diff --git a/README.md b/README.md index 4ccd2029322d8726aa036cdb36baa8adc0c80c95..cb93f84f336f56a2cc8cc64f81fb2abb246362b1 100644 --- a/README.md +++ b/README.md @@ -2245,6 +2245,7 @@ configs: - split: utensils_scissors_a01 path: - viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/utensils_scissors_a01.parquet + - viewer/nv25-qwen38-27b-medium-pi-none-turn64-20261021/by_asset/utensils_scissors_a01.parquet - split: wheelassembly_wheel_rim_a01 path: - viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/wheelassembly_wheel_rim_a01.parquet diff --git a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/utensils_scissors_a01/reconstruction-1/harbor-trajectory-4.json b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/utensils_scissors_a01/reconstruction-1/harbor-trajectory-4.json new file mode 100644 index 0000000000000000000000000000000000000000..6af3c9a99af101bfd2eba903e3d3d784966eac17 --- /dev/null +++ b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/utensils_scissors_a01/reconstruction-1/harbor-trajectory-4.json @@ -0,0 +1,3356 @@ +{ + "schema_version": "ATIF-v1.7", + "session_id": "01a15f67-cebc-77e5-b151-10ab4a51fcd3", + "agent": { + "name": "pi", + "version": "0.85.1", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra" + }, + "steps": [ + { + "step_id": 1, + "timestamp": "2026-10-21T17:00:03.134Z", + "source": "user", + "message": [ + { + "type": "text", + "text": "\nReconstruct the supplied object as /output/asset.usd.\nNominal dimensions in canonical metres XYZ: [0.06751428544521332, 0.19996289908885956, 0.009697046800283715]\nRead /task/contract.md, /task/tool-docs.md and /task/scoring-policy.json. Identify the rigid parts, joints and their motion before authoring, then reconstruct appearance and mechanical structure. Use Python/PXR. Do not use Blender. Validate and inspect the NVIDIA findings before submitting.\n" + }, + { + "type": "image", + "source": { + "media_type": "image/png", + "path": "images/pi_image_1.png" + } + } + ], + "extra": { + "pi_event_id": "e9e39a9b", + "pi_parent_id": "08bfffec" + } + }, + { + "step_id": 2, + "timestamp": "2026-10-21T17:00:06.849Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "I'll start by reading the task files to understand the requirements.", + "reasoning_content": "Let me start by understanding the task. I need to reconstruct a pair of scissors as a USD asset. Let me read the contract, tool docs, and scoring policy first.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a1d980b687b04464", + "function_name": "read", + "arguments": { + "path": "/task/contract.md" + } + }, + { + "tool_call_id": "chatcmpl-tool-ba328055022cf3f5", + "function_name": "read", + "arguments": { + "path": "/task/tool-docs.md" + } + }, + { + "tool_call_id": "chatcmpl-tool-a5a68cb8a0df70e5", + "function_name": "read", + "arguments": { + "path": "/task/scoring-policy.json" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a1d980b687b04464", + "content": "# Reconstruction contract\n\nReconstruct the supplied object at /output/asset.usd using Python/PXR. Include\nits local USD and texture dependencies and place authoring scripts in /tmp.\nRead the supplied dimensions, image and scoring-policy.json.\n\nThe evaluation reports three independent scores:\n\n- Formal fidelity: NVIDIA SimReady-Foundation Robotics-Prop 4.0.0. Each of its\n 46 mandatory requirements counts once, with 95 * passed / 46 points and five\n further points when all pass. The 51 optional requirements are reported separately.\n- Visual fidelity: reference-scale shape, colours, textures and surface appearance.\n- Kinematic fidelity: the object's connected rigid parts, joint types, hinge or\n sliding axes, attachment locations and allowed ranges of motion.\n\nIdentify the object's parts and their mechanical relationships before authoring.\nKeep parts that move relative to one another as distinct rigid bodies and author\nthe corresponding UsdPhysics joints. Specify each joint's connected bodies,\nlocal positions, local orientations, axis and appropriate motion limits. For\nexample, folding eyewear needs hinged temples rather than one rigid mesh.\nUse fixed joints for genuine fixed attachments and keep genuinely rigid objects\nrigid. Base this structure on the supplied observations and the object's function.\n\nCheck that joint frames meet at each attachment, that movable parts can travel\nthrough their intended range and that the bodies and joints have the appropriate\nenabled and kinematic states. Preserve the observed shape and materials while\nconstructing this mechanical structure.\n\nUse validate_candidate to inspect the NVIDIA findings and repair the candidate.\nThe final submission freezes the authored files for evaluation.", + "extra": { + "tool_name": "read", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-ba328055022cf3f5", + "content": "# Authoring tools\n\nget_task_thumbnail returns the reference image. validate_candidate accepts {\"request_id\":\"check-1\"} and returns the current score, remaining validation calls and nvidia_validator_report.file_path. Search that JSON file with rg for a requirement ID or candidate prim path. get_validation_report reads a selected range of the same report.\n\nUse a new request ID after each repair. submit_asset accepts {\"request_id\":\"final\"} and stops authoring. The model has 64 inference requests, with provider-native output limits. Captures appear in the final report.", + "extra": { + "tool_name": "read", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-a5a68cb8a0df70e5", + "content": "{\n \"benchmark_output_token_cap\": null,\n \"composite_scores\": {\n \"formal\": \"SimReady Robotics-Prop mandatory requirements\",\n \"kinematic\": \"joint recovery and allowed relative motion correspondence\",\n \"visual\": \"geometric mean of shape and appearance material correspondence\"\n },\n \"limits\": {\n \"agent_seconds\": 231000,\n \"final_seconds\": 600,\n \"inference_requests\": 64,\n \"preview_requests\": 12,\n \"preview_seconds\": 90,\n \"validation_calls\": 5,\n \"validation_seconds\": 120,\n \"views_per_preview\": 4\n },\n \"model_call_budget\": 64,\n \"reward_reporting\": {\n \"formula\": \"95 * passed / fixed_applicable + 5_if_all_pass\",\n \"harbor_key\": \"simready_reward\",\n \"scale\": [\n 0,\n 100\n ]\n },\n \"semantic_labels\": {\n \"criterion\": \"mandatory NVIDIA SL IDs only\",\n \"required\": true,\n \"scoring\": true\n },\n \"validator_scoring\": {\n \"all_pass_bonus_percent\": 5,\n \"applicability\": \"fixed_profile_and_task_before_candidate\",\n \"applicable_requirement_ids\": [\n \"com.nvidia.simready.HI.010\",\n \"com.nvidia.simready.NP.002\",\n \"com.nvidia.simready.NP.003\",\n \"com.nvidia.simready.NP.004\",\n \"com.nvidia.simready.NP.005\",\n \"com.nvidia.simready.NP.007\",\n \"com.nvidia.simready.NP.008\",\n \"com.nvidia.simready.RB.001\",\n \"com.nvidia.simready.RB.007\",\n \"com.nvidia.simready.RB.010\",\n \"com.nvidia.simready.RB.COL.001\",\n \"com.nvidia.simready.RB.COL.002\",\n \"com.nvidia.simready.RB.COL.003\",\n \"com.nvidia.simready.SL.001\",\n \"com.nvidia.simready.SL.002\",\n \"com.nvidia.simready.SL.003\",\n \"com.nvidia.simready.SL.MAT.001\",\n \"com.nvidia.simready.SL.QCODE.001\",\n \"com.nvidia.simready.SL.TIME.001\",\n \"com.nvidia.simready.SR.002\",\n \"com.nvidia.simready.SR.004\",\n \"com.nvidia.simready.UN.006\",\n \"com.nvidia.simready.UN.007\",\n \"com.nvidia.simready.VG.008\",\n \"com.nvidia.simready.VG.025\",\n \"com.nvidia.simready.VG.MESH.001\",\n \"com.nvidia.simready.VM.MAT.001\",\n \"com.nvidia.simready.VM.PS.002\",\n \"com.nvidia.simready.VM.TEX.001\",\n \"com.nvidia.simready.VM.TEX.003\",\n \"com.nvidia.usd.AA.001\",\n \"com.nvidia.usd.AA.002\",\n \"com.nvidia.usd.HI.001\",\n \"com.nvidia.usd.HI.003\",\n \"com.nvidia.usd.HI.004\",\n \"com.nvidia.usd.RB.003\",\n \"com.nvidia.usd.RB.005\",\n \"com.nvidia.usd.RB.009\",\n \"com.nvidia.usd.RB.COL.004\",\n \"com.nvidia.usd.VG.002\",\n \"com.nvidia.usd.VG.014\",\n \"com.nvidia.usd.VG.027\",\n \"com.nvidia.usd.VG.028\",\n \"com.nvidia.usd.VG.029\",\n \"com.nvidia.usd.VM.BIND.001\",\n \"com.nvidia.usd.VM.PS.001\"\n ],\n \"base_credit_percent\": 95,\n \"early_stop_penalty_percent\": 0,\n \"optional_requirements\": \"report_only\",\n \"policy_id\": \"NVIDIA-Robotics-Prop-4.0.0-mandatory-95-plus-5-v1\",\n \"process_shaping_percent\": 0,\n \"profile\": {\n \"id\": \"Robotics-Prop\",\n \"version\": \"4.0.0\"\n },\n \"profile_inventory_sha256\": \"5a8dccd559cd3625025cedd08f7e2c174df32b8bbe0b17da9c94a588c86da13c\",\n \"report_only_mandatory_ids\": [],\n \"schema\": \"simready-validator-scoring-policy-v1\",\n \"scope\": \"all_mandatory_profile\",\n \"scoring_unit\": \"one_mandatory_requirement_ID\",\n \"stop_bonus_percent\": 0,\n \"unknown\": \"null_score_fixed_denominator\"\n }\n}", + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 3208, + "completion_tokens": 135, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 3343 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "02866b47", + "pi_parent_id": "e9e39a9b", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RtYyANzr92WTEvqgTj9sXJC3", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 3, + "timestamp": "2026-10-21T17:00:18.094Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me understand the task. I'm reconstructing a pair of scissors as a USD asset. Let me look at the available MCP tools first, and check the current state of the working directory.\n\nThe object is a pair of scissors:\n- Two rigid blades (silver/stainless steel) connected at a pivot/screw\n- Two handles (gold/brass loops)\n- The scissors have a hinge joint at the pivot screw\n\nThe nominal dimensions in meters: [0.06751428544521332, 0.19996289908885956, 0.009697046800283715]\nSo X = 0.0675 (width), Y = 0.2 (length ~20cm), Z = 0.0097 (thickness ~1cm)\n\nLet me check the working directory and the MCP tools available.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a04b649621ed5e02", + "function_name": "bash", + "arguments": { + "command": "cd /output && ls -la && echo \"---TASK---\" && ls -la /task/ && echo \"---PYTHON---\" && python3 -c \"import pxr; print(pxr.__file__)\" 2>&1 | head" + } + }, + { + "tool_call_id": "chatcmpl-tool-b0c7cd750a082228", + "function_name": "mcp", + "arguments": { + "action": "mcpScript" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a04b649621ed5e02", + "content": "total 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..\n---TASK---\ntotal 824\ndr-xr-xr-x 2 actor actor 160 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..\n-r--r--r-- 1 actor actor 1746 Oct 21 16:59 contract.md\n-r--r--r-- 1 actor actor 455 Oct 21 16:59 instruction.md\n-r--r--r-- 1 actor actor 3305 Oct 21 16:59 scoring-policy.json\n-r--r--r-- 1 actor actor 435 Oct 21 16:59 simready-bench-native-output-policy.ts\n-r--r--r-- 1 actor actor 820516 Oct 21 16:59 thumbnail.png\n-r--r--r-- 1 actor actor 572 Oct 21 16:59 tool-docs.md\n---PYTHON---\n/usr/local/lib/python3.12/dist-packages/pxr/__init__.py", + "extra": { + "tool_name": "bash", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-b0c7cd750a082228", + "content": "MCP: 1/1 servers, 4 tools\n\n\u2713 benchmark (4 tools, legacy notification path)\n\nmcp({ server: \"name\" }) to list tools, mcp({ search: \"...\" }) to search", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 5111, + "completion_tokens": 319, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 5430 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "943686e8", + "pi_parent_id": "a8f100cc", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RTeaZ6eU9cxOPYgtnVdr0i9t", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 4, + "timestamp": "2026-10-21T17:00:21.328Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me look at the instruction.md and the benchmark tools.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9f1fbc2a57841b64", + "function_name": "read", + "arguments": { + "path": "/task/instruction.md" + } + }, + { + "tool_call_id": "chatcmpl-tool-963d896083455287", + "function_name": "mcp", + "arguments": { + "search": "" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9f1fbc2a57841b64", + "content": "Reconstruct the supplied object as /output/asset.usd.\nNominal dimensions in canonical metres XYZ: [0.06751428544521332, 0.19996289908885956, 0.009697046800283715]\nRead /task/contract.md, /task/tool-docs.md and /task/scoring-policy.json. Identify the rigid parts, joints and their motion before authoring, then reconstruct appearance and mechanical structure. Use Python/PXR. Do not use Blender. Validate and inspect the NVIDIA findings before submitting.", + "extra": { + "tool_name": "read", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-963d896083455287", + "content": "Search query cannot be empty", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 5819, + "completion_tokens": 65, + "cached_tokens": 3136, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 5884 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "9ed295ff", + "pi_parent_id": "ba2cbba1", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rucz55upkRXE19ZaQzLXB7DG", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 5, + "timestamp": "2026-10-21T17:00:23.222Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me look at the benchmark tools available.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b1be390f792e95b6", + "function_name": "mcp", + "arguments": { + "server": "benchmark" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b1be390f792e95b6", + "content": "benchmark (4 tools):\n\n- benchmark_get_task_thumbnail - Read the supplied task thumbnail and public brief.\n- benchmark_validate_candidate - Validate a frozen candidate and return NVIDIA...\n- benchmark_submit_asset - End authoring and freeze the submitted asset....\n- benchmark_get_validation_report - Read a requested range of a prior NVIDIA report....", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 6056, + "completion_tokens": 38, + "cached_tokens": 4704, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 6094 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "5a04968c", + "pi_parent_id": "b888e77d", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RDGr0R5jivhB5fhEiHhFUt2r", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 6, + "timestamp": "2026-10-21T17:01:06.617Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me understand the object: a pair of scissors. \n\nRigid parts:\n1. Blade assembly 1 (one stainless steel blade + one gold handle) - actually in scissors, each \"scissor arm\" is one rigid piece: a blade and a handle connected. There are two such arms, connected by a central pivot screw (hinge).\n\nSo:\n- Rigid body A: blade A + handle A (one piece of metal, the gold loop connects to the silver blade via a shared arm)\n- Rigid body B: blade B + handle B\n- Joint: hinge (revolute) at the central pivot screw, axis perpendicular to the scissor plane (Z axis in local, since thickness is Z).\n\nActually, let me think about the geometry. The scissors lie flat. Dimensions: X = 0.0675 (width across handles/blades), Y = 0.2 (length along the scissors from tip to handle end), Z = 0.0097 (thickness).\n\nIn the image, the scissors are diagonal. The length is along the long axis (~20cm). The blades point to bottom-right, handles to top-left.\n\nFor a scissors, the two arms are hinged at the pivot. Each arm contains both a blade and a handle. When you squeeze handles together, blades open, and vice versa.\n\nSo I'll create two rigid bodies:\n- Arm1: blade + handle (rigid, they're one piece in real scissors - actually in real scissors the blade and handle are separate pieces fastened together, but mechanically for scissors it's typically modeled as one rigid arm per side). Actually a real scissor: there are 4 pieces - 2 blades, 2 handles, plus a screw. But typically each blade+handle pair on one side is one rigid body. Let me keep it simple: 2 rigid arms + a hinge at pivot.\n\nLet me think about the SimReady requirements to satisfy. This is the key for formal fidelity. Let me look at what's needed. The applicable requirement IDs include physics (RB), materials (VM.MAT), transforms (VG), etc.\n\nLet me get the validator report understanding. But first I need to create the asset, then validate. Let me build a solid USD with:\n\n- UsdPhysics.RigidBodyAPI on the two arms\n- A revolute joint (UsdPhysics.RevoluteJoint) connecting the two arms at the pivot\n- Collider (mesh collider) on each arm\n- Materials (stainless steel silver, gold)\n- Proper mass/volume properties\n- Mesh with normals, UVs, faces\n\nLet me think about the 46 mandatory requirements. Common SimReady Robotics-Prop requirements:\n- NP.002-008: prim naming / node properties\n- RB.001, RB.007, RB.010: rigid body\n- SL.001-003: skeletal? no, SL = something\n- SL.MAT.001: materials\n- UN.006, UN.007: units\n- VG.008, VG.025: geometry\n- VM.MAT.001, VM.PS.002, VM.TEX.001, VM.TEX.003: materials/PS/textures\n- AA.001, AA.002: assets\n- HI.001/003/004: hierarchy\n- RB.COL.004\n- VG.002/014/027/028/029\n- VM.BIND.001: material binding\n\nThis is a lot. I need to build a proper SimReady-compliant asset. The best approach is to look at a reference SimReady asset structure. But I don't have one. Let me build carefully based on known SimReady conventions.\n\nActually, the best strategy: build the asset, run validate_candidate, read the report, and iterate on the failures. That's the intended workflow (5 validation calls, 64 turns).\n\nLet me first build a good-quality asset with PXR. Let me plan the geometry.\n\nLet me think about the scissors geometry in canonical space. Let me set up:\n- The whole thing spans Y from -0.1 to +0.1 (length 0.2). \n- Handles at negative Y (top-left), blades at positive Y (bottom-right). Actually let me just say: pivot at origin. Blades extend to +Y, handles to -Y.\n- Width across X is ~0.0675 max.\n- Thickness Z ~0.0097.\n\nEach arm:\n- Blade: from pivot (Y=0) extending to tip (Y=+0.11), a thin tapered flat piece.\n- Handle: from pivot extending to Y=-0.09, with a loop (finger ring) at the end.\n\nThe two arms are mirror-ish but actually in scissors the two arms cross at the pivot. In the closed position (as shown in image, blades nearly closed), the two blades are parallel and overlapping, handles form two rings.\n\nFor simplicity and to keep each arm rigid, I'll model:\n- Arm 1: blade on top, handle ring on one side\n- Arm 2: blade below, handle ring on other side\n\nIn the closed scissors pose shown, the blades are overlapping (nearly closed). The handles form two distinct rings.\n\nLet me design the geometry programmatically. I'll build meshes with Python. I'll create:\n\nFor each arm, a combined mesh:\n- Blade: a tapered flat box (thin in Z)\n- Shank: connection\n- Handle ring: a torus-like loop\n\nActually modeling the handle ring as a solid torus and blade as a box, combined into one mesh per arm. That's doable with trimesh if available, or I build vertices/faces manually with PXR.\n\nLet me check if trimesh is available.\n\nLet me plan materials:\n- Gold/brass handles: metallic, gold color (0.85, 0.65, 0.3), roughness ~0.3\n- Stainless steel blades: metallic, silver color (0.9,0.9,0.92), roughness ~0.2\n\nI'll use USD PreviewSurface (UsdPreviewSurface) materials.\n\nLet me build. I'll write a Python script in /tmp and run it.\n\nLet me think about SimReady compliance details. Key requirements I recall for SimReady assets:\n- Meters unit: stage.SetTimePeriods? Actually units via `stage.GetRootLayer().customLayerData`? No. USD units: set in the stage. Actually SimReady requires meters - the USD \"metersPerUnit\" customLayerData. Set `rootLayer.customLayerData = {... \"metersPerUnit\": 1.0}`.\n- Physics: RigidBodyAPI with mass, massPropertiesMode, collider.\n- Collision: UsdPhysics.MeshCollisionAPI on the mesh.\n- Revolute joint with two bodies, positions, axis, limits.\n- Materials bound.\n- Unique material names.\n- Names must be valid (no spaces, start with letter).\n- No up-axis issues: +Y up? USD default is Y-up for USD, but SimReady... Actually SimReady uses... The canonical dims XYZ. Let me keep Y as the long axis? Hmm.\n\nActually the \"canonical metres XYZ\" gives dimensions. X=0.0675 (width), Y=0.2 (length), Z=0.0097 (thickness). In the image the length is along the diagonal. So the object's longest axis is Y. That's fine; I'll orient blades along Y.\n\nWait, but up-axis. SimReady typically +Y up. The thickness being Z=0.0097 suggests Z is the thin dimension (the flat plane is XY). So the scissors lie in the XY plane, thin in Z. That means Z is \"up\" in object space (the plane normal). If up-axis is Z... Hmm.\n\nActually for the flat scissors, the plane of the scissors is the large face. Thickness is the smallest = 0.0097 = Z. So the object's natural \"up\" (face normal) is Z. But SimReady up-axis... Robotics-Prop might use +Y or +Z. Let me not overthink; the dims are given as XYZ so I'll build in that canonical frame: X width, Y length, Z thickness.\n\nLet me proceed to build. Let me check trimesh.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-840fdd7cb1b2ec9f", + "function_name": "bash", + "arguments": { + "command": "python3 -c \"import trimesh; print('trimesh', trimesh.__version__)\" 2>&1; python3 -c \"import numpy; print('numpy', numpy.__version__)\" 2>&1; python3 -c \"from pxr import UsdPhysics, Sdf, Usd, UsdGeom, Gf; print('pxr ok')\" 2>&1" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-840fdd7cb1b2ec9f", + "content": "Traceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'trimesh'\nnumpy 2.2.6\npxr ok", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 6176, + "completion_tokens": 1964, + "cached_tokens": 5488, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 8140 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "bb44c16b", + "pi_parent_id": "ecbd1cdf", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R2dtdyFMqxLeXBfd9h2l519A", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 7, + "timestamp": "2026-10-21T17:04:31.233Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "I'll build the scissors with PXR. Let me start with a geometry helper and generate the mesh, then author the full USD with physics and materials.", + "reasoning_content": "No trimesh, but I have numpy and pxr. I'll build geometry manually. Let me write a comprehensive Python script that builds the scissors.\n\nLet me plan the geometry carefully.\n\nCanonical frame: X = width (across), Y = length (blades to handles), Z = thickness.\n\nTotal: X extent 0.0675, Y extent 0.2, Z extent 0.0097.\n\nPivot (screw) is somewhere along Y. Looking at image, the screw is roughly 40% from the blade tip. Blade tip to screw \u2248 60% of length, screw to handle end \u2248 40%.\n\nLet me set pivot at Y = 0.12 (so blades go from Y=0.12 up to... hmm). Let me define:\n- Total length 0.2, from Y = -0.1 (handle end) to Y = +0.1 (blade tip).\n- Pivot at Y = +0.02 (screw location).\n\nBlade: from pivot (Y=0.02) to tip (Y=0.1). Length ~0.08.\nHandle: from pivot (Y=0.02) to end (Y=-0.1), length ~0.12.\n\nWidth: handles splay out. Max width 0.0675 at the handle rings.\n\nLet me model each arm:\n\nArm geometry (I'll build in the arm's local coordinates then place). Actually simpler: build both arms in world/canonical frame with the scissors in closed position.\n\nLet me define Arm A (blade on top):\n- Blade: a thin flat tapered plate. From pivot (0, 0.02, +0.0024) to tip (0, 0.1, 0). Slightly splayed in X.\n- Handle: a loop (ring) at the far end.\n\nThis is getting complex. Let me simplify the shape to be recognizable: \n\nEach arm = blade (tapered box) + handle (a rounded ring/torus loop + connecting shank).\n\nLet me create the meshes with explicit vertex/face generation.\n\nBlade (tapered flat plate):\nA quadrilateral prism (box) that tapers. Vertices:\nNear pivot (Y=0.02): width in X = wb, half-thickness t.\nAt tip (Y=0.10): width = 0 (pointed) or small.\n\nActually a scissor blade is flat (thin in Z), wide in X near base, tapering to a point at tip. So:\n- Blade is thin in Z (thickness ~0.003 per blade, two blades stacked = 0.006, plus handles thicker).\n\nHmm the total thickness 0.0097. Two blades ~0.006, that fits.\n\nLet me define blade cross-section: width in X from ~0.02 at base tapering to ~0.002 at tip. Thickness in Z ~0.003.\n\nI'll model the blade as a set of quads.\n\nLet me just build a helper to make a \"flat tapered blade\" and a \"handle ring\".\n\nHandle ring: model as a torus in the XY plane? No - the finger ring is a loop you put fingers through. In the image, the rings are in the plane of the scissors (XY plane), oval shaped. The ring's \"hole\" faces up (+Z). So the ring is a torus lying flat in XY plane (major circle in XY plane, tube cross-section). Yes - like the gold loops, they're flat ovals lying in the plane.\n\nSo handle = an oval torus (major radius in XY, tube radius ~0.003) + a shank connecting the ring to the pivot.\n\nLet me build:\n\nFunction to make a torus (ring): major circle centered at (cx, cy), major radius R in XY plane, tube radius r, N segments around major, M around tube. This gives a ring with hole facing Z.\n\nFunction to make a shank: a tapered box connecting pivot to ring.\n\nFunction to make blade: tapered flat plate.\n\nThen merge blade+shank+ring into one mesh per arm.\n\nBut wait - the whole arm (blade + shank + handle ring) is ONE rigid body in my model. Good, that's mechanically correct: in real scissors each side is blade+handle as one rigid arm pivoting at the screw.\n\nActually, more precisely, real scissors: each side = one handle + one blade, and they ARE one rigid piece in most scissors? No! In scissors, the blade and the handle are DIFFERENT pieces that are both attached to the central pivot. Hmm. Actually in a typical scissor, one physical metal piece is a handle, and a separate piece is a blade, both screwed at pivot. So per side there are 2 pieces (handle piece and blade piece), and they pivot relative to EACH OTHER at the same screw? No, they don't pivot relative to each other - they're both clamped at the screw so they're rigid together on that side.\n\nFor a scissors, mechanically: 2 rigid arms, each arm = (blade + handle) on one side, pivoting about the central screw. The blade on one side and handle on the same side are rigidly connected. This is the standard model. I'll go with 2 rigid arms + 1 revolute joint.\n\nNow which handle goes with which blade? In the image, top handle ring connects to the blade that's... the scissor arms cross at pivot. So handle at top-left-bottom connects to blade at bottom-right. They're offset/crossed. For simplicity in closed pose, I'll place:\n- Arm A: handle ring at (-X side of handles), blade on +Z (top)\n- Arm B: handle ring at (+X side of handles), blade on -Z (bottom)\n\nAnd the crossing: handle on -X connects to blade that ends on +X side at tip. This crossing is what makes scissors work. Let me incorporate a slight crossing so handles are on opposite sides from blades.\n\nHmm, this is getting complicated for geometry. Let me keep it visually close to the image: handles are two rings side by side (one at -X, one at +X roughly, actually in image they overlap a bit). Blades are two overlapping flat blades.\n\nLet me look at the image again: The two gold rings are at top-left, side by side (one lower-left, one upper). The blades come to bottom-right overlapping. So handles splay in X: one ring center at X\u2248-0.015, other at X\u2248+0.01, and in Y they're offset. Actually the rings appear arranged along the handle axis.\n\nFor simplicity, I'll place the two handle rings side by side along X at the handle end, and the two blades overlapping along X (slightly offset in Z) at the blade end. That matches \"width across X = 0.0675\".\n\nLet me not overthink crossing. I'll do:\n- Arm A: ring center at X=-0.014, blade occupies Z=+0.0015 side\n- Arm B: ring center at X=+0.014, blade occupies Z=-0.0015 side\n\nBoth rings share similar Y position (handle end). Both blades overlap.\n\nThe rigid arm A connects its ring (at X=-0.014) to its blade. In a real scissor the ring and its blade are on the SAME side of pivot (collinear through pivot). So arm A: ring at (X=-0.014, Y=-0.07), and blade at (X=+... the blade extends to +Y at some X). For the arm to be a straight-ish rigid piece through the pivot, blade should be roughly collinear with ring through pivot. If ring is at X=-0.014 (handle side, -Y), then blade (at +Y) would be at X=+0.014 (opposite side) for a straight line through pivot at origin. That's the crossing! So:\n- Arm A: ring at X=-0.014 (handle), blade at X=+0.014 (tip). \n- Arm B: ring at X=+0.014 (handle), blade at X=-0.014 (tip).\n\nBut then in the image, the blades overlap in the middle and both are centered-ish. With crossing, blade A tip at +X, blade B tip at -X, they'd diverge. In the image the blades look parallel/overlapping, tips aligned. Hmm.\n\nReal scissors in closed position: the two blades are on top of each other (aligned), and the two handles are on top of each other (aligned), NOT crossed in X. The crossing happens in the sense that arm A's handle and arm A's blade: the handle is on one side but... \n\nUgh. Let me think physically. Take scissors closed. Look from above (the plane). You see two handle rings overlapping and two blades overlapping. The left handle ring belongs to the left blade. Left handle and left blade are collinear through the pivot? NO. In scissors, the left handle connects to the RIGHT blade. That's the scissor mechanism (the arms cross at the pivot). \n\nSo: left handle ring (X<0) \u2192 right blade (X>0 at tip). Right handle ring (X>0) \u2192 left blade (X<0 at tip). And in closed position the blades overlap (they cross over each other near pivot then the tips... no). \n\nActually in closed scissors the blades are stacked and both point the same direction, tips together. The handles are stacked and both point the other way. The \"crossing\" is that the physical arm goes handle(-X) \u2192 pivot \u2192 blade(+X continues to... ) no.\n\nI think I'm overanalyzing. Let me just make it look like the image: two overlapping rings at handle end, two overlapping blades at blade end, all roughly in the same X region (slight offset). I'll make each arm's ring and blade have a small X offset so there's a slight crossing, and set the closed pose. The visual just needs to look like scissors. Let me do a mild crossing: offset each arm by \u00b10.008 in X.\n\nLet me define arm A and arm B, each = blade + shank + ring, as rigid bodies. Pivot at origin.\n\nArm A (offset +d in X where d=0.006):\n- Blade: base at pivot (0.006, 0.02), tip at (0.006, 0.10), flat in Z at +0.0015\n- Shank: from pivot (0.006,0.02) to ring center (0.006-0.014... ) \n\nHmm if I offset blade to +0.006 and ring to -0.006, that gives crossing within the arm. Let me do:\nArm A:\n- Blade at X=+0.006 (base to tip)\n- Ring at X=-0.006\nArm B:\n- Blade at X=-0.006\n- Ring at X=+0.006\n\nThis gives a mild crossing (each arm is an S/cross shape), which is the real scissor geometry. The two blades overlap (\u00b10.006 offset), tips at \u00b10.006. Two rings overlap at \u00b10.006. Good, matches image (blades and rings slightly offset, overlapping).\n\nThe handle ring center Y: at -0.06. Ring major radius: 0.025 (oval). So ring spans Y from -0.035 to -0.085. Handle end at ~-0.085. Plus shank from ring to pivot.\n\nWait total handle end should be Y=-0.1. Ring center Y=-0.06, major radius 0.03 \u2192 spans Y -0.03 to -0.09. Then handle end ~-0.09. Close enough to -0.1. Let me tune to hit total length 0.2: blade tip Y=+0.10, handle end Y=-0.09 \u2192 total 0.19. Need 0.2. Let me make blade tip Y=0.105, handle end Y=-0.095. \n\nLet me just compute and then scale the whole thing at the end to match nominal dims exactly. That's the robust approach: build geometry in arbitrary units, compute bounding box, scale to [0.0675, 0.2, 0.0097]. \n\nYes! I'll build geometry, compute bbox, and apply a scale to match nominal dimensions. That guarantees dimension fidelity.\n\nLet me now write the script.\n\nGeometry helpers:\n\n1. flat_box(vertices) - a tapered flat blade.\n\nBlade: I'll model as a shape that's thin in Z, with a profile in XY that tapers from base width to tip point.\n\nLet me define blade in local arm coords (before X offset & Z placement):\nPoints along the blade length (Y from y0=0.02 base to y1=0.105 tip):\nAt base: half-width in X = 0.009 (so width 0.018)\nTaper linearly to tip: half-width \u2192 0.0005\nThickness in Z: 0.003 (one blade), centered at z.\n\nI'll create a quad strip. For a flat plate I need top and bottom faces (Z+ and Z-). Let me make it a thin box with 4 cross-sections? Simpler: create a \"flat blade\" as a closed polygon extruded in Z.\n\nCross-section profile in XY (a blade outline):\nbase corners: (-w0, y0), (w0, y0)\nthen taper to tip: (0, y1)\nSo it's a triangle-ish trapezoid: (-w0,y0),(w0,y0),(0,y1) \u2014 a triangle. To make it look like a scissor blade (slightly curved), a triangle is fine, maybe add a mid point.\n\nLet me make profile: \np0 = (-w0, y0)\np1 = (w0, y0)\np2 = (w1, (y0+y1)/2) # mid\np3 = (0, y1) # tip\np4 = (-w1, (y0+y1)/2)\nClose. That's a pentagon outline. Extrude in Z by thickness.\n\nExtrude: create top and bottom caps (pentagon) + side walls.\n\n2. Torus ring (handle):\nMajor ellipse in XY centered (cx, cy), semi-axes a (X) and b (Y). Tube radius r.\nStandard torus parameterization.\n\n3. Shank: a tapered box from pivot to ring. I'll make it a box connecting pivot area to the ring's near edge. Actually I can make the shank a simple box from (x, 0.0) to (ring center x, ring top). Let me make shank a flat tapered box in XY, thin in Z, from base (width ~0.012 at pivot) to the ring (width ~ tube). To keep it simple, I'll make a straight tapered plate from pivot to ring center, and let the ring merge on top.\n\nLet me combine: blade (Z top) + shank + ring into one mesh.\n\nLet me write code to generate vertex/face arrays and merge.\n\nI'll write a Mesh helper class that accumulates vertices and faces and can transform.\n\nLet me write it.\n\nFor faces, I'll use triangles or quads. USD SdfPolyMesh supports quads and triangles (facingRatio, polygonWeights). I'll use quads where possible but triangles are safe. Let me output triangles to be safe with face winding. Actually SimReady VG.MESH.001 might require... let me just use quads for clean topology. Actually let me use a mix; Sdf.M\u0ab6\u0a95elsesx... I'll use quads and triangles, both fine in a polygon mesh.\n\nLet me just build with quads for the extruded shapes and the torus.\n\nLet me write the full script now. I'll be careful.\n\nFor the extruded pentagon:\noutline points P[0..4] in XY.\nbottom face (z=zc-th/2): fan from P0: (0,1,2),(0,2,3),(0,3,4)\ntop face (z=zc+th/2): (5,7,6),(5,8,7),(5,9,8) [reversed winding for outward normal]\nActually let me define top vertices T_i = (Px, Py, ztop), bottom B_i = (Px,Py, zbot).\nSide wall i: quad (B_i, B_{i+1}, T_{i+1}, T_i) or reversed for outward. Let me just generate and not worry about exact outward normals; SimReady might check normals but I can compute them. Let me set correct winding: bottom face should face -Z, top face +Z, side faces outward.\n\nFor a convex polygon going CCW when viewed from +Z:\nTop face (viewed from +Z, CCW = outward +Z): (T0,T1,T2),(T0,T2,T3),(T0,T3,T4)\nBottom face (outward -Z, viewed from -Z CCW): (B0,B2,B1),(B0,B3,B2),(B0,B4,B3)\nSide walls outward: for edge from P_i to P_{i+1} (CCW), outward normal is to the right. Quad (B_i, T_i, T_{i+1}, B_{i+1})? Let me just do (B_i, B_{i+1}, T_{i+1}, T_i). Winding might be inconsistent but let me compute normals after via a fix, or set verticesWinding. \n\nHonestly, for robustness I'll build the mesh, then compute face normals and flip any inward-facing faces relative to centroid. That guarantees correct normals. Let me do that.\n\nActually simpler: I'll build using quads and then use a post-process: for each face, if normal points toward the object interior (dot(normal, facecenter - meshcenter) < 0), flip. This works for convex-ish solids. Good.\n\nLet me implement.\n\nLet me write the script now. I'll put geometry in a helper, generate two arms, plus the pivot screw (a small cylinder) as a separate small part or merged. The screw is the pivot - I'll model it as part of... it's a fastener. I can make it a small cylinder as a third rigid body or merge into one arm. To keep joint clean, I'll make the pivot screw a small static/decorative cylinder merged into arm A (or its own body). Actually the pivot screw holds the two arms; I'll make it a separate small rigid body with a fixed joint, or just merge into one arm. Let me merge a small cylinder into arm A at the pivot (decorative screw head visible on top). That's simplest and looks right (screw head visible on top blade).\n\nNow physics:\n- Two RigidBodyAPI: on ArmA and ArmB.\n- MeshCollisionAPI (collider) on each arm's mesh.\n- RevoluteJoint: body1=ArmA, body2=ArmB, at pivot (origin), axis = Z (perpendicular to scissor plane, since thickness is Z, the rotation axis is Z). Axis in joint local space.\n- Limits: scissors open/close a limited angle. ~ \u00b10.5 rad maybe. Let me set limits -0.7 to 0.7 rad. Actually scissors can open quite wide (~90\u00b0+). Let me do -1.2 to 1.2? The blades open to maybe 60\u00b0 each way. I'll set -1.0 to 1.0.\n- revoluteJoint lowerAngleLimit / upperAngleLimit.\n\nFor the joint to have a \"ground\"/reference, one body should be the moving, other fixed? In a scissors both arms move relative to a fixed pivot. But with only 2 bodies and 1 revolute joint, one becomes effectively the reference. The pivot screw should be attached to a fixed frame. Hmm. In SimReady robotics props, a common pattern: have a base body (static, kinematic or with fixed position) and the moving body.\n\nFor scissors, the natural model: the pivot screw is a fixed anchor. So maybe 3 bodies:\n- Body0: pivot block (fixed/kinematic) - the central hub\n- Body1: Arm A (revolute joint to Body0)\n- Body2: Arm B (revolute joint to Body0)\n\nBut the \"fixed\" body needs a way to be anchored. In USD physics, a rigid body with no joint can be static. To make it truly fixed, I can set it as kinematic (kinematicEnabled = true) or just leave it as a static rigid body (it won't move if no forces... actually it's dynamic). \n\nSimplest robust approach: Make the pivot hub a rigid body, and connect Arm A and Arm B each with a revolute joint to the hub. Mark the hub... Actually for a prop that just needs to demonstrate the joint, 2 bodies + 1 revolute joint is the classic scissors representation. Many references do 2 bodies + 1 revolute joint. Let me do that: the joint references body1 and body2, both are rigid bodies. The joint's world position is the pivot. \n\nBut then the whole assembly has no fixed reference \u2014 in sim it would free-fall. For a prop asset that's often acceptable (they're separate parts). But the SimReady validator may want a proper setup. Let me add a third element: the hub as a fixed body with RigidBodyAPI and make it not dynamic... Actually I can set the joint on the hub. \n\nLet me reconsider: The cleanest kinematic model that also looks correct:\n- Rigid body: Hub (the pivot screw + a small block) \u2014 this represents the fixed frame. Give it RigidBodyAPI. To keep it fixed in a standalone prop, I could also just leave it; but for the joint", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-85db7fdfa5bf4568", + "function_name": "write", + "arguments": { + "path": "/tmp/geom.py", + "content": "import numpy as np\n\ndef cross(a,b):\n return np.cross(a,b)\n\ndef _norm(v):\n n=np.linalg.norm(v)\n return v/n if n>1e-12 else np.array([0,0,1.0])\n\nclass Mesh:\n def __init__(self):\n self.V=[] # list of (x,y,z)\n self.F=[] # list of face index tuples\n def add_v(self,pts):\n base=len(self.V)\n for p in pts:\n self.V.append((float(p[0]),float(p[1]),float(p[2])))\n return base\n def add_face(self, idxs):\n self.F.append(tuple(idxs))\n def add_faces(self, faces):\n for f in faces: self.F.append(tuple(f))\n\ndef extrude_profile(profile_xy, z, th):\n \"\"\"profile_xy: list of (x,y) CCW (viewed from +Z). Extrude in Z around zc=z, thickness th.\"\"\"\n m=Mesh()\n n=len(profile_xy)\n zb=z-th/2.0; zt=z+th/2.0\n B=[(x, y, zb) for (x,y) in profile_xy]\n T=[(x, y, zt) for (x,y) in profile_xy]\n b0=m.add_v(B); t0=b0+n\n # bottom face (outward -Z): reverse winding\n for i in range(1,n-1):\n m.add_face((b0+0,b0+i+1,b0+i))\n # top face (outward +Z)\n for i in range(1,n-1):\n m.add_face((t0+0,t0+i,t0+i+1))\n # side walls\n for i in range(n):\n j=(i+1)%n\n m.add_face((b0+i,b0+j,t0+j,t0+i))\n return m\n\ndef plate_profile(y0,y1,w0,w1, mid=True):\n \"\"\"trapezoid/triangle blade outline CCW. w0 half-width at base(y0), w1 half width at mid, tip at y1.\"\"\"\n pts=[]\n pts.append((-w0,y0))\n if mid:\n pts.append((-w1,(y0+y1)/2.0))\n pts.append((0.0,y1))\n if mid:\n pts.append((w1,(y0+y1)/2.0))\n pts.append((w0,y0))\n # order CCW? (-w0,y0)->(-w1,mid)->(0,y1)->(w1,mid)->(w0,y0) is CCW\n return pts\n\ndef blade(xoff, zc, y0=0.0, y1=0.085, w0=0.0075, w1=0.0045, th=0.0028):\n prof=plate_profile(y0,y1,w0,w1)\n m=extrude_profile(prof, zc, th)\n return m\n\ndef torus(cx,cy, a, b, r, nseg=24, mseg=8):\n \"\"\"oval ring in XY centered (cx,cy), semi-axes a(x),b(y), tube radius r. hole faces +Z.\"\"\"\n m=Mesh()\n verts=[]\n for i in range(nseg):\n u=2*np.pi*i/nseg\n # center ring\n px=cx+a*np.cos(u); py=cy+b*np.sin(u)\n # local frame\n du=(-a*np.sin(u), b*np.cos(u))\n dux,duy=du\n ln=np.hypot(dux,duy)\n tx,ty=dux/ln,duy/ln\n # radial dir (in-plane, pointing away from center)\n rx,ry=(px-cx)/a if a else 1.0,(py-cy)/b if b else 1.0\n lnr=np.hypot(rx,ry); rx,ry=rx/lnr,ry/lnr\n # normal = t x r ... use z\n nx,ny,nz=0.0,0.0,1.0\n # tangent x normal -> in-plane radial\n qx, qy = ty* nz - ty*0, 0 # placeholder\n # basis: e1=radial(rx,ry), e2=up(0,0,1), e3 = e1 x e2? use\n e1=np.array([rx,ry,0.0]); e2=np.array([0,0,1.0]); e3=np.cross(e1,e2)\n for j in range(mseg):\n v=2*np.pi*j/mseg\n c=r*np.cos(v); s=r*np.sin(v)\n # offset = c*e1 + s*e3 (e1 radial, e3 out-of-plane-ish? e3 = e1 x e2 is in-plane perpendicular)\n off=c*e1 + s*e2\n verts.append((px+off[0],py+off[1], 0.0+off[2]))\n V=[]\n for p in verts: V.append((float(p[0]),float(p[1]),float(p[2])))\n m.add_v(V)\n for i in range(nseg):\n i2=(i+1)%nseg\n for j in range(mseg):\n j2=(j+1)%mseg\n a0=i*mseg+j; a1=i2*mseg+j; a2=i2*mseg+j2; a3=i*mseg+j2\n m.add_face((a0,a1,a2,a3))\n return m\n\ndef box(x0,x1,y0,y1,z0,z1):\n m=Mesh()\n v=[(x0,y0,z0),(x1,y0,z0),(x1,y1,z0),(x0,y1,z0),\n (x0,y0,z1),(x1,y0,z1),(x1,y1,z1),(x0,y1,z1)]\n m.add_v(v)\n faces=[(0,1,2,3),(7,6,5,4),(0,4,5,1),(1,5,6,2),(2,6,7,3),(3,7,4,0)]\n m.add_faces(faces)\n return m\n\ndef cylinder(cx,cy,cz, r, h, nseg=20):\n m=Mesh()\n top=[];bot=[]\n for i in range(nseg):\n u=2*np.pi*i/nseg\n top.append((cx+r*np.cos(u), cy+r*np.sin(u), cz+h/2.0))\n bot.append((cx+r*np.cos(u), cy+r*np.sin(u), cz-h/2.0))\n b0=m.add_v(bot); t0=m.add_v(top)\n m.add_face(tuple([b0]+[b0+(i+1)%nseg for i in range(1,nseg-1)]))\n m.add_face(tuple([t0]+[t0+(i) for i in range(1,nseg-1)]))\n for i in range(nseg):\n j=(i+1)%nseg\n m.add_face((b0+i,b0+j,t0+j,t0+i))\n return m\n\ndef merge(ms):\n m=Mesh()\n for x in ms:\n base=len(m.V)\n m.V.extend(x.V)\n for f in x.F:\n m.F.append(tuple(i+base for i in f))\n return m\n\ndef fix_normals(m):\n c=np.mean(np.array(m.V),axis=0)\n newF=[]\n for f in m.F:\n vs=np.array([m.V[i] for i in f])\n nrm=np.cross(vs[1]-vs[0],vs[2]-vs[0])\n fc=vs.mean(axis=0)\n if np.dot(nrm, fc-c) < 0:\n f=tuple(reversed(f))\n newF.append(f)\n m.F=newF\n return m\n\ndef bbox(m):\n a=np.array(m.V)\n return a.min(axis=0),a.max(axis=0)\n\ndef scale_to(m, target):\n mn,mx=bbox(m)\n cur=mx-mn\n s=target/cur\n c=np.array([mn[0],0,0])\n # scale about center then translate to center target at same center origin\n ctr=(mn+mx)/2.0\n tctr=np.array(target)/2.0\n V=[]\n for (x,y,z) in m.V:\n p=np.array([x,y,z])\n p=(p-ctr)*s\n p=p-tctr+np.array(target)/2.0 # center result in [0,target]\n V.append((float(p[0]),float(p[1]),float(p[2])))\n m.V=V\n return m\n" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-85db7fdfa5bf4568", + "content": "Successfully wrote to /tmp/geom.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 8200, + "completion_tokens": 7046, + "cached_tokens": 5488, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 15246 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "5e56a277", + "pi_parent_id": "c51464c9", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RdBfewmKf6Tsfdngqmt4DnYl", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 8, + "timestamp": "2026-10-21T17:04:48.307Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me build the scissors arms. Let me write a test to generate the geometry and check the bbox.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a5f758528c8cbcd4", + "function_name": "write", + "arguments": { + "content": "import numpy as np\nfrom geom import *\n\ndef arm(sx, blade_z, ring_x, ring_y):\n parts=[]\n # blade\n parts.append(blade(xoff=0.0, zc=blade_z, y0=0.002, y1=0.085))\n # shank: tapered plate from pivot to ring\n shank = plate_profile(-0.05, 0.015, 0.006, 0.009)\n # shift so it goes from y~0.01 down to ring\n sm=extrude_profile([(x*1.0, y-0.055) for (x,y) in shank], 0.0, 0.003)\n # offset shank x to align between blade base and ring\n sm2=Mesh(); base=0\n # we just place shank centered near ring_x\n parts.append(sm)\n # ring\n parts.append(torus(ring_x, ring_y, 0.020, 0.028, 0.0035, nseg=28, mseg=10))\n m=merge(parts)\n return m\n\n# Arm A: blade at z +, ring at x -\naA=arm(+1, +0.0016, -0.006, -0.062)\n# Arm B: blade at z -, ring at x +\naB=arm(-1, -0.0016, +0.006, -0.062)\n# pivot screw (on top blade, z+)\nscrew=cylinder(0.0, 0.020, 0.0035, 0.006, 0.004, nseg=20)\n\nfull=merge([aA,aB,screw])\nmn,mx=bbox(full)\nprint(\"bbox min\",mn,\"max\",mx,\"size\",mx-mn)\ntarget=np.array([0.06751428544521332, 0.19996289908885956, 0.009697046800283715])\nfull=scale_to(full,target)\nfix_normals(full)\nmn,mx=bbox(full)\nprint(\"final size\",mx-mn,\"min\",mn)\nprint(\"num verts\",len(full.V),\"faces\",len(full.F))\n# save for inspection\nimport pickle\npickle.dump({\"V\":full.V,\"F\":full.F}, open(\"/tmp/full.pkl\",\"wb\"))\n# per-arm bboxes for joint center\ndef armbbox(a):\n mn,mx=bbox(a); return mn,mx\nprint(\"AA\",armbbox(aA)); print(\"AB\",armbbox(aB))\n", + "path": "/tmp/build_geom.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a5f758528c8cbcd4", + "content": "Successfully wrote to /tmp/build_geom.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 15270, + "completion_tokens": 719, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 15989 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c49590f7", + "pi_parent_id": "7a5b6449", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R7DpKQOoSxMQ0mWZjaDr2Gy0", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 9, + "timestamp": "2026-10-21T17:04:52.413Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run the geometry build to check dimensions and sanity.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b881ea72b6af8cdd", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 build_geom.py 2>&1 | head -30" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b881ea72b6af8cdd", + "content": "bbox min [-0.0295 -0.105 -0.0033287] max [0.0295 0.085 0.0055] size [0.059 0.19 0.0088287]\nfinal size [0.06751429 0.1999629 0.00969705] min [-0.03375714 -0.09998145 -0.00484852]\nnum verts 620 faces 626\nAA (array([-0.0295 , -0.105 , -0.0033287]), array([0.0175 , 0.085 , 0.0033287]))\nAB (array([-0.0175 , -0.105 , -0.0033287]), array([0.0295 , 0.085 , 0.0033287]))", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 16013, + "completion_tokens": 58, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 16071 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "d89e5418", + "pi_parent_id": "b67c2b6e", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RMn0cqHfgKg3VGCVjiiFd6oH", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 10, + "timestamp": "2026-10-21T17:06:33.577Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "The geometry works. Let me restructure so each arm's local origin is at the pivot screw, enabling a clean revolute joint.", + "reasoning_content": "The geometry looks reasonable. Now I need to build the full USD asset. Let me think about the structure:\n\nThe scissors have:\n1. Two blade/handle arms (Arm A and Arm B) that pivot around the screw\n2. The pivot screw at the center\n\nThe rigid parts:\n- Arm A (blade + shank + ring handle) - one rigid body\n- Arm B (blade + shank + ring handle) - one rigid body\n- The screw is a fixed attachment (it's the pivot point)\n\nActually, the scissors have a hinge joint at the screw. Two rigid bodies connected by a revolute joint. The axis of the revolute joint is along Z (the thickness direction, since the scissors open in the XY plane). Wait, actually the scissors open by rotating around the screw axis, which is perpendicular to the plane of the blades. The blades lie roughly in the XY plane (X is width, Y is length, Z is thickness). The scissors open by rotating around the Z axis (perpendicular to the blade plane). So the revolute joint axis is Z.\n\nWait, let me reconsider. The scissors in the image: the blades and handles lie in a plane. The nominal dimensions: X=0.0675 (width), Y=0.2 (length, along the blade/handle), Z=0.0097 (thickness). So the flat plane is XY, and Z is the thin dimension. The scissors pivot around an axis perpendicular to that plane = Z axis.\n\nSo:\n- Body A: Arm A (rigid body with collider)\n- Body B: Arm B (rigid body with collider)\n- Revolute joint connecting A and B, at the screw location, axis = Z\n\nThe screw itself is a fixed small cylinder \u2014 it's part of the assembly. In real scissors the screw is fixed to one side, but for kinematic fidelity, I'll model the screw as part of one arm or as a separate fixed element. Actually the screw is what they rotate around. Let me keep the screw as part of Arm A (the top blade, which has the visible screw head). \n\nActually, for a revolute joint, we need two connected bodies. The screw is the pivot. Let me make:\n- Body A = Arm A (top blade + its handle ring) \u2014 includes the screw head\n- Body B = Arm B (bottom blade + its handle ring)\n- Revolute joint: body1 = A, body2 = B, at the screw center, axis Z.\n\nWait, but a single revolute joint between two free-floating bodies just means they can rotate relative to each other \u2014 that's exactly a scissors hinge. Good.\n\nActually, real scissors: both arms are free (held in hand), and they pivot relative to each other around the screw. So a single revolute joint between the two bodies with no ground is correct.\n\nNow I need to build proper USD with:\n- Root model\n- World/prop \n- Two rigid bodies (UsdPhysics.RigidBodyAPI)\n- Mesh colliders (UsdPhysics.MeshCollisionAPI) \n- Revolute joint (UsdPhysics.RevoluteJoint) with axis Z, with angular limits\n- Materials (gold handles, steel blades)\n- Meters units\n\nLet me think about the SimReady requirements. The scoring policy lists many requirement IDs. Key ones:\n- RB.001, RB.007, RB.010, RB.COL.001/002/003/004: rigid body / collision\n- SL.MAT.001, SL.QCODE.001, SL.TIME.001: materials, QCode, time\n- SR.002, SR.004: something\n- UN.006, UN.007: units (meters)\n- VG.*: geometry\n- VM.*: material binding\n- AA.001, AA.002\n- HI.*: hierarchy\n\nThis is a lot. Rather than guess, I should build a reasonable, well-formed asset and then run validate_candidate to get the NVIDIA findings, and repair iteratively.\n\nLet me build a good baseline. Let me structure:\n\n```\n/Scissors (Xform, root model)\n /Scissors/Pivot (Xform at screw location) -- actually joint positions are in body-local frames\n```\n\nActually for UsdPhysics joints, the joint prim references body1 and body2, and has localPosition1, localPosition2, localRotation1, localRotation2 (or axis). Let me set:\n- joint at /Scissors/Joints/pivot\n- body1 = /Scissors/ArmA (the mesh prim or its parent with RigidBodyAPI)\n- body2 = /Scissors/ArmB\n- axis = (0,0,1)\n- localPosition1 = position of screw in ArmA local space\n- localPosition2 = position of screw in ArmB local space\n\nSince both arms share the same screw location and I'm placing them at origin with the screw at (0, 0.02*scalefactor...), I need to figure out the screw location in each arm's local frame.\n\nLet me restructure. I'll place each arm as its own Xform+Mesh. The mesh geometry I generated is in \"full\" space (both arms together, centered). But for the joint to work, I need each arm in its own local frame where the screw is at a known local position.\n\nLet me restructure: generate each arm's geometry separately, place the screw at a known local point (e.g., origin of each arm's local space = screw location), then position the arms.\n\nLet me redo: I'll build each arm centered so the screw (pivot) is at the local origin of that arm. Then place both arms with the screw at world position P (the screw world location). The revolute joint localPosition1 = (0,0,0), localPosition2 = (0,0,0), axis = (0,0,1).\n\nLet me rebuild the geometry so each arm's local origin is the pivot screw center. The screw is at y\u22480.02 in my current full geometry (screw at y=0.02, which scaled... let me recompute). Actually in the pre-scale geometry the screw was at (0, 0.020, 0.0035). After scaling the screw moves. Let me just build arms relative to the pivot.\n\nLet me restructure the geometry build:\n- Build Arm A geometry in a local frame where pivot (screw) is at origin.\n- Build Arm B similarly.\n- The whole assembly: place both arm Xforms so their local origins coincide at the world screw position.\n\nThe world screw position: I'll center the whole object so the final bbox is centered at origin or at [0,target]. Let me center at origin for cleanliness (bbox min = -target/2). Actually nominal dims are just the size; center can be anywhere. Let me center at origin.\n\nLet me rebuild with pivot at local origin. I'll offset each arm's geometry by -screw_local_offset. In my build, the screw in \"full\" local space was at approximately (0, 0.020, 0.0035) pre-scale, but scaling complicates. \n\nSimpler: build each arm geometry, find the screw local coordinate, translate so screw->origin, then scale each arm uniformly (same scale factor s computed from the full assembly) so that the whole thing matches target dims. But scaling each arm about its own origin (the screw) keeps the screw at origin. The scale factor should be uniform (same s on all axes) to preserve shape. But target dims require anisotropic scaling (different scale per axis). Anisotropic scaling distorts. \n\nHmm, the nominal dims are the actual physical size. I can build the geometry at the right proportions and use a single uniform scale so the dims come out close, OR accept anisotropic scaling. The dims given: X=0.0675, Y=0.20, Z=0.0097. My generated proportions: X=0.059, Y=0.19, Z=0.0088. Ratio target/generated: 1.144, 1.052, 1.098. These are close (within ~14%), so anisotropic scaling won't distort much visually. But to be safe and keep shape nice, I could tune the generation to match proportions and use uniform scale. \n\nActually the requirement is \"reference-scale shape\" - matching the nominal dims matters. Let me just do anisotropic scaling to hit exactly the target bbox. The distortion is minor. But anisotropic scaling per arm about the pivot is fine.\n\nLet me do this: \n1. Generate the FULL assembly (both arms + screw) as I did, in a local frame.\n2. Compute uniform scale to match the LONGEST dim proportionally? No.\n\nLet me instead generate each arm, place screw at a fixed local point, and apply the SAME anisotropic scale to both arms (and screw) about the global origin (screw location), so proportions stay consistent between arms. Since the pivot is at the same point for both, scaling about the pivot keeps them aligned.\n\nPlan:\n- Generate Arm A mesh vertices in global-local space with screw at S=(sx,sy,0).\n- Generate Arm B similarly.\n- Translate each so screw at origin.\n- Apply anisotropic scale s=(sx_scale, sy_scale, sz_scale) about origin to each arm.\n- Now each arm's local origin = screw, and dims are scaled.\n- World placement: put both arm Xforms at world screw position W. \n\nThe world screw position: I'll place it so that the full bbox is centered at origin. Compute full bbox after scaling, set W = -fullbbox_center... but each arm's transform = translate(W). Since both share W and their origins = screw, the assembly bbox = union. Let me compute W = -(center of full bbox) to center at origin. Actually simpler: set W=0 (screw at world origin). Then bbox won't be centered but that's fine. Actually centering at origin is nicer. Let me compute full bbox with W=0, then set W = -center.\n\nLet me just do W=0 (screw at origin) to keep it simple. The dims are what matter.\n\nLet me rewrite the geometry build cleanly.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-913240f46afc99ed", + "function_name": "write", + "arguments": { + "content": "import numpy as np\nfrom geom import *\n\n# Pivot (screw) local position in pre-scale geometry\nSCREW = np.array([0.0, 0.020, 0.0])\n\ndef make_arm(blade_z, ring_x):\n parts=[]\n parts.append(blade(xoff=0.0, zc=blade_z, y0=0.002, y1=0.085))\n shank = plate_profile(-0.055, 0.02, 0.006, 0.009)\n parts.append(extrude_profile([(x, y) for (x,y) in shank], 0.0, 0.003))\n parts.append(torus(ring_x, -0.062, 0.020, 0.028, 0.0035, nseg=28, mseg=10))\n m=merge(parts)\n # screw head only on top arm\n return m\n\ndef local_originate(m):\n V=[(x-SCREW[0], y-SCREW[1], z-SCREW[2]) for (x,y,z) in m.V]\n m.V=V\n return m\n\naA=make_arm(+0.0016, -0.006)\naB=make_arm(-0.0016, +0.006)\nlocal_originate(aA); local_originate(aB)\n\n# uniform combined geometry to compute anisotropic scale about screw (origin)\nfull=merge([aA,aB])\nmn,mx=bbox(full)\ncur=mx-mn\ntarget=np.array([0.06751428544521332, 0.19996289908885956, 0.009697046800283715])\nscale=target/cur\ndef apply_scale(m,s):\n m.V=[(x*s[0], y*s[1], z*s[2]) for (x,y,z) in m.V]\n return m\napply_scale(aA, scale); apply_scale(aB, scale)\nfix_normals(aA); fix_normals(aB)\n\n# screw (small cylinder) local-origin at origin\nscrew=cylinder(0.0,0.0, 0.0, 0.0055, 0.006, nseg=20)\nscrew=apply_scale(merge([screw]), scale) # just scale\nfix_normals(screw)\n\n# full bbox for world centering\nfull=merge([aA,aB,screw])\nmn,mx=bbox(full)\nprint(\"final size\",mx-mn)\nW=-np.array((mn+mx)/2.0) # center at origin\nprint(\"world offset W\", W)\n\nimport pickle\npickle.dump({\"aA\":(aA.V,aA.F),\"aB\":(aB.V,aB.F),\"screw\":(screw.V,screw.F),\n \"scale\":scale,\"W\":list(W)}, open(\"/tmp/parts.pkl\",\"wb\"))\nprint(\"verts A\",len(aA.V),\"B\",len(aB.V),\"screw\",len(screw.V))\n", + "path": "/tmp/build_geom2.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-913240f46afc99ed", + "content": "Successfully wrote to /tmp/build_geom2.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 16368, + "completion_tokens": 3081, + "cached_tokens": 15680, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19449 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "b4bcd089", + "pi_parent_id": "69c326ef", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RNlZX3BS2FLFA6VhX2BgBl0n", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 11, + "timestamp": "2026-10-21T17:06:36.880Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run this to verify.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9870662dfc97bf72", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 build_geom2.py 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9870662dfc97bf72", + "content": "final size [0.06751429 0.1999629 0.00969705]\nworld offset W [-0. 0.02716583 -0. ]\nverts A 290 B 290 screw 40", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 19474, + "completion_tokens": 51, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19525 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "a0ebc9a1", + "pi_parent_id": "85a57806", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RULDvb95iJA2S0bJwIFZwDEN", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 12, + "timestamp": "2026-10-21T17:08:16.599Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Now let me generate the split steel/gold meshes per arm for multi-material binding and per-mesh collision.", + "reasoning_content": "Good, geometry is finalized. Now let me write the full USD authoring script. Let me structure the USD:\n\n```\n/ (stage, meters)\n /Scissors (Xform, root model)\n /Scissors/ArmA (Xform, RigidBodyAPI)\n /Scissors/ArmA/Geometry (Mesh, MeshCollisionAPI)\n ... \n /Scissors/ArmB (Xform, RigidBodyAPI)\n /Scissors/ArmB/Geometry (Mesh, MeshCollisionAPI)\n /Scissors/Screw (Xform, static)\n /Scissors/Screw/Geometry (Mesh)\n /Scissors/Joints/Pivot (RevoluteJoint)\n materials...\n```\n\nWait, the screw - should it be a rigid body? It's the pivot. In real scissors the screw is fixed to one arm. Let me make the screw part of Arm A (rigid). Actually simpler: merge screw into Arm A. But then Arm A's local origin is the screw. If I merge screw into Arm A's mesh, Arm A has the screw head. That's fine and simpler (2 bodies total). But the screw spans Z across both blades. If it's part of Arm A, it rotates with Arm A. Acceptable.\n\nActually, to keep it clean and match \"pivot screw holds them\", let me make the screw its own small rigid body? No \u2014 simplest correct: 2 bodies (Arm A, Arm B) + 1 revolute joint. Merge screw into Arm A. Let me do that.\n\nWait, but then the screw cylinder (which is centered, spanning full Z) merged into Arm A means Arm A collider includes the screw. Fine.\n\nLet me merge screw into Arm A. So:\n- Body A = Arm A mesh (blade + shank + ring + screw head). Actually I'll just merge the full screw.\n- Body B = Arm B mesh.\n\nBoth have RigidBodyAPI + MeshCollisionAPI.\nRevolute joint: body1=A, body2=B, axis Z, at origin (both local origins = screw).\n\nNow materials:\n- Steel material (blades + shanks): but each arm is one mesh. The blade is steel, the ring is gold. So each arm has TWO materials (steel blade+shank, gold ring). I need per-face material binding.\n\nThat means I need to split the mesh into two sets of faces (steel faces and gold faces) and bind different materials. In USD, a single Mesh can have multiple material bindings via different prim bindings... Actually a UsdGeomMesh can have multiple materials bound to subsets via \"faceVariance\" or by binding material to the mesh and using relationships per face? No. Standard way: bind material to the mesh prim (whole mesh), OR split into multiple meshes each with one material, OR use face-variant materials via Sdf's material:binding with a subset.\n\nThe cleanest for USD: create sub-geometries. But RigidBody needs one collider mesh. Hmm, the collider can be one mesh while visual is split.\n\nSimplest robust approach: \n- For each arm, create the mesh with TWO materials via two child Mesh prims? But then collider needs to reference... I can put MeshCollisionAPI on the Xform with a single collider mesh, OR put it on a mesh.\n\nLet me restructure per arm:\n```\n/Scissors/ArmA (Xform, RigidBodyAPI, MeshCollisionAPI)\n /Scissors/ArmA/steel (Mesh) bound to steel material\n /Scissors/ArmA/gold (Mesh) bound to gold material\n```\nAnd MeshCollisionAPI on ArmA with an explicit collider mesh? MeshCollisionAPI needs a mesh. I can add a separate collider mesh prim with MeshCollisionAPI, or bind MeshCollisionAPI to the Xform and it uses descendant meshes. Actually UsdPhysics.MeshCollisionAPI applied to a prim that is a Mesh makes that mesh a collider. If applied to a Xform... no.\n\nLet me do: \n```\n/Scissors/ArmA (Xform, RigidBodyAPI)\n /Scissors/ArmA/Body (Mesh, MeshCollisionAPI, bound to steel material) <- collider + visual steel\n /Scissors/ArmA/Handle (Mesh, bound to gold material) <- visual gold only\n```\nThe collider is the Body mesh (blade+shank). The handle ring (gold) is visual only, no collider. That's fine - the ring is a finger loop, not critical for collision. Actually including it in collision would be more accurate but the ring hole matters. Let me keep collider = blade+shank+... hmm. To be safe for sim, put MeshCollisionAPI on the whole-merged mesh? But then one material.\n\nAlternative: keep it simplest \u2014 bind the material to the whole mesh and use a single material per arm? No, we need gold+steel colors for visual fidelity.\n\nLet me do the face-based approach properly. A UsdGeomMesh supports multiple materials bound to it IF we use face-by-face binding? The standard mechanism: `Sdf.BindMaterial` / a prim's \"material:binding\" rel, and for per-face, you use the mesh's `faceMaterialIDs`? No, that's a MaterialX/ogre thing. In USD, you bind a material to a mesh prim; to have different materials on faces of the same mesh you need to either (a) split into multiple meshes, or (b) use \"inherited token\" per face isn't a thing.\n\nActually USD does support it: you can add material binding to a mesh and then there's `mesh:faceVariance`? No. The real mechanism: a mesh can reference multiple materials in its `material:binding` relationship? No, material:binding is one material per prim (inherited token). \n\nThe correct USD way for multi-material mesh: split geometry into multiple Mesh prims (each bound to one material). That's what I'll do. And for the collider, I'll put MeshCollisionAPI on the Xform? Let me check: UsdPhysics.MeshCollisionAPI is applied to a UsdGeomMesh prim. To have a collider for the whole arm, I can add a hidden collider mesh.\n\nLet me do this per arm:\n```\n/Scissors/ArmA (Xform, RigidBodyAPI)\n /Scissors/ArmA/Steel (Mesh, bound=steelMat)\n /Scissors/ArmA/Gold (Mesh, bound=goldMat)\n /Scissors/ArmA/Collider (Mesh, MeshCollisionAPI, no material) <- full merged mesh for physics\n```\nThe Collider is a hidden (display off / invisible) full mesh used only for collision. To hide it, set `invisible` on it or use UsdGeomImageable's renderVisible=false. SimReady might not like invisible colliders but it's common. Alternatively, skip separate collider and put MeshCollisionAPI on the Steel mesh (blade) \u2014 the blade is the main collision. But the ring extends beyond. For sim accuracy the ring should collide.\n\nHmm, let me reconsider. Maybe simplest: each arm = ONE mesh (steel+gold combined) with a SINGLE combined material? No, we want gold handles + steel blades clearly.\n\nOK here's a clean solution: Use face-based material assignment by creating TWO meshes per arm (Steel, Gold), and apply MeshCollisionAPI to BOTH Steel and Gold meshes (each mesh becomes its own collider, both part of the same rigid body). Two colliders on one rigid body is allowed. That gives full collision (blade+shank+ring) with two materials. \n\nSo:\n```\n/Scissors/ArmA (Xform, RigidBodyAPI)\n /Scissors/ArmA/Steel (Mesh, MeshCollisionAPI, material=steel)\n /Scissors/ArmA/Gold (Mesh, MeshCollisionAPI, material=gold)\n```\nEach Mesh collider with its own faces. That's clean. Screw: merge into Arm A as steel (cylinder steel). \n\nSo I need to split each arm's faces into steel faces and gold faces. The gold part is just the torus ring faces. The steel = blade + shank (+ screw for A). I know which faces belong to the ring because I can track them: the torus is added last. Let me build the arm returning (steelMesh, goldMesh) separately.\n\nLet me refactor make_arm to return steel mesh and gold(ring) mesh.\n\nFor Arm A steel: blade + shank + screw.\nFor Arm A gold: ring.\nFor Arm B steel: blade + shank.\nFor Arm B gold: ring.\n\nLet me rewrite the geometry to produce these 4 meshes (plus merge screw into A steel). All already local-origin and scaled.\n\nLet me write build_geom3.py.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-903af087d46ced04", + "function_name": "write", + "arguments": { + "content": "import numpy as np\nfrom geom import *\n\nSCREW = np.array([0.0, 0.020, 0.0])\ntarget=np.array([0.06751428544521332, 0.19996289908885956, 0.009697046800283715])\n\ndef blade_geo(): return blade(xoff=0.0, zc=0.0, y0=0.002, y1=0.085)\ndef shank_geo():\n shank = plate_profile(-0.055, 0.02, 0.006, 0.009)\n return extrude_profile([(x, y) for (x,y) in shank], 0.0, 0.003)\ndef ring_geo(ring_x): return torus(ring_x, -0.062, 0.020, 0.028, 0.0035, nseg=28, mseg=10)\n\ndef build():\n aA_steel = merge([blade_geo(), shank_geo()])\n aA_gold = ring_geo(-0.006)\n aB_steel = merge([blade_geo(), shank_geo()])\n aB_gold = ring_geo(+0.006)\n screw = cylinder(0.0,0.0,0.0, 0.0055, 0.006, nseg=20)\n aA_steel = merge([aA_steel, screw])\n\n meshes={\"aA_steel\":aA_steel,\"aA_gold\":aA_gold,\"aB_steel\":aB_steel,\"aB_gold\":aB_gold}\n # local originate\n for k,m in meshes.items():\n m.V=[(x-SCREW[0], y-SCREW[1], z-SCREW[2]) for (x,y,z) in m.V]\n # compute scale from full\n full=merge(list(meshes.values()))\n mn,mx=bbox(full); scale=(mx-mn)/ (0) # placeholder\n mn,mx=bbox(full); scale=(mx-mn)/target*target/(mx-mn)\n scale=target/(mx-mn)\n for k,m in meshes.items():\n m.V=[(x*scale[0], y*scale[1], z*scale[2]) for (x,y,z) in m.V]\n fix_normals(m)\n full=merge(list(meshes.values()))\n mn,mx=bbox(full)\n print(\"final size\",mx-mn,\"min\",mn,\"max\",mx)\n W=-np.array((mn+mx)/2.0)\n return {k:(m.V,m.F) for k,m in meshes.items()}, list(W)\n\nP, W = build()\nimport pickle\npickle.dump({\"parts\":P,\"W\":W}, open(\"/tmp/parts.pkl\",\"wb\"))\nfor k,v in P.items():\n print(k, len(v[0]),\"verts\",len(v[1]),\"faces\")\nprint(\"W\",W)\n", + "path": "/tmp/build_geom3.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-903af087d46ced04", + "content": "Successfully wrote to /tmp/build_geom3.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 19616, + "completion_tokens": 2697, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 22313 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "1a5e9034", + "pi_parent_id": "0ebd7bf8", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RBzC03WvCZzM3h8FBjgfAoZX", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 13, + "timestamp": "2026-10-21T17:08:19.059Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run this and verify.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-93bf63e6f160b48b", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 build_geom3.py 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-93bf63e6f160b48b", + "content": "/tmp/build_geom3.py:27: RuntimeWarning: divide by zero encountered in divide\n mn,mx=bbox(full); scale=(mx-mn)/ (0) # placeholder\nTraceback (most recent call last):\n File \"/tmp/build_geom3.py\", line 39, in \n P, W = build()\n ^^^^^^^\n File \"/tmp/build_geom3.py\", line 32, in build\n fix_normals(m)\n File \"/tmp/geom.py\", line 138, in fix_normals\n vs=np.array([m.V[i] for i in f])", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 22337, + "completion_tokens": 51, + "cached_tokens": 17248, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 22388 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2faea496", + "pi_parent_id": "62a280d8", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rk9LEuK90a7wByh4cZ5EElrr", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 14, + "timestamp": "2026-10-21T17:08:58.222Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The face index issue - after fix_normals, faces reference original indices which is fine since I didn't reindex. Wait, the error is in fix_normals: `m.V[i] for i in f` - index out of range? That means face indices exceed vert count. This happens because after scaling I reused but the merge... no. Let me check: the meshes are built, local_originated (vertices changed count? no). Then scaled (same count). Then fix_normals. The face indices should be valid.\n\nWait the error is a divide by zero warning then index error. Let me check - the aA_gold etc. Actually the problem: `merge` for aA_steel merges blade+shank+screw. Fine. But ring_geo torus - the torus function builds its own mesh with V and F. Let me check torus F indices: a0=i*mseg+j ... with nseg=28,mseg=10, max index=28*10=280 verts. F uses indices up to 279. OK.\n\nWait the actual issue: after scaling, m.V list is fine. The fix_normals references m.F faces. Let me check: is it possible a face has an index >= len(V)? For the shank extrude: plate_profile with 5 points, extrude gives B (5) + T (5) = 10 verts. faces reference b0..b4, t0..t4. b0=0 base, so indices 0-9. fine.\n\nHmm let me just debug by printing lengths. Actually maybe the issue: in `build()`, I do `meshes` dict, then for each I recompute m.V via list comp \u2014 that's fine, same length. Then merge. Then scale again... no I scale in the same loop after. Let me look: the loop does scale then fix_normals in same iteration. But I recompute `full` only after all. The merge earlier for scale computation: `full=merge(list(meshes.values()))` \u2014 merge copies. That's fine.\n\nThe IndexError in fix_normals means some face index >= len(m.V). Let me just add a guard/print. Actually, wait \u2014 maybe the torus has a bug producing faces with wrong indices. Let me check torus: nseg=28, mseg=10. verts appended: for i in range(28): for j in range(10): append \u2192 280 verts. m.add_v(V) where V has 280 entries. Faces: a0=i*10+j max = 27*10+9=279. OK valid.\n\nLet me check plate_profile: returns 5 pts. extrude_profile: n=5. B=5,T=5, add_v(B)=base0, t0=base0+5=5. bottom faces: (b0,b0+2,b0+1) etc valid 0-4. top (t0,...)=5-9. sides: (b0+i,b0+j,t0+j,t0+i) valid.\n\nHmm. Let me check blade: plate_profile(0.002,0.085,0.0075,0.0045) 5 pts. fine.\n\nWait \u2014 screw cylinder nseg=20: 40 verts, faces reference b0+... base=0,20. m.add_v(bot) returns 0 (base), t0=20. bottom face: (b0, [b0+(i+1)%nseg for i in range(1,nseg-1)]) = (0, 1..18) that's 18 faces points? (0,1,2,...,18) = 18-gon? indices 0-18, valid (<20). top face (20,21,...,37). sides valid. merge with aA_steel.\n\nSo where's the invalid index? Let me just print. Actually maybe the problem is the aA_gold etc share \u2014 no. Let me just run with a try and print which mesh/face.\n\nActually, I bet the issue: I call fix_normals on `m` where m is the same object as meshes[k], but I already did `full=merge(...)` earlier which is separate. Should be fine.\n\nLet me just add debug.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b0e494fdbddb1562", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nimport numpy as np\nfrom geom import *\naA_steel = merge([blade(xoff=0.0, zc=0.0, y0=0.002, y1=0.085), extrude_profile([(x,y) for (x,y) in plate_profile(-0.055,0.02,0.006,0.009)],0.0,0.003), cylinder(0.0,0.0,0.0,0.0055,0.006,nseg=20)])\nprint('steel verts',len(aA_steel.V),'max face idx',max(max(f) for f in aA_steel.F))\ng=torus(-0.006,-0.062,0.020,0.028,0.0035,nseg=28,mseg=10)\nprint('gold verts',len(g.V),'max face idx',max(max(f) for f in g.F))\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b0e494fdbddb1562", + "content": "steel verts 50 max face idx 49\ngold verts 280 max face idx 279", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 22538, + "completion_tokens": 1216, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 23754 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "057e5171", + "pi_parent_id": "2f91ea86", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RF9MNnCpNHgwAFsK1GwmDgsm", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 15, + "timestamp": "2026-10-21T17:09:34.225Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "These are fine. The problem must be in the merge of full for scale computation - no. Wait, the error was at fix_normals for one of the meshes. Let me re-examine: in build_geom3 the loop `for k,m in meshes.items(): m.V=[...]` reassigns m.V. Then `full=merge(list(meshes.values()))`. Then another loop `for k,m in meshes.items(): m.V=scale; fix_normals(m)`. That's fine.\n\nWait the first loop: `m.V=[(x-SCREW...) ...]`. That's fine.\n\nHmm, but the error trace: line 32 `fix_normals(m)` inside the scale loop. Let me check: after scaling, m.V has same length. So face indices valid. Unless... the placeholder line `mn,mx=bbox(full); scale=(mx-mn)/ (0)` divides by zero producing inf/nan in scale! Then `apply_scale`... no I don't call apply_scale. But `scale` at that line is inf/nan, then next line `scale=target/(mx-mn)` recomputes correctly. So scale is fine after.\n\nWait, actually the warning \"divide by zero\" then it continues. The real error is IndexError in fix_normals. Let me just directly test the exact build path.\n\nActually, let me reconsider: after local originate, then scale, then fix_normals \u2014 all same length. The only way face idx >= vert count is if a face was created with bad indices. Let me test the exact full build in one script.\n\nActually wait \u2014 I think the issue is `merge` creates new V by extending. When I do `merge(list(meshes.values()))` for the FIRST bbox, that's fine. But then in the scaling loop I modify m.V in place. Fine.\n\nLet me just run build_geom3 with traceback fully.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-ab8bc33e85c214e1", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i '/scale=(mx-mn)\\/ (0)/d' build_geom3.py && python3 -c \"\nimport numpy as np, traceback\nfrom geom import *\nSCREW=np.array([0.0,0.020,0.0]); target=np.array([0.06751428544521332,0.19996289908885956,0.009697046800283715])\nmeshes={'aA_gold':torus(-0.006,-0.062,0.020,0.028,0.0035,nseg=28,mseg=10)}\nfor k,m in meshes.items():\n m.V=[(x-SCREW[0],y-SCREW[1],z-SCREW[2]) for (x,y,z) in m.V]\nfull=merge(list(meshes.values())); mn,mx=bbox(full); scale=target/(mx-mn)\nfor k,m in meshes.items():\n m.V=[(x*scale[0],y*scale[1],z*scale[2]) for (x,y,z) in m.V]\n try:\n fix_normals(m)\n print('ok',k)\n except Exception as e:\n print('ERR',k,e); print('len V',len(m.V),'maxidx',max(max(f) for f in m.F))\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-ab8bc33e85c214e1", + "content": "ok aA_gold", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 23794, + "completion_tokens": 771, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 24565 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "38c5e950", + "pi_parent_id": "ff778869", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RIBq3VLVtAYwMQ1GOsEylHGq", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 16, + "timestamp": "2026-10-21T17:09:42.119Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "That works fine. So the issue in build_geom3 must be in a different mesh. Let me just run the fixed build_geom3.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bf3cb785bfed435e", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 build_geom3.py 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bf3cb785bfed435e", + "content": "Traceback (most recent call last):\n File \"/tmp/build_geom3.py\", line 38, in \n P, W = build()\n ^^^^^^^\n File \"/tmp/build_geom3.py\", line 31, in build\n fix_normals(m)\n File \"/tmp/geom.py\", line 138, in fix_normals\n vs=np.array([m.V[i] for i in f])\n ~~~^^^\nIndexError: list index out of range", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 24584, + "completion_tokens": 72, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 24656 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "bc33b014", + "pi_parent_id": "38fb2ffe", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RfqbxXr1uQRxxSLiLi51gGZM", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 17, + "timestamp": "2026-10-21T17:09:50.231Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "So one of the steel meshes has the issue. The steel mesh is merge of blade + shank + screw. Let me test aA_steel.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b197015db17b5aa6", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nimport numpy as np\nfrom geom import *\nSCREW=np.array([0.0,0.020,0.0])\nm=merge([blade(xoff=0.0,zc=0.0,y0=0.002,y1=0.085), extrude_profile([(x,y) for (x,y) in plate_profile(-0.055,0.02,0.006,0.009)],0.0,0.003), cylinder(0.0,0.0,0.0,0.0055,0.006,nseg=20)])\nprint('steel len V',len(m.V),'maxidx',max(max(f) for f in m.F))\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b197015db17b5aa6", + "content": "steel len V 50 maxidx 49", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 24782, + "completion_tokens": 246, + "cached_tokens": 17248, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25028 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "9d163404", + "pi_parent_id": "1727b2af", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-ReQBomFDGPVlXyaQG2sxCM8n", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 18, + "timestamp": "2026-10-21T17:10:00.239Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The steel mesh alone is fine. So the issue in build_geom3 is that I have a leftover duplicate `mn,mx=bbox(full); cur=mx-mn; target...; s=target/cur` ... let me look at the file. Actually the sed removed the `(0)` line. Let me re-read the current file.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8a7a64df599907e0", + "function_name": "read", + "arguments": { + "path": "/tmp/build_geom3.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8a7a64df599907e0", + "content": "import numpy as np\nfrom geom import *\n\nSCREW = np.array([0.0, 0.020, 0.0])\ntarget=np.array([0.06751428544521332, 0.19996289908885956, 0.009697046800283715])\n\ndef blade_geo(): return blade(xoff=0.0, zc=0.0, y0=0.002, y1=0.085)\ndef shank_geo():\n shank = plate_profile(-0.055, 0.02, 0.006, 0.009)\n return extrude_profile([(x, y) for (x,y) in shank], 0.0, 0.003)\ndef ring_geo(ring_x): return torus(ring_x, -0.062, 0.020, 0.028, 0.0035, nseg=28, mseg=10)\n\ndef build():\n aA_steel = merge([blade_geo(), shank_geo()])\n aA_gold = ring_geo(-0.006)\n aB_steel = merge([blade_geo(), shank_geo()])\n aB_gold = ring_geo(+0.006)\n screw = cylinder(0.0,0.0,0.0, 0.0055, 0.006, nseg=20)\n aA_steel = merge([aA_steel, screw])\n\n meshes={\"aA_steel\":aA_steel,\"aA_gold\":aA_gold,\"aB_steel\":aB_steel,\"aB_gold\":aB_gold}\n # local originate\n for k,m in meshes.items():\n m.V=[(x-SCREW[0], y-SCREW[1], z-SCREW[2]) for (x,y,z) in m.V]\n # compute scale from full\n full=merge(list(meshes.values()))\n mn,mx=bbox(full); scale=(mx-mn)/target*target/(mx-mn)\n scale=target/(mx-mn)\n for k,m in meshes.items():\n m.V=[(x*scale[0], y*scale[1], z*scale[2]) for (x,y,z) in m.V]\n fix_normals(m)\n full=merge(list(meshes.values()))\n mn,mx=bbox(full)\n print(\"final size\",mx-mn,\"min\",mn,\"max\",mx)\n W=-np.array((mn+mx)/2.0)\n return {k:(m.V,m.F) for k,m in meshes.items()}, list(W)\n\nP, W = build()\nimport pickle\npickle.dump({\"parts\":P,\"W\":W}, open(\"/tmp/parts.pkl\",\"wb\"))\nfor k,v in P.items():\n print(k, len(v[0]),\"verts\",len(v[1]),\"faces\")\nprint(\"W\",W)", + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25054, + "completion_tokens": 100, + "cached_tokens": 7840, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25154 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c204f1f1", + "pi_parent_id": "b063c1b4", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RZYSOOZNSCj2t7zWan0ArYoH", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 19, + "timestamp": "2026-10-21T17:10:29.384Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The meshes look fine individually. Wait \u2014 the issue: `full=merge(list(meshes.values()))` then I reassign `m.V` for scaling in place. But `full` already has a copy. That's fine. Then fix_normals on each m.\n\nBut wait, the error happened at line 31 which is inside the scaling loop `fix_normals(m)`. The first mesh in dict is aA_steel. When I test aA_steel alone it's fine. But in build, aA_steel was merged twice: first `aA_steel = merge([blade_geo(), shank_geo()])` then `aA_steel = merge([aA_steel, screw])`. Double merge. Let me test that exact.\n\nActually the standalone test did exactly that triple merge and it was fine (50 verts). \n\nHmm wait, in the standalone I merged blade+shank+screw in ONE call. In build I do merge(blade,shank) then merge(that, screw). Should be same. Let me test the double-merge version.\n\nActually the difference: order of dict. The failing mesh \u2014 let me add per-mesh try/except to build.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8898226ee1e0a91d", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nimport numpy as np, traceback\nfrom geom import *\nSCREW=np.array([0.0,0.020,0.0]); target=np.array([0.06751428544521332,0.19996289908885956,0.009697046800283715])\naA_steel = merge([blade(xoff=0.0,zc=0.0,y0=0.002,y1=0.085), extrude_profile([(x,y) for (x,y) in plate_profile(-0.055,0.02,0.006,0.009)],0.0,0.003)])\nscrew=cylinder(0.0,0.0,0.0,0.0055,0.006,nseg=20)\naA_steel=merge([aA_steel,screw])\nprint('doublemerge len',len(aA_steel.V),'maxidx',max(max(f) for f in aA_steel.F))\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8898226ee1e0a91d", + "content": "doublemerge len 50 maxidx 49", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25888, + "completion_tokens": 560, + "cached_tokens": 24304, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 26448 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "02ea69f5", + "pi_parent_id": "38ff21bd", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rw9EwiMiV3Iah5ZnLIDxG6su", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 20, + "timestamp": "2026-10-21T17:10:49.478Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "That's fine too. So why does build_geom3 fail? The difference must be the local-originate step or scaling. Wait \u2014 in build, `fix_normals` is called AFTER scaling. Scaling multiplies coords but doesn't change indices. So indices same. But fix_normals on scaled mesh... indices still valid.\n\nWait, actually maybe the issue is different: in the standalone tests I never called the full build() function. Let me just add per-mesh error reporting directly to build_geom3.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-88603c6a95430ac6", + "function_name": "edit", + "arguments": { + "path": "/tmp/build_geom3.py", + "edits": [ + { + "oldText": " for k,m in meshes.items():\n m.V=[(x*scale[0], y*scale[1], z*scale[2]) for (x,y,z) in m.V]\n fix_normals(m)", + "newText": " for k,m in meshes.items():\n m.V=[(x*scale[0], y*scale[1], z*scale[2]) for (x,y,z) in m.V]\n print(k,'lenV',len(m.V),'maxidx',max(max(f) for f in m.F))\n fix_normals(m)" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-88603c6a95430ac6", + "content": "Successfully replaced 1 block(s) in /tmp/build_geom3.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 26474, + "completion_tokens": 278, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 26752 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "dc4be627", + "pi_parent_id": "08649aa4", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RBFnY2xSQdp2m4iKqkPlTJNC", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 21, + "timestamp": "2026-10-21T17:10:56.650Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run it with the debug print.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-952fec23979d392f", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 build_geom3.py 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-952fec23979d392f", + "content": "aA_steel lenV 50 maxidx 49\naA_gold lenV 280 maxidx 279\naB_steel lenV 10 maxidx 14\nTraceback (most recent call last):\n File \"/tmp/build_geom3.py\", line 39, in \n P, W = build()\n ^^^^^^^\n File \"/tmp/build_geom3.py\", line 32, in build\n fix_normals(m)\n File \"/tmp/geom.py\", line 138, in fix_normals", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 26782, + "completion_tokens": 53, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 26835 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c495c721", + "pi_parent_id": "fd4d727c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R3bd9vpFbGLBkG6nnpE4S2cz", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 22, + "timestamp": "2026-10-21T17:11:54.960Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Found it. aB_steel has lenV 10 but maxidx 14! Because aB_steel = merge([blade_geo(), shank_geo()]) \u2014 but blade_geo() and shank_geo() call functions that return fresh meshes each time, so that's fine. Wait, aA_steel got 50 (with screw) and aB_steel got 10? That means aB_steel only has 10 verts = just one extrude (shank is 10 verts: 5+5). So the blade didn't merge into aB_steel!\n\nOh I see \u2014 aA_steel = merge([blade, shank]) = 20 verts, then +screw=40 \u2192 60? No it shows 50. Hmm 50 = 20 (blade+shank) + ... no. Let me recompute: blade extrude = 10 verts, shank extrude = 10 verts, screw = 40 verts. merge = 60. But aA_steel shows 50. And aB_steel shows 10.\n\nWait, that's weird. aA_steel = 50, aB_steel = 10. The difference is the screw (40 verts) only added to A. 50-40=10, and 10 = blade(10)+shank(10)? No, that's 20.\n\nHmm. blade_geo() returns blade() which is extrude of 5-pt profile = 10 verts. shank = 10 verts. merge = 20. So aA_steel before screw = 20, +screw 40 = 60. But shows 50. And aB_steel shows 10, maxidx 14 (14>=10 \u2192 error).\n\nThe problem: `merge` mutates? Let me check geom.merge. It creates new Mesh m, extends V, adds faces with base offset. That's fine. But blade_geo() calls blade() which... let me check if blade or the module-level functions share state. No.\n\nWait \u2014 maybe blade() with mid=True default... plate_profile returns 5 points only if mid=True. blade() calls plate_profile(y0,y1,w0,w1) with default mid=True \u2192 5 points \u2192 extrude 10 verts. OK.\n\nSo merge(blade,shank) = 20 verts, faces referencing 0-19. Then merge(that, screw 40) = 60 verts.\n\nBut aA_steel shows 50?? and aB_steel shows 10 with maxidx 14. \n\n50 = 10 + 40. So aA_steel = 10 + 40 = only ONE extrude (10) + screw(40). So merge([blade,shank]) gave only 10 verts not 20?! That means one of them is empty or shared.\n\nAnd aB_steel = merge([blade,shank]) = 10 verts maxidx 14. So merge(blade,shank) = 10 verts with maxidx 14?? That means the second mesh's faces weren't offset correctly, OR one mesh is 10 and the other 0... 10 verts total but maxidx 14.\n\nOh! I bet `merge` is buggy. Let me re-read geom.merge:\n\n```\ndef merge(ms):\n m=Mesh()\n for x in ms:\n base=len(m.V)\n m.V.extend(x.V)\n for f in x.F:\n m.F.append(tuple(i+base for i in f))\n return m\n```\nThis looks correct. base is computed per mesh. For merge([blade,shank]): blade base=0 (0-9), shank base=10 (10-19). Total 20 verts, maxidx 19. \n\nBut we got 10 verts maxidx 14. That means shank had 0 verts?? Or blade had 10 and shank had 0.\n\nWait, maybe blade_geo() and shank_geo() \u2014 the `shank` variable name conflicts? In build I defined `def shank_geo()`. In make... no.\n\nHold on \u2014 in build, `aA_steel = merge([blade_geo(), shank_geo()])`. But there's ALSO a global name `shank`? No. Let me just test directly.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a2ebc22b26d60a56", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nfrom geom import *\nb=blade(xoff=0.0,zc=0.0,y0=0.002,y1=0.085); print('blade',len(b.V),len(b.F))\ns=extrude_profile([(x,y) for (x,y) in plate_profile(-0.055,0.02,0.006,0.009)],0.0,0.003); print('shank',len(s.V),len(s.F))\nmm=merge([b,s]); print('merged',len(mm.V),len(mm.F),'maxidx',max(max(f) for f in mm.F))\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a2ebc22b26d60a56", + "content": "blade 5 11\nshank 5 11\nmerged 10 22 maxidx 14", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 26977, + "completion_tokens": 1183, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 28160 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "0c3eb9f5", + "pi_parent_id": "eb36ca5d", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RzAvCgxAiSMzpnyqrUHBGahh", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 23, + "timestamp": "2026-10-21T17:12:28.331Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The blade has only 5 verts! plate_profile with mid=True returns... let me check. plate_profile(-0.055, 0.02, 0.006, 0.009):\n```\npts.append((-w0,y0)) # 1\nif mid: pts.append((-w1,(y0+y1)/2.0)) # 2\npts.append((0.0,y1)) # 3\nif mid: pts.append((w1,(y0+y1)/2.0)) # 4\npts.append((w0,y0)) # 5\n```\n5 points. extrude \u2192 10 verts. But blade shows 5 verts! \n\nOh, `blade()` calls `plate_profile(y0,y1,w0,w1)`. Let me check blade signature: `def blade(xoff, zc, y0=0.0, y1=0.085, w0=0.0075, w1=0.0045, th=0.0028)`. It calls `plate_profile(y0,y1,w0,w1)`. plate_profile signature: `plate_profile(y0,y1,w0,w1, mid=True)`. OK 5 pts.\n\nBut blade returns 5 verts and 11 faces. 5 verts 11 faces = it's NOT extruded, it's just... a fan? 5 verts, 11 faces. That's a single polygon fan (4 triangles) plus... 11 faces is a lot for 5 verts.\n\nWait, extrude_profile with n=5: adds 5 B + 5 T = 10 verts. But blade shows 5 verts. So extrude_profile isn't being called, or plate_profile returns... \n\nOh! I think `blade` and `plate_profile` \u2014 maybe there's a name shadowing. Let me look: in geom.py, `def blade(xoff, zc, ...)`. It calls plate_profile. Returns extrude_profile(...). Should be 10 verts.\n\nUnless plate_profile returns only... Let me check: is `mid` defaulting? In blade I call `plate_profile(y0,y1,w0,w1)` \u2014 4 args, mid defaults True. 5 points.\n\n5 verts 11 faces... that's weird. 11 faces from 5 verts. Let me look \u2014 maybe extrude_profile with n=5: bottom fan (n-2=3 faces), top fan (3 faces), sides (5 quads) = 11 faces! Yes 3+3+5=11 faces. But that needs 10 verts. Yet len(V)=5.\n\nSo V has 5 but F references up to 14? No, maxidx in merged was 14 with 10 verts. So each sub-mesh: blade 5 verts? No \u2014 merged shows 10 verts total for two meshes each \"5 verts\". So blade=5, shank=5, merged=10. But faces: blade 11, shank 11. For a 5-vert mesh to have 11 faces with maxidx... in merged (10 verts), blade faces 0-? and shank offset by 5.\n\nWait this means extrude_profile only added 5 verts not 10. Let me check add_v: `def add_v(self,pts): base=len(self.V); for p in pts: append; return base`. In extrude: `b0=m.add_v(B); t0=m.add_v(T)`. B has 5, T has 5 \u2192 should add 10.\n\nUnless B and T are same length 5 each \u2192 10 total. So why 5?\n\nLet me actually print extrude directly.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8192c7231491f54b", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nfrom geom import *\nprof=plate_profile(0.002,0.085,0.0075,0.0045)\nprint('profile pts',len(prof),prof)\ne=extrude_profile(prof, 0.0, 0.0028)\nprint('extrude verts',len(e.V),'faces',len(e.F),'maxidx',max(max(f) for f in e.F))\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8192c7231491f54b", + "content": "profile pts 5 [(-0.0075, 0.002), (-0.0045, 0.043500000000000004), (0.0, 0.085), (0.0045, 0.043500000000000004), (0.0075, 0.002)]\nextrude verts 5 faces 11 maxidx 9", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 28202, + "completion_tokens": 970, + "cached_tokens": 17248, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 29172 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "6e7e4bbf", + "pi_parent_id": "a6f2d9e9", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RFPPOacUoyKZIY60viRRZ30J", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 24, + "timestamp": "2026-10-21T17:12:42.193Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "extrude_profile gives 5 verts but faces reference up to 9! So `m.add_v(B)` and `m.add_v(T)` \u2014 B and T have 5 each, but only 5 total verts. That means add_v isn't appending both. Let me look at Mesh.add_v:\n\n```\ndef add_v(self,pts):\n base=len(self.V)\n for p in pts:\n self.V.append((float(p[0]),float(p[1]),float(p[2])))\n return base\n```\nThis appends len(pts) verts. For B (5) \u2192 appends 5, V len 5, returns 0. For T (5) \u2192 appends 5, V len 10, returns 5. So t0=5. Should be 10 verts.\n\nBut it shows 5. So extrude_profile's B and T... let me check: \n```\nB=[(x, y, zb) for (x,y) in profile_xy]\nT=[(x, y, zt) for (x,y) in profile_xy]\n```\n5 each. add_v(B)\u21925, add_v(T)\u219210. \n\nUnless Mesh() __init__... Let me check the actual file \u2014 maybe my write got mangled. Let me re-read geom.py Mesh class.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9baf62ee1bd5948d", + "function_name": "read", + "arguments": { + "path": "/tmp/geom.py", + "limit": 40 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9baf62ee1bd5948d", + "content": "import numpy as np\n\ndef cross(a,b):\n return np.cross(a,b)\n\ndef _norm(v):\n n=np.linalg.norm(v)\n return v/n if n>1e-12 else np.array([0,0,1.0])\n\nclass Mesh:\n def __init__(self):\n self.V=[] # list of (x,y,z)\n self.F=[] # list of face index tuples\n def add_v(self,pts):\n base=len(self.V)\n for p in pts:\n self.V.append((float(p[0]),float(p[1]),float(p[2])))\n return base\n def add_face(self, idxs):\n self.F.append(tuple(idxs))\n def add_faces(self, faces):\n for f in faces: self.F.append(tuple(f))\n\ndef extrude_profile(profile_xy, z, th):\n \"\"\"profile_xy: list of (x,y) CCW (viewed from +Z). Extrude in Z around zc=z, thickness th.\"\"\"\n m=Mesh()\n n=len(profile_xy)\n zb=z-th/2.0; zt=z+th/2.0\n B=[(x, y, zb) for (x,y) in profile_xy]\n T=[(x, y, zt) for (x,y) in profile_xy]\n b0=m.add_v(B); t0=b0+n\n # bottom face (outward -Z): reverse winding\n for i in range(1,n-1):\n m.add_face((b0+0,b0+i+1,b0+i))\n # top face (outward +Z)\n for i in range(1,n-1):\n m.add_face((t0+0,t0+i,t0+i+1))\n # side walls\n for i in range(n):\n j=(i+1)%n\n\n[127 more lines in file. Use offset=41 to continue.]", + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 29308, + "completion_tokens": 332, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 29640 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "13022f46", + "pi_parent_id": "eb3f09f8", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RbIfNURHcv2kDQj1szmkJak7", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 25, + "timestamp": "2026-10-21T17:12:54.833Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The file looks correct. Let me actually debug the extrude directly with a fresh Mesh to see why only 5 verts.\n\nWait, the printed `extrude verts 5` but the code adds 10. Let me re-run in a clean process and print len at each step.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-93fe2d351a62d86f", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nimport geom\nprint(geom.Mesh.add_v.__module__ if hasattr(geom.Mesh.add_v,'__module__') else '')\nm=geom.Mesh()\nprint('after B', )\nb0=m.add_v([(0,0,0),(1,0,0),(2,0,0)])\nprint('len after first add_v(3):',len(m.V))\nt0=m.add_v([(0,0,1),(1,0,1),(2,0,1)])\nprint('len after second add_v(3):',len(m.V))\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-93fe2d351a62d86f", + "content": "geom\nafter B\nlen after first add_v(3): 3\nlen after second add_v(3): 6", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 30097, + "completion_tokens": 227, + "cached_tokens": 29008, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 30324 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "92f6030e", + "pi_parent_id": "fc1fe18f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RzRtT9yAXeQGWtZE3SdAKkgm", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 26, + "timestamp": "2026-10-21T17:13:15.496Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "So add_v works correctly (3, then 6). So why does extrude_profile give 5 verts? Let me re-run the extrude and print m.V length step by step.\n\nWait \u2014 maybe there's a stale .pyc or the running file differs. Let me check: I wrote geom.py with `write`. The read shows correct content. Let me just call extrude_profile and inspect m.V directly by inlining the function.\n\nActually wait \u2014 earlier test: `e=extrude_profile(prof, 0.0, 0.0028)` \u2192 5 verts, 11 faces, maxidx 9. 11 faces and maxidx 9 means faces reference index 9, but only 5 verts. So add_v only added 5 not 10. But my direct test adds correctly.\n\nDifference: in extrude_profile, B and T are lists of 3-tuples. In my direct test I used 3-tuples too. Same. \n\nOH WAIT. I bet the issue: I re-wrote geom.py but maybe there's a DIFFERENT extrude being imported. Let me check `geom.extrude_profile` source via inspect.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8d442071ccedf524", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && rm -f __pycache__ -rf && python3 -c \"\nimport inspect, geom\nprint(inspect.getsource(geom.extrude_profile))\n\" 2>&1 | head -30" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8d442071ccedf524", + "content": "def extrude_profile(profile_xy, z, th):\n \"\"\"profile_xy: list of (x,y) CCW (viewed from +Z). Extrude in Z around zc=z, thickness th.\"\"\"\n m=Mesh()\n n=len(profile_xy)\n zb=z-th/2.0; zt=z+th/2.0\n B=[(x, y, zb) for (x,y) in profile_xy]\n T=[(x, y, zt) for (x,y) in profile_xy]\n b0=m.add_v(B); t0=b0+n\n # bottom face (outward -Z): reverse winding\n for i in range(1,n-1):\n m.add_face((b0+0,b0+i+1,b0+i))\n # top face (outward +Z)\n for i in range(1,n-1):\n m.add_face((t0+0,t0+i,t0+i+1))\n # side walls\n for i in range(n):\n j=(i+1)%n\n m.add_face((b0+i,b0+j,t0+j,t0+i))\n return m", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 30365, + "completion_tokens": 328, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 30693 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "9653eab8", + "pi_parent_id": "1e4c82c6", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RIaOEh80TssrzhZ7aFZ74otH", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 27, + "timestamp": "2026-10-21T17:13:23.542Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The source is correct and should add 10 verts. Let me just run it directly and count.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8b56828ec4209165", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nimport geom\ne=geom.extrude_profile([(0,0),(1,0),(1,1),(0,1)],0.0,0.1)\nprint('verts',len(e.V))\nfor v in e.V: print(v)\n\" 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8b56828ec4209165", + "content": "verts 4\n(0.0, 0.0, -0.05)\n(1.0, 0.0, -0.05)\n(1.0, 1.0, -0.05)\n(0.0, 1.0, -0.05)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 30970, + "completion_tokens": 121, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 31091 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2b0ca92f", + "pi_parent_id": "c64a6724", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R3P4G0w5q8a8HVFNsmvboUo6", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 28, + "timestamp": "2026-10-21T17:13:46.123Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Found it: `extrude_profile` never calls `m.add_v(T)`. Let me fix it.", + "reasoning_content": "Only 4 verts added (just B, the bottom)! T was not added. So `m.add_v(T)` isn't appending. But my direct test with two add_v calls worked (3 then 6). \n\nThe difference: in extrude_profile, `b0=m.add_v(B); t0=b0+n` \u2014 wait, that's ONE statement. Then it never calls m.add_v(T)! Let me re-read... The source shows:\n```\nb0=m.add_v(B); t0=b0+n\n```\nIt computes t0 = b0+n but NEVER calls m.add_v(T)! There's no `m.add_v(T)` line! So T verts are never added. That's the bug \u2014 only B (bottom) verts are added, T assumed at offset but not present.\n\nSo the mesh only has the bottom ring verts. The faces reference top verts (t0..t0+n-1) which don't exist. That's why maxidx > vertcount.\n\nI need to add `m.add_v(T)`. Let me fix geom.py.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-96d0850275ee2283", + "function_name": "edit", + "arguments": { + "path": "/tmp/geom.py", + "edits": [ + { + "oldText": " b0=m.add_v(B); t0=b0+n\n # bottom face", + "newText": " b0=m.add_v(B); t0=m.add_v(T)\n # bottom face" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-96d0850275ee2283", + "content": "Successfully replaced 1 block(s) in /tmp/geom.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 31177, + "completion_tokens": 343, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 31520 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "b08d3d24", + "pi_parent_id": "4ff54856", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RnKVAYGPf8oAAt6CNjZyqyQ4", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 29, + "timestamp": "2026-10-21T17:13:50.981Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me rerun build_geom3.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-945438473c24c019", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 build_geom3.py 2>&1 | head" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-945438473c24c019", + "content": "aA_steel lenV 60 maxidx 59\naA_gold lenV 280 maxidx 279\naB_steel lenV 20 maxidx 19\naB_gold lenV 280 maxidx 279\nfinal size [0.06751429 0.1999629 0.00969705] min [-0.03375714 -0.12714728 -0.00484852] max [0.03375714 0.07281562 0.00484852]\naA_steel 60 verts 44 faces\naA_gold 280 verts 280 faces\naB_steel 20 verts 22 faces\naB_gold 280 verts 280 faces\nW [np.float64(-0.0), np.float64(0.027165828027478127), np.float64(-0.0)]", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 31549, + "completion_tokens": 52, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 31601 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "e3b27438", + "pi_parent_id": "6012591f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RM0fs80mtNpOiV5EUHoGCvhC", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 30, + "timestamp": "2026-10-21T17:16:08.125Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "The geometry bug is fixed and dimensions match exactly. Now let me write the full USD authoring script.", + "reasoning_content": "Now the geometry is correct. Final size matches target exactly. Now let me write the USD authoring script.\n\nLet me now author the full USD. I need to be careful about SimReady requirements. Let me write a comprehensive authoring script.\n\nStructure:\n```\n/ (meters)\n /Scissors (Xform) -- root model, at origin\n /Scissors/ArmA (Xform) [RigidBodyAPI, mass, etc]\n /Scissors/ArmA/Steel (Mesh) [MeshCollisionAPI, steel material]\n /Scissors/ArmA/Gold (Mesh) [MeshCollisionAPI, gold material]\n /Scissors/ArmB (Xform) [RigidBodyAPI]\n /Scissors/ArmB/Steel (Mesh) [MeshCollisionAPI, steel material]\n /Scissors/ArmB/Gold (Mesh) [MeshCollisionAPI, gold material]\n /Scissors/Joints/RevoluteA (RevoluteJoint)\n /materials (Materials)\n```\n\nBoth arms positioned at W (world offset). Their local origins = screw. Revolute joint connects ArmA & ArmB at local (0,0,0) each, axis Z.\n\nLet me now think about SimReady compliance for the 46 mandatory requirements. Let me recall the NVIDIA SimReady requirements for Robotics-Prop profile:\n\n- HI.001: Hierarchy - single root, no empty containers? Actually hierarchy requirements.\n- HI.003, HI.004: ?\n- AA.001, AA.002: assets (proper asset structure)\n- NP.002-008: ?\n- RB.001, RB.007, RB.010: rigid body requirements\n- RB.COL.001-004: collision\n- SL.001-003: ?\n- SL.MAT.001, SL.QCODE.001, SL.TIME.001\n- SR.002, SR.004\n- UN.006, UN.007: units\n- VG.002, VG.008, VG.014, VG.025, VG.027, VG.028, VG.029, VG.MESH.001\n- VM.MAT.001, VM.PS.001, VM.PS.002, VM.TEX.001, VM.TEX.003, VM.BIND.001\n\nI don't remember exact text of each. The best strategy is to build a clean, complete asset, validate, read the report, and fix specific failures. I have 5 validation calls and 35 rounds. Let me build a solid first version.\n\nLet me recall typical SimReady robotics-prop mandatory requirements (from NVIDIA Omniverse SimReady):\n\nRigid body / physics:\n- RB.001: Rigid body must have mass (or massProperties) \n- RB.COL.001: Colliders must have valid geometry\n- RB.COL.002: \n- RB.COL.003: \n- RB.COL.004:\n- RB.007: \n- RB.010: \n\nUnits:\n- UN.006: metersPerUnit set (meters)\n- UN.007: \n\nMaterials (VM = visual material):\n- VM.MAT.001: materials use valid/preview surface\n- VM.BIND.001: every mesh has a material bound\n- VM.PS.001: ?\n- VM.PS.002: \n- VM.TEX.001: textures\n- VM.TEX.003: \n\nVG (visual geometry):\n- VG.002: ?\n- VG.008: \n- VG.014: \n- VG.025: \n- VG.027/028/029: normals/UVs\n- VG.MESH.001: mesh valid\n\nSL = ? maybe \"shape/structural\"? SL.MAT.001 = material on mesh, SL.QCODE.001 = QR code (SimReady assets require a QCode texture? No...). Actually QCode might be about a QR. Hmm. SL.TIME.001 = time.\n\nI'll build and validate to see. Let me focus on a clean, complete, well-formed asset with:\n1. Meters units (customLayerData metersPerUnit=1)\n2. Two rigid bodies with RigidBodyAPI + massPropertiesMode=mass + mass, density\n3. Mesh colliders (MeshCollisionAPI with convexHull or mesh collider)\n4. Revolute joint with two bodies, axis, limits\n5. Two materials (steel, gold) as PreviewSurface with metallic/roughness\n6. Materials bound to all meshes\n7. Proper names (valid, no leading underscore, no spaces)\n8. Normal computation\n\nLet me write the authoring script. I'll create a helper to build a mesh prim from V,F.\n\nFor mesh collision, UsdPhysics.MeshCollisionAPI on the Mesh prim. Set `collidable` / it's implied. Also set `UsdPhysics.MeshCollisionAPI` with default convex decomposition? For a prop, convex hull is typical. I'll use MeshCollisionAPI (creates a mesh collider). To be safe, use `UsdPhysics.MeshCollisionAPI.Apply` which makes the mesh a collider with convexHulls=true by default? Actually MeshCollisionAPI has no params; it just marks the mesh as a collider (uses triangulated convex decomposition). That's fine.\n\nActually, better for physics: apply UsdPhysics.MeshCollisionAPI to each mesh. That's standard.\n\nFor the rigid body: RigidBodyAPI on the Arm Xform. Set:\n- `rigidBody:enabled` = True\n- `rigidBody:massPropertiesMode` = \"massAndInertia\" or \"mass\" or \"auto\"\n- `rigidBody:mass` = some value (e.g., 0.05 kg)\n- `rigidBody:density` = 7800 (steel) \u2014 for auto mode\n\nLet me set massPropertiesMode=\"auto\" with density, so inertia is computed. Actually \"auto\" computes mass from density and volume. That's realistic. Let me set density=7800 (steel) for the whole body \u2014 but arm has gold+steel. Average density ~ use 8000. Set massPropertiesMode=\"auto\", density=8000.\n\nHmm but \"auto\" requires the collider to have volume (convex). Should be fine.\n\nLet me also add `UsdPhysics.CollisionAPI` on colliders (enabled). MeshCollisionAPI includes CollisionAPI.\n\nFor the revolute joint:\n- UsdPhysics.RevoluteJoint\n- joint:body1 = /Scissors/ArmA\n- joint:body2 = /Scissors/ArmB\n- joint:localPosition1 = (0,0,0)\n- joint:localPosition2 = (0,0,0)\n- joint:localRotation1 = identity\n- joint:localRotation2 = identity\n- joint:axis = (0,0,1)\n- joint:lowerAngleLimit = -1.0\n- joint:upperAngleLimit = 1.0\n\nWait, the joint axis is in the joint's frame. For a revolute joint, axis is a vector property `joint:axis`. Let me set axis=(0,0,1).\n\nNow the bodies: ArmA and ArmB are Xforms with RigidBodyAPI. The joint body1/body2 reference the prim with RigidBodyAPI. Good.\n\nBut wait \u2014 both bodies are dynamic and connected only to each other via one revolute joint. There's no ground constraint. The whole assembly would free-fall in sim. For a prop, that might be flagged. But scissors genuinely float in hand. SimReady robotics prop \u2014 I think it's fine to have free bodies. But to be safe and realistic (scissors held at pivot), I could add a fixed joint or make one body static. Hmm.\n\nActually the kinematic fidelity wants the correct joint (revolute at pivot). Free-fall is physically how scissors behave when not held. I'll leave them as dynamic bodies with the revolute joint. That's the honest mechanical model.\n\nActually, wait. Let me reconsider whether to make the screw a separate thing. I merged screw into Arm A steel. So Arm A has the screw head. Good, 2 bodies.\n\nNow, one concern: the two arms currently intersect (the blades overlap in Z, rings overlap in X). At rest they interpenetrate slightly. For a closed scissors that's realistic (blades touch). Should be OK.\n\nLet me also consider: should the joint allow the arms to actually open without collision? With the current closed pose, opening rotates them apart. Fine.\n\nLet me now also handle the \"up axis\". The object's thin axis is Z. SimReady/USD default upAxis... USD doesn't mandate. NVIDIA SimReady uses +Y up typically? Actually the canonical dims given X,Y,Z with Z=thickness suggests the flat plane is XY. If up-axis is Z that's fine for this object. I won't set upAxis explicitly (leave default). Actually many requirements might want an up-axis declaration. Let me not worry; validate will tell me.\n\nLet me write the authoring script now. I'll bind materials, set units, and save to /output/asset.usd.\n\nFor materials, use UsdShade / UsdPreviewSurface:\n- steel: metallic=1.0, roughness=0.25, baseColor=(0.85,0.86,0.88)\n- gold: metallic=1.0, roughness=0.35, baseColor=(0.85,0.64,0.30)\n\nCreate material prims in a /materials container with MaterialAPI + UsdPreviewSurface, and bind to meshes with MaterialBindingAPI (bind to mesh prim).\n\nLet me write it.\n\nFor mesh creation, I'll create UsdGeomMesh, set point vertex indices (faces), points, and normals. I should compute normals. Let me compute per-vertex normals in the build. Actually I can let USD compute, but better to provide normals. Let me compute smooth-ish normals: average of face normals per vertex. I'll add a normal computation.\n\nActually VG.MESH.001 might just require valid mesh. Normals (VG.027/028/029) might require explicit normals or UVs. Let me add normals and UVs to be safe. UVs: simple planar projection.\n\nLet me write a robust authoring script.\n\nLet me compute vertex normals in Python.\n\nLet me write /tmp/author.py.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-85178e2625fcfb36", + "function_name": "write", + "arguments": { + "content": "import numpy as np, pickle, sys\nsys.path.insert(0,'/tmp')\nfrom pxr import Usd, UsdGeom, UsdPhysics, UsdShade, Sdf, Gf, Gf, Vt\n\nd=pickle.load(open(\"/tmp/parts.pkl\",\"rb\"))\nparts=d[\"parts\"]; W=np.array(d[\"W\"])\n\nstage=Usd.Stage.CreateInMemory()\nstage.SetDefaultPrim(Usd.SprimRootPath())\n# units: meters\nstage.GetRootLayer().customLayerData[\"metersPerUnit\"]=1.0\nstage.GetRootLayer().customLayerData[\"upAxis\"]=\"Z\"\n\nroot=UsdGeom.Xform.Define(stage, \"/Scissors\")\n\n# ---- materials ----\ndef make_mat(path, name, base, metal, rough):\n mat=UsdShade.Material.Define(stage, path)\n mat.CreateInfo().SetMaterialType(UsdShade.MATERIAL_API_SCHEMA_TOKEN if False else Sdf.Token(\"preload\"))\n sp=UsdShade.Shader.Define(stage, path+\"/surface\")\n sp.CreateIdAttr(\"UsdPreviewSurface\")\n sp.CreateInput(\"baseColor\", Vt.Vector3f(base[0],base[1],base[2]))\n sp.CreateInput(\"metallic\", Vt.Float(metal))\n sp.CreateInput(\"roughness\", Vt.Float(rough))\n mat.CreateSurfaceOutput().ConnectToSource(sp.ConnectableAPI(), \"surface\")\n return mat\n\nsteel=make_mat(\"/Materials/Steel\",\"Steel\",(0.86,0.87,0.89),1.0,0.22)\ngold =make_mat(\"/Materials/Gold\",\"Gold\",(0.85,0.62,0.28),1.0,0.34)\n\n# ---- mesh builder ----\ndef vnormals(V,F):\n V=np.array(V,float); N=np.zeros_like(V)\n for f in F:\n if len(f)<3: continue\n a,b,c=V[f[0]],V[f[1]],V[f[2]]\n n=np.cross(b-a,c-a); nn=np.linalg.norm(n)\n if nn<1e-12: continue; n/=nn\n for i in f: N[i]+=n\n nn=np.linalg.norm(N,axis=1,keepdims=True); nn[nn<1e-12]=1\n return N/nn\n\ndef planar_uv(V):\n a=np.array(V); mn=a.min(0); mx=a.max(0); r=mx-mn; r[r<1e-9]=1\n return [( (x-mn[0])/r[0], (y-mn[1])/r[1]) for (x,y,z) in V]\n\ndef make_mesh(stage, path, V, F, mat):\n m=UsdGeom.Mesh.Define(stage, path)\n m.AddPointsAttr([Vt.Vector3f(x,y,z) for (x,y,z) in V])\n m.AddFaceVertexIndicesAttr([list(f) for f in F])\n m.AddVertexNormalsAttr([Vt.Vector3f(*n) for n in vnormals(V,F)])\n m.AddPrimvarsAttr(\"uv\", Sdf.Token(\"point\"),\n [Gf.Vec2f(*u) for u in planar_uv(V)])\n m.CreateSubdivisionsSchemeAttr(\"none\")\n m.GetPrim().GetAPIs()\n # material binding\n rel=m.CreateRelationshipsAttr(\"material:binding\") if False else None\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")\n return m\n\ndef make_collider(mesh_prim):\n UsdPhysics.MeshCollisionAPI.Apply(mesh_prim)\n\ndef make_rigidbody(xform, mass, density):\n rb=UsdPhysics.RigidBodyAPI.Apply(xform)\n rb.CreateKinematicEnabledAttr(False)\n rb.CreateMassPropertiesModeAttr(\"auto\")\n rb.CreateDensityAttr(float(density))\n rb.CreateMassAttr(float(mass))\n rb.CreateAverageDensityAttr(float(density))\n\n# Arm A (top blade + screw, gold ring)\narmA=UsdGeom.Xform.Define(stage, \"/Scissors/ArmA\")\nxformA=UsdGeom.Xformable(armA.GetPrim())\nxformA.AddTranslateOp().Set(Vt.Vector3f(*W))\nmake_rigidbody(armA, 0.06, 8500.0)\naA_st=make_mesh(stage,\"/Scissors/ArmA/Steel\",parts[\"aA_steel\"][0],parts[\"aA_steel\"][1],steel)\naA_gd=make_mesh(stage,\"/Scissors/ArmA/Gold\",parts[\"aA_gold\"][0],parts[\"aA_gold\"][1],gold)\nmake_collider(aA_st); make_collider(aA_gd)\n\n# Arm B\narmB=UsdGeom.Xform.Define(stage, \"/Scissors/ArmB\")\nxformB=UsdGeom.Xformable(armB.GetPrim())\nxformB.AddTranslateOp().Set(Vt.Vector3f(*W))\nmake_rigidbody(armB, 0.06, 8500.0)\naB_st=make_mesh(stage,\"/Scissors/ArmB/Steel\",parts[\"aB_steel\"][0],parts[\"aB_steel\"][1],steel)\naB_gd=make_mesh(stage,\"/Scissors/ArmB/Gold\",parts[\"aB_gold\"][0],parts[\"aB_gold\"][1],gold)\nmake_collider(aB_st); make_collider(aB_gd)\n\n# Revolute joint at the pivot screw (local origin of both arms), axis Z\nj=UsdPhysics.RevoluteJoint.Define(stage,\"/Scissors/Joints/Pivot\")\nj.CreateBody1Rel().SetTargets([armA.GetPrim()])\nj.CreateBody2Rel().SetTargets([armB.GetPrim()])\nj.CreateLocalPosition1Attr((0,0,0))\nj.CreateLocalPosition2Attr((0,0,0))\nj.CreateLocalRotation1Attr(())\nj.CreateLocalRotation2Attr(())\nj.CreateAxisAttr((0,0,1))\nj.CreateLowerAngleLimitAttr(-1.1)\nj.CreateUpperAngleLimitAttr(1.1)\n\nout=\"/output/asset.usd\"\nstage.Export(out)\nprint(\"exported\", out)\n", + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-85178e2625fcfb36", + "content": "Successfully wrote to /tmp/author.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 31885, + "completion_tokens": 3873, + "cached_tokens": 31360, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 35758 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "26d43469", + "pi_parent_id": "4ca02e16", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rgox6ZGWDLjHO2PoBptdHQ6x", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 31, + "timestamp": "2026-10-21T17:16:49.545Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Let me clean up the authoring script (remove messy leftover lines) before running.", + "reasoning_content": "I have a budget concern. Let me clean up the authoring script (there's some messy leftover code) and run it. Let me fix the make_mat \u2014 I used a weird SetMaterialType call. Let me simplify. Let me rewrite author.py cleanly.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8a9881d96fad7c00", + "function_name": "write", + "arguments": { + "content": "import numpy as np, pickle, sys\nsys.path.insert(0,'/tmp')\nfrom pxr import Usd, UsdGeom, UsdPhysics, UsdShade, Sdf, Gf, Vt\n\nd=pickle.load(open(\"/tmp/parts.pkl\",\"rb\"))\nparts=d[\"parts\"]; W=np.array(d[\"W\"])\n\nstage=Usd.Stage.CreateInMemory()\n# units: meters, up axis Z (thin axis)\nstage.GetRootLayer().customLayerData[\"metersPerUnit\"]=1.0\nstage.GetRootLayer().customLayerData[\"upAxis\"]=\"Z\"\n\nroot=UsdGeom.Xform.Define(stage, \"/Scissors\")\n\ndef make_mat(path, base, metal, rough):\n mat=UsdShade.Material.Define(stage, path)\n sp=UsdShade.Shader.Define(stage, path+\"/surface\")\n sp.CreateIdAttr(\"UsdPreviewSurface\")\n sp.CreateInput(\"baseColor\", Vt.Vector3f(base[0],base[1],base[2]))\n sp.CreateInput(\"metallic\", Vt.Float(metal))\n sp.CreateInput(\"roughness\", Vt.Float(rough))\n mat.CreateSurfaceOutput().ConnectToSource(sp.ConnectableAPI(), \"surface\")\n return mat\n\nsteel=make_mat(\"/Materials/Steel\",(0.86,0.87,0.89),1.0,0.22)\ngold =make_mat(\"/Materials/Gold\",(0.85,0.62,0.28),1.0,0.34)\n\ndef vnormals(V,F):\n V=np.array(V,float); N=np.zeros_like(V)\n for f in F:\n if len(f)<3: continue\n a,b,c=V[f[0]],V[f[1]],V[f[2]]\n n=np.cross(b-a,c-a); nn=np.linalg.norm(n)\n if nn<1e-12: continue; n/=nn\n for i in f: N[i]+=n\n nn=np.linalg.norm(N,axis=1,keepdims=True); nn[nn<1e-12]=1\n return N/nn\n\ndef planar_uv(V):\n a=np.array(V); mn=a.min(0); mx=a.max(0); r=mx-mn; r[r<1e-9]=1\n return [((x-mn[0])/r[0], (y-mn[1])/r[1]) for (x,y,z) in V]\n\ndef make_mesh(stage, path, V, F, mat):\n m=UsdGeom.Mesh.Define(stage, path)\n m.AddPointsAttr([Vt.Vector3f(x,y,z) for (x,y,z) in V])\n m.AddFaceVertexIndicesAttr([list(f) for f in F])\n m.AddVertexNormalsAttr([Vt.Vector3f(*n) for n in vnormals(V,F)])\n m.AddPrimvarsAttr(\"uv\", Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])\n m.CreateSubdivisionsSchemeAttr(\"none\")\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")\n return m\n\ndef make_collider(mesh_prim):\n UsdPhysics.MeshCollisionAPI.Apply(mesh_prim)\n\ndef make_rigidbody(xform, mass, density):\n rb=UsdPhysics.RigidBodyAPI.Apply(xform)\n rb.CreateKinematicEnabledAttr(False)\n rb.CreateMassPropertiesModeAttr(\"auto\")\n rb.CreateDensityAttr(float(density))\n rb.CreateMassAttr(float(mass))\n\ndef new_arm(path, st_key, gd_key):\n arm=UsdGeom.Xform.Define(stage, path)\n UsdGeom.Xformable(arm.GetPrim()).AddTranslateOp().Set(Vt.Vector3f(*W))\n make_rigidbody(arm, 0.06, 8500.0)\n st=make_mesh(stage,path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n gd=make_mesh(stage,path+\"/Gold\",parts[gd_key][0],parts[gd_key][1],gold)\n make_collider(st); make_collider(gd)\n return arm\n\narmA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\narmB=new_arm(\"/Scissors/ArmB\",\"aB_steel\",\"aB_gold\")\n\nj=UsdPhysics.RevoluteJoint.Define(stage,\"/Scissors/Joints/Pivot\")\nj.CreateBody1Rel().SetTargets([armA.GetPrim()])\nj.CreateBody2Rel().SetTargets([armB.GetPrim()])\nj.CreateLocalPosition1Attr((0,0,0))\nj.CreateLocalPosition2Attr((0,0,0))\nj.CreateLocalRotation1Attr(())\nj.CreateLocalRotation2Attr(())\nj.CreateAxisAttr((0,0,1))\nj.CreateLowerAngleLimitAttr(-1.1)\nj.CreateUpperAngleLimitAttr(1.1)\n\nout=\"/output/asset.usd\"\nstage.Export(out)\nprint(\"exported\", out)\n", + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8a9881d96fad7c00", + "content": "Successfully wrote to /tmp/author.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 35780, + "completion_tokens": 1269, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 37049 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "0a10ea26", + "pi_parent_id": "4ccf63c5", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RiC3cEcNAbLogybc9vMp94Ui", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 32, + "timestamp": "2026-10-21T17:16:53.744Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm aware of my budget. Let me run the authoring script.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-84af1ad587fc506f", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-84af1ad587fc506f", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 25, in \n steel=make_mat(\"/Materials/Steel\",(0.86,0.87,0.89),1.0,0.22)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 19, in make_mat\n sp.CreateInput(\"baseColor\", Vt.Vector3f(base[0],base[1],base[2]))\n ^^^^^^^^^^^\nAttributeError: module 'pxr.Vt' has no attribute 'Vector3f'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 37072, + "completion_tokens": 60, + "cached_tokens": 35280, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 37132 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "7dd35f0d", + "pi_parent_id": "45b6e1b1", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RiBpWZTMO6Y9N4eKrKzyqULn", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 33, + "timestamp": "2026-10-21T17:17:00.487Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Vt doesn't have Vector3f; it's Gf.Vec3f. Let me fix all Vt.Vector3f to Gf.Vec3f, Vt.Float stays (Vt.Float exists? Vt.Float is just float). Actually Vt.Float is fine. Vt.Vector3f \u2192 Gf.Vec3f.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8ac3422b75d3eb0f", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/Vt\\.Vector3f/Gf.Vec3f/g' author.py && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8ac3422b75d3eb0f", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 25, in \n steel=make_mat(\"/Materials/Steel\",(0.86,0.87,0.89),1.0,0.22)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 19, in make_mat\n sp.CreateInput(\"baseColor\", Gf.Vec3f(base[0],base[1],base[2]))\nBoost.Python.ArgumentError: Python argument types in\n Shader.CreateInput(Shader, str, Vec3f)\ndid not match C++ signature:\n CreateInput(pxrInternal_v0_26_8__pxrReserved__::UsdShadeShader {lvalue}, pxrInternal_v0_26_8__pxrReserved__::TfToken name, pxrInternal_v0_26_8__pxrReserved__::SdfValueTypeName type)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 37293, + "completion_tokens": 139, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 37432 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "ec7a1d36", + "pi_parent_id": "8c234a62", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RirpeV27o8wRhKfEVOFtXJGT", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 34, + "timestamp": "2026-10-21T17:17:31.988Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "CreateInput needs a type. Let me use sp.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color) or use CreateInput(name, type). Let me pass the type explicitly. For baseColor: Sdf.ValueTypeNames.Color or Vt.Vector3f type. Let me use the two-arg form CreateInput(name, type) then Set, or CreateInput with type. Simpler: use `sp.CreateInput(\"baseColor\", Sdf.ValueTypeNames.ColorRGBA)`? For preview surface baseColor is a Color. Let me use `Sdf.ValueTypeNames.Color`. Actually UsdPreviewSurface baseColor is a Color (3-component). Let me just create the input and set value.\n\nSimplest: `sp.CreateInput(\"baseColor\", Vt.Vector3f(...))` \u2014 but Vt.Vector3f doesn't exist. The value type is Vt.Color? Let me just use the two-arg CreateInput(name, typeName) then Set value.\n\nLet me define a helper set_input(sp, name, typeToken, value). For baseColor type = Sdf.ValueTypeNames.Color, value = Gf.Vec3f. metallic/roughness type = Sdf.ValueTypeNames.Float, value = float.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-95833d0422af4d30", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": " sp=UsdShade.Shader.Define(stage, path+\"/surface\")\n sp.CreateIdAttr(\"UsdPreviewSurface\")\n sp.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color).Set(Gf.Vec3f(base[0],base[1],base[2]))\n sp.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(float(metal))\n sp.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(float(rough))", + "oldText": " sp=UsdShade.Shader.Define(stage, path+\"/surface\")\n sp.CreateIdAttr(\"UsdPreviewSurface\")\n sp.CreateInput(\"baseColor\", Gf.Vec3f(base[0],base[1],base[2]))\n sp.CreateInput(\"metallic\", Vt.Float(metal))\n sp.CreateInput(\"roughness\", Vt.Float(rough))" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-95833d0422af4d30", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 37674, + "completion_tokens": 517, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 38191 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "d2081fbd", + "pi_parent_id": "4aed1a0b", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RD2jLLzQFb64t0KxNywk3eoQ", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 35, + "timestamp": "2026-10-21T17:17:37.131Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm on round 34. Let me run and iterate efficiently.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-84c2e1dd1c89ad2a", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-84c2e1dd1c89ad2a", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 25, in \n steel=make_mat(\"/Materials/Steel\",(0.86,0.87,0.89),1.0,0.22)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 19, in make_mat\n sp.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color).Set(Gf.Vec3f(base[0],base[1],base[2]))\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: type object 'ValueTypeNames' has no attribute 'Color'. Did you mean: 'Color3d'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 38220, + "completion_tokens": 60, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 38280 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "bf24b580", + "pi_parent_id": "2f8778ad", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RBfgSh9KmDBdubmXQaGlH6Tu", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 36, + "timestamp": "2026-10-21T17:17:40.334Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Use Color3f. Let me fix.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9c52d75396d13c0f", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/Sdf.ValueTypeNames.Color)/Sdf.ValueTypeNames.Color3f)/' author.py && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9c52d75396d13c0f", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 72, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 66, in new_arm\n make_rigidbody(arm, 0.06, 8500.0)\n File \"/tmp/author.py\", line 57, in make_rigidbody\n rb=UsdPhysics.RigidBodyAPI.Apply(xform)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nBoost.Python.ArgumentError: Python argument types in\n RigidBodyAPI.Apply(Xform)\ndid not match C++ signature:\n Apply(pxrInternal_v0_26_8__pxrReserved__::UsdPrim prim)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 38460, + "completion_tokens": 79, + "cached_tokens": 33712, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 38539 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "bfa2d4a1", + "pi_parent_id": "2b67a82c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RdqQwxVpL0VrdXeqytgQQVl3", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 37, + "timestamp": "2026-10-21T17:17:59.802Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "RigidBodyAPI.Apply expects a UsdPrim. I passed `arm` which is a UsdGeom.Xform. Need to pass arm.GetPrim(). Let me fix make_rigidbody calls: pass arm.GetPrim(). Actually in new_arm I call make_rigidbody(arm,...) where arm is Xform. Let me change to arm.GetPrim().", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8c5a56a95e5ec6f5", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/make_rigidbody(arm, 0.06, 8500.0)/make_rigidbody(arm.GetPrim(), 0.06, 8500.0)/' author.py && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8c5a56a95e5ec6f5", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 72, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 66, in new_arm\n make_rigidbody(arm.GetPrim(), 0.06, 8500.0)\n File \"/tmp/author.py\", line 59, in make_rigidbody\n rb.CreateMassPropertiesModeAttr(\"auto\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'RigidBodyAPI' object has no attribute 'CreateMassPropertiesModeAttr'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 38753, + "completion_tokens": 168, + "cached_tokens": 38416, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 38921 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "97ac9479", + "pi_parent_id": "93fabb10", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-ROec6G3rZL0Y0g8sw4Xh2rMb", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 38, + "timestamp": "2026-10-21T17:18:09.993Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The attribute name is `CreateMassPropertiesModeAttr`? Let me check the actual API. UsdPhysics.RigidBodyAPI has:\n- CreateMassPropertiesModeAttr()\n- CreateMassAttr()\n- CreateInertiaAttr()\n- CreateInertiaRotationAttr()\n- CreateAverageDensityAttr()\n- CreateDensityAttr()\n- CreateKinematicEnabledAttr()\n- CreateEnabledAttr()\n\nLet me check \u2014 maybe it's `CreateMassPropertiesModeAttr` exists but... the error says no attribute. Let me check the actual names.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8befd6dc882fecaf", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"from pxr import UsdPhysics; print([m for m in dir(UsdPhysics.RigidBodyAPI) if 'Create' in m or 'Set' in m or 'Get' in m])\" 2>&1 | tail" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8befd6dc882fecaf", + "content": "['CreateAngularVelocityAttr', 'CreateKinematicEnabledAttr', 'CreateRigidBodyEnabledAttr', 'CreateSimulationOwnerRel', 'CreateStartsAsleepAttr', 'CreateVelocityAttr', 'Get', 'GetAngularVelocityAttr', 'GetKinematicEnabledAttr', 'GetPath', 'GetPrim', 'GetRigidBodyEnabledAttr', 'GetSchemaAttributeNames', 'GetSchemaClassPrimDefinition', 'GetSchemaKind', 'GetSimulationOwnerRel', 'GetStartsAsleepAttr', 'GetVelocityAttr', '_GetStaticTfType']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 39100, + "completion_tokens": 200, + "cached_tokens": 38416, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 39300 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "dfd98084", + "pi_parent_id": "d0fb880e", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RGI6vDuhKsOkPGfcmA6tIWJH", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 39, + "timestamp": "2026-10-21T17:18:16.488Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The RigidBodyAPI here doesn't have mass attributes \u2014 those are in a separate API. In newer UsdPhysics, mass is via `UsdPhysics.MassAPI` and inertia via `UsdPhysics.MassAPI`. Actually there's `UsdPhysics.MassAPI` (mass, massPropertiesMode, averageDensity) and `UsdPhysics.MassProperties`? Let me check. There's `UsdPhysics.MassAPI` with CreateMassAttr, CreateMassPropertiesModeAttr, CreateAverageDensityAttr. And RigidBodyAPI has kinematicEnabled, rigidBodyEnabled, etc.\n\nAlso I should use CreateRigidBodyEnabledAttr (not the old \"enabled\").\n\nLet me check MassAPI.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8b47e97475acfb65", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"from pxr import UsdPhysics; print('MassAPI', [m for m in dir(UsdPhysics.MassAPI) if 'Create' in m])\" 2>&1 | tail" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8b47e97475acfb65", + "content": "MassAPI ['CreateCenterOfMassAttr', 'CreateDensityAttr', 'CreateDiagonalInertiaAttr', 'CreateMassAttr', 'CreatePrincipalAxesAttr']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 39429, + "completion_tokens": 224, + "cached_tokens": 38416, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 39653 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "63c9e5ff", + "pi_parent_id": "fbb7fbc0", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R1hzESgFedJgjHOfQAHGDFYO", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 40, + "timestamp": "2026-10-21T17:18:26.648Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 39 of 64, with 25 model rounds remaining. Let me be efficient. Let me fix the rigid body setup using MassAPI for mass/density and RigidBodyAPI for enabled/kinematic.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b3109a0c753070c0", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "def make_rigidbody(xform, mass, density):\n rb=UsdPhysics.RigidBodyAPI.Apply(xform)\n rb.CreateRigidBodyEnabledAttr(True)\n rb.CreateKinematicEnabledAttr(False)\n rb.CreateStartsAsleepAttr(False)\n ma=UsdPhysics.MassAPI.Apply(xform)\n ma.CreateDensityAttr(float(density))\n ma.CreateMassAttr(float(mass))", + "oldText": "def make_rigidbody(xform, mass, density):\n rb=UsdPhysics.RigidBodyAPI.Apply(xform)\n rb.CreateKinematicEnabledAttr(False)\n rb.CreateMassPropertiesModeAttr(\"auto\")\n rb.CreateDensityAttr(float(density))\n rb.CreateMassAttr(float(mass))" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b3109a0c753070c0", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 39701, + "completion_tokens": 265, + "cached_tokens": 39200, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 39966 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "f5c2968a", + "pi_parent_id": "ff63fd29", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RkX5m9B6Crx34X5FBUXriSw8", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 41, + "timestamp": "2026-10-21T17:18:47.681Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run the authoring script.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b5e31620bcd8d3b9", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b5e31620bcd8d3b9", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 74, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 69, in new_arm\n st=make_mesh(stage,path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 45, in make_mesh\n m.AddPointsAttr([Gf.Vec3f(x,y,z) for (x,y,z) in V])\n ^^^^^^^^^^^^^^^\nAttributeError: 'Mesh' object has no attribute 'AddPointsAttr'. Did you mean: 'GetPointsAttr'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 39995, + "completion_tokens": 53, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 40048 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c7f0d7c0", + "pi_parent_id": "cb2288f5", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RgYnb3744N0wSSLod14C4pGr", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 42, + "timestamp": "2026-10-21T17:19:13.060Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "UsdGeom.Mesh uses `DefinePointsAttr` not `AddPointsAttr` (AddPointsAttr is on UsdGeom points-based... actually Mesh has `DefinePointsAttr`, `DefineFaceVertexIndicesAttr`, `DefineNormalsAttr`, `DefineFaceVertexNormalsAttr`). Let me use Define* methods.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-82bdf3f4b4593b00", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": " m=UsdGeom.Mesh.Define(stage, path)\n m.DefinePointsAttr([Gf.Vec3f(x,y,z) for (x,y,z) in V])\n m.DefineFaceVertexIndicesAttr([list(f) for f in F])\n m.DefineNormalsAttr([Gf.Vec3f(*n) for n in vnormals(V,F)])\n m.AddPrimvarsAttr(\"uv\", Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])\n m.CreateSubdivisionsSchemeAttr(\"none\")", + "oldText": " m=UsdGeom.Mesh.Define(stage, path)\n m.AddPointsAttr([Gf.Vec3f(x,y,z) for (x,y,z) in V])\n m.AddFaceVertexIndicesAttr([list(f) for f in F])\n m.AddVertexNormalsAttr([Vt.Vector3f(*n) for n in vnormals(V,F)])\n m.AddPrimvarsAttr(\"uv\", Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])\n m.CreateSubdivisionsSchemeAttr(\"none\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-82bdf3f4b4593b00", + "content": "Could not find the exact text in /tmp/author.py. The old text must match exactly including all whitespace and newlines.", + "extra": { + "tool_name": "edit", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 40266, + "completion_tokens": 386, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 40652 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "064d1b41", + "pi_parent_id": "9c99b05c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R5eqV0lvJZeXabbiwcvuWiAL", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 43, + "timestamp": "2026-10-21T17:19:22.437Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 42 of 64, 22 model rounds remain. Let me be efficient. Let me view the current author.py and fix the mesh attributes.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b7c6f82eee0b66d9", + "function_name": "read", + "arguments": { + "path": "/tmp/author.py", + "offset": 44, + "limit": 8 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b7c6f82eee0b66d9", + "content": "m=UsdGeom.Mesh.Define(stage, path)\n m.AddPointsAttr([Gf.Vec3f(x,y,z) for (x,y,z) in V])\n m.AddFaceVertexIndicesAttr([list(f) for f in F])\n m.AddVertexNormalsAttr([Gf.Vec3f(*n) for n in vnormals(V,F)])\n m.AddPrimvarsAttr(\"uv\", Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])\n m.CreateSubdivisionsSchemeAttr(\"none\")\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")\n return m\n\n[40 more lines in file. Use offset=52 to continue.]", + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 40693, + "completion_tokens": 92, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 40785 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "bb10974d", + "pi_parent_id": "09f0972b", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RPgkdyB9gtSFPjc0HJ9R0Oa1", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 44, + "timestamp": "2026-10-21T17:19:29.096Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me fix these lines using sed to be efficient.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9018f4246b8f3eb2", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i \\\n -e 's/m.AddPointsAttr(/m.DefinePointsAttr(/' \\\n -e 's/m.AddFaceVertexIndicesAttr(/m.DefineFaceVertexIndicesAttr(/' \\\n -e 's/m.AddVertexNormalsAttr(/m.DefineNormalsAttr(/' \\\n author.py && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9018f4246b8f3eb2", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 74, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 69, in new_arm\n st=make_mesh(stage,path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 45, in make_mesh\n m.DefinePointsAttr([Gf.Vec3f(x,y,z) for (x,y,z) in V])\n ^^^^^^^^^^^^^^^^^^\nAttributeError: 'Mesh' object has no attribute 'DefinePointsAttr'. Did you mean: 'CreatePointsAttr'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 40967, + "completion_tokens": 123, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 41090 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "da6bf2e0", + "pi_parent_id": "ed2be07a", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RjqCz5kf0eCeb9w8weZkTezK", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 45, + "timestamp": "2026-10-21T17:19:46.877Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me use CreatePointsAttr instead.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a5bfe9a374f2fefc", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i \\\n -e 's/m.DefinePointsAttr(/m.CreatePointsAttr(/' \\\n -e 's/m.DefineFaceVertexIndicesAttr(/m.CreateFaceVertexIndicesAttr(/' \\\n -e 's/m.DefineNormalsAttr(/m.CreateNormalsAttr(/' \\\n author.py && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a5bfe9a374f2fefc", + "content": "Warning: in GetType at line 379 of /opt/USD/pxr/base/vt/value.cpp -- Returning unknown type for VtValue with unregistered C++ type vector >\nTraceback (most recent call last):\n File \"/tmp/author.py\", line 74, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 69, in new_arm\n st=make_mesh(stage,path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 46, in make_mesh\n m.CreateFaceVertexIndicesAttr([list(f) for f in F])\npxr.Tf.ErrorException: \n\tError in 'pxrInternal_v0_26_8__pxrReserved__::UsdStage::_SetValue' at line 2045 in file /opt/USD/pxr/usd/usd/stage.cpp : 'Type mismatch for : expected 'VtArray', got 'vector >''", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 41310, + "completion_tokens": 119, + "cached_tokens": 39984, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 41429 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "87d58f1c", + "pi_parent_id": "82baf7f8", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RQciHu4HXMERmZa5Ikuld2QG", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 46, + "timestamp": "2026-10-21T17:19:55.222Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 45, 19 model rounds remain. Let me fix the faceVertexIndices - it wants a flat VtArray, not a list of lists.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b2d1494f74a18251", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/m.CreateFaceVertexIndicesAttr(\\[list(f) for f in F\\])/m.CreateFaceVertexIndicesAttr([i for f in F for i in f])/' author.py && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b2d1494f74a18251", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 74, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 69, in new_arm\n st=make_mesh(stage,path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 48, in make_mesh\n m.AddPrimvarsAttr(\"uv\", Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])\n ^^^^^^^^^^^^^^^^^\nAttributeError: 'Mesh' object has no attribute 'AddPrimvarsAttr'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 41750, + "completion_tokens": 126, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 41876 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "af6a0e76", + "pi_parent_id": "ba140c3b", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rr9KXyf2TG06CxDJjB9K9Drm", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 47, + "timestamp": "2026-10-21T17:20:22.296Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "18 model rounds remain. Let me fix the primvar - use m.CreatePrimvar for uv. Actually Mesh doesn't have AddPrimvarsAttr. Let me use UsdGeomprim.CreatePrimvar. Let me just skip UVs or use CreatePrimvar via the prim. Actually the simplest: use m.GetPrim() \u2192 Sdf. Or use `UsdGeom.BasisCurves`... no.\n\nMesh has `CreatePrimvar`? UsdGeomMesh extends UsdGeomBasisCurves? No, it extends UsdGeomMeshPrimitive which extends UsdGeomPrimvarAPI. UsdGeomPrimvarAPI has CreatePrimvar. Let me use m.CreatePrimvar(\"uv\", Sdf.ValueTypeNames.Vector2fArray, Sdf.Token(\"point\"), values).", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a9d6aa70123509d9", + "function_name": "edit", + "arguments": { + "path": "/tmp/author.py", + "edits": [ + { + "oldText": " m.AddPrimvarsAttr(\"uv\", Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])", + "newText": " m.CreatePrimvar(\"uv\", Sdf.ValueTypeNames.Vector2fArray, Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a9d6aa70123509d9", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 42094, + "completion_tokens": 297, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 42391 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "18dda940", + "pi_parent_id": "6ccdd854", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RNTdixPMtPcffOveO6FAhHvi", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 48, + "timestamp": "2026-10-21T17:20:26.376Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "17 model rounds remain. Let me run.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a325acb214822e40", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a325acb214822e40", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 74, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 69, in new_arm\n st=make_mesh(stage,path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 48, in make_mesh\n m.CreatePrimvar(\"uv\", Sdf.ValueTypeNames.Vector2fArray, Sdf.Token(\"point\"), [Gf.Vec2f(*u) for u in planar_uv(V)])\n ^^^^^^^^^^^^^^^\nAttributeError: 'Mesh' object has no attribute 'CreatePrimvar'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 42420, + "completion_tokens": 55, + "cached_tokens": 32928, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 42475 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "8d32db13", + "pi_parent_id": "67697b9c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RmBcKJi3QD9jvuJJ3ggU4xSp", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 49, + "timestamp": "2026-10-21T17:20:38.821Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "16 model rounds remain. Let me skip UV primvar to save time, or use UsdGeomPrimvarAPI properly. Let me just drop the UV line to get it working first, then validate. Actually UVs may be needed for a requirement. But let me first get it exporting. Let me comment out the UV line and run.\n\nActually let me use the correct API: `from pxr import UsdGeomPrimvarAPI` no. UsdGeomPrimvar is the schema. `m.CreatePrimvar` should exist on UsdGeomPrimvar. Let me check if mesh is a UsdGeomPrimvar. Actually the issue - maybe it's a different name. Let me just remove UVs for now to get a working export, then re-add if needed.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-87d5035d0853c441", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nfrom pxr import Usd, UsdGeom\nst=Usd.Stage.CreateInMemory()\nm=UsdGeom.Mesh.Define(st,'/m')\nprint([x for x in dir(m) if 'rimvar' in x or 'Primvar' in x])\nprint(type(m).__mro__)\n\" 2>&1 | tail -5" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-87d5035d0853c441", + "content": "['CreateDisplayColorPrimvar', 'CreateDisplayOpacityPrimvar', 'GetDisplayColorPrimvar', 'GetDisplayOpacityPrimvar']\n(, , , , , , , , , )", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 42701, + "completion_tokens": 276, + "cached_tokens": 32928, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 42977 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "7faf3b54", + "pi_parent_id": "b3d8dd98", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R5iso7gOSwUt6GK5ySyGkJGi", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 50, + "timestamp": "2026-10-21T17:20:59.438Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Let me drop the UV primvar line to get a working export fast.", + "reasoning_content": "15 model rounds remain. Mesh doesn't have CreatePrimvar directly. Let me use UsdGeomPrimvarAPI via the prim. Actually I can use `Usd.Prim.GetAPI` no. The primvar API is `UsdGeomPrimvar` schema. Let me use `from pxr import UsdGeomPrimvarAPI`? No. \n\nThe cleanest: use the Sdf layer directly or use `m.GetPrim().GetAttribute` ... Actually, I'll just drop the UV primvar since it's not critical, to move fast. Let me comment it out.\n\nActually, let me use UsdGeomPrimvar properly: `UsdGeomPrimvar(m.GetPrim(), \"uv\")` then Set. Let me just remove the UV line to get a working export quickly. I'll re-add via a working method if validation requires it.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9e69fa85d26a6518", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/^ m.CreatePrimvar(\"uv\".*/ _uv=[Gf.Vec2f(*u) for u in planar_uv(V)]\\n UsdGeomPrimvarAPI = m.GetPrim()\\n _pv = UsdGeomPrimvar(m.GetPrim(), \"uv\")\\n _pv.Create().Set(_uv).SetTimeSamples if False else None\\n _pv = UsdGeomPrimvar(m.GetPrim(), \"uv\"); _pv.Create(1) if False else None/' author.py 2>&1 | tail -3\necho \"--- checking; simpler to just remove ---\"\ngrep -n 'uv' author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9e69fa85d26a6518", + "content": "--- checking; simpler to just remove ---\n39:def planar_uv(V):\n48: _uv=[Gf.Vec2f(*u) for u in planar_uv(V)]\n50: _pv = UsdGeomPrimvar(m.GetPrim(), \"uv\")\n51: _pv.Create().Set(_uv).SetTimeSamples if False else None\n52: _pv = UsdGeomPrimvar(m.GetPrim(), \"uv\"); _pv.Create(1) if False else None", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 43138, + "completion_tokens": 370, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 43508 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "32a7b906", + "pi_parent_id": "2c6aa44d", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RxheA7MEs9xHaO8B0Pu87EMc", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 51, + "timestamp": "2026-10-21T17:21:53.218Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Let me rewrite the authoring script cleanly in one pass to avoid iterative debugging.", + "reasoning_content": "I'm at round 50 of 64, 14 model rounds remain. That's tight. Let me be very efficient. Let me rewrite the whole author.py cleanly in one go with correct APIs, run it, validate, and submit. Let me rewrite the file completely to avoid the messy sed edits.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9f47d9c7c5adf91e", + "function_name": "write", + "arguments": { + "content": "import numpy as np, pickle, sys\nsys.path.insert(0,'/tmp')\nfrom pxr import Usd, UsdGeom, UsdPhysics, UsdShade, Sdf, Gf, Vt\n\nd=pickle.load(open(\"/tmp/parts.pkl\",\"rb\"))\nparts=d[\"parts\"]; W=np.array(d[\"W\"])\n\nstage=Usd.Stage.CreateInMemory()\nstage.GetRootLayer().customLayerData[\"metersPerUnit\"]=1.0\nstage.GetRootLayer().customLayerData[\"upAxis\"]=\"Z\"\n\nroot=UsdGeom.Xform.Define(stage, \"/Scissors\")\n\ndef make_mat(path, base, metal, rough):\n mat=UsdShade.Material.Define(stage, path)\n sp=UsdShade.Shader.Define(stage, path+\"/surface\")\n sp.CreateIdAttr(\"UsdPreviewSurface\")\n sp.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color3f).Set(Gf.Vec3f(base[0],base[1],base[2]))\n sp.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(float(metal))\n sp.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(float(rough))\n mat.CreateSurfaceOutput().ConnectToSource(sp.ConnectableAPI(), \"surface\")\n return mat\n\nsteel=make_mat(\"/Materials/Steel\",(0.86,0.87,0.89),1.0,0.22)\ngold =make_mat(\"/Materials/Gold\",(0.85,0.62,0.28),1.0,0.34)\n\ndef vnormals(V,F):\n V=np.array(V,float); N=np.zeros_like(V)\n for f in F:\n if len(f)<3: continue\n a,b,c=V[f[0]],V[f[1]],V[f[2]]\n n=np.cross(b-a,c-a); nn=np.linalg.norm(n)\n if nn<1e-12: continue; n/=nn\n for i in f: N[i]+=n\n nn=np.linalg.norm(N,axis=1,keepdims=True); nn[nn<1e-12]=1\n return N/nn\n\ndef make_mesh(path, V, F, mat):\n m=UsdGeom.Mesh.Define(stage, path)\n m.CreatePointsAttr([Gf.Vec3f(x,y,z) for (x,y,z) in V])\n m.CreateFaceVertexIndicesAttr([i for f in F for i in f])\n m.CreateNormalsAttr([Gf.Vec3f(*n) for n in vnormals(V,F)])\n m.CreateSubdivisionsSchemeAttr(\"none\")\n # uv primvar\n a=np.array(V,float); mn=a.min(0); mx=a.max(0); r=mx-mn; r[r<1e-9]=1\n uvs=[Gf.Vec2f((x-mn[0])/r[0],(y-mn[1])/r[1]) for (x,y,z) in V]\n pv=UsdGeom.Primvar.Define(m.GetPrim(),\"uv\")\n pv.SetVariability(Usd.Tokens.point)\n pv.Set(uvs)\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")\n UsdPhysics.MeshCollisionAPI.Apply(m.GetPrim())\n return m\n\ndef make_rigidbody(prim, mass, density):\n rb=UsdPhysics.RigidBodyAPI.Apply(prim)\n rb.CreateRigidBodyEnabledAttr(True)\n rb.CreateKinematicEnabledAttr(False)\n rb.CreateStartsAsleepAttr(False)\n ma=UsdPhysics.MassAPI.Apply(prim)\n ma.CreateDensityAttr(float(density))\n ma.CreateMassAttr(float(mass))\n\ndef new_arm(path, st_key, gd_key):\n arm=UsdGeom.Xform.Define(stage, path)\n UsdGeom.Xformable(arm.GetPrim()).AddTranslateOp().Set(Gf.Vec3f(*W))\n make_rigidbody(arm.GetPrim(), 0.06, 8500.0)\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n make_mesh(path+\"/Gold\",parts[gd_key][0],parts[gd_key][1],gold)\n return arm\n\narmA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\narmB=new_arm(\"/Scissors/ArmB\",\"aB_steel\",\"aB_gold\")\n\nj=UsdPhysics.RevoluteJoint.Define(stage,\"/Scissors/Joints/Pivot\")\nj.CreateBody1Rel().SetTargets([armA.GetPrim()])\nj.CreateBody2Rel().SetTargets([armB.GetPrim()])\nj.CreateLocalPosition1Attr((0,0,0))\nj.CreateLocalPosition2Attr((0,0,0))\nj.CreateLocalRotation1Attr(())\nj.CreateLocalRotation2Attr(())\nj.CreateAxisAttr((0,0,1))\nj.CreateLowerAngleLimitAttr(-1.1)\nj.CreateUpperAngleLimitAttr(1.1)\n\nstage.Export(\"/output/asset.usd\")\nprint(\"exported /output/asset.usd\")\n", + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9f47d9c7c5adf91e", + "content": "Successfully wrote to /tmp/author.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 43635, + "completion_tokens": 1303, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 44938 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "ffa4ce29", + "pi_parent_id": "471d4208", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RuOpd1eIFqAB2ChyAVXfzVXF", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 52, + "timestamp": "2026-10-21T17:21:56.907Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 51, 13 rounds remain. Let me run this now.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a22a510f3d0341e8", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a22a510f3d0341e8", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 71, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 67, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 43, in make_mesh\n m.CreateSubdivisionsSchemeAttr(\"none\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Mesh' object has no attribute 'CreateSubdivisionsSchemeAttr'. Did you mean: 'CreateSubdivisionSchemeAttr'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 44961, + "completion_tokens": 65, + "cached_tokens": 28224, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 45026 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "73f31aae", + "pi_parent_id": "cfcd56a4", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RHHbpvIwm0ICJI2Wv4iToEuz", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 53, + "timestamp": "2026-10-21T17:22:07.589Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me fix: CreateSubdivisionSchemeAttr. Let me run and fix in one go.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9bd87b83cbd6077c", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/CreateSubdivisionsSchemeAttr/CreateSubdivisionSchemeAttr/' author.py && python3 author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9bd87b83cbd6077c", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 71, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 67, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 47, in make_mesh\n pv=UsdGeom.Primvar.Define(m.GetPrim(),\"uv\")\n ^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: type object 'Primvar' has no attribute 'Define'. Did you mean: 'IsDefined'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 45215, + "completion_tokens": 84, + "cached_tokens": 44688, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 45299 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "52ba4741", + "pi_parent_id": "17768372", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RIhl3KuTOgeME8vBGjGKHjLY", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 54, + "timestamp": "2026-10-21T17:22:25.990Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "11 rounds left. Let me remove the UV block to get a working export quickly, then validate.", + "reasoning_content": "11 rounds remain. Let me fix the Primvar. UsdGeom.Primvar is a prim-based API. I should use `UsdGeom.Primvar(m.GetPrim(), \"uv\")` and then create it. Actually the primvar schema: `UsdGeomPrimvar(prim, name)` then `.Define()`? Let me use the simpler approach: just drop UVs to save rounds. UVs aren't strictly required for the formal score likely. Let me remove the UV block and run.\n\nLet me just delete the UV lines to get a working export fast, then validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a4ad27a19e69ab25", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": " m.CreateSubdivisionSchemeAttr(\"none\")\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")", + "oldText": " m.CreateSubdivisionSchemeAttr(\"none\")\n # uv primvar\n a=np.array(V,float); mn=a.min(0); mx=a.max(0); r=mx-mn; r[r<1e-9]=1\n uvs=[Gf.Vec2f((x-mn[0])/r[0],(y-mn[1])/r[1]) for (x,y,z) in V]\n pv=UsdGeom.Primvar.Define(m.GetPrim(),\"uv\")\n pv.SetVariability(Usd.Tokens.point)\n pv.Set(uvs)\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a4ad27a19e69ab25", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 45486, + "completion_tokens": 385, + "cached_tokens": 44688, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 45871 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "4e9de559", + "pi_parent_id": "b6eb2020", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rk7dkYl2R6P4oVJqKkGX2cm3", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 55, + "timestamp": "2026-10-21T17:22:34.181Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "10 model rounds remain. Let me run and then validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-aeb18bbcdd1c1655", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-aeb18bbcdd1c1655", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 65, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 61, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 44, in make_mesh\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")\nBoost.Python.ArgumentError: Python argument types in\n MaterialBindingAPI.Bind(Material, Prim, str)\ndid not match C++ signature:\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdCollectionAPI collection, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingName='', pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 45900, + "completion_tokens": 69, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 45969 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "b27c2da4", + "pi_parent_id": "1fd3e075", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RV2O2RR2sWDMbFdXbRqVJZIk", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 56, + "timestamp": "2026-10-21T17:22:45.062Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me fix the material binding - use the 2-arg form.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a78f4173e245a522", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\")/UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\", Usd.Tokens.default)/' author.py && python3 -c \"\nfrom pxr import UsdShade\nimport inspect\nprint(inspect.signature(UsdShade.MaterialBindingAPI.Bind))\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a78f4173e245a522", + "content": "Traceback (most recent call last):\n File \"\", line 4, in \n File \"/usr/lib/python3.12/inspect.py\", line 3310, in signature\n return Signature.from_callable(obj, follow_wrapped=follow_wrapped,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/lib/python3.12/inspect.py\", line 3054, in from_callable\n return _signature_from_callable(obj, sigcls=cls,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/lib/python3.12/inspect.py\", line 2571, in _signature_from_callable\n return _signature_from_builtin(sigcls, obj,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/lib/python3.12/inspect.py\", line 2361, in _signature_from_builtin\n raise ValueError(\"no signature found for builtin {!r}\".format(func))\nValueError: no signature found for builtin \n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 46456, + "completion_tokens": 132, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 46588 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "86556f48", + "pi_parent_id": "df6c6aff", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R9VcMt8dseeudxUYjwPHd7T6", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 57, + "timestamp": "2026-10-21T17:22:52.059Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "The binding form is `Bind(prim, material, strength)`. Let me just use the 2-arg form Bind(material, prim) without the string. Actually from the signature: `Bind(UsdShadeMaterialBindingAPI, UsdShadeMaterial, TfToken bindingName='', ...)`. Wait the first form is `Bind(prim, collection, material)`. Let me just use `UsdShade.MaterialBindingAPI.Bind(prim, material)`.\n\nLet me fix and run in one shot.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-ba2be366c27add34", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \"over\", Usd.Tokens.default)/UsdShade.MaterialBindingAPI.Bind(m.GetPrim(), mat, \"over\")/' author.py && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-ba2be366c27add34", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 65, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 61, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 44, in make_mesh\n UsdShade.MaterialBindingAPI.Bind(m.GetPrim(), mat, \"over\")\nBoost.Python.ArgumentError: Python argument types in\n MaterialBindingAPI.Bind(Prim, Material, str)\ndid not match C++ signature:\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdCollectionAPI collection, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingName='', pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 46864, + "completion_tokens": 212, + "cached_tokens": 46256, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 47076 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "0ef8cb8a", + "pi_parent_id": "b066c04f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RZIgU7Y6hzaXXN1Vo2NYex7P", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 58, + "timestamp": "2026-10-21T17:23:04.527Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "7 model rounds remain. The Bind signature: `Bind(collection, material, bindingName, bindingStrength, materialPurpose)`. The issue is the string \"over\" is being interpreted as bindingName but the type order is collection, material, bindingName. So `Bind(prim, mat, \"over\")` = collection=prim, material=mat, bindingName=\"over\". That should match first overload. But it errored. Hmm, \"over\" as TfToken... it wants TfToken. The issue: passing a python str for bindingName should convert to TfToken. But error says \"did not match\". \n\nWait, maybe the problem is that the first overload needs collection AND material as separate. The str \"over\" \u2014 maybe it's trying to match and failing because \"over\" isn't a valid... no.\n\nActually the simplest working form from the docs: `UsdShade.MaterialBindingAPI.Bind(material, prim)` \u2014 2 args (material, collection/prim). Let me use exactly `Bind(mat, m.GetPrim())`.\n\nLet me fix and run.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9bc50159cbb1ac77", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/UsdShade.MaterialBindingAPI.Bind(m.GetPrim(), mat, \"over\")/UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim())/' author.py && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9bc50159cbb1ac77", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 65, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 61, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 44, in make_mesh\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim())\nBoost.Python.ArgumentError: Python argument types in\n MaterialBindingAPI.Bind(Material, Prim)\ndid not match C++ signature:\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdCollectionAPI collection, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingName='', pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 47565, + "completion_tokens": 321, + "cached_tokens": 46256, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 47886 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "d674cdb2", + "pi_parent_id": "f2dc65eb", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RrfyuKC9k3nj3DvX7U0yC6hq", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 59, + "timestamp": "2026-10-21T17:23:18.552Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "6 model rounds remain. I need to be efficient. The second overload is `Bind(material, collection)` \u2014 wait no. The overloads are:\n1. `Bind(collection, material, bindingName, bindingStrength, materialPurpose)` \n2. `Bind(material, bindingStrength, materialPurpose)` \u2014 no collection\n\nNeither is `Bind(material, collection)`. The first wants collection FIRST, then material. So `Bind(prim, mat)` = collection=prim, material=mat. But that gave an error earlier when I tried `Bind(prim, mat, \"over\")`? No, that error was because \"over\" as 3rd arg = bindingName. Let me try `Bind(m.GetPrim(), mat)` (collection, material).\n\nWait I did try `Bind(m.GetPrim(), mat, \"over\")` and it failed. Let me try `Bind(m.GetPrim(), mat)` without the string.\n\nActually, material binding can be done more simply via Sdf. But I'm short on time. Let me just try `Bind(m.GetPrim(), mat)`.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-94b7abeb8cdbbd39", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && sed -i 's/UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim())/UsdShade.MaterialBindingAPI.Bind(m.GetPrim(), mat)/' author.py && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-94b7abeb8cdbbd39", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 65, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 61, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 44, in make_mesh\n UsdShade.MaterialBindingAPI.Bind(m.GetPrim(), mat)\nBoost.Python.ArgumentError: Python argument types in\n MaterialBindingAPI.Bind(Prim, Material)\ndid not match C++ signature:\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdCollectionAPI collection, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingName='', pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n Bind(pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterialBindingAPI {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeMaterial material, pxrInternal_v0_26_8__pxrReserved__::TfToken bindingStrength='fallbackStrength', pxrInternal_v0_26_8__pxrReserved__::TfToken materialPurpose='')\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 48369, + "completion_tokens": 319, + "cached_tokens": 47040, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 48688 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "5fcb36f8", + "pi_parent_id": "b62a6de7", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R2ZT982dAD7Nc23hp16pd3Sx", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 60, + "timestamp": "2026-10-21T17:23:35.616Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Material binding API is finicky; I'll bind via a Sdf relationship directly. Let me make this decisive in the final round.", + "reasoning_content": "I'm out of time \u2014 only 5 model rounds remain. The material binding via API is failing. Let me just bind material via the Sdf relationship directly, which always works, and get the export done. Let me use `m.GetPrim()` Sdf binding: create a relationship `material:binding`. \n\nActually simplest: `m.CreateRelationship(\"material:binding\", [mat.GetPrim().GetPath()])`. Let me do that via the UsdPrim. Let me replace the Bind line with a Sdf relationship.\n\n5 rounds left. Let me fix binding with CreateRelationship, run, validate, submit. Let me be decisive.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b714ed5d05886034", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\nimport re\ns=open('author.py').read()\ns=s.replace(' UsdShade.MaterialBindingAPI.Bind(m.GetPrim(), mat)',\n ' m.GetPrim().CreateRelationship(\\\"material:binding\\\", [mat.GetPrim().GetPath()])')\nopen('author.py','w').write(s)\nprint('patched')\n\" && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b714ed5d05886034", + "content": "patched\nTraceback (most recent call last):\n File \"/tmp/author.py\", line 65, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 61, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 44, in make_mesh\n m.GetPrim().CreateRelationship(\"material:binding\", [mat.GetPrim().GetPath()])\nBoost.Python.ArgumentError: Python argument types in\n Prim.CreateRelationship(Prim, str, list)\ndid not match C++ signature:\n CreateRelationship(pxrInternal_v0_26_8__pxrReserved__::UsdPrim {lvalue}, std::vector, std::allocator >, std::allocator, std::allocator > > > nameElts, bool custom=True)\n CreateRelationship(pxrInternal_v0_26_8__pxrReserved__::UsdPrim {lvalue}, pxrInternal_v0_26_8__pxrReserved__::TfToken name, bool custom=True)\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 49172, + "completion_tokens": 298, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 49470 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "99185d45", + "pi_parent_id": "592b5638", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RCAKrnmcSi071z2L0cOyacPB", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 61, + "timestamp": "2026-10-21T17:23:58.501Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Let me bind materials via the Sdf layer directly (always reliable) and export.", + "reasoning_content": "4 model rounds remain. Let me use the Sdf layer directly to bind the material relationship, which always works. Let me use `m.GetPrim().GetPseudoRoot()`... Actually the cleanest: use the Sdf prim API directly on the layer.\n\nLet me write the material binding directly via the Sdf Layer's spec. Actually, the simplest robust way: after exporting, I can't easily edit. Let me do the binding in the Sdf layer:\n\n```\nspec = m.GetPrim().InLocalLayer().GetPrimAtPath(m.GetPrim().GetPath())\nrel = Sdf.Relationship('material:binding', None, [Sdf.AssetPath(mat.GetPrim().GetPath().pathString)])\nspec.AddRelationship(rel)\n```\n\nThat always works. Let me patch and run, then validate and submit in remaining rounds.\n\nActually let me reconsider - I'm at 4 rounds. Let me:\n1. This round: fix binding via Sdf, run author, confirm export.\n2. Round 2: validate_candidate (check-1), read report.\n3. Round 3: fix top issues + submit.\n4. Round 4: submit.\n\nActually I should validate then submit. Let me do binding fix + export this round.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-847d6edf0991c160", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\ns=open('author.py').read()\ns=s.replace(' m.GetPrim().CreateRelationship(\\\"material:binding\\\", [mat.GetPrim().GetPath()])',\n''' _spec=m.GetPrim().InLocalLayer().GetPrimAtPath(m.GetPrim().GetPath())\n _spec.AddRelationship(Sdf.Relationship(\\\"material:binding\\\", None, [Sdf.AssetPath(mat.GetPrim().GetPath().pathString)]))''')\nopen('author.py','w').write(s)\nprint('patched')\n\" && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-847d6edf0991c160", + "content": "patched\nTraceback (most recent call last):\n File \"/tmp/author.py\", line 66, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 62, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 44, in make_mesh\n _spec=m.GetPrim().InLocalLayer().GetPrimAtPath(m.GetPrim().GetPath())\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Prim' object has no attribute 'InLocalLayer'\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 49860, + "completion_tokens": 459, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 50319 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "119a779d", + "pi_parent_id": "e7144f37", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RXr71yRpvMiTXZ004oozdAJw", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 62, + "timestamp": "2026-10-21T17:24:05.685Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "2 rounds remain after this. Let me use `stage.GetRootLayer()` instead of InLocalLayer.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9611d49d93168cc8", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\ns=open('author.py').read()\ns=s.replace('_spec=m.GetPrim().InLocalLayer().GetPrimAtPath(m.GetPrim().GetPath())',\n '_spec=stage.GetRootLayer().GetPrimAtPath(m.GetPrim().GetPath())')\nopen('author.py','w').write(s)\n\" && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9611d49d93168cc8", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 66, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 62, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 45, in make_mesh\n _spec.AddRelationship(Sdf.Relationship(\"material:binding\", None, [Sdf.AssetPath(mat.GetPrim().GetPath().pathString)]))\n ^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'PrimSpec' object has no attribute 'AddRelationship'. Did you mean: 'relationships'?\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 50564, + "completion_tokens": 151, + "cached_tokens": 32928, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 50715 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "55fe5f51", + "pi_parent_id": "1526b122", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RTTRmQgqyp8HwtVnAHiFv2hx", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 63, + "timestamp": "2026-10-21T17:24:31.667Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "I'm at the final rounds. Let me fix the Sdf relationship assignment and export now.", + "reasoning_content": "I'm very short on rounds - 2 model rounds remain after this. Let me do the relationship assignment correctly and export, then use my last rounds wisely.\n\nThe Sdf PrimSpec uses `spec.relationships[\"material:binding\"] = Sdf.Relationship(...)`. Let me do that.\n\nActually, I only have 2 rounds after this one (rounds 63 and 64). Round 64 is the last. I need to: export asset (this round, 62), then round 63 = validate or submit, round 64 = submit. \n\nActually I can't afford a full validate+fix cycle. Let me just get the asset exported correctly this round, and submit. But the contract says validate before submitting. With only 2 rounds left, I should export this round, then validate+submit... but submit is the final action. Let me export this round, then in round 63 do a quick validate to confirm it's valid, round 64 submit. Actually if validate shows problems I can't fix in 1 round.\n\nBest: Get a correct export now (round 62), then round 63 validate (to be safe per contract), round 64 submit. If I skip validate, I save a round but contract says to validate. Let me export correctly now.\n\nLet me fix the Sdf relationship: `spec.relationships[\"material:binding\"] = Sdf.Relationship(\"material:binding\", None, [Sdf.AssetPath(...)])`.\n\nLet me do it.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b6d254591c7bbec1", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\ns=open('author.py').read()\ns=s.replace(''' _spec=stage.GetRootLayer().GetPrimAtPath(m.GetPrim().GetPath())\n _spec.AddRelationship(Sdf.Relationship(\\\"material:binding\\\", None, [Sdf.AssetPath(mat.GetPrim().GetPath().pathString)]))''',\n ''' _spec=stage.GetRootLayer().GetPrimAtPath(m.GetPrim().GetPath())\n _spec.relationships[\\\"material:binding\\\"]=Sdf.Relationship(\\\"material:binding\\\", None, [Sdf.AssetPath(mat.GetPrim().GetPath().pathString)])''')\nopen('author.py','w').write(s)\n\" && python3 author.py 2>&1 | tail -20 && echo \"===\" && ls -la /output/" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b6d254591c7bbec1", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 66, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 62, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 45, in make_mesh\n _spec.relationships[\"material:binding\"]=Sdf.Relationship(\"material:binding\", None, [Sdf.AssetPath(mat.GetPrim().GetPath().pathString)])\n ^^^^^^^^^^^^^^^^\nAttributeError: module 'pxr.Sdf' has no attribute 'Relationship'. Did you mean: 'RelationshipSpec'?\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 50973, + "completion_tokens": 548, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 51521 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "eea6e534", + "pi_parent_id": "66c96e4f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R7GYMwwc7wzk8Kqhoeno5lno", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 64, + "timestamp": "2026-10-21T17:25:13.402Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "This is my last authoring round. Let me use `Material.Bind` (reliable) and ensure the export succeeds.", + "reasoning_content": "I have only 1 round remaining after this one (round 64). This is the last real chance. I must produce a valid exported asset.usd in THIS round, and then submit in round 64.\n\nThe issue is just the relationship. Let me use the simplest possible material binding that definitely works. The `UsdShade.MaterialBindingAPI.Bind` second overload was `Bind(material, collection)` \u2014 wait no, both overloads need specific args. \n\nActually, the most reliable: after everything is defined, just use `mat.Bind(prim)` \u2014 the Material object has a Bind method! `UsdShade.Material.Bind(prim)`. Let me use `mat.Bind(m.GetPrim())`.\n\nActually Material has `Bind(self, primOrPurposedPrim, bindingStrength, materialPurpose)`. Let me use `mat.Bind(m.GetPrim())`.\n\nBut I'm at the last real round. I need to get the export to succeed THIS round. Let me make the binding bulletproof by using the Material.Bind method, and also guard it so even if it fails, the export still happens. Actually let me just wrap the whole mesh+binding so that binding failure doesn't stop export \u2014 no, better to make it work.\n\nLet me use `mat.Bind(m.GetPrim())` \u2014 UsdShade.Material.Bind exists and takes (prim, bindingStrength, materialPurpose). Let me replace the two _spec lines with `mat.Bind(m.GetPrim())`.\n\nI have to get this right in one shot. Let me write it carefully and run. If export succeeds, I have the asset. Then round 64 = submit (I'll skip validate to save the round, OR do validate. But submit is the required final action and I only have 1 round left after this. So round 64 MUST be submit_asset).\n\nWait, re-reading: \"Authoring round 63 of 64. 1 model round remains after this round.\" So after this round there's 1 more model round (64). Round 64 should be submit. So THIS round (63) I must finalize the export.\n\nLet me make the export robust. Let me replace the binding with mat.Bind and also make sure export happens. Let me just do it.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bbcf8e9cf62fc38f", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\ns=open('author.py').read()\nimport re\ns=s.replace(''' _spec=stage.GetRootLayer().GetPrimAtPath(m.GetPrim().GetPath())\n _spec.relationships[\\\"material:binding\\\"]=Sdf.Relationship(\\\"material:binding\\\", None, [Sdf.AssetPath(mat.GetPrim().GetPath().pathString)])''',\n ' mat.Bind(m.GetPrim())')\nopen('author.py','w').write(s)\n\" && python3 author.py 2>&1 | tail -25 && echo \"===\" && ls -la /output/ && echo \"--- prim count ---\" && python3 -c \"\nfrom pxr import Usd\nst=Usd.Stage.Open('/output/asset.usd')\nn=sum(1 for _ in st.Traverse())\nprint('prims',n)\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bbcf8e9cf62fc38f", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 65, in \n armA=new_arm(\"/Scissors/ArmA\",\"aA_steel\",\"aA_gold\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/author.py\", line 61, in new_arm\n make_mesh(path+\"/Steel\",parts[st_key][0],parts[st_key][1],steel)\n File \"/tmp/author.py\", line 44, in make_mesh\n mat.Bind(m.GetPrim())\n ^^^^^^^^\nAttributeError: 'Material' object has no attribute 'Bind'\n===\ntotal 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 17:00 ..\n--- prim count ---\nTraceback (most recent call last):\n File \"\", line 3, in \npxr.Tf.ErrorException: \n\tError in 'pxrInternal_v0_26_8__pxrReserved__::UsdStage::Open' at line 1276 in file /opt/USD/pxr/usd/usd/stage.cpp : 'Failed to open layer @/output/asset.usd@'\n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 51785, + "completion_tokens": 720, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 52505 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "eed2ab2f", + "pi_parent_id": "ba2b6ad3", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R79kSD5Y62AR6zBLxnqcS9c4", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 65, + "timestamp": "2026-10-21T17:26:02.807Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "Final round. Let me make the export bulletproof (robust material binding with fallbacks, guaranteed export) and run it.", + "reasoning_content": "This is my final round. I must get the asset exported and submit it. The material binding is the only failing piece. Let me use the reliable `UsdShade.MaterialBindingAPI.Bind(prim, material)` \u2014 but that failed earlier too. \n\nActually, the material binding is not strictly required to export the file. The file can export fine WITHOUT material binding \u2014 the meshes just won't have materials bound (they'll still have the material prims defined). To guarantee a successful export this final round, let me remove the binding call entirely (comment it out) so the script runs to completion and exports. The materials will still be defined in the file; binding can be imperfect but at least I get a valid exported asset.\n\nActually wait \u2014 I want material binding for visual fidelity. But I have NO rounds left after this. The priority is to have a valid exported asset.usd that opens. Let me make the export bulletproof: wrap the binding in a try/except so it never blocks export. Then export. Then submit.\n\nLet me make the binding robust with try/except, and use the correct MaterialBindingAPI form. Let me use `UsdShade.MaterialBindingAPI.Bind(prim, mat, \"direct\", Usd.Tokens.default, Usd.Tokens.default)`? The first overload is `Bind(collection, material, bindingName, bindingStrength, materialPurpose)`. Let me try that exact form. But to be safe, wrap in try/except.\n\nActually, I'll do BOTH: try the proper Bind, and in except, fall back to writing the relationship via Sdf into the spec directly using the spec's `.relationships` dict with an Sdf.RelationshipSpec object (not Sdf.Relationship).\n\nLet me construct: \n```\nspec = stage.GetRootLayer().GetPrimAtPath(path)\nrspec = Sdf.RelationshipSpec()\nrspec.targets = [Sdf.Path(mat.GetPrim().GetPath().pathString)]\nspec.relationships['material:binding'] = rspec\n```\n\nActually the relationships dict assignment: `spec.relationships[\"material:binding\"] = Sdf.RelationshipSpec(...)` with targets. Let me use a try/except chain.\n\nLet me just do it robustly with try/except around multiple approaches, guaranteeing export happens. Then submit in the SAME round? No \u2014 I can only do one thing per round but I can make multiple tool calls in a single round as long as they're independent. But submit depends on the export succeeding. So I need export first, THEN submit. But I only have this ONE round.\n\nCan I do both in this round? The bash export and then the submit MCP call \u2014 the submit depends on the file existing. If I do bash (export) and mcp submit in the same block, the submit might run before export completes (they'd be issued together). The instructions say \"make all independent calls in same block, otherwise wait for dependencies.\" Submit depends on export. So I can't do them in the same block.\n\nGiven 0 rounds remain, I MUST submit in this round. But I also need the file exported. Let me do the export via bash AND the submit \u2014 but submit depends on export. \n\nHmm. Actually, I can do the bash export in this round, and it will complete (tool results return). Then... but there are no more rounds. The final round must include the submit call.\n\nWait \u2014 the note says \"Save the USD asset and required files, then submit now.\" This implies I should do both the save and submit. Since they're dependent, but the system will process my bash call and return results within this round's tool execution... Actually in agentic loops, I can make a bash call, see its result, and then make the submit call within the same \"round\" (the round allows multiple sequential tool calls as I reason). The \"round\" is the model's turn which can include multiple tool calls with reasoning between. But it said \"0 model rounds remain after this round\" \u2014 this IS my final model round. Within this round I can make multiple tool calls.\n\nSo: make the bash export call (final robust version), then make the submit call. Since I can reason between them within this round, let me do the export first, verify, then submit.\n\nLet me make the export bulletproof. Let me write the final robust authoring and run it, then submit.\n\nLet me do the bash call first.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-97b73029c5f98b94", + "function_name": "bash", + "arguments": { + "command": "cd /tmp && python3 -c \"\ns=open('author.py').read()\nimport re\n# Replace whatever binding line exists with a robust block\ns=re.sub(r' mat\\.Bind\\(m\\.GetPrim\\(\\)\\)',\n''' _bind_ok=False\n try:\n UsdShade.MaterialBindingAPI.Bind(mat, m.GetPrim(), \\\"direct\\\", Usd.Tokens.default, Usd.Tokens.default)\n _bind_ok=True\n except Exception:\n pass\n if not _bind_ok:\n try:\n _spec=stage.GetRootLayer().GetPrimAtPath(m.GetPrim().GetPath())\n _rs=Sdf.RelationshipSpec()\n _rs.targets=[Sdf.Path(mat.GetPrim().GetPath().pathString)]\n _spec.relationships[\\\"material:binding\\\"]=_rs\n _bind_ok=True\n except Exception as e:\n print('bind fallback fail', e)''')\nopen('author.py','w').write(s)\nprint('patched')\n\" && python3 author.py 2>&1 | tail -20 && echo \"=== EXPORT ===\" && ls -la /output/ && python3 -c \"\nfrom pxr import Usd\nst=Usd.Stage.Open('/output/asset.usd')\nprint('prims', sum(1 for _ in st.Traverse()))\nprint('root bbox:', UsdGeom.ComputeAggregateBound(st.GetPseudoRoot()) if True else '')\n\" 2>&1 | tail -5" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-97b73029c5f98b94", + "content": "Traceback (most recent call last):\n File \"\", line 5, in \nTypeError: sub() missing 1 required positional argument: 'string'\n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 52861, + "completion_tokens": 1308, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 54169 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "a298c25d", + "pi_parent_id": "c8eb81fb", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RDZDuwiBcyX4CkEK1EAeZJCm", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + } + ], + "final_metrics": { + "total_prompt_tokens": 2130556, + "total_completion_tokens": 38201, + "total_cached_tokens": 851424, + "total_steps": 65, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 2168757 + } + } +} \ No newline at end of file diff --git a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/report.html b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/report.html index cc8f6e3a66db48f64e26c23ca6f470e9ab422192..50a3a73dbe33ba31b370deb2d3a94a1bd4729b52 100644 --- a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/report.html +++ b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/report.html @@ -1 +1 @@ -SimReadyBench results

SimReadyBench results

Formal fidelity measures SimReady Robotics-Prop requirements. Visual fidelity combines shape and appearance materials. Kinematic fidelity measures joint recovery and motion correspondence. Each score is reported independently.

8 of 100 reconstruction attempts completed.

Scores CSV | Detailed results JSON

Results by asset

AssetModelHarnessSkillsRepetitionStatusFormal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
box_cardboard_open_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)64001330.31279.971756688292991785987Not measuredNot measuredNot measured
cleaning_cloth_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)64001030.06987.451421893233701445263Not measuredNot measuredNot measured
container_bottle_glass_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed80.54% (39/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/16384)6410945.33906.411487863219111509774Not measuredNot measuredNot measured
food_produce_banana_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed82.61% (40/46)0% (0/2)N/A78.43% (40/51)0% (0/1)0% (0/1)N/A0% (0/20480)6400738.21698.781152527169651169492Not measuredNot measuredNot measured
food_produce_broccoli_b01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)64001367.491323.31550016347451584761Not measuredNot measuredNot measured
kitchenware_pan_j01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)64301112.591073.511725299247671750066Not measuredNot measuredNot measured
pallet_wood_recycled_a05Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)57301044.861013.721206189228031228992Not measuredNot measuredNot measured
ppe_helmet_hardHat_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed84.67% (41/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/15722)64201615.131577.831719168373451756513Not measuredNot measuredNot measured

box_cardboard_open_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64001330.31279.971756688292991785987Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020489.7Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

cleaning_cloth_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64001030.06987.451421893233701445263Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020484.5Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/cleaningCloth_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

container_bottle_glass_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
80.54% (39/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
6410945.33906.411487863219111509774Not measuredNot measuredNot measured

39 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020484.51Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:metallic0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

food_produce_banana_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
82.61% (40/46)0% (0/2)N/A78.43% (40/51)0% (0/1)0% (0/1)N/A0% (0/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
6400738.21698.781152527169651169492Not measuredNot measuredNot measured

40 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020483.02Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_food_produce_banana_a01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/20480
visual:metallic0/20480
visual:opacity0/20480
visual:roughness0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

food_produce_broccoli_b01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64001367.491323.31550016347451584761Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020483.68Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_food_produce_broccoli_b01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/20480
visual:metallic0/20480
visual:opacity0/20480
visual:roughness0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

kitchenware_pan_j01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64301112.591073.511725299247671750066Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020485.27Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_kitchenware_pan_j01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/20480
visual:metallic0/20480
visual:opacity0/20480
visual:roughness0/20480

Generated USD | Asset package manifest | Harbor trajectory 1

pallet_wood_recycled_a05 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
57301044.861013.721206189228031228992Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
00204816.03Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_pallet_wood_recycled_a05_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | Harbor trajectory 1

ppe_helmet_hardHat_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
84.67% (41/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/15722)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64201615.131577.831719168373451756513Not measuredNot measuredNot measured

41 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/15722157221572263.97

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020484.96Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/body_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/13860
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

\ No newline at end of file +SimReadyBench results

SimReadyBench results

Formal fidelity measures SimReady Robotics-Prop requirements. Visual fidelity combines shape and appearance materials. Kinematic fidelity measures joint recovery and motion correspondence. Each score is reported independently.

9 of 100 reconstruction attempts completed.

Scores CSV | Detailed results JSON

Results by asset

AssetModelHarnessSkillsRepetitionStatusFormal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
box_cardboard_open_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)64001330.31279.971756688292991785987Not measuredNot measuredNot measured
cleaning_cloth_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)64001030.06987.451421893233701445263Not measuredNot measuredNot measured
container_bottle_glass_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed80.54% (39/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/16384)6410945.33906.411487863219111509774Not measuredNot measuredNot measured
food_produce_banana_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed82.61% (40/46)0% (0/2)N/A78.43% (40/51)0% (0/1)0% (0/1)N/A0% (0/20480)6400738.21698.781152527169651169492Not measuredNot measuredNot measured
food_produce_broccoli_b01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)64001367.491323.31550016347451584761Not measuredNot measuredNot measured
kitchenware_pan_j01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)64301112.591073.511725299247671750066Not measuredNot measuredNot measured
pallet_wood_recycled_a05Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)57301044.861013.721206189228031228992Not measuredNot measuredNot measured
ppe_helmet_hardHat_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed84.67% (41/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/15722)64201615.131577.831719168373451756513Not measuredNot measuredNot measured
utensils_scissors_a01Qwen/Qwen3.8-27B:deepinfrapinone1completed0% (0/46)0% (0/2)0% (0/1)Not measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/3)0% (0/21)0% (0/20480)64001590.511541.592130556382012168757Not measuredNot measuredNot measured

box_cardboard_open_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64001330.31279.971756688292991785987Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020489.7Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

cleaning_cloth_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64001030.06987.451421893233701445263Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020484.5Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/cleaningCloth_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

container_bottle_glass_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
80.54% (39/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
6410945.33906.411487863219111509774Not measuredNot measuredNot measured

39 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020484.51Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:metallic0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

food_produce_banana_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
82.61% (40/46)0% (0/2)N/A78.43% (40/51)0% (0/1)0% (0/1)N/A0% (0/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
6400738.21698.781152527169651169492Not measuredNot measuredNot measured

40 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020483.02Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_food_produce_banana_a01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/20480
visual:metallic0/20480
visual:opacity0/20480
visual:roughness0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

food_produce_broccoli_b01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64001367.491323.31550016347451584761Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020483.68Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_food_produce_broccoli_b01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/20480
visual:metallic0/20480
visual:opacity0/20480
visual:roughness0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

kitchenware_pan_j01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64301112.591073.511725299247671750066Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020485.27Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_kitchenware_pan_j01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/20480
visual:metallic0/20480
visual:opacity0/20480
visual:roughness0/20480

Generated USD | Asset package manifest | Harbor trajectory 1

pallet_wood_recycled_a05 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)N/ANot measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/1)N/A0% (0/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
57301044.861013.721206189228031228992Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
00204816.03Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_pallet_wood_recycled_a05_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | Harbor trajectory 1

ppe_helmet_hardHat_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
84.67% (41/46)0% (0/2)N/A66.67% (34/51)0% (0/1)0% (0/1)N/A0% (0/15722)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64201615.131577.831719168373451756513Not measuredNot measuredNot measured

41 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/111100
JointsNot applicable0/0000
Materials00/15722157221572263.97

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020484.96Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/body_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled0/11/1
body_kinematic0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/13860
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

utensils_scissors_a01 / Qwen/Qwen3.8-27B:deepinfra / repetition 1

ModelHarnessSkillsRepetitionStatus
Qwen/Qwen3.8-27B:deepinfrapinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
0% (0/46)0% (0/2)0% (0/1)Not measured (0/51), 51 unmeasured, bounds 0%-100%0% (0/1)0% (0/3)0% (0/21)0% (0/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
64001590.511541.592130556382012168757Not measuredNot measuredNot measured

0 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape00/111100
Rigid parts00/333100
Joints00/212121100
Materials00/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving joints00/22/2100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_sm_utensils_scissors_a01_right_handel_joint_00Not measured0Not measuredmissing_joint
/RootNode/Joints/joint_sm_utensils_scissors_a01_left_handel_joint_00Not measured0Not measuredmissing_joint

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
0020483.11Not measuredNot measured

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_utensils_scissors_a01_left_handel_obj_00Not measured0
/RootNode/Geometry/sm_utensils_scissors_a01_reveat_obj_00Not measured0
/RootNode/Geometry/sm_utensils_scissors_a01_right_handel_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
200/21

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled0/33/3
body_kinematic0/33/3

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity0/22/2
joint_enabled0/22/2
body0_enabled0/22/2
body0_kinematic0/22/2
body1_enabled0/22/2
body1_kinematic0/22/2
anchors0/22/2
axes0/22/2
relative_orientation0/22/2
limits0/22/2
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment0/20480
visual:diffuseColor0/20480
visual:metallic0/20480
visual:opacity0/20480
visual:roughness0/20480

Harbor trajectory 1

\ No newline at end of file diff --git a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/results.json b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/results.json index e4f1c1e52b65606c29fd81c2621cc050229917d6..b12d50bcc5fa415c4f292739db12a4960cbff3a3 100644 --- a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/results.json +++ b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/results.json @@ -1,7 +1,7 @@ { "schema": "simready-bench-portable-report-v1", "planned_conditions": 100, - "completed_conditions": 8, + "completed_conditions": 9, "partial": true, "settings": { "reference_assets": [ @@ -15283,6 +15283,2086 @@ "reasoning_effort": "medium" }, "authoring_protocol": "authoring-64-bounded-output-8192-v1" + }, + { + "condition_id": "condition-43308f48d48c7b172797e71efca6502ab9419ba172977576f42e9b3e2f67eec3", + "asset_id": "utensils_scissors_a01", + "requested_model": "Qwen/Qwen3.8-27B:deepinfra", + "harness_id": "pi", + "skill_set_id": "none", + "repetition": 0, + "status": "completed", + "formal_fidelity_percent": 0.0, + "visual_fidelity_percent": 0.0, + "kinematic_fidelity_percent": 0.0, + "simready_reward": 0.0, + "mandatory_passed": 0, + "mandatory_total": 46, + "mandatory_failed": 46, + "mandatory_unknown": 0, + "mandatory_lower_bound_percent": 0.0, + "mandatory_upper_bound_percent": 0.0, + "completion_bonus": 0, + "optional_score_percent": null, + "optional_passed": 0, + "optional_failed": 0, + "optional_unknown": 51, + "optional_total": 51, + "optional_measured": 0, + "optional_coverage": 0.0, + "optional_lower_bound_percent": 0.0, + "optional_upper_bound_percent": 100.0, + "fidelity_shape_percent": 0.0, + "fidelity_rigid_parts_percent": 0.0, + "fidelity_joints_percent": 0.0, + "fidelity_materials_percent": 0.0, + "fidelity_shape_coverage": 1.0, + "fidelity_rigid_parts_coverage": 1.0, + "fidelity_joints_coverage": 1.0, + "fidelity_materials_coverage": 0.8333333333333334, + "fidelity_reference_geometry_status": "complete", + "formal_fidelity_status": "measured", + "formal_fidelity_earned": 0, + "formal_fidelity_eligible": 46, + "formal_fidelity_measured": 46, + "formal_fidelity_coverage": 1.0, + "formal_fidelity_lower_bound_percent": 0.0, + "formal_fidelity_upper_bound_percent": 0.0, + "visual_fidelity_status": "measured", + "visual_fidelity_earned": 0.0, + "visual_fidelity_eligible": 2, + "visual_fidelity_measured": 2, + "visual_fidelity_coverage": 1.0, + "visual_fidelity_lower_bound_percent": 0.0, + "visual_fidelity_upper_bound_percent": 0.0, + "kinematic_fidelity_status": "measured", + "kinematic_fidelity_earned": 0.0, + "kinematic_fidelity_eligible": 1, + "kinematic_fidelity_measured": 1, + "kinematic_fidelity_coverage": 1.0, + "kinematic_fidelity_lower_bound_percent": 0.0, + "kinematic_fidelity_upper_bound_percent": 0.0, + "visual_appearance_percent": 0.0, + "visual_appearance_status": "measured", + "visual_appearance_earned": 0.0, + "visual_appearance_eligible": 2048, + "visual_appearance_measured": 2048, + "visual_appearance_coverage": 1.0, + "visual_appearance_lower_bound_percent": 0.0, + "visual_appearance_upper_bound_percent": 0.0, + "kinematic_reference_joint_count": 2, + "kinematic_candidate_joint_count": 0, + "kinematic_matched_joint_count": 0, + "kinematic_missing_joint_count": 2, + "kinematic_extra_joint_count": 0, + "kinematic_moving_joints_percent": 0.0, + "kinematic_moving_joints_status": "measured", + "kinematic_moving_joints_earned": 0.0, + "kinematic_moving_joints_eligible": 2, + "kinematic_moving_joints_measured": 2, + "kinematic_moving_joints_coverage": 1.0, + "kinematic_moving_joints_lower_bound_percent": 0.0, + "kinematic_moving_joints_upper_bound_percent": 0.0, + "kinematic_fixed_constraints_percent": null, + "kinematic_fixed_constraints_status": "not_applicable", + "kinematic_fixed_constraints_earned": 0, + "kinematic_fixed_constraints_eligible": 0, + "kinematic_fixed_constraints_measured": 0, + "kinematic_fixed_constraints_coverage": 0, + "kinematic_fixed_constraints_lower_bound_percent": null, + "kinematic_fixed_constraints_upper_bound_percent": null, + "fidelity_shape_earned": 0.0, + "fidelity_shape_eligible": 1, + "fidelity_shape_measured": 1, + "fidelity_shape_status": "measured", + "fidelity_rigid_parts_earned": 0.0, + "fidelity_rigid_parts_eligible": 3, + "fidelity_rigid_parts_measured": 3, + "fidelity_rigid_parts_status": "measured", + "fidelity_joints_earned": 0, + "fidelity_joints_eligible": 21, + "fidelity_joints_measured": 21, + "fidelity_joints_status": "measured", + "fidelity_materials_earned": 0, + "fidelity_materials_eligible": 20480, + "fidelity_materials_measured": 20480, + "fidelity_materials_status": "measured", + "fidelity_shape_precision": 0.0, + "fidelity_shape_recall": 0.0, + "fidelity_shape_samples_each_direction": 2048, + "fidelity_rigid_parts_geometry_percent": 0.0, + "fidelity_rigid_parts_structure_percent": 0.0, + "fidelity_rigid_parts_structure_earned": 0, + "fidelity_rigid_parts_structure_eligible": 8, + "fidelity_joints_reference_count": 2, + "fidelity_joints_candidate_count": 0, + "inference_calls_used": 64, + "validation_calls_used": 0, + "model_request_errors": 0, + "elapsed_seconds": 1590.5061107575893, + "model_request_seconds": 1541.5944911204278, + "input_tokens": 2130556, + "output_tokens": 38201, + "total_tokens": 2168757, + "inference_cost_usd": null, + "compute_cost_usd": null, + "total_cost_usd": null, + "seed": 1636564814, + "scoring_policy_id": "NVIDIA-Robotics-Prop-4.0.0-mandatory-95-plus-5-v1", + "official_conformance_passed": null, + "inference_cost_kind": null, + "usage_reconstruction": null, + "simready": { + "schema": "simready-validator-score-v1", + "policy_id": "NVIDIA-Robotics-Prop-4.0.0-mandatory-95-plus-5-v1", + "policy_sha256": "fa544262f43e2e3ebd2656a335fd8fb21438553074b0535d25a250ddfa3dae77", + "status": "invalid_candidate", + "score_percent": 0.0, + "score_fraction": 0.0, + "score_lower_bound": 0.0, + "score_upper_bound": 0.0, + "passed_count": 0, + "failed_count": 46, + "unknown_count": 0, + "applicable_count": 46, + "profile_mandatory_count": 46, + "profile_coverage_fraction": 1.0, + "completion_bonus": 0, + "categories": { + "asset_paths_and_naming": { + "applicable": 8, + "failed": 8, + "passed": 0, + "unknown": 0 + }, + "geometry_mesh": { + "applicable": 8, + "failed": 8, + "passed": 0, + "unknown": 0 + }, + "hierarchy": { + "applicable": 4, + "failed": 4, + "passed": 0, + "unknown": 0 + }, + "materials_textures": { + "applicable": 6, + "failed": 6, + "passed": 0, + "unknown": 0 + }, + "rigid_body_collision": { + "applicable": 10, + "failed": 10, + "passed": 0, + "unknown": 0 + }, + "semantics": { + "applicable": 6, + "failed": 6, + "passed": 0, + "unknown": 0 + }, + "thumbnail_metadata": { + "applicable": 2, + "failed": 2, + "passed": 0, + "unknown": 0 + }, + "units": { + "applicable": 2, + "failed": 2, + "passed": 0, + "unknown": 0 + } + }, + "checks": [ + { + "requirement_id": "com.nvidia.simready.HI.010", + "mandatory": true, + "requirement_version": "0.1.0", + "status_basis": "pinned_NVIDIA_rule_execution_requirement_outcome", + "weight": 1, + "base_credit_percent": 0, + "status": "invalid", + "scoring": true, + "category": "hierarchy" + }, + { + "requirement_id": "com.nvidia.simready.NP.002", + "mandatory": true, + "requirement_version": "0.1.0", + "status_basis": "pinned_NVIDIA_rule_execution_requirement_outcome", + "weight": 1, + "base_credit_percent": 0, + "status": "invalid", + "scoring": true, + "category": "asset_paths_and_naming" + }, + { + "requirement_id": "com.nvidia.simready.NP.003", + "mandatory": true, + "requirement_version": "0.1.0", + "status_basis": "pinned_NVIDIA_rule_execution_requirement_outcome", + "weight": 1, + "base_credit_percent": 0, + "status": "invalid", + "scoring": true, + "category": "asset_paths_and_naming" + }, + { + "requirement_id": "com.nvidia.simready.NP.004", + "mandatory": true, + 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