downloaded": True,
"content_type": headers.get("Content-Type") or headers.get("content-type"),
"error": None,
"attempts": attempts,
"retry_count": attempts - 1,
}
except Exception as exc:
should_retry = (
required
and wait_timeout > 0
and time.monotonic() < deadline
and _is_transient_artifact_error(exc)
)
if should_retry:
time.sleep(max(0.25, poll_interval))
continue
return {
"name": artifact_name,
"url": url,
"path": str(output_path),
"required": required,
"downloaded": False,
"content_type": None,
"error": str(exc),
"attempts": attempts,
"retry_count": attempts - 1,
}
def _required_output_path(agent_key: str, spec: dict[str, Any], asset_path: Path, output_directory: Path) -> Path:
if agent_key == "physics" and asset_path.suffix.lower() in USD_EXTENSIONS:
return output_directory / f"{asset_path.stem}_physics{asset_path.suffix.lower()}"
return output_directory / f"{asset_path.stem}{spec['output_suffix']}"
def _service_fields(args: argparse.Namespace, agent_key: str) -> dict[str, str]:
fields: dict[str, str] = {}
if agent_key == "material":
email = args.email or os.getenv("USER_EMAIL")
if email:
fields["user_email"] = email
if args.prompt:
fields["user_prompt"] = args.prompt
fields["optimize_usd"] = "true" if args.optimize_usd else "false"
if not args.optimize_usd:
fields["skip_instances"] = "true" if args.skip_instances else "false"
elif args.skip_instances:
fields["skip_instances"] = "true"
if args.skip_prototypes:
fields["skip_prototypes"] = "true"
if args.skip_existing_materials:
fields["skip_existing_materials"] = "true"
if args.layer_only:
fields["layer_only"] = "true"
elif agent_key == "physics":
if args.prompt:
fields["user_prompt"] = args.prompt
if args.render_backend:
fields["render_backend"] = args.render_backend
fields["optimize_usd"] = "true" if args.optimize_usd else "false"
fields["enable_deinstance"] = "true" if args.enable_deinstance else "false"
fields["enable_split"] = "true" if args.enable_split else "false"
elif agent_key == "texture":
if args.prompt:
fields["user_prompt"] = args.prompt
if args.material_textures:
fields["material_textures_json"] = args.material_textures
return fields
def _inspect_usd_topology(asset_path: Path) -> dict[str, Any]:
result: dict[str, Any] = {
"inspected": False,
"reason": None,
"default_prim_path": None,
"mesh_count": 0,
"geom_subset_count": 0,
"mesh_with_geom_subset_count": 0,
"instance_count": 0,
"instance_proxy_count": 0,
"prototype_count": 0,
"has_composed_component_topology": False,
"component_topology_reasons": [],
}
try:
from pxr import Usd, UsdGeom
except Exception as exc:
external = _inspect_usd_topology_external(asset_path)
if external.get("inspected"):
external["inspection_runtime"] = "uv-python-3.12"
return external
result["reason"] = (
f"OpenUSD Python APIs are unavailable: {exc}. "
+ str(external.get("reason") or "No alternate OpenUSD Python runtime inspected the stage.")
)
return result
try:
stage = Usd.Stage.Open(str(asset_path))
except Exception as exc:
result["reason"] = f"Could not open USD stage: {exc}"
return result
if stage is None:
result["reason"] = "Could not open USD stage"
return result
default_prim = stage.GetDefaultPrim()
if not default_prim:
result["reason"] = "Stage has no default prim"
return result
result["inspected"] = True
result["default_prim_path"] = str(default_prim.GetPath())
try:
result["prototype_count"] = len(stage.GetPrototypes())
except Exception:
result["prototype_count"] = 0
mesh_paths_with_subsets: set[str] = set()
for prim in Usd.PrimRange(default_prim):
if not prim.IsActive():
continue
if prim.IsA(UsdGeom.Mesh):
result["mesh_count"] += 1
if prim.IsInstance():
result["instance_count"] += 1
if prim.IsInstanceProxy():
result["instance_proxy_count"] += 1
is_geom_subset = prim.GetTypeName() == "GeomSubset"
try:
is_geom_subset = is_geom_subset or bool(UsdGeom.Subset(prim))
except Exception:
pass
if is_geom_subset:
result["geom_subset_count"] += 1
parent = prim.GetParent()
if parent and parent.IsA(UsdGeom.Mesh):
mesh_paths_with_subsets.add(str(parent.GetPath()))
result["mesh_with_geom_subset_count"] = len(mesh_paths_with_subsets)
if result["geom_subset_count"]:
result["component_topology_reasons"].append("geom_subsets")
if result["instance_count"] or result["instance_proxy_count"] or result["prototype_count"]:
result["component_topology_reasons"].append("instances_or_prototypes")
result["has_composed_component_topology"] = bool(result["component_topology_reasons"])
return result
def _apply_physics_auto_optimizer(args: argparse.Namespace, topology: dict[str, Any]) -> dict[str, Any]:
auto_enabled = bool(args.auto_optimize_composed_usd and topology.get("has_composed_component_topology"))
if auto_enabled:
args.optimize_usd = True
args.enable_deinstance = True
args.enable_split = True
return {
"auto_optimize_composed_usd": bool(args.auto_optimize_composed_usd),
"auto_enabled": auto_enabled,
"auto_reasons": list(topology.get("component_topology_reasons") or []),
"optimize_usd": bool(args.optimize_usd),
"enable_deinstance": bool(args.enable_deinstance),
"enable_split": bool(args.enable_split),
}
def _apply_material_auto_optimizer(args: argparse.Namespace, topology: dict[str, Any]) -> dict[str, Any]:
requested_optimize_usd = args.optimize_usd
optimize_usd = True if requested_optimize_usd is None else bool(requested_optimize_usd)
auto_reasons: list[str] = []
instance_only_geometry = bool(
topology.get("inspected")
and topology.get("mesh_count") == 0
and (
topology.get("instance_count")
or topology.get("instance_proxy_count")
or topology.get("prototype_count")
)
)
auto_disabled_optimizer = bool(
requested_optimize_usd is None
and instance_only_geometry
and not args.skip_instances
)
if auto_disabled_optimizer:
optimize_usd = False
auto_reasons.append("instance_only_geometry")
args.optimize_usd = optimize_usd
return {
"requested_optimize_usd": requested_optimize_usd,
"default_optimize_usd": requested_optimize_usd is None,
"auto_disabled_optimizer": auto_disabled_optimizer,
"auto_reasons": auto_reasons,
"optimize_usd": bool(args.optimize_usd),
"skip_instances": bool(args.skip_instances),
"skip_prototypes": bool(args.skip_prototypes),
"skip_existing_materials": bool(args.skip_existing_materials),
}
def _is_crate_usd(path: Path) -> bool:
try:
return path.read_bytes()[:8] == b"PXR-USDC"
except OSError:
return False
def _convert_physics_output_to_usd(source_path: Path, output_path: Path) -> tuple[bool, str, Path]:
if _is_crate_usd(source_path) and source_path.suffix.lower() == ".usd":
return True, f"Physics output is already crate-backed USD: {source_path}", source_path
try:
from pxr import Usd
except Exception as exc:
return False, f"OpenUSD Python APIs are unavailable: {exc}", output_path
stage = Usd.Stage.Open(str(source_path))
if stage is None:
return False, f"Could not open physics output stage for crate conversion: {source_path}", output_path
output_path.parent.mkdir(parents=True, exist_ok=True)
if not stage.GetRootLayer().Export(str(output_path)):
return False, f"OpenUSD failed to export crate USD: {output_path}", output_path
if not output_path.exists() or output_path.stat().st_size == 0:
return False, f"OpenUSD export did not produce a non-empty file: {output_path}", output_path
return True, f"Converted physics output to {output_path}", output_path
def _walk_text(value: Any) -> list[str]:
if value is None:
return []
if isinstance(value, dict):
text: list[str] = []
for key, item in value.items():
text.append(str(key))
text.extend(_walk_text(item))
return text
if isinstance(value, list | tuple | set):
text = []
for item in value:
text.extend(_walk_text(item))
return text
return [str(value)]
def _report_text(report: dict[str, Any]) -> str:
fields = [
report.get("errors"),
report.get("warnings"),
report.get("checks"),
report.get("service_status"),
report.get("service_results"),
report.get("usd_topology"),
report.get("material_optimizer"),
]
return "\n".join(part for field in fields for part in _walk_text(field)).lower()
def _is_material_zero_image_failure(report: dict[str, Any]) -> bool:
text = _report_text(report)
return MATERIAL_ZERO_IMAGE_MARKERS[0] in text or (MATERIAL_ZERO_IMAGE_MARKERS[1] in text and "0 images" in text)
def _attempt_summary(report: dict[str, Any], label: str) -> dict[str, Any]:
return {
"label": label,
"passed": bool(report.get("passed")),
"status": report.get("status"),
"session_id": report.get("session_id"),
"output_usd_path": report.get("output_usd_path"),
"upload_asset_path": report.get("upload_asset_path"),
"upload_packaging": report.get("upload_packaging"),
"material_upload_info": report.get("material_upload_info"),
"material_output_cleanup": report.get("material_output_cleanup"),
"material_optimizer": report.get("material_optimizer"),
"physics_upload_info": report.get("physics_upload_info"),
"physics_optimizer": report.get("physics_optimizer"),
"service_status": report.get("service_status"),
"service_results": report.get("service_results"),
"errors": list(report.get("errors") or []),
"warnings": list(report.get("warnings") or []),
}
def _maybe_retry_material_without_optimizer(report: dict[str, Any], args: argparse.Namespace) -> dict[str, Any] | None:
if report.get("skill") != "material-agent-client":
return None
if getattr(args, "_material_zero_image_retry_attempt", False):
return None
if args.optimize_usd is not True:
return None
if not _is_material_zero_image_failure(report):
return None
retry_args = argparse.Namespace(**vars(args))
retry_args.optimize_usd = False
retry_args.skip_instances = False
retry_args._material_zero_image_retry_attempt = True
retry_report = run(retry_args)
existing_attempts = retry_report.get("attempts") if isinstance(retry_report.get("attempts"), list) else []
retry_report["attempts"] = [
_attempt_summary(report, "initial_optimize_usd_true"),
*existing_attempts,
_attempt_summary(retry_report, "retry_optimize_usd_false"),
]
retry_report.setdefault("warnings", []).append(
"Retried Material Agent with optimize_usd=false and skip_instances=false after a zero-render optimized path failure."
)
if not retry_report.get("passed"):
retry_report.setdefault("errors", []).append(
"Material Agent zero-render retry with optimize_usd=false did not recover the run."
)
return retry_report
def _is_physics_optimizer_failure(report: dict[str, Any]) -> bool:
service_status = report.get("service_status")
if isinstance(service_status, dict):
current_step = service_status.get("current_step")
if isinstance(current_step, dict):
step_text = "\n".join(_walk_text(current_step)).lower()
if "optimize_usd" in step_text:
return True
completed_steps = service_status.get("completed_steps")
if isinstance(completed_steps, list) and not completed_steps and str(service_status.get("status", "")).lower() in TERMINAL_FAILURE:
text = _report_text(report)
if "content agents session status: failed" in text and "optimize_usd" in text:
return True
text = _report_text(report)
return "optimize_usd" in text and any(marker in text for marker in PHYSICS_OPTIMIZER_FAILURE_MARKERS[1:])
def _is_scene_optimizer_permission_failure(report: dict[str, Any]) -> bool:
text = _report_text(report)
return _is_physics_optimizer_failure(report) and all(marker in text for marker in SCENE_OPTIMIZER_PERMISSION_MARKERS)
def _should_attempt_physics_scene_optimizer_repair(report: dict[str, Any]) -> bool:
if _is_scene_optimizer_permission_failure(report):
return True
topology = report.get("usd_topology")
return bool(
_is_physics_optimizer_failure(report)
and isinstance(topology, dict)
and topology.get("has_composed_component_topology")
)
def _physics_scene_optimizer_container_candidates() -> list[str]:
candidates: list[str] = []
for name in ("CONTENT_AGENTS_PHYSICS_AGENT_CONTAINER", "PHYSICS_AGENT_CONTAINER"):
value = os.getenv(name)
if value:
candidates.append(value)
candidates.extend(PHYSICS_SCENE_OPTIMIZER_CONTAINER_CANDIDATES)
return list(dict.fromkeys(candidates))
def _repair_physics_scene_optimizer_permissions() -> dict[str, Any]:
docker = shutil.which("docker")
result: dict[str, Any] = {
"attempted": bool(docker),
"repaired": False,
"container": None,
"command": None,
"errors": [],
}
if not docker:
result["errors"].append("docker was not found on PATH")
return result
for container in _physics_scene_optimizer_container_candidates():
command = [
docker,
"exec",
"--user",
"root",
container,
"chmod",
"-R",
"a+rX",
"/app/.build-resources/scene_optimizer_core",
]
completed = subprocess.run(command, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=60, check=False)
if completed.returncode == 0:
result.update(
{
"attempted": True,
"repaired": True,
"container": container,
"command": ["docker", *command[1:]],
}
)
return result
detail = (completed.stderr or completed.stdout or "").strip()
result["errors"].append(f"{container}: exit {completed.returncode}: {detail[:300]}")
return result
def _maybe_repair_and_retry_physics_scene_optimizer(report: dict[str, Any], args: argparse.Namespace) -> dict[str, Any] | None:
if report.get("skill") != "physics-agent-client":
return None
if getattr(args, "_physics_so_permission_repair_attempt", False):
return None
if args.optimize_usd is not True:
return None
if not _should_attempt_physics_scene_optimizer_repair(report):
return None
repair = _repair_physics_scene_optimizer_permissions()
report["physics_scene_optimizer_permission_repair"] = repair
if not repair.get("repaired"):
report.setdefault("warnings", []).append(
"Could not repair local Physics Agent Scene Optimizer permissions; keeping the optimized failure as the primary result."
)
return None
retry_args = argparse.Namespace(**vars(args))
retry_args._physics_so_permission_repair_attempt = True
retry_report = run(retry_args)
existing_attempts = retry_report.get("attempts") if isinstance(retry_report.get("attempts"), list) else []
retry_report["attempts"] = [
_attempt_summary(report, "initial_physics_optimize_usd_true"),
*existing_attempts,
_attempt_summary(retry_report, "retry_physics_optimize_usd_true_after_so_permission_repair"),
]
retry_report["physics_scene_optimizer_permission_repair"] = repair
retry_report.setdefault("warnings", []).append(
"Repaired local Physics Agent Scene Optimizer permissions and retried with optimize_usd still enabled."
)
if not retry_report.get("passed"):
retry_report.setdefault("errors", []).append(
"Physics Agent retry after Scene Optimizer permission repair did not recover the run."
)
return retry_report
def _maybe_retry_physics_without_optimizer(report: dict[str, Any], args: argparse.Namespace) -> dict[str, Any] | None:
if report.get("skill") != "physics-agent-client":
return None
if getattr(args, "_physics_optimizer_retry_attempt", False):
return None
if args.optimize_usd is not True:
return None
if not _is_physics_optimizer_failure(report):
return None
topology = report.get("usd_topology")
if isinstance(topology, dict) and topology.get("has_composed_component_topology"):
report.setdefault("warnings", []).append(
"Skipped optimize_usd=false Physics Agent retry because composed USD topology still needs optimizer deinstance/split before apply_physics."
)
return None
retry_args = argparse.Namespace(**vars(args))
retry_args.optimize_usd = False
retry_args.enable_deinstance = False
retry_args.enable_split = False
retry_args.auto_optimize_composed_usd = False
retry_args._physics_optimizer_retry_attempt = True
retry_report = run(retry_args)
existing_attempts = retry_report.get("attempts") if isinstance(retry_report.get("attempts"), list) else []
retry_report["attempts"] = [
_attempt_summary(report, "initial_physics_optimize_usd_true"),
*existing_attempts,
_attempt_summary(retry_report, "retry_physics_optimize_usd_false"),
]
retry_report.setdefault("warnings", []).append(
"Retried Physics Agent with optimize_usd=false, enable_deinstance=false, and enable_split=false after the optimized path failed."
)
if not retry_report.get("passed"):
retry_report.setdefault("errors", []).append(
"Physics Agent retry with optimize_usd=false did not recover the run."
)
return retry_report
def _report_markdown(report: dict[str, Any]) -> str:
lines = [
f"# {report['skill']} Report",
"",
f"- Asset: `{report['asset_path']}`",
f"- Agent: `{report['agent']}`",
f"- Passed: `{report['passed']}`",
f"- Status: `{report['status']}`",
f"- Session: `{report.get('session_id')}`",
f"- Output USD: `{report.get('output_usd_path')}`",
f"- Next step: `{report['next_step']}`",
"",
"## Checks",
"",
]
for check in report["checks"]:
state = "PASS" if check["passed"] else "FAIL"
lines.append(f"- `{state}` `{check['name']}`: {check['message']}")
lines.extend(["", "## Artifacts", ""])
for artifact in report.get("artifacts", []):
state = "downloaded" if artifact["downloaded"] else "missing"
lines.append(f"- `{artifact['name']}`: {state} `{artifact.get('path')}`")
if not report.get("artifacts"):
lines.append("- None")
if report.get("errors"):
lines.extend(["", "## Errors", ""])
lines.extend(f"- {error}" for error in report["errors"])
if report.get("warnings"):
lines.extend(["", "## Warnings", ""])
lines.extend(f"- {warning}" for warning in report["warnings"])
cleanup = report.get("material_output_cleanup")
if isinstance(cleanup, dict):
lines.extend(["", "## Material Output Cleanup", ""])
if cleanup.get("skipped_reason"):
lines.append(f"- Skipped: {cleanup['skipped_reason']}")
elif cleanup.get("warning"):
lines.append(f"- Warning: {cleanup['warning']}")
else:
lines.append(f"- Removed stale material count: `{cleanup.get('removed_material_count', 0)}`")
lines.append(f"- Repaired bound shader count: `{cleanup.get('repaired_bound_shader_count', 0)}`")
for material in cleanup.get("removed_materials") or []:
lines.append(f"- Removed `{material}`")
lines.append("")
return "\n".join(lines)
def _emit_report(report: dict[str, Any], report_path: Path | None, markdown_report_path: Path | None) -> None:
emit_json_report(report, report_path, markdown_report_path, _report_markdown(report))
def _base_report(
args: argparse.Namespace,
spec: dict[str, Any],
base_url: str | None,
command: list[str],
output_usd_path: Path,
) -> dict[str, Any]:
return {
"asset_path": str(args.asset_path.resolve()),
"skill": _skill_name(),
"agent": spec["agent"],
"tool": "NVIDIA Omniverse Content Agents service API",
"passed": False,
"status": "FAIL",
"operation": "service_pipeline",
"base_url": base_url,
"session_id": None,
"output_directory": str(args.output_directory.resolve()),
"output_usd_path": str(output_usd_path),
"upload_asset_path": None,
"upload_dependency_count": 0,
"upload_info": None,
"material_upload_info": None,
"material_output_cleanup": None,
"physics_upload_info": None,
"upload_packaging": None,
"command": command,
"prompt": args.prompt,
"checks": [],
"artifacts": [],
"service_status": None,
"service_results": None,
"usd_topology": None,
"material_optimizer": None,
"physics_optimizer": None,
"attempts": [],
"warnings": [],
"errors": [],
"next_step": spec["next_step"],
}
def _command(
args: argparse.Namespace,
*,
agent_key: str,
asset_path: Path,
output_directory: Path,
base_url: str | None,
token: str | None,
) -> list[str]:
command = ["python3", str(Path(__file__).resolve()), str(asset_path), str(output_directory), "--base-url", base_url or "<missing>"]
if token:
command.extend(["--token", "<redacted>"])
if args.prompt:
command.extend(["--prompt", args.prompt])
if agent_key == "material":
if args.optimize_usd:
command.append("--optimize-usd")
else:
command.append("--no-optimize-usd")
if args.skip_instances:
command.append("--skip-instances")
if args.skip_prototypes:
command.append("--skip-prototypes")
if args.skip_existing_materials:
command.append("--skip-existing-materials")
if args.layer_only:
command.append("--layer-only")
if not args.material_output_cleanup:
command.append("--no-material-output-cleanup")
elif agent_key == "physics":
if args.render_backend:
command.extend(["--render-backend", args.render_backend])
if args.optimize_usd:
command.append("--optimize-usd")
if args.enable_deinstance:
command.append("--enable-deinstance")
else:
command.append("--disable-deinstance")
if args.enable_split:
command.append("--enable-split")
if args.convert_output_to_usd:
command.append("--convert-output-to-usd")
if not args.auto_optimize_composed_usd:
command.append("--no-auto-optimize-composed-usd")
elif agent_key == "texture" and args.material_textures:
command.extend(["--material-textures", args.material_textures])
return command
def run(args: argparse.Namespace) -> dict[str, Any]:
spec = _spec()
agent_key = spec["agent_key"]
asset_path = args.asset_path.resolve()
output_directory = args.output_directory.resolve()
base_url, base_url_source = _resolve_base_url(args.base_url, spec)
token = args.token or _env_or_file_first(spec["token_env"])
output_usd_path = _required_output_path(agent_key, spec, asset_path, output_directory)
report = _base_report(args, spec, base_url, [], output_usd_path)
checks = report["checks"]
if preflight_required() and args.base_url is None:
preflight_check = preflight_status_check(_skill_name(), agent_key)
checks.append(preflight_check)
if not preflight_check["passed"]:
report["status"] = "BLOCKED"
report["errors"] = [preflight_check["message"]]
return report
checks.append(_check("asset_exists", asset_path.exists(), "Asset path exists" if asset_path.exists() else "Asset path does not exist"))
if not asset_path.exists():
report["errors"] = [check["message"] for check in checks if not check["passed"]]
return report
supported = asset_path.suffix.lower() in USD_EXTENSIONS
checks.append(
_check(
"supported_usd_extension",
supported,
"Asset uses a supported USD extension" if supported else "Asset must be .usd, .usda, .usdc, or .usdz",
)
)
if not supported:
report["errors"] = [check["message"] for check in checks if not check["passed"]]
return report
if agent_key == "material":
topology = _inspect_usd_topology(asset_path)
report["usd_topology"] = topology
optimizer = _apply_material_auto_optimizer(args, topology)
report["material_optimizer"] = optimizer
if optimizer["auto_disabled_optimizer"]:
checks.append(
_check(
"material_instance_traversal_enabled",
True,
"Disabled Material Agent optimize_usd and kept skip_instances=false for instance/prototype-only USD topology",
"info",
)
)
elif topology.get("inspected"):
checks.append(
_check(
"material_optimizer_default_enabled",
True,
"Using Material Agent optimize_usd path after USD topology inspection",
"info",
)
)
else:
checks.append(
_check(
"material_optimizer_inspection_skipped",
True,
str(topology.get("reason") or "USD topology inspection was skipped; using Material Agent optimize_usd default"),
"info",
)
)
elif agent_key == "physics":
topology = _inspect_usd_topology(asset_path)
report["usd_topology"] = topology
optimizer = _apply_physics_auto_optimizer(args, topology)
report["physics_optimizer"] = optimizer
if optimizer["auto_enabled"]:
checks.append(
_check(
"physics_auto_optimizer_enabled",
True,
"Enabled optimize_usd, deinstance, and split for composed USD topology: "
+ ", ".join(optimizer["auto_reasons"]),
"info",
)
)
elif topology.get("inspected"):
checks.append(
_check(
"physics_auto_optimizer_not_needed",
True,
"No GeomSubset, instance, or prototype topology detected for automatic Physics Agent optimization",
"info",
)
)
else:
checks.append(
_check(
"physics_auto_optimizer_inspection_skipped",
True,
str(topology.get("reason") or "USD topology inspection was skipped"),
"info",
)
)
report["command"] = _command(
args,
agent_key=agent_key,
asset_path=asset_path,
output_directory=output_directory,
base_url=base_url,
token=token,
)
checks.append(
_check(
"base_url_available",
bool(base_url),
f"Using Content Agents service {base_url}"
if base_url
else f"Set --base-url or one of {', '.join(spec['default_env'])}",
)
)
if base_url_source:
checks.append(_check(f"base_url_from_{base_url_source}", True, f"Resolved base URL from {base_url_source}", "info"))
if not base_url:
report["status"] = "BLOCKED"
report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
return report
if agent_key == "texture" and args.material_textures:
try:
json.loads(args.material_textures)
except json.JSONDecodeError as exc:
checks.append(_check("material_textures_json_valid", False, f"Invalid --material-textures JSON: {exc}"))
report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
return report
checks.append(_check("material_textures_json_valid", True, "Material texture config JSON is valid", "info"))
output_directory.mkdir(parents=True, exist_ok=True)
material_upload_info: dict[str, Any] | None = None
if agent_key == "material":
asset_path, material_upload_info = _stage_material_upload_asset(asset_path)
report["material_upload_info"] = material_upload_info
if material_upload_info.get("warning"):
checks.append(_check("material_upload_prep_skipped", True, material_upload_info["warning"], "info"))
elif material_upload_info.get("staged"):
if material_upload_info.get("stripped_mdl_source_assets"):
checks.append(
_check(
"material_upload_mdl_source_assets_stripped",
True,
"Staged Material Agent upload without "
f"{material_upload_info['stripped_mdl_source_assets']} MDL sourceAsset references",
"info",
)
)
if material_upload_info.get("cleared_unresolved_service_asset_paths"):
checks.append(
_check(
"material_upload_unresolved_service_asset_paths_cleared",
True,
"Staged Material Agent upload without "
f"{material_upload_info['cleared_unresolved_service_asset_paths']} service-internal asset paths",
"info",
)
)
physics_upload_info: dict[str, Any] | None = None
if agent_key == "physics":
asset_path, physics_upload_info = _stage_physics_upload_asset(asset_path)
report["physics_upload_info"] = physics_upload_info
if physics_upload_info.get("warning"):
checks.append(_check("physics_upload_prep_skipped", True, physics_upload_info["warning"], "info"))
elif physics_upload_info.get("staged"):
if physics_upload_info.get("stripped_mdl_source_assets"):
checks.append(
_check(
"physics_upload_mdl_source_assets_stripped",
True,
"Staged Physics Agent upload without "
f"{physics_upload_info['stripped_mdl_source_assets']} MDL sourceAsset references",
"info",
)
)
if physics_upload_info.get("cleared_unresolved_service_asset_paths"):
checks.append(
_check(
"physics_upload_unresolved_service_asset_paths_cleared",
True,
"Staged Physics Agent upload without "
f"{physics_upload_info['cleared_unresolved_service_asset_paths']} service-internal asset paths",
"info",
)
)
try:
upload_asset_path, upload_info = _prepare_upload_asset(asset_path, output_directory)
except Exception as exc:
checks.append(_check("upload_asset_prepared", False, str(exc)))
report["upload_asset_path"] = str(asset_path)
report["upload_packaging"] = "failed"
report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
return report
report["upload_asset_path"] = str(upload_asset_path)
report["upload_packaging"] = upload_info["packaging"]
report["upload_dependency_count"] = upload_info["dependency_count"]
report["upload_info"] = upload_info
if upload_info["inspection_error"]:
checks.append(_check("upload_dependency_inspection_skipped", True, upload_info["inspection_error"], "info"))
elif upload_info["packaging"] == "usdz":
checks.append(
_check(
"upload_asset_packaged",
True,
f"Packaged {upload_info['dependency_count']} USD dependencies into {upload_asset_path} for Content Agents upload",
"info",
)
)
elif upload_info["packaging"] == "already_usdz":
checks.append(_check("upload_asset_already_packaged", True, "Input asset is already a USDZ package", "info"))
else:
checks.append(_check("upload_asset_single_file", True, "No external USD dependencies detected for upload", "info"))
session_id: str | None = None
try:
session_id = _post_pipeline(upload_asset_path, base_url, token, _service_fields(args, agent_key), args.request_timeout)
report["session_id"] = session_id
checks.append(_check("session_started", True, f"Started Content Agents session {session_id}", "info"))
service_status = _wait_for_status(
base_url,
token,
session_id,
timeout=args.timeout,
poll_interval=args.poll_interval,
request_timeout=args.request_timeout,
)
report["service_status"] = service_status
poll_warnings = service_status.get("poll_warnings")
if isinstance(poll_warnings, list):
for warning in poll_warnings:
report["warnings"].append(f"Recovered transient status poll error: {warning}")
state = str(service_status.get("status", "")).lower()
checks.append(_check("session_completed", state in TERMINAL_SUCCESS, f"Content Agents session status: {service_status.get('status')}"))
try:
report["service_results"] = _json_request(
"GET",
urljoin(f"{base_url.rstrip('/')}/", f"pipeline/{session_id}/results"),
token=token,
timeout=args.request_timeout,
)
except Exception as exc:
report["warnings"].append(f"Could not fetch service results: {exc}")
except Exception as exc:
checks.append(_check("service_pipeline_completed", False, str(exc)))
report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
retry_report = _maybe_retry_material_without_optimizer(report, args)
if retry_report is not None:
return retry_report
retry_report = _maybe_repair_and_retry_physics_scene_optimizer(report, args)
if retry_report is not None:
return retry_report
retry_report = _maybe_retry_physics_without_optimizer(report, args)
if retry_report is not None:
return retry_report
return report
if any(check["severity"] == "error" and not check["passed"] for check in checks):
report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
retry_report = _maybe_retry_material_without_optimizer(report, args)
if retry_report is not None:
return retry_report
retry_report = _maybe_repair_and_retry_physics_scene_optimizer(report, args)
if retry_report is not None:
return retry_report
retry_report = _maybe_retry_physics_without_optimizer(report, args)
if retry_report is not None:
return retry_report
return report
artifacts = report["artifacts"]
required_artifact = _download_artifact(
base_url,
token,
session_id,
spec["output_label"],
spec["output_endpoint"],
output_usd_path,
True,
args.request_timeout * 2,
allow_response_usd_suffix=agent_key == "physics",
wait_timeout=args.artifact_timeout,
poll_interval=args.poll_interval,
)
artifacts.append(required_artifact)
if required_artifact.get("retry_count"):
report["warnings"].append(
f"Required artifact {spec['output_label']} became available after "
f"{required_artifact['retry_count']} retry attempt(s)."
)
if required_artifact["downloaded"] and required_artifact["path"]:
output_usd_path = Path(required_artifact["path"])
report["output_usd_path"] = str(output_usd_path)
if agent_key == "material" and args.material_output_cleanup and required_artifact["downloaded"] and output_usd_path:
cleanup = cleanup_material_output(output_usd_path)
report["material_output_cleanup"] = cleanup
if cleanup.get("warning"):
checks.append(_check("material_output_cleanup_warning", True, cleanup["warning"], "info"))
report["warnings"].append(str(cleanup["warning"]))
elif cleanup.get("skipped_reason"):
checks.append(_check("material_output_cleanup_skipped", True, str(cleanup["skipped_reason"]), "info"))
elif cleanup.get("removed_material_count") or cleanup.get("repaired_bound_shader_count"):
checks.append(
_check(
"material_output_broken_source_assets_cleaned",
True,
"Removed "
f"{cleanup.get('removed_material_count', 0)} unbound material subtree(s) and repaired "
f"{cleanup.get('repaired_bound_shader_count', 0)} bound shader(s) with broken sourceAsset references",
"info",
)
)
else:
checks.append(
_check(
"material_output_cleanup_noop",
True,
"No unbound material subtrees with broken sourceAsset shader references were found",
"info",
)
)
if cleanup.get("kept_bound_invalid_shader_count"):
report["warnings"].append(
"Material output cleanup found broken sourceAsset shader references on bound materials and left them unchanged."
)
elif agent_key == "material" and not args.material_output_cleanup:
report["material_output_cleanup"] = {
"attempted": False,
"path": str(output_usd_path),
"skipped_reason": "disabled by --no-material-output-cleanup",
}
for artifact_name, endpoint, suffix, required in spec["optional_artifacts"]:
artifact = _download_artifact(
base_url,
token,
session_id,
artifact_name,
endpoint,
output_directory / f"{asset_path.stem}_{agent_key}_{artifact_name}{suffix}",
required,
args.request_timeout * 2,
)
artifacts.append(artifact)
if not artifact["required"] and not artifact["downloaded"]:
report["warnings"].append(f"Optional artifact {artifact_name} was not downloaded: {artifact['error']}")
required_missing = [artifact for artifact in artifacts if artifact["required"] and not artifact["downloaded"]]
checks.append(
_check(
"required_artifacts_downloaded",
not required_missing,
"Downloaded required output artifact" if not required_missing else "; ".join(artifact["error"] or artifact["name"] for artifact in required_missing),
)
)
if agent_key == "physics" and args.convert_output_to_usd and not required_missing:
converted, message, converted_path = _convert_physics_output_to_usd(output_usd_path, output_usd_path.with_suffix(".usd"))
checks.append(_check("physics_output_converted_to_usd", converted, message))
if converted:
report["output_usd_path"] = str(converted_path)
artifacts.append(
{
"name": "physics_usd_crate",
"url": "local:usda-to-usd",
"path": str(converted_path),
"required": True,
"downloaded": True,
"content_type": "model/vnd.usd",
"error": None,
}
)
errors = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
report["errors"] = errors
report["passed"] = not errors
report["status"] = "PASS" if not errors else "FAIL"
if errors:
report["output_usd_path"] = None
return report
def _parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description="Portable Content Agents service wrapper.")
parser.add_argument("asset_path", type=Path)
parser.add_argument("output_directory", type=Path)
parser.add_argument("--base-url")
parser.add_argument(
"--token",
help=(
"Last-resort bearer token fallback. Prefer service-specific token "
"environment variables or *_FILE variables so secrets do not appear "
"in process arguments."
),
)
parser.add_argument("--prompt")
parser.add_argument("--timeout", type=int, default=1800)
parser.add_argument("--request-timeout", type=int, default=120)
parser.add_argument("--poll-interval", type=float, default=2.0)
parser.add_argument(
"--artifact-timeout",
type=float,
default=180.0,
help="Seconds to retry required artifact downloads after a terminal service status.",
)
parser.add_argument("--report", type=Path)
parser.add_argument("--markdown-report", type=Path)
parser.add_argument("--email")
optimize_usd = parser.add_mutually_exclusive_group()
optimize_usd.add_argument("--optimize-usd", dest="optimize_usd", action="store_true")
optimize_usd.add_argument("--no-optimize-usd", dest="optimize_usd", action="store_false")
parser.set_defaults(optimize_usd=None)
parser.add_argument("--skip-instances", action="store_true")
parser.add_argument("--skip-prototypes", action="store_true")
parser.add_argument("--skip-existing-materials", action="store_true")
parser.add_argument("--layer-only", action="store_true")
parser.add_argument(
"--no-material-output-cleanup",
dest="material_output_cleanup",
action="store_false",
help=(
"Disable the post-Material-Agent cleanup that removes unbound material subtrees "
"and repairs bound shaders with broken sourceAsset references from downloaded USD outputs."
),
)
parser.set_defaults(material_output_cleanup=True)
parser.add_argument("--render-backend", choices=("warp", "ovrtx", "remote"))
deinstance = parser.add_mutually_exclusive_group()
deinstance.add_argument("--enable-deinstance", dest="enable_deinstance", action="store_true")
deinstance.add_argument("--disable-deinstance", dest="enable_deinstance", action="store_false")
parser.set_defaults(enable_deinstance=True)
parser.add_argument("--enable-split", action="store_true")
auto_optimize = parser.add_mutually_exclusive_group()
auto_optimize.add_argument("--auto-optimize-composed-usd", dest="auto_optimize_composed_usd", action="store_true")
auto_optimize.add_argument("--no-auto-optimize-composed-usd", dest="auto_optimize_composed_usd", action="store_false")
parser.set_defaults(auto_optimize_composed_usd=True)
parser.add_argument("--convert-output-to-usd", action="store_true")
parser.add_argument("--material-textures")
return parser
def main(argv: list[str] | None = None) -> int:
args = _parser().parse_args(argv)
report = run(args)
_emit_report(report, args.report, args.markdown_report)
return 0 if report["passed"] else 1
if __name__ == "__main__":
raise SystemExit(main())
Requirements and compatibility
Written for: OpenAI Codex
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an API key, Needs Python
The author says: Orchestrator skill. Managed Content Agents deployment requires NVIDIA_API_KEY (build.nvidia.com), Docker + NVIDIA Container Toolkit + GPU, Python 3.12, and an upstream checkout of nvidia-omniverse/content-agents on branch main. Reused/provided endpoints may instead use explicit endpoint and usage-token environment variables. Linux/macOS only.
Security
What our scanner noticed· Medium risk
- Large base64-encoded blobs
- Instructions that use the network
- Downloads piped into a shell
- Scripts that your agent may run
This skill includes scripts that your agent may run. Read them before you use it.
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- Omniverse
- Publisher
- OpenAI (Official)
- Distributed by
- OpenAI
- Source
- openai/plugins · plugins/nvidia/skills/omniverse-cad-to-simready · commit d420d13
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (written by AutoGineer)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Omniverse or OpenAI.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download omniverse-cad-to-simready.zip