diff --git a/README.md b/README.md index a68f63535bf1daa01b670e44e40db228c1f87588..f763f97ad9697728b3da29c4640c88720b6d809d 100644 --- a/README.md +++ b/README.md @@ -2182,6 +2182,7 @@ configs: - split: container_bottle_glass_a01 path: - viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/container_bottle_glass_a01.parquet + - viewer/nv25-qwen38-27b-medium-pi-none-turn64-20261021/by_asset/container_bottle_glass_a01.parquet - split: enginecomponent_camshaft_a01 path: - viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/enginecomponent_camshaft_a01.parquet @@ -2194,7 +2195,7 @@ configs: - split: food_produce_banana_a01 path: - viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/food_produce_banana_a01.parquet - - viewer/nv25-qwen38-27b-medium-pi-none-turn64-20261021/scores.parquet + - viewer/nv25-qwen38-27b-medium-pi-none-turn64-20261021/by_asset/food_produce_banana_a01.parquet - split: food_produce_broccoli_b01 path: - viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/food_produce_broccoli_b01.parquet diff --git a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/assets/container_bottle_glass_a01/reconstruction-1/candidate/asset.usd b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/assets/container_bottle_glass_a01/reconstruction-1/candidate/asset.usd new file mode 100644 index 0000000000000000000000000000000000000000..6305538bf564d846033c2e95efb17fe3a65a9ff1 Binary files /dev/null and b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/assets/container_bottle_glass_a01/reconstruction-1/candidate/asset.usd differ diff --git a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/assets/container_bottle_glass_a01/reconstruction-1/candidate/manifest.json b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/assets/container_bottle_glass_a01/reconstruction-1/candidate/manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cf630eb31a5b9153ffd538fdeae79a6d47d7aebb --- /dev/null +++ b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/assets/container_bottle_glass_a01/reconstruction-1/candidate/manifest.json @@ -0,0 +1,14 @@ +{ + "copied_independently": true, + "entrypoint": "asset.usd", + "files": [ + { + "relative_path": "asset.usd", + "sha256": "684c348810d11dc7a7c63b84c4cf3aba95fb5a6685538953cffe985f5e84dbef", + "size_bytes": 55222 + } + ], + "schema": "simready-bench-submission-v1", + "size_bytes": 55222, + "snapshot_sha256": "5f8b396720168f07d550b92f9d6ff292655ce478abacc16b8c8b6d6818ca17bf" +} diff --git a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/container_bottle_glass_a01/reconstruction-1/harbor-trajectory-4.json b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/container_bottle_glass_a01/reconstruction-1/harbor-trajectory-4.json new file mode 100644 index 0000000000000000000000000000000000000000..a966d5262ad13c9b1fafed0f6e278ee3e6e24198 --- /dev/null +++ b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/container_bottle_glass_a01/reconstruction-1/harbor-trajectory-4.json @@ -0,0 +1,3503 @@ +{ + "schema_version": "ATIF-v1.7", + "session_id": "01a15f67-ad14-737b-815d-ed29be1312d9", + "agent": { + "name": "pi", + "version": "0.85.1", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra" + }, + "steps": [ + { + "step_id": 1, + "timestamp": "2026-10-21T16:59:54.508Z", + "source": "user", + "message": [ + { + "type": "text", + "text": "\nReconstruct the supplied object as /output/asset.usd.\nNominal dimensions in canonical metres XYZ: [0.17572927474975586, 0.1757183074951172, 0.24786941520869732]\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": "699a9051", + "pi_parent_id": "f94cf8a1" + } + }, + { + "step_id": 2, + "timestamp": "2026-10-21T16:59:57.580Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me start by reading the task files to understand the contract, tool docs, and scoring policy.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b2cb4f502239971a", + "function_name": "read", + "arguments": { + "path": "/task/contract.md" + } + }, + { + "tool_call_id": "chatcmpl-tool-968d3f65228fe30f", + "function_name": "read", + "arguments": { + "path": "/task/tool-docs.md" + } + }, + { + "tool_call_id": "chatcmpl-tool-91fd729c2e4097c6", + "function_name": "read", + "arguments": { + "path": "/task/scoring-policy.json" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b2cb4f502239971a", + "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-968d3f65228fe30f", + "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-91fd729c2e4097c6", + "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": 3206, + "completion_tokens": 106, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 3312 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "22a49b2f", + "pi_parent_id": "699a9051", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R4HsF6UqWfOEE6EIV4ciG5zW", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 3, + "timestamp": "2026-10-21T17:00:00.745Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me look at the MCP tools available for benchmark to understand validate_candidate, etc.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-81d365e0c6812ab9", + "function_name": "mcp", + "arguments": { + "search": "validate" + } + }, + { + "tool_call_id": "chatcmpl-tool-a472520c9910b191", + "function_name": "mcp", + "arguments": { + "search": "submit" + } + }, + { + "tool_call_id": "chatcmpl-tool-a0e1cbde1e1f7273", + "function_name": "mcp", + "arguments": { + "search": "task" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-81d365e0c6812ab9", + "content": "Found 1 tool matching \"validate\":\n\nbenchmark_validate_candidate\n Validate a frozen candidate and return NVIDIA findings. Each new request consumes one validation call. Repeating a request ID returns its existing result.\n\n Shape:\n { request_id: string; }", + "extra": { + "tool_name": "mcp", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-a472520c9910b191", + "content": "Found 1 tool matching \"submit\":\n\nbenchmark_submit_asset\n End authoring and freeze the submitted asset. Returns the submission hash.\n\n Shape:\n { request_id: string; }", + "extra": { + "tool_name": "mcp", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-a0e1cbde1e1f7273", + "content": "Found 1 tool matching \"task\":\n\nbenchmark_get_task_thumbnail\n Read the supplied task thumbnail and public brief.\n\n Shape:\n {}", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 5080, + "completion_tokens": 95, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 5175 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "848d5f4e", + "pi_parent_id": "805f8fd2", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RicwIOTiysVM2ysNXiKnyWef", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 4, + "timestamp": "2026-10-21T17:00:21.699Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me look at the thumbnail via the MCP tool, and inspect the full tool list for benchmark.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bd16d6f913fd4ccf", + "function_name": "mcp", + "arguments": { + "tool": "benchmark_get_task_thumbnail" + } + }, + { + "tool_call_id": "chatcmpl-tool-a9f983fc23f4a928", + "function_name": "mcp", + "arguments": { + "search": "report" + } + }, + { + "tool_call_id": "chatcmpl-tool-84dcbf173e3e95ed", + "function_name": "mcp", + "arguments": { + "search": "preview" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bd16d6f913fd4ccf", + "content": [ + { + "type": "text", + "text": "{\"status\": \"completed\", \"task\": \"Reconstruct the supplied object as /output/asset.usd.\\nNominal dimensions in canonical metres XYZ: [0.17572927474975586, 0.1757183074951172, 0.24786941520869732]\\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\", \"thumbnail\": {\"height\": 1024, \"sha256\": \"4ee6c2db2de4d706084da84b1cc21f04315480760d539e88d630a654cd36071e\", \"width\": 1024}}" + }, + { + "type": "image", + "source": { + "media_type": "image/png", + "path": "images/pi_image_2.png" + } + } + ], + "extra": { + "tool_name": "mcp", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-a9f983fc23f4a928", + "content": "Found 1 tool matching \"report\":\n\nbenchmark_get_validation_report\n Read a requested range of a prior NVIDIA report. The complete report is already saved at the file_path returned by validation. Prefer rg and targeted local file reads. Read-only and free of validation quota.\n\n Shape:\n { report_id: string; offset?: number; limit?: number; }", + "extra": { + "tool_name": "mcp", + "is_error": false + } + }, + { + "source_call_id": "chatcmpl-tool-84dcbf173e3e95ed", + "content": "No tools matching \"preview\"", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 5326, + "completion_tokens": 102, + "cached_tokens": 4704, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 5428 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "07d1e6f6", + "pi_parent_id": "434d51f9", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RnBjl4JGrXz6jMTFKy9374dH", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 5, + "timestamp": "2026-10-21T17:01:50.542Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me analyze the object. It's a black glossy bell/dome shape \u2014 looks like a fixed bell or a lantern finial/bell. Let me look carefully:\n\n- A wide base (flared foot) at the bottom with a torus-like rim (a beaded ring).\n- A cylindrical/domed body.\n- A domed top (bell-shaped) that tapers up.\n- A top neck/collar (a short cylinder with a rounded rim and a hollow opening at the very top).\n\nThis looks like a bell (e.g., a hand bell or a lantern bell/finial). Actually it resembles a \"bell\" or a ceramic vessel. The dimensions: X=0.1757, Y=0.1757 (roughly equal footprint, circular), Z=0.2479 (height). So it's a rotationally symmetric object ~17.6cm diameter, 24.8cm tall.\n\nLooking at the shape: it's like a bell \u2014 flared base, dome top, and a neck/collar at top with an opening. This is a single rigid object (a bell). Actually the top neck has a hollow opening \u2014 it looks like a decorative finial/bell or a ceramic jar.\n\nFor kinematic fidelity: This is a rigid object. The contract says \"genuinely rigid objects rigid.\" A bell is a single rigid body. But wait \u2014 a bell typically has a clapper. But the top opening suggests it's an ornamental bell (church bell / handbell top). Actually the top collar with hollow opening is like the crown of a bell. \n\nGiven it's clearly a single rigid object, I'll author it as one rigid body with a UsdPhysics RigidBodyAPI + CollisionAPI, no joints needed (or a fixed structure). Since the object is rigid, no joints.\n\nActually, let me reconsider. The scoring has \"kinematic fidelity: joint recovery and allowed relative motion correspondence.\" For a rigid object there are no moving joints. So I keep it rigid.\n\nNow for the formal fidelity (NVIDIA SimReady Foundation Robotics-Prop 4.0.0). There are 46 mandatory requirements listed in applicable_requirement_ids (that's 44 IDs actually... let me count). Let me count the list:\n\ncom.nvidia.simready.HI.010\ncom.nvidia.simready.NP.002\ncom.nvidia.simready.NP.003\ncom.nvidia.simready.NP.004\ncom.nvidia.simready.NP.005\ncom.nvidia.simready.NP.007\ncom.nvidia.simready.NP.008\ncom.nvidia.simready.RB.001\ncom.nvidia.simready.RB.007\ncom.nvidia.simready.RB.010\ncom.nvidia.simready.RB.COL.001\ncom.nvidia.simready.RB.COL.002\ncom.nvidia.simready.RB.COL.003\ncom.nvidia.simready.SL.001\ncom.nvidia.simready.SL.002\ncom.nvidia.simready.SL.003\ncom.nvidia.simready.SL.MAT.001\ncom.nvidia.simready.SL.QCODE.001\ncom.nvidia.simready.SL.TIME.001\ncom.nvidia.simready.SR.002\ncom.nvidia.simready.SR.004\ncom.nvidia.simready.UN.006\ncom.nvidia.simready.UN.007\ncom.nvidia.simready.VG.008\ncom.nvidia.simready.VG.025\ncom.nvidia.simready.VG.MESH.001\ncom.nvidia.simready.VM.MAT.001\ncom.nvidia.simready.VM.PS.002\ncom.nvidia.simready.VM.TEX.001\ncom.nvidia.simready.VM.TEX.003\ncom.nvidia.usd.AA.001\ncom.nvidia.usd.AA.002\ncom.nvidia.usd.HI.001\ncom.nvidia.usd.HI.003\ncom.nvidia.usd.HI.004\ncom.nvidia.usd.RB.003\ncom.nvidia.usd.RB.005\ncom.nvidia.usd.RB.009\ncom.nvidia.usd.RB.COL.004\ncom.nvidia.usd.VG.002\ncom.nvidia.usd.VG.014\ncom.nvidia.usd.VG.027\ncom.nvidia.usd.VG.028\ncom.nvidia.usd.VG.029\ncom.nvidia.usd.VM.BIND.001\ncom.nvidia.usd.VM.PS.001\n\nThat's 44 IDs. The contract says 46 mandatory requirements. Anyway, the validator will tell me what's needed.\n\nThe best strategy: build a clean SimReady-compliant asset. Let me recall the SimReady Foundation requirements for a robotics prop:\n\nKey SimReady Foundation USD requirements:\n- UP axis: root prim \"World\" -> \"UpAxis\" = Z (HI.010/HI.001 etc). Actually SimReady requires a root \"World\" prim with UpAxis Z, FrontAxis Y or -Y.\n- Naming: \"Model\" prim as the model root.\n- Units: meters (UN.006 = units meters, UN.007 = time).\n- Material: PhysicallyBasedMaterial with standard surface (VM.MAT.001, SL.MAT.001).\n- Material binding (VM.BIND.001).\n- Textures: use USD texture API (VM.TEX.001, VM.TEX.003) \u2014 texture files must be proper.\n- Normals: mesh must have normals (VG.MESH.001).\n- Mesh: valid, no NaN, watertight-ish.\n- RigidBody API (RB) with mass, massProperties.\n- Collision API (RB.COL) with collision shape.\n- No unused/bad prims, etc.\n- AA (asset assembly): variant sets? AA.001, AA.002 \u2014 maybe \"asset assembly\" rules.\n- QCODE, TIME: SL.QCODE.001 (quantum code?), SL.TIME.001 time sampling.\n\nThis is complex. Rather than try to fully spec it from memory, I'll build a reasonable SimReady asset and iterate with validate_candidate. I have 5 validation calls. Let me be efficient.\n\nLet me check the environment: what's the python, pxr available. Let me check the /output and /tmp directories and pxr version.\n\nLet me plan the geometry: A bell shape. I'll create it as a surface of revolution (lathe) for a smooth bell profile. Actually simpler: build a profile of radii vs height and lathe it. That gives a clean rotational mesh with proper normals.\n\nProfile (radius, height) in meters. Total height H=0.2479, max radius ~0.0878 (diameter 0.1757). Let me define the silhouette from bottom to top:\n\nLooking at the image:\n- Bottom: flared foot. There's a beaded/torus base at the very bottom (radius slightly larger than body, ~0.0878). The base flares out.\n- Then a cylindrical-ish body that's narrower at bottom then the dome.\n- Actually the base flares outward (a foot ring), then curves in, then the body bulges (dome) reaching max radius around mid-upper, then tapers up to the neck.\n- Top: a collar/neck (cylinder) with a rounded lip and a hollow opening.\n\nLet me define a lathe profile. Radius in meters, max R = 0.175718/2 = 0.08786.\n\nHeight profile from z=0 to z=0.2479:\n- z=0.000: foot bottom, radius ~0.070 (recessed) \u2014 actually the very bottom is a small ring foot.\n- Let me look: bottom has a torus beading. The bottom foot: outer radius ~0.0879 at some small height, then curves in to body radius ~0.082, body is roughly cylindrical/convex up to near top, then the dome curves up to neck radius ~0.033, and the neck is a short cylinder ~0.033 radius up to a rounded lip at top z=0.2479.\n\nLet me just make a nice bell/urn profile. I'll define points:\n\nz, r:\n0.000, 0.060 (foot inner bottom)\n0.008, 0.078\n0.014, 0.0879 (max, foot bead outer)\n0.024, 0.082\n0.040, 0.080\n0.080, 0.082\n0.120, 0.083 (body widest)\n0.150, 0.080\n0.175, 0.070\n0.195, 0.055\n0.210, 0.042\n0.222, 0.035\n0.228, 0.0335 (neck start)\n0.240, 0.0335 (neck)\n0.245, 0.0345 (lip)\n0.2479, 0.0335 (top rim)\n\nThen top has an opening (hollow). For a hollow opening, I could make the top cap with a hole, but for a watertight mesh and simplicity, I'll just close the top with the rim and add an inner wall going down a bit to represent the hollow (visible dark opening). Actually the opening shows black inside. I can create an inner bore. But for collision/rigid body simplicity and watertightness, maybe just make the top rim and an inward lip.\n\nTo keep it manageable and watertight, I'll make it a solid surface-of-revolution that includes the top opening as a recessed dish: the profile goes up the outer wall, over the rounded lip, then back down an inner wall to an inner floor (representing the hollow). That creates the hollow opening.\n\nHmm, but the inner hollow goes deep (we see it's a deep cylinder). For visual fidelity from the top view, an inner bore of radius ~0.030 going down ~0.03 would show a dark hole. I'll add that.\n\nLet me build the lathe profile as a closed solid actually: to be watertight I need the profile to be a closed loop. A solid of revolution of a closed 2D profile (a region) gives a watertight mesh. So the profile in the (r, z) half-plane should be a closed loop from the axis out and back.\n\nClosed profile (going around the cross-section, r>=0):\nStart at top center axis? The top has a hole, so the top is not on the axis. Let me instead make the cross-section a closed loop:\n\nActually simpler: make the whole thing a solid (no actual hole) but shape the top as a shallow dish. But image clearly shows a deep black hole. For visual fidelity that matters somewhat but the object is mostly the black glossy body. I'll make a deep-ish recess.\n\nLet me define closed cross-section polygon (r, z), going clockwise:\n1. top outer rim: (r_rim=0.0345, z=0.2479)\n2. down outer lip to neck: (0.0335, 0.245)\n3. (0.0335, 0.228)\n... down the outer body to foot ...\n... foot ...\n... bottom center: (0.0, z=0.0) -- on axis at bottom\nthen back up the INNER surface to form the hollow:\nActually to have a hole at top, the cross-section region must not include the top axis. Let me define:\n\nOuter boundary from bottom-axis up to top-rim, then inner boundary from top-rim back down to a bottom-of-bore, then across to... hmm this is getting complicated.\n\nLet me just do a solid of revolution where the profile is an open curve that I revolve, and I add end caps (top ring cap around the hole, bottom disk cap). USD meshes don't need to be strictly watertight for most SimReady checks but VG checks may want closed. To be safe I'll make it watertight by constructing a proper closed polygon.\n\nLet me define the closed cross-section polygon (each point is (r,z), revolve around Z):\n\nGoing from bottom axis, out along bottom, up outer wall, over top lip, down inner wall to bore floor, then... the bore floor center is not on axis (hole). To close the loop I'd connect bore inner to bottom axis via the bottom interior. But there's material below the bore (the body is solid). \n\nSimplest watertight approach: full closed loop:\nA. (0.0, 0.0) bottom axis\nB. (0.060, 0.0) bottom outer edge (foot)\n ... foot bead ...\n ... outer wall up ...\n ... over top lip to rim outer (0.0345, 0.2479)\nC. (0.030, 0.2479) top rim inner (the hole edge)\n down inner bore wall\nD. (0.030, 0.215) bore floor inner\nE. (0.0, 0.215) bore floor center -> closes toward axis? but then from (0,0.215) we need to get back to (0,0.0) along axis -> that's the interior axis line, which when revolved degenerates (r=0 line). A degenerate line on the axis is fine (it's the center seam, no area). Actually revolving a segment at r=0 from z=0.215 to z=0.0 gives zero area \u2014 fine, it's a degenerate edge along axis. That keeps the mesh valid (no faces there).\n\nSo closed polygon:\n(0.0,0.0)\n(0.060,0.0)\n(0.078,0.008)\n(0.0879,0.014) max foot\n(0.082,0.024)\n(0.080,0.045)\n(0.082,0.090)\n(0.0835,0.120) max body\n(0.080,0.150)\n(0.070,0.175)\n(0.055,0.195)\n(0.042,0.210)\n(0.035,0.222)\n(0.0335,0.235) neck\n(0.0335,0.245)\n(0.0345,0.2479) top rim outer\n(0.030,0.2479) top rim inner\n(0.030,0.215) bore floor\n(0.0,0.215) bore floor center (axis)\nback to (0.0,0.0) via axis (degenerate)\n\nRevolve 360 with N segments (e.g., 96). This yields watertight mesh. Good.\n\nI'll generate the mesh with numpy, compute face normals, produce a Mesh prim with point positions, faceVertexIndices, and normals (or let USD compute). I'll also create the material (a black glossy PBR material) and bind it. Then add RigidBodyAPI + CollisionAPI (convex or mesh collision) + mass.\n\nFor SimReady, the recommended structure:\n- World (root)\n - Model\n - \n - (actually material often under Model or a Materials folder)\n\nLet me recall SimReady Foundation structure:\n- \"World\" root prim, with metadata UpAxis=\"Z\", FrontAxis=\"Y\", metersPerUnit=1, ... Actually UpAxis is a \"custom\" attribute? In SimReady, World has \"upAxis\" custom attribute? No. Standard: stage metadata. But SimReady uses a \"World\" prim with custom attributes? Let me recall: SimReady Foundation schema requires:\n - root prim named \"World\"\n - \"Model\" prim (the model assembly)\n - material prims with \"Materials\" relationship via MaterialBinding\n - The \"upAxis\" is a custom attribute on World? Actually SimReady defines: World prim has custom attribute \"upAxis\" (value \"Z\") and \"frontAxis\" (\"Y\"). Hmm.\n\nThe validator will tell me. Let me just build and iterate.\n\nGiven budget (64 turns, 5 validations), let me write a solid first attempt based on best knowledge of SimReady Foundation, validate, then fix.\n\nLet me check environment first.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-89aa3805fa2de84f", + "function_name": "bash", + "arguments": { + "command": "cd /output && ls -la && python3 -c \"import pxr; print(pxr.__file__)\" 2>&1 | head; python3 --version; ls /tmp" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-89aa3805fa2de84f", + "content": "total 0\ndrwxrwxrwx 2 actor actor 40 Oct 21 16:59 .\ndrwxr-xr-x 1 root root 56 Oct 21 16:59 ..\n/usr/local/lib/python3.12/dist-packages/pxr/__init__.py\nPython 3.12.3\nharbor-pi-agent\nharbor-pi-mcp-adapter\njiti\nnode-compile-cache\npi-mcp-output-OzUhAL\nsimready-relay.ready", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 6818, + "completion_tokens": 3951, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 10769 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "339f7091", + "pi_parent_id": "87f18458", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R0ovfSIpLZuOERBenWKZnAeE", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 6, + "timestamp": "2026-10-21T17:01:55.025Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "pxr is available. Let me check the SimReady schema availability and version.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-879f16aa597d6e80", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 -c \"\nimport pxr\nprint('pxr version', pxr.GetVersion())\nfrom pxr import Sdf, Usd, UsdGeom, Gf, PhysxSchema, UsdPhysics, UsdPhysics as up\nprint('ok physx')\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-879f16aa597d6e80", + "content": "Traceback (most recent call last):\n File \"\", line 3, in \nAttributeError: module 'pxr' has no attribute 'GetVersion'\n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 10904, + "completion_tokens": 109, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 11013 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "6983b2c2", + "pi_parent_id": "4900b2da", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rb40z4NUo44GAQLSPZOf8elG", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 7, + "timestamp": "2026-10-21T17:02:01.221Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me check what's available.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a0c5307a59fb0324", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 -c \"\nfrom pxr import Sdf, Usd, UsdGeom, Gf, UsdPhysics, PhysxSchema, UsdShade\nprint('imports ok')\nprint('usd physics', UsdPhysics.__name__)\nimport pxr\nprint(getattr(pxr, 'ApiVersion', 'n/a'))\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a0c5307a59fb0324", + "content": "Traceback (most recent call last):\n File \"\", line 2, in \nImportError: cannot import name 'PhysxSchema' from 'pxr' (/usr/local/lib/python3.12/dist-packages/pxr/__init__.py)\n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 11073, + "completion_tokens": 114, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 11187 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2f465c45", + "pi_parent_id": "dd53567e", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RpL3qa147j7IE5zu9jkwc7aH", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 8, + "timestamp": "2026-10-21T17:03:29.054Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "PhysxSchema not available (no PhysX build of USD). That's fine. Let me check what's available: UsdPhysics, UsdShade. Let me build the asset.\n\nLet me write the authoring script. I'll create the geometry as a surface of revolution.\n\nLet me write the full Python script.\n\nKey SimReady Foundation USD structure requirements (from my knowledge):\n- Root prim \"World\"\n - custom attribute \"upAxis\" = \"Z\", \"frontAxis\" = \"Y\" (actually these might be metadata). Let me recall. In SimReady the requirements:\n - NR/WORLD: root prim name \"World\".\n - The \"upAxis\" and \"frontAxis\" are CustomLayer metadata? Actually SimReady Foundation uses: the root \"World\" prim has a \"UpAxis\" metadata = \"Z\". Hmm.\n\nLet me just include both Sdf metadata and custom attributes to be safe: I'll set the stage metadata units=meters, and on World prim add metadata? Actually USD prim metadata vs attributes.\n\nSimReady \"HI.010\" (HieRarchy?) Let me not guess IDs. I'll build a standard structure and let the validator guide me.\n\nStandard SimReady Foundation recommended layout:\n```\nWorld (root, Xform)\n\u251c\u2500\u2500 upAxis (custom? no)\n\u251c\u2500\u2500 Model (Xform) <- the model, this is what gets bound / has physics\n\u2502 \u251c\u2500\u2500 geometry prims (Mesh)\n\u251c\u2500\u2500 Materials (Xform) [optional folder]\n\u2502 \u2514\u2500\u2500 Material_x (Material)\n```\n\nRequirements I recall for SimReady Foundation (Roblox/SimReady USD):\n1. Root prim named \"World\".\n2. UpAxis metadata on root = \"Z\".\n3. FrontAxis = \"Y\" (or -Y).\n4. Units: stage metadata metersPerUnit = 1 (useSIunits true). Actually USD default is meters; UN.006 wants explicit.\n5. A \"Model\" prim.\n6. Materials: Preflighted standard shading \u2014 PhysicallyBased with UsdPreviewSurface or Shader with \"material:preview:surface\"? SimReady uses \"OmniPBR\"/UsdPreviewSurface. VM.MAT.001 requires a \"Shading\" \u2014 material with preview surface.\n7. Material binding: bind to mesh.\n8. Mesh: has normals (VG.MESH.001), pointCountAttribute.\n9. RigidBody: RigidBodyAPI with mass, massProperties; or for a static asset just collision.\n10. Collision: CollisionAPI with UsdPhysics collision API + a collision mesh.\n11. Names: prims should have valid names (no leading digits).\n12. Textures: if any, proper.\n13. No NaN.\n\nI'll aim for a solid prop. Let me write it.\n\nFor material: I'll use UsdPreviewSurface (Shader prim with info:id = \"UsdPreviewSurface\") which is the standard preview material that NVIDIA/Omnix recognize. Black glossy: baseColor near (0.02,0.02,0.02), metallic=0 (it's ceramic black, glossy not metal \u2014 the highlights are specular). Actually the reflections look like glossy ceramic/plastic. I'll set roughness ~0.05, metallic 0.0, baseColor black. Or make it look like black lacquer. Use UsdPreviewSurface with baseColor, roughness, metallic, specular, clearcoat.\n\nLet me build.\n\nFor collision: I'll add UsdPhysics.CollisionAPI + a Mesh with UsdPhysicsMeshCollisionAPI, or use convexHull. I'll add both RigidBodyAPI (mass, massProperties auto) and CollisionAPI.\n\nActually for a static prop, I could use \"kinematicEnabled=false\". The contract: \"genuinely rigid objects rigid.\" A bell \u2014 is it static or movable? It's a rigid object with no moving parts. I'll make it a single rigid body.\n\nLet me write the script now.\n\nGeometry via numpy lathe:\n- N=128 segments around.\n- profile points (r,z) as above, closed loop.\n- Build vertices: for each profile point i, for each angle j, position = (r*cos, r*sin, z). For r=0 points, all angles coincide (degenerate). That creates duplicate vertices on axis \u2014 causes zero-area triangles. Better: for r=0 profile points, only create 1 vertex (shared). To avoid complexity, I'll make the profile avoid exact r=0; instead use a tiny radius like 0.0001 and just cap? No, that leaves a pinhole.\n\nAlternative: build the surface as an open revolved band from foot bottom rim to top rim, then add two disk caps (bottom annulus and top annulus). Actually let me just do it cleanly with a helper that handles r=0 by collapsing.\n\nSimpler: Build the full closed cross-section but handle axis rows by having only ONE vertex for r=eps everywhere and close the top hole and bottom with explicit disk fans, and connect axis with a single center vertex.\n\nLet me restructure: I'll NOT put r=0 in the profile. Instead:\n- Outer surface: profile from bottom rim (r_b0,z=0) up to top rim outer. All r>0.\n- I then add:\n - bottom cap: a disk at z=0 from r_b0 down to center (fan to center vertex at (0,0,0)).\n - top cap: from top rim, but there's a hole. The top cap is an annulus: from rim outer (r=0.0345) to rim inner (r=0.030) \u2014 but these are at same z=0.2479, essentially a thin ring. I'll include the rim in the profile so the top edge has two radii at top.\n - bore: inner wall from rim inner (0.030,0.2479) down to (0.030,0.215), then bore floor disk from 0.030 to center (0,0.215) fan.\n\nSo the profile (open, all r>0) is a single continuous path:\nstart bottom outer (r_b0,0) ... but bottom cap needs to connect to center. Hmm the outer path starts at bottom rim and I cap the bottom separately.\n\nLet me define two separate surface strips + caps:\n\nStrip 1 (outer wall), open path from bottom rim to top rim outer:\nP = [\n (0.060,0.000) # but bottom edge; actually foot bottom\n (0.078,0.008)\n (0.0879,0.014)\n (0.082,0.024)\n (0.080,0.045)\n (0.082,0.090)\n (0.0835,0.120)\n (0.080,0.150)\n (0.070,0.175)\n (0.055,0.195)\n (0.042,0.210)\n (0.035,0.222)\n (0.0335,0.235)\n (0.0335,0.245)\n (0.0345,0.2479) # top rim outer\n (0.030,0.2479) # top rim inner\n (0.030,0.215) # bore floor edge\n]\nAll r>0. Revolve this open strip -> a tube from bottom rim to bore floor edge.\n\nThen bottom cap: fan at z=0 from r=0.060 ring to center (0,0,0). But wait bottom of P starts at (0.060,0.0). The foot: bottom at z=0 is radius 0.060? But the foot outer at z=0.014 is 0.0879. The bottom face of the foot: at z=0 the foot only exists between r where? The very bottom of the object should be a ring/foot. Realistically the object sits on a small foot. The bottom at z=0 spans from center to the foot outer radius at z=0. But my profile at z=0 is r=0.060. So bottom cap from r 0.060 to 0 at z=0. Good, that's a flat bottom disk of radius 0.060. Fine.\n\nTop: the strip ends at (0.030,0.215) bore floor edge and the top rim. The bore floor: fan from r=0.030 ring at z=0.215 to center (0,0.215). And the top rim between (0.0345,0.2479) and (0.030,0.2479) is a small flat ring already part of strip (a single quad ring). Good.\n\nSo I build:\n- tube (revolve P, N segments) -> N*(len(P)-1) quads\n- bottom fan: 1 center vertex + N ring (the first row of P) -> N tris\n- top bore fan: 1 center vertex + N ring (last row of P) -> N tris\n\nWait the top rim: the last row of P is (0.030,0.215) which is the bore floor edge, and the top opening is between row (0.0345) and (0.030) at z=0.2479 which are both in the tube. The bore floor fan closes the bottom of the bore (z=0.215, r 0.030->0). Good, that gives the dark hole appearance when viewed from top (we see into the bore). \n\nGreat, all consistent, watertight (tube sides + bottom disk + bore floor disk; the top is open = the hole, which is correct/intended).\n\nLet me code the lathe producing positions and faceVertexIndices, plus compute vertex normals (area-weighted) for smooth shading. I'll set normals attribute.\n\nLet me write it.\n\nMaterials: \nMaterial \"mat_black_gloss\" using UsdPreviewSurface.\nBind to the Mesh.\n\nPhysics: \nOn Model (or on the Mesh?) SimReady RB: RigidBodyAPI on the \"Model\" prim? Typically the rigid body API goes on the model/assembly prim, and collision on the mesh. Let me put:\n- Model prim: UsdPhysics.RigidBodyAPI + UsdPhysics.MassAPI (mass) or MassPropertiesAPI.\n- Mesh: UsdPhysics.CollisionAPI + UsdPhysics.MeshCollisionAPI (approximation mesh) referencing itself.\n\nMass ~ for a ceramic/metal bell ~ say 3 kg. massProperties density. I'll set UsdPhysics.MassAPI mass = 3.0 and massPropertiesAPI? RigidBodyAPI.mass. Let me set RigidBodyAPI with \"mass\" = 3.0, and massProperties on a child? Actually MassAPI gives mass + COM + inertia. I'll set mass and massPropertiesAPI (diagonalInertia, COM at center). Let me set:\n- RigidBodyAPI.mass = 3.0\n- UsdPhysics.MassPropertiesAPI on Model: centerOfMass=(0,0, H/2), diagonalInertia computed roughly, invDiagonalInertia... SimReady RB.001 requires mass; RB.003 massProperties? Let me just add mass and massProperties.\n\nLet me get inertia: approximate solid of radius ~0.08, height 0.25, mass 3: I ~ (1/12) M (3R^2 + H^2)? For cylinder about x: I = M(3R^2+H^2)/12 = 3*(3*0.08^2+0.2479^2)/12 = 3*(3*0.0064+0.0615)/12 = 3*(0.0192+0.0615)/12=3*0.0807/12=0.0202 kg m^2. diagonalInertia ~ (0.02,0.02, 0.5*M*R^2=0.5*3*0.0064=0.0096). I'll set diagonalInertia=(0.02,0.02,0.01), COM=(0,0,0.124).\n\nNow World/Model structure & metadata.\n\nLet me write it and validate.\n\nRegarding upAxis: SimReady requires the root \"World\" with a \"upAxis\" \u2014 I believe it's a custom attribute on World named \"upAxis\" with value \"Z\", and \"frontAxis\" = \"Y\". Also the stage metadata metersPerUnit. Let me add:\n- stage.SetMetadata('metersPerUnit', 1.0)? Actually Sdf.Metadata \"units\" = \"centimeters\"/\"meters\". USD uses metadata \"units\" on the layer = \"meters\"? The default. SimReady UN.006 wants units meters. I'll set Sdf layer metadata \"units\" = \"meters\" and also metersPerUnit.\n\nLet me write.\n\nFor axis: I'll set World metadata? In SimReady, the \"upAxis\"/\"frontAxis\" are actually custom attributes (Sdf custom) on the World prim, I'm fairly confident. Let me add custom attributes \"upAxis\"=\"Z\", \"frontAxis\"=\"Y\" on World. Also I recall SimReady uses these as prim custom attributes named exactly \"upAxis\" and \"frontAxis\".\n\nLet me proceed and let the validator correct me.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8f5a80f3e99dba0e", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 -c \"\nfrom pxr import Sdf, Usd, UsdGeom, Gf, UsdPhysics, UsdShade\nprint('ok')\nprint([n for n in dir(UsdPhysics) if 'Mass' in n or 'Rigid' in n or 'Collision' in n])\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8f5a80f3e99dba0e", + "content": "ok\n['CollisionAPI', 'CollisionGroup', 'CollisionGroupDesc', 'CollisionGroupDescVector', 'CollisionGroupTable', 'MassAPI', 'MassUnits', 'MassUnitsAre', 'MeshCollisionAPI', 'RigidBodyAPI', 'RigidBodyDesc', 'RigidBodyDescVector', 'RigidBodyMaterialDesc', 'RigidBodyMaterialDescVector']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 11267, + "completion_tokens": 3574, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 14841 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2596b311", + "pi_parent_id": "84923c55", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RpoRLg6Q9jQUwlcMgfeeUMTC", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 9, + "timestamp": "2026-10-21T17:04:18.975Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me write the authoring script now.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9172d76129350569", + "function_name": "write", + "arguments": { + "path": "/tmp/author.py", + "content": "#!/usr/bin/env python3\n\"\"\"Author /output/asset.usd : a black glossy bell/urn (single rigid prop).\"\"\"\nimport numpy as np\nfrom pxr import Sdf, Usd, UsdGeom, Gf, UsdPhysics, UsdShade\n\nOUT = \"/output/asset.usd\"\nN = 128 # segments around Z\n\n# ---- Cross-section profile (r, z) in metres, open strip from bottom rim to bore-floor edge ----\nprofile = [\n (0.060, 0.0000), # bottom rim (foot)\n (0.078, 0.0080),\n (0.0879, 0.0140), # foot bead (max width)\n (0.0820, 0.0240),\n (0.0800, 0.0450),\n (0.0820, 0.0900),\n (0.0835, 0.1200), # body widest\n (0.0800, 0.1500),\n (0.0700, 0.1750),\n (0.0550, 0.1950),\n (0.0420, 0.2100),\n (0.0350, 0.2220),\n (0.0335, 0.2350), # neck\n (0.0335, 0.2450),\n (0.0345, 0.2479), # top rim outer (lip)\n (0.0300, 0.2479), # top rim inner\n (0.0300, 0.2150), # bore floor edge\n]\nH = 0.24786941520869732\n\nangles = np.linspace(0.0, 2.0 * np.pi, N, endpoint=False)\ncos = np.cos(angles); sin = np.sin(angles)\n\npositions = []\nface_index = []\n\n# tube rows\nrow_start = 0\nfor (r, z) in profile:\n for j in range(N):\n positions.append((r * cos[j], r * sin[j], z))\nnrows = len(profile)\nbase = 0\n# quads between consecutive rows\nfor i in range(nrows - 1):\n a = i * N\n b = (i + 1) * N\n for j in range(N):\n j2 = (j + 1) % N\n face_index += [a + j, a + j2, b + j2, b + j]\n\n# bottom cap fan (z=0, r=profile[0][0]) to center\nbottom_center = len(positions)\npositions.append((0.0, 0.0, 0.0))\nring0 = 0 # first row\nfor j in range(N):\n j2 = (j + 1) % N\n face_index += [bottom_center, ring0 + j2, ring0 + j]\n\n# bore floor fan (z=0.215, r=profile[-1][0]) to center\nbore_center = len(positions)\npositions.append((0.0, 0.0, 0.215))\nringb = (nrows - 1) * N\nfor j in range(N):\n j2 = (j + 1) % N\n face_index += [bore_center, ringb + j, ringb + j2]\n\npositions = np.array(positions, dtype=np.float64)\n# build flat face vertex list\nfvi = []\nfor f in face_index:\n fvi.extend(f)\n\n# ---- compute area-weighted vertex normals ----\nverts = positions\nnum_v = len(verts)\nnormals = np.zeros((num_v, 3), dtype=np.float64)\nfaces = np.array(face_index, dtype=np.int64).reshape(-1, 4)\nfor f in faces:\n p0 = verts[f[0]]; p1 = verts[f[1]]; p2 = verts[f[2]]; p3 = verts[f[3]]\n # split quad\n for tri in (p0, p1, p2), (p0, p2, p3):\n n = np.cross(tri[1] - tri[0], tri[2] - tri[0])\n for idx in (f[[tri.index(t) for t in ()]] if False else []):\n pass\n # attribute to the three verts\n for v in (f[0], f[1], f[2]):\n pass\n# simpler: accumulate per face normal weighted to its vertices\nfaces3 = np.array(face_index, dtype=np.int64).reshape(-1, 4)\nfor f in faces3:\n a, b, c, d = f\n p0, p1, p2, p3 = verts[a], verts[b], verts[c], verts[d]\n n1 = np.cross(p1 - p0, p2 - p0)\n n2 = np.cross(p0 - p2, p3 - p2)\n n = n1 + n2\n for idx in (a, b, c, d):\n normals[idx] += n\nnn = np.linalg.norm(normals, axis=1, keepdims=True)\nnn[nn == 0] = 1.0\nnormals = normals / nn\n\n# ---- write USD ----\nstage = Usd.Stage.CreateNew(OUT)\nstage.SetMetadata(\"upAxis\", Sdf.ValueTypeNames.AxisZ)\nstage.SetMetadata(\"defaultPrim\", \"Model\")\n# meters\nstage.GetRootLayer().AddRelationship # noop\nSdf.Layer.FindOrCreate(OUT) # ensure\n# set units via metadata\nstage.GetRootLayer().specifier # noop\n\nworld = UsdGeom.Xform.Define(stage, \"World\")\n# SimReady world metadata\nworld.GetPrim().AddRelationship # noop\n# custom upAxis/frontAxis on World\nUsd.AddPrim # noop\n\nmodel = UsdGeom.Xform.Define(stage, \"/World/Model\")\n\n# mesh\nmesh = UsdGeom.Mesh.Define(stage, \"/World/Model/BellBody\")\nmesh.CreatePointsAttr([Gf.Vec3d(*p) for p in positions])\nmesh.CreateFaceVertexIndicesAttr(fvi)\nmesh.CreateVertexNormalsAttr([Gf.Vec3f(*n) for n in normals])\nmesh.SetSubdivisionScheme(\"none\")\n\n# orient world so model local origin at base center; position model at origin\n# (canonical: base at z=0, centered on X/Y). Already centered.\n\n# ---- Material ----\nmat = UsdShade.Material.Define(stage, \"/World/Materials/BellBlackGloss\")\nmat.CreateSurfaceOutput()\nmatp = mat.GetPrim()\nshader = mat.CreateShader(\"UsdPreviewSurface\")\nshader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\nfor attr, val in [\n (\"baseColor\", (0.020, 0.020, 0.022)),\n (\"metallic\", 0.0),\n (\"roughness\", 0.06),\n (\"specular\", 1.0),\n (\"clearcoat\", 0.4),\n (\"clearcoatRoughness\", 0.08),\n]:\n shader.CreateInput(attr, Sdf.ValueTypeNames.Color3f if attr == \"baseColor\" else Sdf.ValueTypeNames.Float).Set(val)\nsurf_out = mat.GetPrim().GetAttribute(\"outputs:surface\")\n# wire surface\nmat.Bind(surface=None) # noop\nbind_api = UsdShade.MaterialBindingAPI.Apply(mat)\nbind_api.BindDirect(mesh.GetPrim())\n\n# ---- Rigid body + collision ----\nmodel_api = UsdPhysics.RigidBodyAPI.Apply(model)\nmodel_api.CreateMassAttr(3.0)\nmodel_api.CreateKinematicEnabledAttr(False)\n\nmp = UsdPhysics.MassPropertiesAPI.Apply(model)\nmp.CreateCenterOfMassAttr(Gf.Vec3d(0.0, 0.0, 0.12))\nmp.CreateDiagonalInertiaAttr(Gf.Vec3d(0.02, 0.02, 0.01))\n\ncol_api = UsdPhysics.CollisionAPI.Apply(mesh)\nmcol = UsdPhysics.MeshCollisionAPI.Apply(mesh)\nmcol.CreateCollisionExtentsAttr([Gf.Vec3f(0.088, 0.088, 0.248)])\n\n# world up/front axis custom attributes (SimReady)\nprim = world.GetPrim()\nprim.CreateAttribute(\"upAxis\", Sdf.ValueTypeNames.Token).Set(\"Z\")\nprim.CreateAttribute(\"frontAxis\", Sdf.ValueTypeNames.Token).Set(\"Y\")\n\nstage.GetRootLayer().Export()\nprint(\"WROTE\", OUT)\n" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9172d76129350569", + "content": "Successfully wrote to /tmp/author.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 14929, + "completion_tokens": 2123, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 17052 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "763132f6", + "pi_parent_id": "1f83a641", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RhEHXSioc71u2iTIvLwWZxSz", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 10, + "timestamp": "2026-10-21T17:05:31.319Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I have some messy noop lines in my script. Let me clean it up before running.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-84ffd756cc3f1b56", + "function_name": "write", + "arguments": { + "content": "#!/usr/bin/env python3\n\"\"\"Author /output/asset.usd : a black glossy bell/urn (single rigid prop).\"\"\"\nimport numpy as np\nfrom pxr import Sdf, Usd, UsdGeom, Gf, UsdPhysics, UsdShade\n\nOUT = \"/output/asset.usd\"\nN = 128 # segments around Z\n\n# Cross-section profile (r, z) in metres, open strip from bottom rim to bore-floor edge\nprofile = [\n (0.060, 0.0000), # bottom rim (foot)\n (0.078, 0.0080),\n (0.0879, 0.0140), # foot bead (max width)\n (0.0820, 0.0240),\n (0.0800, 0.0450),\n (0.0820, 0.0900),\n (0.0835, 0.1200), # body widest\n (0.0800, 0.1500),\n (0.0700, 0.1750),\n (0.0550, 0.1950),\n (0.0420, 0.2100),\n (0.0350, 0.2220),\n (0.0335, 0.2350), # neck\n (0.0335, 0.2450),\n (0.0345, 0.2479), # top rim outer (lip)\n (0.0300, 0.2479), # top rim inner\n (0.0300, 0.2150), # bore floor edge\n]\n\nangles = np.linspace(0.0, 2.0 * np.pi, N, endpoint=False)\ncos = np.cos(angles); sin = np.sin(angles)\n\npositions = []\nface_index = []\nnrows = len(profile)\nfor (r, z) in profile:\n for j in range(N):\n positions.append((r * cos[j], r * sin[j], z))\nfor i in range(nrows - 1):\n a = i * N\n b = (i + 1) * N\n for j in range(N):\n j2 = (j + 1) % N\n face_index += [a + j, a + j2, b + j2, b + j]\n\n# bottom cap fan (z=0) to center\nbottom_center = len(positions)\npositions.append((0.0, 0.0, 0.0))\nring0 = 0\nfor j in range(N):\n j2 = (j + 1) % N\n face_index += [bottom_center, ring0 + j2, ring0 + j]\n\n# bore floor fan (z=0.215) to center\nbore_center = len(positions)\npositions.append((0.0, 0.0, 0.215))\nringb = (nrows - 1) * N\nfor j in range(N):\n j2 = (j + 1) % N\n face_index += [bore_center, ringb + j, ringb + j2]\n\nverts = np.array(positions, dtype=np.float64)\nnum_v = len(verts)\nnormals = np.zeros((num_v, 3), dtype=np.float64)\nfaces3 = np.array(face_index, dtype=np.int64).reshape(-1, 4)\nfor f in faces3:\n a, b, c, d = f\n p0, p1, p2, p3 = verts[a], verts[b], verts[c], verts[d]\n n1 = np.cross(p1 - p0, p2 - p0)\n n2 = np.cross(p0 - p2, p3 - p2)\n n = n1 + n2\n for idx in (a, b, c, d):\n normals[idx] += n\nnn = np.linalg.norm(normals, axis=1, keepdims=True)\nnn[nn == 0] = 1.0\nnormals = normals / nn\n\nfvi = []\nfor f in face_index:\n fvi.extend(f)\n\n# ---- write USD ----\nstage = Usd.Stage.CreateNew(OUT)\nstage.SetDefaultPrim(\"/World/Model\")\n# units meters\nstage.GetRootLayer().AddReferenceToContents = None # noop guard\n\nworld = UsdGeom.Xform.Define(stage, \"World\")\nmodel = UsdGeom.Xform.Define(stage, \"/World/Model\")\n\n# mesh\nmesh = UsdGeom.Mesh.Define(stage, \"/World/Model/BellBody\")\nmesh.CreatePointsAttr([Gf.Vec3d(*p) for p in positions])\nmesh.CreateFaceVertexIndicesAttr(fvi)\nmesh.CreateVertexNormalsAttr([Gf.Vec3f(*n) for n in normals])\nmesh.SetSubdivisionScheme(\"none\")\n\n# ---- Material ----\nmat = UsdShade.Material.Define(stage, \"/World/Materials/BellBlackGloss\")\nmatp = mat.GetPrim()\nshader = mat.CreateShader(\"UsdPreviewSurface\")\nshader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\nshader.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color3f).Set((0.020, 0.020, 0.022))\nshader.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(0.0)\nshader.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(0.06)\nshader.CreateInput(\"specular\", Sdf.ValueTypeNames.Float).Set(1.0)\nshader.CreateInput(\"clearcoat\", Sdf.ValueTypeNames.Float).Set(0.4)\nshader.CreateInput(\"clearcoatRoughness\", Sdf.ValueTypeNames.Float).Set(0.08)\nmat.ConnectShaderToOutput(shader, \"\", \"surface\")\n\nbind_api = UsdShade.MaterialBindingAPI.Apply(mat)\nbind_api.BindDirect(mesh.GetPrim())\n\n# ---- Rigid body + collision ----\nmodel_api = UsdPhysics.RigidBodyAPI.Apply(model)\nmodel_api.CreateMassAttr(3.0)\nmodel_api.CreateKinematicEnabledAttr(False)\nmp = UsdPhysics.MassPropertiesAPI.Apply(model)\nmp.CreateCenterOfMassAttr(Gf.Vec3d(0.0, 0.0, 0.12))\nmp.CreateDiagonalInertiaAttr(Gf.Vec3d(0.02, 0.02, 0.01))\n\ncol_api = UsdPhysics.CollisionAPI.Apply(mesh)\nmcol = UsdPhysics.MeshCollisionAPI.Apply(mesh)\nmcol.CreateCollisionExtentsAttr([Gf.Vec3f(0.088, 0.088, 0.248)])\n\n# SimReady world up/front axis\nprim = world.GetPrim()\nprim.CreateAttribute(\"upAxis\", Sdf.ValueTypeNames.Token).Set(\"Z\")\nprim.CreateAttribute(\"frontAxis\", Sdf.ValueTypeNames.Token).Set(\"Y\")\n\nstage.GetRootLayer().Export()\nprint(\"WROTE\", OUT)\nprint(\"verts\", num_v, \"faces\", len(face_index))\n", + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-84ffd756cc3f1b56", + "content": "Successfully wrote to /tmp/author.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 17074, + "completion_tokens": 1763, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 18837 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "5f71b124", + "pi_parent_id": "b5a09b7f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RZSXGQGcBK7yS1SollWLDISI", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 11, + "timestamp": "2026-10-21T17:05:38.600Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me remove the noop guard line and set the units properly. Let me fix the units: stage.GetRootLayer().AddReferenceToContents is a bad line. Let me set metadata. Actually USD stage metadata for units is via the Sdf layer \"units\"? Let me just set it. Let me run and fix.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-87b0bc13b351e21d", + "function_name": "edit", + "arguments": { + "path": "/tmp/author.py", + "edits": [ + { + "oldText": "stage.SetDefaultPrim(\"/World/Model\")\n# units meters\nstage.GetRootLayer().AddReferenceToContents = None # noop guard\n", + "newText": "stage.SetDefaultPrim(\"/World/Model\")\n# units meters\nstage.GetRootLayer().AddMetadata(\"units\", Sdf.ValueTypeNames.Token, \"meters\")\n" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-87b0bc13b351e21d", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 18861, + "completion_tokens": 193, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19054 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "0f1a1e9b", + "pi_parent_id": "ef372e5d", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R9kduJkv0qIdyX7Ih9A4zvsS", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 12, + "timestamp": "2026-10-21T17:05:42.085Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run the script.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b718b4cd2a0201bc", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b718b4cd2a0201bc", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 80, in \n fvi.extend(f)\nTypeError: 'int' object is not iterable", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 19083, + "completion_tokens": 54, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19137 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "6c26251f", + "pi_parent_id": "963ce5d8", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rttsq7BPWpPqeQfoRLHQ2Jbh", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 13, + "timestamp": "2026-10-21T17:05:48.849Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "fvi loop: `for f in face_index: fvi.extend(f)` \u2014 but face_index is a flat list of ints. I need to reshape face_index into quads first. Let me fix: face_index is flat list. Build fvi = list(face_index) directly, and faces3 = np.array(face_index).reshape(-1,4).", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9e62985f28d3aa89", + "function_name": "edit", + "arguments": { + "path": "/tmp/author.py", + "edits": [ + { + "oldText": "fvi = []\nfor f in face_index:\n fvi.extend(f)\n", + "newText": "fvi = list(face_index)\n" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9e62985f28d3aa89", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 19195, + "completion_tokens": 158, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19353 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "0d4758e8", + "pi_parent_id": "5d566573", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RUwXdl6mfyZ49UL2emUBfdbp", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 14, + "timestamp": "2026-10-21T17:06:00.122Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run it now.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9041d9dac21094cf", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9041d9dac21094cf", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 82, in \n stage.SetDefaultPrim(\"/World/Model\")\nBoost.Python.ArgumentError: Python argument types in\n Stage.SetDefaultPrim(Stage, str)\ndid not match C++ signature:\n SetDefaultPrim(pxrInternal_v0_26_8__pxrReserved__::UsdStage {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdPrim prim)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 19382, + "completion_tokens": 54, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19436 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "aa4f5283", + "pi_parent_id": "e1eb2923", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RaSLpvlvoFVLIrdzkr5TmXLI", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 15, + "timestamp": "2026-10-21T17:06:10.259Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Need to set default prim after creating the prim. Let me move SetDefaultPrim to the end, or use GetPrimIdentifier. Let me create the prim first then set default.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a36b583e10bdca12", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "# units meters\nstage.GetRootLayer().AddMetadata(\"units\", Sdf.ValueTypeNames.Token, \"meters\")\n", + "oldText": "stage.SetDefaultPrim(\"/World/Model\")\n# units meters\nstage.GetRootLayer().AddMetadata(\"units\", Sdf.ValueTypeNames.Token, \"meters\")\n" + }, + { + "newText": "prim = world.GetPrim()\nprim.CreateAttribute(\"upAxis\", Sdf.ValueTypeNames.Token).Set(\"Z\")\nprim.CreateAttribute(\"frontAxis\", Sdf.ValueTypeNames.Token).Set(\"Y\")\n\nstage.SetDefaultPrim(Usd.Prim(stage, \"/World/Model\"))\n", + "oldText": "prim = world.GetPrim()\nprim.CreateAttribute(\"upAxis\", Sdf.ValueTypeNames.Token).Set(\"Z\")\nprim.CreateAttribute(\"frontAxis\", Sdf.ValueTypeNames.Token).Set(\"Y\")\n" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a36b583e10bdca12", + "content": "Successfully replaced 2 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 19567, + "completion_tokens": 285, + "cached_tokens": 17248, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19852 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "b65a84ed", + "pi_parent_id": "cc5a81ca", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R7roeA6bp6YfVziQ4TKbKhTa", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 16, + "timestamp": "2026-10-21T17:06:12.888Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run it now.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9d08244e2ed1fdb5", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9d08244e2ed1fdb5", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 83, in \n stage.GetRootLayer().AddMetadata(\"units\", Sdf.ValueTypeNames.Token, \"meters\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Layer' object has no attribute 'AddMetadata'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 19881, + "completion_tokens": 54, + "cached_tokens": 18816, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 19935 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "31a8413f", + "pi_parent_id": "a370551c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RkGRRBMHfSGehrUUwK9kodjB", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 17, + "timestamp": "2026-10-21T17:06:26.229Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me use SetInfo for metadata on the layer. Actually Sdf layer metadata is set via layer.AddInfo or by setting the \"metersPerUnit\". The simplest way to set units: `layer.addRelationship`? No. Sdf layer: metadata like \"upAxis\", \"frontAxis\", \"units\" are set via `layer.AddMetadata`? That doesn't exist. It's `layer.AddInfo(name, value)` for info, and metadata via... In PXR, Sdf.Layer metadata is set with `layer.AddMetadata`? Let me check. Actually the method is `Sdf.Layer.AddMetadata(key, value, typeName)`? No. It's not available in all builds. \n\nThe cleanest approach: create the layer and set `units` through the metadata. Actually the correct API is `layer.AddMetadata(\"units\", Sdf.Token(\"meters\"))`? Not available. \n\nThe metersPerUnit is a stage metadata that defaults to 1.0 (meters). USD's default unit is already meters (metersPerUnit=1.0). So I might not need to set units at all. The default USD stage units are meters. Let me just remove the units line.\n\nLet me remove it.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bfca72711556595b", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "# units meters (USD default is 1 m / unit)\ntry:\n stage.GetRootLayer().AddMetadata(\"units\", Sdf.ValueTypeNames.Token, \"meters\")\nexcept Exception:\n pass\n", + "oldText": "# units meters\nstage.GetRootLayer().AddMetadata(\"units\", Sdf.ValueTypeNames.Token, \"meters\")\n" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bfca72711556595b", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 20026, + "completion_tokens": 385, + "cached_tokens": 18816, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 20411 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "438c441e", + "pi_parent_id": "283015f6", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RFnFNv85UOVvOmdeLRUFKmzb", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 18, + "timestamp": "2026-10-21T17:06:29.853Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run and validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a272a4f08372c611", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20 && ls -la /output" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a272a4f08372c611", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 88, in \n world = UsdGeom.Xform.Define(stage, \"World\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\npxr.Tf.ErrorException: \n\tError in 'pxrInternal_v0_26_8__pxrReserved__::UsdStage::_IsValidPathForCreatingPrim' at line 3775 in file /opt/USD/pxr/usd/usd/stage.cpp : 'Path must be an absolute path: '\ntotal 4\ndrwxrwxrwx 2 actor actor 60 Oct 21 17:06 .\ndrwxr-xr-x 1 root root 56 Oct 21 16:59 ..\n-rw-r--r-- 1 actor actor 492 Oct 21 17:06 asset.usd", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 20440, + "completion_tokens": 60, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 20500 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "5d299935", + "pi_parent_id": "ec7aad64", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R6AQ8nClcdiN4sfaPMg5n8hh", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 19, + "timestamp": "2026-10-21T17:06:33.801Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Use absolute paths for World.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9e15998bd65bab70", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "world = UsdGeom.Xform.Define(stage, \"/World\")", + "oldText": "world = UsdGeom.Xform.Define(stage, \"World\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9e15998bd65bab70", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 20728, + "completion_tokens": 92, + "cached_tokens": 19600, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 20820 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c03def36", + "pi_parent_id": "5a8b1a5f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RJTUE5SQtMb9CjSOvmAIgLpM", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 20, + "timestamp": "2026-10-21T17:06:55.152Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run and validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-89fdde051aaf786e", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-89fdde051aaf786e", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 95, in \n mesh.CreateVertexNormalsAttr([Gf.Vec3f(*n) for n in normals])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Mesh' object has no attribute 'CreateVertexNormalsAttr'. Did you mean: 'CreateNormalsAttr'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 20849, + "completion_tokens": 54, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 20903 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "8d12bf69", + "pi_parent_id": "6e96f525", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RYGtVwkoR0TilKRyESP1wRzH", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 21, + "timestamp": "2026-10-21T17:07:01.400Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me use CreateNormalsAttr.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-af3da87f95cc3120", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "mesh.CreateNormalsAttr([Gf.Vec3f(*n) for n in normals])", + "oldText": "mesh.CreateVertexNormalsAttr([Gf.Vec3f(*n) for n in normals])" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-af3da87f95cc3120", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 21003, + "completion_tokens": 103, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 21106 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "bf9a816a", + "pi_parent_id": "4290a6f2", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RZigpo1FP34D1SkIXgJOfIoJ", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 22, + "timestamp": "2026-10-21T17:07:06.575Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run and then validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9ba0f1be0853794d", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9ba0f1be0853794d", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 96, in \n mesh.SetSubdivisionScheme(\"none\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Mesh' object has no attribute 'SetSubdivisionScheme'. Did you mean: 'GetSubdivisionSchemeAttr'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 21135, + "completion_tokens": 55, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 21190 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "1e7b2cad", + "pi_parent_id": "78fb9c0f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RII4cFrkG5tpLG3jFc4n21OD", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 23, + "timestamp": "2026-10-21T17:07:11.175Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me set the subdivision scheme attribute. UsdGeom.Mesh has a SetSubdivisionSchemeAttr? Actually it's mesh.GetSubdivisionSchemeAttr().Set(\"none\"). Let me use that.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b5372a02c910a026", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "mesh.GetSubdivisionSchemeAttr().Set(\"none\")", + "oldText": "mesh.SetSubdivisionScheme(\"none\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b5372a02c910a026", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 21278, + "completion_tokens": 115, + "cached_tokens": 20384, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 21393 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "3fa1e72b", + "pi_parent_id": "88dbcc0c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RpOuk0ZNbUudLh8KgZDhzxDn", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 24, + "timestamp": "2026-10-21T17:07:14.563Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run it.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-84cd6cdd95966d07", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-84cd6cdd95966d07", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 101, in \n shader = mat.CreateShader(\"UsdPreviewSurface\")\n ^^^^^^^^^^^^^^^^\nAttributeError: 'Material' object has no attribute 'CreateShader'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 21422, + "completion_tokens": 53, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 21475 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2936601f", + "pi_parent_id": "4a11ae19", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R4nzcVFbaE4z04utgRHI5ca3", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 25, + "timestamp": "2026-10-21T17:07:48.486Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 24 of 64, with 40 model rounds left. I need to be efficient. Let me fix the material creation: UsdShade.Material doesn't have CreateShader. Instead I create a UsdShade.Shader prim. Let me create a Shader prim directly under the material.\n\nLet me use:\n```\nshader = UsdShade.Shader.Define(stage, \"/World/Materials/BellBlackGloss/Shader\")\nshader.CreateSourceAttr(\"id\").Set(\"UsdPreviewSurface\")\n...\nmat.ConnectShaderToOutput(shader, \"surface\", \"surface\") # or mat.CreateOutput(\"surface\").ConnectToSource(shader, \"surface\")\n```\nActually material surface: `mat.CreateOutput(\"surface\")` and connect to shader's \"surface\" output. UsdPreviewSurface has an output named \"surface\". Connect: `mat.CreateOutput(\"surface\").ConnectToSource(shader.GetPrim(), \"surface\")`.\n\nLet me rewrite the material section.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-86c57f409525841a", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "mat = UsdShade.Material.Define(stage, \"/World/Materials/BellBlackGloss\")\nmatp = mat.GetPrim()\nshader = UsdShade.Shader.Define(stage, \"/World/Materials/BellBlackGloss/Shader\")\nshader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\nshader.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color3f).Set((0.020, 0.020, 0.022))\nshader.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(0.0)\nshader.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(0.06)\nshader.CreateInput(\"specular\", Sdf.ValueTypeNames.Float).Set(1.0)\nshader.CreateInput(\"clearcoat\", Sdf.ValueTypeNames.Float).Set(0.4)\nshader.CreateInput(\"clearcoatRoughness\", Sdf.ValueTypeNames.Float).Set(0.08)\nout = mat.CreateOutput(\"surface\")\nout.ConnectToSource(shader.GetPrim(), \"surface\")", + "oldText": "mat = UsdShade.Material.Define(stage, \"/World/Materials/BellBlackGloss\")\nmatp = mat.GetPrim()\nshader = mat.CreateShader(\"UsdPreviewSurface\")\nshader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\nshader.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color3f).Set((0.020, 0.020, 0.022))\nshader.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(0.0)\nshader.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(0.06)\nshader.CreateInput(\"specular\", Sdf.ValueTypeNames.Float).Set(1.0)\nshader.CreateInput(\"clearcoat\", Sdf.ValueTypeNames.Float).Set(0.4)\nshader.CreateInput(\"clearcoatRoughness\", Sdf.ValueTypeNames.Float).Set(0.08)\nsurf_out = mat.GetPrim().GetAttribute(\"outputs:surface\")\n# wire surface\nmat.Bind(surface=None) # noop" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-86c57f409525841a", + "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": 21553, + "completion_tokens": 757, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 22310 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "1d56018c", + "pi_parent_id": "731f0658", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-REDwAmPKrRidUACH599q7gWn", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 26, + "timestamp": "2026-10-21T17:07:52.589Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me read the current material section to get exact text.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9966d095b5cd4225", + "function_name": "read", + "arguments": { + "path": "/tmp/author.py", + "offset": 98, + "limit": 20 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9966d095b5cd4225", + "content": "# ---- Material ----\nmat = UsdShade.Material.Define(stage, \"/World/Materials/BellBlackGloss\")\nmatp = mat.GetPrim()\nshader = mat.CreateShader(\"UsdPreviewSurface\")\nshader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\nshader.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color3f).Set((0.020, 0.020, 0.022))\nshader.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(0.0)\nshader.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(0.06)\nshader.CreateInput(\"specular\", Sdf.ValueTypeNames.Float).Set(1.0)\nshader.CreateInput(\"clearcoat\", Sdf.ValueTypeNames.Float).Set(0.4)\nshader.CreateInput(\"clearcoatRoughness\", Sdf.ValueTypeNames.Float).Set(0.08)\nmat.ConnectShaderToOutput(shader, \"\", \"surface\")\n\nbind_api = UsdShade.MaterialBindingAPI.Apply(mat)\nbind_api.BindDirect(mesh.GetPrim())\n\n# ---- Rigid body + collision ----\nmodel_api = UsdPhysics.RigidBodyAPI.Apply(model)\nmodel_api.CreateMassAttr(3.0)\nmodel_api.CreateKinematicEnabledAttr(False)\n\n[19 more lines in file. Use offset=118 to continue.]", + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 22351, + "completion_tokens": 68, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 22419 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "92074e25", + "pi_parent_id": "a94d30c1", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RlnUedLvEVe9MAj9pDBhC7VJ", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 27, + "timestamp": "2026-10-21T17:08:07.036Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 26 of 64. I have 38 rounds left. Let me fix the material creation.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9aef55f0dd680c95", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "mat = UsdShade.Material.Define(stage, \"/World/Materials/BellBlackGloss\")\nmatp = mat.GetPrim()\nshader = UsdShade.Shader.Define(stage, \"/World/Materials/BellBlackGloss/Shader\")\nshader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\nshader.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color3f).Set((0.020, 0.020, 0.022))\nshader.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(0.0)\nshader.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(0.06)\nshader.CreateInput(\"specular\", Sdf.ValueTypeNames.Float).Set(1.0)\nshader.CreateInput(\"clearcoat\", Sdf.ValueTypeNames.Float).Set(0.4)\nshader.CreateInput(\"clearcoatRoughness\", Sdf.ValueTypeNames.Float).Set(0.08)\nout = mat.CreateOutput(\"surface\")\nout.ConnectToSource(shader.GetPrim(), \"surface\")", + "oldText": "mat = UsdShade.Material.Define(stage, \"/World/Materials/BellBlackGloss\")\nmatp = mat.GetPrim()\nshader = mat.CreateShader(\"UsdPreviewSurface\")\nshader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\nshader.CreateInput(\"baseColor\", Sdf.ValueTypeNames.Color3f).Set((0.020, 0.020, 0.022))\nshader.CreateInput(\"metallic\", Sdf.ValueTypeNames.Float).Set(0.0)\nshader.CreateInput(\"roughness\", Sdf.ValueTypeNames.Float).Set(0.06)\nshader.CreateInput(\"specular\", Sdf.ValueTypeNames.Float).Set(1.0)\nshader.CreateInput(\"clearcoat\", Sdf.ValueTypeNames.Float).Set(0.4)\nshader.CreateInput(\"clearcoatRoughness\", Sdf.ValueTypeNames.Float).Set(0.08)\nmat.ConnectShaderToOutput(shader, \"\", \"surface\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9aef55f0dd680c95", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 22741, + "completion_tokens": 556, + "cached_tokens": 21952, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 23297 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2ce19985", + "pi_parent_id": "3e7c0262", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RPCHpLfOOuw7c7ngnXYXm3Fc", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 28, + "timestamp": "2026-10-21T17:08:10.917Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run the script now.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-badb69dda35b16f9", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-badb69dda35b16f9", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 102, in \n shader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Shader' object has no attribute 'CreateSourceAttribute'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 23326, + "completion_tokens": 55, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 23381 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "a1c7ed93", + "pi_parent_id": "317a40bc", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RqL4jeZFcpV496AJ2DKKH9lD", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 29, + "timestamp": "2026-10-21T17:08:16.406Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me fix: UsdShade.Shader has CreateSourceAttr, not CreateSourceAttribute.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-884bbb1ff47a4daf", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "shader.CreateSourceAttr(\"id\").Set(\"UsdPreviewSurface\")", + "oldText": "shader.CreateSourceAttribute(\"id\").Set(\"UsdPreviewSurface\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-884bbb1ff47a4daf", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 23466, + "completion_tokens": 107, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 23573 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "0dc0e062", + "pi_parent_id": "dc53c02e", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RBo8NUYmS2FC3A5lQcCpR9bN", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 30, + "timestamp": "2026-10-21T17:08:20.652Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9b80d70600cae6e4", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9b80d70600cae6e4", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 102, in \n shader.CreateSourceAttr(\"id\").Set(\"UsdPreviewSurface\")\n ^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Shader' object has no attribute 'CreateSourceAttr'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 23602, + "completion_tokens": 52, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 23654 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "4f2dc918", + "pi_parent_id": "44a7e80e", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RI7S6uyD6qEwwtxhw9DxzbOk", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 31, + "timestamp": "2026-10-21T17:08:25.571Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me check the Shader API methods available.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b15eebda9b23d64f", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 -c \"\nfrom pxr import UsdShade\nprint([m for m in dir(UsdShade.Shader) if 'Source' in m or 'Attribute' in m or 'Create' in m])\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b15eebda9b23d64f", + "content": "['CreateIdAttr', 'CreateImplementationSourceAttr', 'CreateInput', 'CreateOutput', 'GetImplementationSource', 'GetImplementationSourceAttr', 'GetSchemaAttributeNames', 'GetShaderNodeForSourceType', 'GetSourceAsset', 'GetSourceAssetSubIdentifier', 'GetSourceCode', 'GetSourceTypes', 'SetSourceAsset', 'SetSourceAssetSubIdentifier', 'SetSourceCode']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 23737, + "completion_tokens": 92, + "cached_tokens": 21952, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 23829 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "b59ac937", + "pi_parent_id": "4b8a1852", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RRWqn9kI41987uKwJDePLmlz", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 32, + "timestamp": "2026-10-21T17:08:57.010Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me use CreateIdAttr to set the id, and CreateImplementationSourceAttr for the \"id\" type. Actually for UsdPreviewSurface, the source is \"usd-preview-surface\" and id is \"UsdPreviewSurface\". Let me use SetSourceType. Actually the simplest: use CreateIdAttr for \"id\". The implementation source is \"shader\" (built-in). Let me set implementation source to \"usd-preview-surface\"? \n\nStandard: \n```\nshader.CreateIdAttr().Set(\"UsdPreviewSurface\")\nshader.GetImplementationSourceAttr().Set(\"usd-preview-surface\")\n```\nWait, GetImplementationSourceAttr().Set expects a token value. Let me set source to \"usd-preview-surface\".\n\nActually the createIdAttr sets the \"id\" attribute. Let me do that.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-af18d75e0a6f09ba", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "shader.GetImplementationSourceAttr().Set(\"usd-preview-surface\")\nshader.CreateIdAttr().Set(\"UsdPreviewSurface\")", + "oldText": "shader.CreateSourceAttr(\"id\").Set(\"UsdPreviewSurface\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-af18d75e0a6f09ba", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 23926, + "completion_tokens": 271, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 24197 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "36616715", + "pi_parent_id": "909f6e00", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RgaQ2bOYYim3teYRQdO4KHcN", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 33, + "timestamp": "2026-10-21T17:09:01.541Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run and check.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-ad6c6c470bd105b9", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-ad6c6c470bd105b9", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 110, in \n out = mat.CreateOutput(\"surface\")\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\nBoost.Python.ArgumentError: Python argument types in\n NodeGraph.CreateOutput(Material, str)\ndid not match C++ signature:\n CreateOutput(pxrInternal_v0_26_8__pxrReserved__::UsdShadeNodeGraph {lvalue}, pxrInternal_v0_26_8__pxrReserved__::TfToken name, pxrInternal_v0_26_8__pxrReserved__::SdfValueTypeName typeName)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 24225, + "completion_tokens": 54, + "cached_tokens": 22736, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 24279 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "38a60a9e", + "pi_parent_id": "c628b298", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RwDowK4PQAV3eEbdAiD5HvGg", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 34, + "timestamp": "2026-10-21T17:09:07.642Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "CreateOutput needs a type name. The \"surface\" output type is \"token\". Let me pass Sdf.ValueTypeNames.Token.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bfd663a848027472", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "out = mat.CreateOutput(\"surface\", Sdf.ValueTypeNames.Token)", + "oldText": "out = mat.CreateOutput(\"surface\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bfd663a848027472", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 24443, + "completion_tokens": 106, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 24549 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "6db76ee3", + "pi_parent_id": "3651f0b5", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rvw9DMnuw3DjSPLRLQjlqyNo", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 35, + "timestamp": "2026-10-21T17:09:24.928Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run and validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a35a3f35e9433b1a", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a35a3f35e9433b1a", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 111, in \n out.ConnectToSource(shader.GetPrim(), \"surface\")\nBoost.Python.ArgumentError: Python argument types in\n Output.ConnectToSource(Output, Prim, str)\ndid not match C++ signature:\n ConnectToSource(pxrInternal_v0_26_8__pxrReserved__::UsdShadeOutput {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeOutput sourceOutput)\n ConnectToSource(pxrInternal_v0_26_8__pxrReserved__::UsdShadeOutput {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeInput sourceInput)\n ConnectToSource(pxrInternal_v0_26_8__pxrReserved__::UsdShadeOutput {lvalue}, pxrInternal_v0_26_8__pxrReserved__::SdfPath sourcePath)\n ConnectToSource(pxrInternal_v0_26_8__pxrReserved__::UsdShadeOutput {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeConnectableAPI source, pxrInternal_v0_26_8__pxrReserved__::TfToken sourceName, pxrInternal_v0_26_8__pxrReserved__::UsdShadeAttributeType sourceType=pxr.UsdShade.AttributeType.Output, pxrInternal_v0_26_8__pxrReserved__::SdfValueTypeName typeName=)\n ConnectToSource(pxrInternal_v0_26_8__pxrReserved__::UsdShadeOutput {lvalue}, pxrInternal_v0_26_8__pxrReserved__::UsdShadeConnectionSourceInfo source, pxrInternal_v0_26_8__pxrReserved__::UsdShadeConnectionModification mod=pxr.UsdShade.ConnectionModification.Replace)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 24578, + "completion_tokens": 54, + "cached_tokens": 24304, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 24632 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "36f6fd85", + "pi_parent_id": "b6234c9d", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RcMSUZjUBjVBzUfJcUAXdxxN", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 36, + "timestamp": "2026-10-21T17:09:32.872Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "ConnectToSource with a path: Sdf.Path. Let me use a path string for the shader's surface output.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a4ccf0da6da5a564", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "out.ConnectToSource(Sdf.Path(\"/World/Materials/BellBlackGloss/Shader.outputs:surface\"))", + "oldText": "out.ConnectToSource(shader.GetPrim(), \"surface\")" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a4ccf0da6da5a564", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25124, + "completion_tokens": 117, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25241 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2cb48dba", + "pi_parent_id": "01836d00", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RynFkQq8A1JsEPtt1DDN2ahM", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 37, + "timestamp": "2026-10-21T17:09:37.678Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Need to import Sdf (already imported). Let me run.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-959faf3881ce1a44", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-959faf3881ce1a44", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 113, in \n bind_api = UsdShade.MaterialBindingAPI.Apply(mat)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nBoost.Python.ArgumentError: Python argument types in\n MaterialBindingAPI.Apply(Material)\ndid not match C++ signature:\n Apply(pxrInternal_v0_26_8__pxrReserved__::UsdPrim prim)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25270, + "completion_tokens": 61, + "cached_tokens": 25088, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25331 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "f21f8afa", + "pi_parent_id": "4bd28583", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RqUnP9qlTn3MUZ9OvHzb9FZZ", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 38, + "timestamp": "2026-10-21T17:09:44.080Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Apply needs a Prim. Apply to the mesh prim (the binding target). Actually MaterialBindingAPI.Apply(prim) applies to a prim. Let me apply to mesh.GetPrim() and BindDirect... Actually simpler: use mat.BindDirect(mesh.GetPrim()).\n\nUsdShade.Material has BindDirect(prim). Let me use that.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bf2e42e36fe1f29e", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "mat.BindDirect(mesh.GetPrim())", + "oldText": "bind_api = UsdShade.MaterialBindingAPI.Apply(mat)\nbind_api.BindDirect(mesh.GetPrim())" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bf2e42e36fe1f29e", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25452, + "completion_tokens": 154, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25606 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "4268876a", + "pi_parent_id": "c9c4c071", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rzmv40jFaCZVCAW8OSyRfVxz", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 39, + "timestamp": "2026-10-21T17:09:48.223Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I need to be more efficient. Let me run the script.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bdb980791afef7a4", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bdb980791afef7a4", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 113, in \n mat.BindDirect(mesh.GetPrim())\n ^^^^^^^^^^^^^^\nAttributeError: 'Material' object has no attribute 'BindDirect'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25635, + "completion_tokens": 61, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25696 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "577aab9d", + "pi_parent_id": "20bd70bb", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RIuC4QZZh6G3AHOFy5qXmhko", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 40, + "timestamp": "2026-10-21T17:09:52.299Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me use MaterialBindingAPI.Apply(mesh.GetPrim()) then BindDirect on the api.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-802de3455b55f10d", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "bind_api = UsdShade.MaterialBindingAPI.Apply(mesh.GetPrim())\nbind_api.BindDirect(mat)", + "oldText": "mat.BindDirect(mesh.GetPrim())" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-802de3455b55f10d", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25769, + "completion_tokens": 104, + "cached_tokens": 25088, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25873 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "dc72cef5", + "pi_parent_id": "27458d22", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RTk0KKfM9BNKQm4uQYLcoawP", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 41, + "timestamp": "2026-10-21T17:09:59.025Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run the script now.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-be736e8d277be9e0", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-be736e8d277be9e0", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 114, in \n bind_api.BindDirect(mat)\n ^^^^^^^^^^^^^^^^^^^\nAttributeError: 'MaterialBindingAPI' object has no attribute 'BindDirect'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25902, + "completion_tokens": 55, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 25957 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "5d6c881c", + "pi_parent_id": "ba0b8f25", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-ROCg6VGsZLT7d0WdpMfZPyzW", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 42, + "timestamp": "2026-10-21T17:10:05.094Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I need to be much more efficient. Let me check the MaterialBindingAPI methods quickly and fix everything at once.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b9502e9b0ef25c71", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 -c \"\nfrom pxr import UsdShade\nprint([m for m in dir(UsdShade.MaterialBindingAPI) if 'Bind' in m])\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b9502e9b0ef25c71", + "content": "['AddPrimToBindingCollection', 'Bind', 'CollectionBinding', 'CreateMaterialBindSubset', 'DirectBinding', 'GetCollectionBindingRel', 'GetCollectionBindingRels', 'GetCollectionBindings', 'GetDirectBinding', 'GetDirectBindingRel', 'GetMaterialBindSubsets', 'GetMaterialBindSubsetsFamilyType', 'GetMaterialBindingStrength', 'GetResolvedTargetPathFromBindingRel', 'RemovePrimFromBindingCollection', 'SetMaterialBindSubsetsFamilyType', 'SetMaterialBindingStrength', 'UnbindAllBindings', 'UnbindCollectionBinding', 'UnbindDirectBinding']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 26032, + "completion_tokens": 95, + "cached_tokens": 25872, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 26127 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "7a68316e", + "pi_parent_id": "1da7a419", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RNhE9MtYVmYiDZJIxTrVvNkZ", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 43, + "timestamp": "2026-10-21T17:10:12.028Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I need to be very efficient now. 22 model rounds remaining. Let me use DirectBinding API.\n\n```\nbinding = bind_api.DirectBinding\n# DirectBinding is a class; use DirectBinding.Bind(prim, mat)\nUsdShade.MaterialBindingAPI.DirectBinding.Bind(mesh.GetPrim(), mat)\n```\n\nActually the static class MaterialBindingAPI.DirectBinding has a Bind(prim, material) method. Let me use that directly instead of Apply.\n\nLet me replace those two lines with:\n```\nUsdShade.MaterialBindingAPI.DirectBinding.Bind(mesh.GetPrim(), mat)\n```", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8db861e45b79a269", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "UsdShade.MaterialBindingAPI.DirectBinding.Bind(mesh.GetPrim(), mat)", + "oldText": "bind_api = UsdShade.MaterialBindingAPI.Apply(mesh.GetPrim())\nbind_api.BindDirect(mat)" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8db861e45b79a269", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 26266, + "completion_tokens": 221, + "cached_tokens": 25088, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 26487 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "33afe55c", + "pi_parent_id": "dca1ad7e", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rg8leFDKkuRQV0otouRlqNe0", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 44, + "timestamp": "2026-10-21T17:10:16.025Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Let me run the script now.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-944819adb97eacdc", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-944819adb97eacdc", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 113, in \n UsdShade.MaterialBindingAPI.DirectBinding.Bind(mesh.GetPrim(), mat)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: type object 'DirectBinding' has no attribute 'Bind'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 26516, + "completion_tokens": 55, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 26571 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "575cbded", + "pi_parent_id": "b005a28b", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RjLEnlTfi9UcMuft2udoAdC2", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 45, + "timestamp": "2026-10-21T17:10:27.103Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 44/64 with 20 model rounds left. I need to be very efficient now. Let me use the Apply method on the prim, then BindDirect. Wait, DirectBinding has a Bind method? Let me just use MaterialBindingAPI.Apply on the material... no it needs a prim. \n\nActually the standard approach: \n```\nb = UsdShade.MaterialBindingAPI.Apply(mat) # no\n```\nWait earlier Apply needs a Prim. Let me do Apply on mesh prim, then use the .DirectBinding? No. Let me just check the DirectBinding class methods.\n\nActually, the simplest robust way to bind a material: use the \"materials:bindingAPI\" relationship via material rel. Let me just set the relationship manually. Actually, MaterialBindingAPI on the mesh: `UsdShade.MaterialBindingAPI.Apply(meshprim)` returns a binding API with a method... Let me check the instance methods.\n\nI'm burning rounds. Let me just check what methods exist on a binding instance quickly and also bind via relationship directly.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-aaa101968cbda654", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 -c \"\nfrom pxr import UsdShade\nimport inspect\nd = UsdShade.MaterialBindingAPI.DirectBinding\nprint('DirectBinding:', [m for m in dir(d) if not m.startswith('__')])\nb = UsdShade.MaterialBindingAPI\nprint([m for m in dir(b) if not m.startswith('_')])\n\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-aaa101968cbda654", + "content": "DirectBinding: ['GetBindingRel', 'GetMaterial', 'GetMaterialPath', 'GetMaterialPurpose']\n['AddPrimToBindingCollection', 'Apply', 'Bind', 'CanApply', 'CanContainPropertyName', 'CollectionBinding', 'ComputeBoundMaterial', 'ComputeBoundMaterials', 'CreateMaterialBindSubset', 'DirectBinding', 'Get', 'GetCollectionBindingRel', 'GetCollectionBindingRels', 'GetCollectionBindings', 'GetDirectBinding', 'GetDirectBindingRel', 'GetMaterialBindSubsets', 'GetMaterialBindSubsetsFamilyType', 'GetMaterialBindingStrength', 'GetMaterialPurposes', 'GetPath', 'GetPrim', 'GetResolvedTargetPathFromBindingRel', 'GetSchemaAttributeNames', 'GetSchemaClassPrimDefinition', 'GetSchemaKind', 'IsAPISchema', 'IsAppliedAPISchema', 'IsConcrete', 'IsMultipleApplyAPISchema', 'IsTyped', 'RemovePrimFromBindingCollection', 'SetMaterialBindSubsetsFamilyType', 'SetMaterialBindingStrength', 'UnbindAllBindings', 'UnbindCollectionBinding', 'UnbindDirectBinding']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 26662, + "completion_tokens": 333, + "cached_tokens": 17248, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 26995 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "3d82d9c0", + "pi_parent_id": "8606389f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RZIjJac1ZXRYITnUPxc7Yz35", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 46, + "timestamp": "2026-10-21T17:10:39.444Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 45, 19 left. I need to be efficient. Let me bind via the relationship directly using Sdf on the material prim. The material binding uses a \"material:binding:direct\" relationship on the mesh prim pointing to the material. Let me just add the relationship directly:\n\n```\nmesh.GetPrim().CreateRelationship(\"material:binding:direct\", [Sdf.Path(\"/World/Materials/BellBlackGloss\")])\n```\n\nThat's the standard binding relationship. Let me use that.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a12bb69745bb8502", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "mesh.GetPrim().CreateRelationship(\"material:binding:direct\", [Sdf.Path(\"/World/Materials/BellBlackGloss\")])", + "oldText": "UsdShade.MaterialBindingAPI.DirectBinding.Bind(mesh.GetPrim(), mat)" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a12bb69745bb8502", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 27244, + "completion_tokens": 214, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 27458 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2871cf13", + "pi_parent_id": "29d5a444", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Ryd2VSyD0xgdLTenmcPBWdn1", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 47, + "timestamp": "2026-10-21T17:10:50.848Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 46, 18 left. Let me run and then validate in the same round to save time.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a9d1ca58c84700b6", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20 && echo \"---VALIDATE---\"" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a9d1ca58c84700b6", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 113, in \n mesh.GetPrim().CreateRelationship(\"material:binding:direct\", [Sdf.Path(\"/World/Materials/BellBlackGloss\")])\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---VALIDATE---", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 27487, + "completion_tokens": 82, + "cached_tokens": 26656, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 27569 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "d6d95c28", + "pi_parent_id": "7ebac88c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RYR5LWZ5q8mnBc01Br0Ju0ff", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 48, + "timestamp": "2026-10-21T17:11:19.500Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "CreateRelationship takes name as a list of name elements (split by colon) or a TfToken. Let me use UsdShade.MaterialBindingAPI properly. Actually the relationship name \"material:binding:direct\" has colons - must pass as list of elements. Let me use:\n\n```\nmesh.GetPrim().CreateRelationship(Sdf.RelationshipPath(\"material:binding:direct\"), [Sdf.Path(...)])\n```\nWait, the signature says nameElts is std::vector. So pass the name as a TfToken? Actually \"material:binding:direct\" \u2014 the colons make it a relationship with a path-like name. In PXR, relationship names can contain colons if it's a valid relationship. The binding uses relationship name \"material:binding:direct\". \n\nThe API: CreateRelationship(name, [paths]) where name is TfToken. But it gave signature list-of-strings for nameElts OR TfToken. Let me just pass TfToken via the other overload but it also needs the target list. Hmm the two overloads: (Prim, vector nameElts, bool) and (Prim, TfToken name, bool). Neither takes targets! So CreateRelationship without targets, then add target.\n\nActually the relationship name \"material:binding:direct\" contains a colon which is the separator between the relationship name and the path. So nameElts = [\"material\", \"binding\", \"direct\"]. Let me pass that list, then it creates empty relationship, then I need to add the target. That's awkward.\n\nBetter: use UsdShade.MaterialBindingAPI.Apply(mat)? No, needs prim. Let me use it on the mesh prim and then set the direct binding relationship.\n\nActually simplest: MaterialBindingAPI has a relationship. Let me use the API's GetDirectBindingRel().Create target. \n\nLet me do:\n```\nba = UsdShade.MaterialBindingAPI.Apply(mesh.GetPrim())\nba.GetDirectBindingRel().CreateTarget(Sdf.Path(\"/World/Materials/BellBlackGloss\"))\n```\n\nGetDirectBindingRel returns a UsdRelationship that I can CreateTarget on. Let me try.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-904ef3b615337395", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "ba = UsdShade.MaterialBindingAPI.Apply(mesh.GetPrim())\nba.GetDirectBindingRel().CreateTarget(Sdf.Path(\"/World/Materials/BellBlackGloss\"))", + "oldText": "mesh.GetPrim().CreateRelationship(\"material:binding:direct\", [Sdf.Path(\"/World/Materials/BellBlackGloss\")])" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-904ef3b615337395", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 27818, + "completion_tokens": 577, + "cached_tokens": 27440, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 28395 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "4dec8788", + "pi_parent_id": "4dbc6677", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R8zgRj4d7QW21Fh756qQSQ3f", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 49, + "timestamp": "2026-10-21T17:11:25.451Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "16 rounds left. Let me run the script and validate in the same round.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a7dea2e7ccaccc7d", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a7dea2e7ccaccc7d", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 114, in \n ba.GetDirectBindingRel().CreateTarget(Sdf.Path(\"/World/Materials/BellBlackGloss\"))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'Relationship' object has no attribute 'CreateTarget'. Did you mean: 'ClearTargets'?", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 28424, + "completion_tokens": 65, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 28489 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "1d4c006a", + "pi_parent_id": "4453cb29", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rm8KXgMoOvL2tcK2H47GRj4d", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 50, + "timestamp": "2026-10-21T17:11:32.283Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "15 rounds left. Let me use SetTargets instead of CreateTarget.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-adf64ccab2a89d2c", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "ba = UsdShade.MaterialBindingAPI.Apply(mesh.GetPrim())\nba.GetDirectBindingRel().SetTargets([Sdf.Path(\"/World/Materials/BellBlackGloss\")])", + "oldText": "ba = UsdShade.MaterialBindingAPI.Apply(mesh.GetPrim())\nba.GetDirectBindingRel().CreateTarget(Sdf.Path(\"/World/Materials/BellBlackGloss\"))" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-adf64ccab2a89d2c", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 28590, + "completion_tokens": 153, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 28743 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "e8013903", + "pi_parent_id": "bb6e7acc", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-R7py3DBcysdXVw2FcZwpGRXc", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 51, + "timestamp": "2026-10-21T17:11:45.738Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "14 model rounds left. Let me run the script and then validate in the same round to save time.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b8e7ccb742c52bfe", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b8e7ccb742c52bfe", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 117, in \n model_api = UsdPhysics.RigidBodyAPI.Apply(model)\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": 28772, + "completion_tokens": 70, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 28842 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "e82f3c10", + "pi_parent_id": "fad54e9f", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RqdFnBErFjsDdrIgWGFCRQN7", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 52, + "timestamp": "2026-10-21T17:11:57.354Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Apply needs a UsdPrim. Let me pass model.GetPrim(). Let me fix all remaining physics calls to use GetPrim().", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-88e315173af2e38b", + "function_name": "read", + "arguments": { + "limit": 30, + "offset": 115, + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-88e315173af2e38b", + "content": "# ---- Rigid body + collision ----\nmodel_api = UsdPhysics.RigidBodyAPI.Apply(model)\nmodel_api.CreateMassAttr(3.0)\nmodel_api.CreateKinematicEnabledAttr(False)\nmp = UsdPhysics.MassPropertiesAPI.Apply(model)\nmp.CreateCenterOfMassAttr(Gf.Vec3d(0.0, 0.0, 0.12))\nmp.CreateDiagonalInertiaAttr(Gf.Vec3d(0.02, 0.02, 0.01))\n\ncol_api = UsdPhysics.CollisionAPI.Apply(mesh)\nmcol = UsdPhysics.MeshCollisionAPI.Apply(mesh)\nmcol.CreateCollisionExtentsAttr([Gf.Vec3f(0.088, 0.088, 0.248)])\n\n# SimReady world up/front axis\nprim = world.GetPrim()\nprim.CreateAttribute(\"upAxis\", Sdf.ValueTypeNames.Token).Set(\"Z\")\nprim.CreateAttribute(\"frontAxis\", Sdf.ValueTypeNames.Token).Set(\"Y\")\n\nstage.SetDefaultPrim(Usd.Prim(stage, \"/World/Model\"))\n\nstage.GetRootLayer().Export()\nprint(\"WROTE\", OUT)\nprint(\"verts\", num_v, \"faces\", len(face_index))", + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 28963, + "completion_tokens": 83, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 29046 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "8149ed8c", + "pi_parent_id": "04f34b3a", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RKqA3spY5HHgXN0024yliVHk", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 53, + "timestamp": "2026-10-21T17:12:27.681Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 52, 12 model rounds left. I need to be very efficient. Let me fix the physics API calls (they need UsdPrim).", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-9736e5812fee60a5", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "# ---- Rigid body + collision ----\nmodel_api = UsdPhysics.RigidBodyAPI.Apply(model.GetPrim())\nmodel_api.CreateMassAttr(3.0)\nmodel_api.CreateKinematicEnabledAttr(False)\nmp = UsdPhysics.MassPropertiesAPI.Apply(model.GetPrim())\nmp.CreateCenterOfMassAttr(Gf.Vec3d(0.0, 0.0, 0.12))\nmp.CreateDiagonalInertiaAttr(Gf.Vec3d(0.02, 0.02, 0.01))\n\ncol_api = UsdPhysics.CollisionAPI.Apply(mesh.GetPrim())\nmcol = UsdPhysics.MeshCollisionAPI.Apply(mesh.GetPrim())\nmcol.CreateCollisionExtentsAttr([Gf.Vec3f(0.088, 0.088, 0.248)])", + "oldText": "# ---- Rigid body + collision ----\nmodel_api = UsdPhysics.RigidBodyAPI.Apply(model)\nmodel_api.CreateMassAttr(3.0)\nmodel_api.CreateKinematicEnabledAttr(False)\nmp = UsdPhysics.MassPropertiesAPI.Apply(model)\nmp.CreateCenterOfMassAttr(Gf.Vec3d(0.0, 0.0, 0.12))\nmp.CreateDiagonalInertiaAttr(Gf.Vec3d(0.02, 0.02, 0.01))\n\ncol_api = UsdPhysics.CollisionAPI.Apply(mesh)\nmcol = UsdPhysics.MeshCollisionAPI.Apply(mesh)\nmcol.CreateCollisionExtentsAttr([Gf.Vec3f(0.088, 0.088, 0.248)])" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-9736e5812fee60a5", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 29341, + "completion_tokens": 465, + "cached_tokens": 19600, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 29806 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "1971580d", + "pi_parent_id": "2742bcac", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RU1LIGV3bbmk642stcGvOo6w", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 54, + "timestamp": "2026-10-21T17:12:37.896Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 53, 11 left. Let me run the script and validate in the same round to save rounds. Let me run the author script and immediately validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a5cd92216300468d", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a5cd92216300468d", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 118, in \n model_api.CreateMassAttr(3.0)\n ^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'RigidBodyAPI' object has no attribute 'CreateMassAttr'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 29835, + "completion_tokens": 86, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 29921 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "93f7be37", + "pi_parent_id": "6c434880", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RIJ5HZd87CU0wF1c2PddsBN0", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 55, + "timestamp": "2026-10-21T17:12:52.988Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 54, 10 left. RigidBodyAPI doesn't have CreateMassAttr \u2014 mass is on MassAPI. Let me remove mass from RigidBodyAPI and put it in MassAPI. Actually UsdPhysics.MassAPI has mass. MassPropertiesAPI has centerOfMass and diagonalInertia. Let me restructure:\n\n- RigidBodyAPI.Apply(model) \u2014 just applies (kinematic enabled)\n- MassAPI.Apply(model).CreateMassAttr(3.0)\n- MassPropertiesAPI.Apply(model).CreateCenterOfMassAttr / CreateDiagonalInertiaAttr\n\nLet me check MassAPI has CreateMassAttr. Yes, UsdPhysics.MassAPI.CreateMassAttr.\n\nLet me fix.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-92e6eff8dad2adf9", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "model_api = UsdPhysics.RigidBodyAPI.Apply(model.GetPrim())\nmodel_api.CreateKinematicEnabledAttr(False)\nmass = UsdPhysics.MassAPI.Apply(model.GetPrim())\nmass.CreateMassAttr(3.0)", + "oldText": "model_api = UsdPhysics.RigidBodyAPI.Apply(model.GetPrim())\nmodel_api.CreateMassAttr(3.0)\nmodel_api.CreateKinematicEnabledAttr(False)" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-92e6eff8dad2adf9", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 30003, + "completion_tokens": 292, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 30295 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "78ba23dc", + "pi_parent_id": "15082a23", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-REFtaY11e3VHHCwUTbJCRFFa", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 56, + "timestamp": "2026-10-21T17:12:57.213Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 55, 9 left. Let me run and validate in the same round.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8b73321de9d2f837", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8b73321de9d2f837", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 121, in \n mp = UsdPhysics.MassPropertiesAPI.Apply(model.GetPrim())\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: module 'pxr.UsdPhysics' has no attribute 'MassPropertiesAPI'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 30323, + "completion_tokens": 70, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 30393 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "86bced72", + "pi_parent_id": "6ed5dce6", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RcrHrLzlZrtDTJeJIxB7bZrT", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 57, + "timestamp": "2026-10-21T17:13:08.718Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "MassPropertiesAPI was earlier listed in dir(UsdPhysics)? Earlier it showed 'MassAPI' but not 'MassPropertiesAPI' in the second check... Actually the first check listed only 'MassAPI', 'MassUnits'. So MassPropertiesAPI may not be available in this build. Let me remove the MassPropertiesAPI and just keep MassAPI with mass, and set COM/inertia on MassAPI? MassAPI has CreateMassAttr, CreateCenterOfMassAttr, CreateDiagonalInertiaAttr. Let me put COM and inertia on MassAPI.\n\nLet me restructure to use only MassAPI for mass, COM, diagonalInertia.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-aa5e0ca9d22f011b", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "mass = UsdPhysics.MassAPI.Apply(model.GetPrim())\nmass.CreateMassAttr(3.0)\nmass.CreateCenterOfMassAttr(Gf.Vec3d(0.0, 0.0, 0.12))\nmass.CreateDiagonalInertiaAttr(Gf.Vec3d(0.02, 0.02, 0.01))", + "oldText": "mass = UsdPhysics.MassAPI.Apply(model.GetPrim())\nmass.CreateMassAttr(3.0)\nmp = UsdPhysics.MassPropertiesAPI.Apply(model.GetPrim())\nmp.CreateCenterOfMassAttr(Gf.Vec3d(0.0, 0.0, 0.12))\nmp.CreateDiagonalInertiaAttr(Gf.Vec3d(0.02, 0.02, 0.01))" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-aa5e0ca9d22f011b", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 30483, + "completion_tokens": 376, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 30859 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "4ef906cb", + "pi_parent_id": "3af31650", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rtqsd5NtaSIJ5WLTv6kU0lKF", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 58, + "timestamp": "2026-10-21T17:13:16.013Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "8 model rounds remain after this. Let me run and validate in this round.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a22a3dfd033ba85a", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a22a3dfd033ba85a", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 126, in \n mcol.CreateCollisionExtentsAttr([Gf.Vec3f(0.088, 0.088, 0.248)])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAttributeError: 'MeshCollisionAPI' object has no attribute 'CreateCollisionExtentsAttr'", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 30888, + "completion_tokens": 64, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 30952 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "b5938a37", + "pi_parent_id": "3ea2b0d7", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rc9mwllbixqPlrTq6f0BXwlk", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 59, + "timestamp": "2026-10-21T17:13:24.602Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "6 rounds remain after this. Let me remove the collision extents line (not essential), keep just CollisionAPI + MeshCollisionAPI applied. Let me remove that line.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-bb390b210c567272", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "col_api = UsdPhysics.CollisionAPI.Apply(mesh.GetPrim())\nmcol = UsdPhysics.MeshCollisionAPI.Apply(mesh.GetPrim())", + "oldText": "col_api = UsdPhysics.CollisionAPI.Apply(mesh.GetPrim())\nmcol = UsdPhysics.MeshCollisionAPI.Apply(mesh.GetPrim())\nmcol.CreateCollisionExtentsAttr([Gf.Vec3f(0.088, 0.088, 0.248)])" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-bb390b210c567272", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 31062, + "completion_tokens": 184, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 31246 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c040bfaa", + "pi_parent_id": "6434d495", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RLlPOQdip7Q1YlmTBNUtdrtN", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 60, + "timestamp": "2026-10-21T17:13:37.299Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "5 model rounds remain after this. Let me run the script and then validate. I have 5 left. Let me run the author script now, and if it succeeds, validate immediately.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-a1d708e81df820f6", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-a1d708e81df820f6", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 132, in \n stage.SetDefaultPrim(Usd.Prim(stage, \"/World/Model\"))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nBoost.Python.ArgumentError: Python argument types in\n Prim.__init__(Prim, Stage, str)\ndid not match C++ signature:\n __init__(_object*)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 31275, + "completion_tokens": 86, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 31361 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "afe1d052", + "pi_parent_id": "02ce95cf", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RJJvsOFwxjPkvbNxnDkzJbsT", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 61, + "timestamp": "2026-10-21T17:13:53.440Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "4 rounds remain after this. Let me fix the SetDefaultPrim (use GetPrimIdentifier) and run, then validate. Let me be efficient: fix and run in one bash, then validate.\n\nSetDefaultPrim expects a TfToken (identifier). Let me use stage.SetDefaultPrim(\"World/Model\"). Actually earlier SetDefaultPrim(\"/World/Model\") failed because it needed UsdPrim. But there's an overload. Let me use the identifier token: `stage.SetDefaultPrim(Usd.PrimIdentifier(\"/World/Model\"))`? Actually simplest: after building, do `model.GetPrim().MakeInstanceable`? No.\n\nUsdStage.SetDefaultPrim takes a TfToken identifier in newer versions. Let me just use the token: the earlier error said it needed UsdPrim. There's no GetPrimIdentifier-based constructor easily. Let me use stage.SetDefaultPrim with a token? The C++ signature only showed UsdPrim. \n\nAlternative: use Sdf to set defaultPrim on the layer directly: `stage.GetRootLayer().defaultPrim = \"/World/Model\"`? In Python, Sdf.Layer has `.defaultPrim` attribute? Actually Sdf.Layer has defaultPrim? No, it's in the layer's \"prim\" field. In the layer's opened form, `layer.defaultPrim` isn't exposed. But I can do `stage.GetRootLayer().AddInfo`? \n\nSimplest: `stage.GetDefaultPrim()` currently None; I can set via the layer: `layer = stage.GetRootLayer(); layer.defaultPrim` \u2014 Let me check. Actually Sdf Layer object has attribute `defaultPrim`? Let me just try `stage.SetDefaultPrim(Usd.Prim(stage, \"/World/Model\"))` failed because constructor needs a specific path type. Let me use SdfPath: `Usd.Prim(stage, Sdf.Path(\"/World/Model\"))`.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-89139c806de5a635", + "function_name": "edit", + "arguments": { + "edits": [ + { + "newText": "stage.SetDefaultPrim(Usd.Prim(stage, Sdf.Path(\"/World/Model\")))", + "oldText": "stage.SetDefaultPrim(Usd.Prim(stage, \"/World/Model\"))" + } + ], + "path": "/tmp/author.py" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-89139c806de5a635", + "content": "Successfully replaced 1 block(s) in /tmp/author.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 31471, + "completion_tokens": 488, + "cached_tokens": 17248, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 31959 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c0d57cd1", + "pi_parent_id": "5d7a7f5c", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-Rw1qFvW7aOACEA4UyqxjACQW", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 62, + "timestamp": "2026-10-21T17:14:00.236Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "I'm at round 61, 3 model rounds remain after this. I need to run the script and validate in the remaining rounds. Let me run the script now and validate.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-914d43d9b12fdbab", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-914d43d9b12fdbab", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 132, in \n stage.SetDefaultPrim(Usd.Prim(stage, Sdf.Path(\"/World/Model\")))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nBoost.Python.ArgumentError: Python argument types in\n Prim.__init__(Prim, Stage, Path)\ndid not match C++ signature:\n __init__(_object*)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 31988, + "completion_tokens": 86, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 32074 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c15ce7d7", + "pi_parent_id": "49c5ddc7", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RXNwqfm09EYywaW2E36FZcs4", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 63, + "timestamp": "2026-10-21T17:14:38.272Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Only 2 model rounds remain. I must finish. The Usd.Prim constructor is tricky. Let me just use the layer's defaultPrim via the Sdf layer. Actually the simplest: `stage.GetDefaultPrimIdentifier()`... no.\n\nLet me remove SetDefaultPrim entirely and set it via the layer directly. In PXR, `stage.GetRootLayer()` is an Sdf.Layer; it has a `defaultPrim` attribute? Actually the metadata is stored. Let me use `Usd.Tf` ... \n\nAlternative that definitely works: \n```\ndefault_prim = stage.GetPrimAtPath(Sdf.Path(\"/World/Model\"))\nstage.SetDefaultPrim(default_prim)\n```\nWait that's the same as Usd.Prim(stage, path) essentially. GetPrimAtPath returns a Usd.Prim object properly. The issue is the Prim constructor binding. GetPrimAtPath returns a real Prim. Let me use that.\n\nLet me do the edit and run in one go, then validate next round (1 round left after). Actually I have 2 rounds: this round (edit+run) and one more (validate). I should combine: edit + run in this round via one bash that first edits? No, I can't edit file in bash easily. Let me do the edit now, and run+validate won't fit in one. \n\nLet me do the edit + run in this round (using two tools in parallel won't work since run depends on edit). Actually I can edit then in same message... no, dependencies.\n\nLet me just edit and run in one bash by using a sed/python inline. Better: use the write/edit then a single bash. But that's 2 tool calls in one round (allowed, independent? No, run depends on edit). \n\nGiven constraints, let me edit (this tool call) and run in the same round is not possible in parallel. Let me instead do a single bash that rewrites the offending line and runs. I'll use python to patch the file and run it.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-8a5107b6f8d52396", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 - <<'EOF'\nimport re\ns=open('/tmp/author.py').read()\ns=s.replace('stage.SetDefaultPrim(Usd.Prim(stage, Sdf.Path(\"/World/Model\")))','stage.SetDefaultPrim(stage.GetPrimAtPath(Sdf.Path(\"/World/Model\")))')\nopen('/tmp/author.py','w').write(s)\nEOF\npython3 /tmp/author.py 2>&1 | tail -20" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-8a5107b6f8d52396", + "content": "Traceback (most recent call last):\n File \"/tmp/author.py\", line 134, in \n stage.GetRootLayer().Export()\nBoost.Python.ArgumentError: Python argument types in\n Layer.Export(Layer)\ndid not match C++ signature:\n Export(pxrInternal_v0_26_8__pxrReserved__::TfWeakPtr, std::__cxx11::basic_string, std::allocator > filename, std::__cxx11::basic_string, std::allocator > comment='', pxrInternal_v0_26_8__pxrReserved__::pxr_boost::python::dict args={})", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 32189, + "completion_tokens": 545, + "cached_tokens": 31360, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 32734 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "342567ed", + "pi_parent_id": "bf578575", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RolvIDPzWOp48eKnCWLqC4BW", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 64, + "timestamp": "2026-10-21T17:15:06.122Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "Only 1 round remains. Export needs a filename. Let me just call Export(OUT) or use Save. Actually stage.Save() would work. Let me patch Export to pass the filename, run, and validate \u2014 all in one bash round. I must submit too though. submit_asset is a separate tool call. I have 1 round left. I should: run the fixed script AND validate AND submit? That's risky. \n\nActually \"1 model round remains after this round\" \u2014 this is round 63, so round 64 is my last. Let me make this round do: fix+run+validate. Then round 64 I submit. But if validation reveals big issues I can't fix. \n\nBetter: this round fix+run+validate to see findings, and round 64 submit (asset already written, submit just freezes). Validation doesn't change the file; submit freezes current file. So plan: this round run the corrected script to produce a good asset.usd, and validate to confirm. Round 64: submit.\n\nLet me do fix+run+validate now in one bash + one mcp call (parallel? validate depends on file existing after run, so sequential). Let me do bash (run) then in same round call validate via mcp \u2014 but mcp is separate tool. I can call both in one turn since... they're dependent (validate needs file). I'll do the bash run first, then mcp validate \u2014 but I can put them in the same turn only if independent. They're dependent. \n\nGiven 1 round left, let me just do: bash to fix+run (produce asset), and also submit in round 64. Actually I can do run + submit in this round? submit freezes the current file \u2014 if I run the script in this round and it succeeds, the file is good, then submit. But I lose the chance to see validation findings. \n\nThe contract says validate before submitting, but I'm out of budget. Let me at least produce a valid file and submit. I'll run the corrected script now (fix Export), and if it succeeds, submit in the same turn? submit is an MCP tool call; I can do run (bash) then submit (mcp) \u2014 dependent. Let me just do the bash run this round to ensure a valid file exists, then next round submit.\n\nActually the export failing means asset.usd may be incomplete/empty. Let me fix Export and run, verify file. Then round 64 submit.\n\nLet me patch Export to Export(OUT) and run.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b38af934fada6f21", + "function_name": "bash", + "arguments": { + "command": "cd /output && python3 - <<'EOF'\ns=open('/tmp/author.py').read()\ns=s.replace('stage.GetRootLayer().Export()','stage.Save()')\nopen('/tmp/author.py','w').write(s)\nEOF\npython3 /tmp/author.py 2>&1 | tail -8 && echo \"OK\" && ls -la /output/asset.usd" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b38af934fada6f21", + "content": "WROTE /output/asset.usd\nverts 2178 faces 8960\nOK\n-rw-r--r-- 1 actor actor 55222 Oct 21 17:15 /output/asset.usd", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 32929, + "completion_tokens": 647, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 33576 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "c232e5ca", + "pi_parent_id": "1d65bf73", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RT5YuzfUDU3EjUJiNH1A4qtj", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + }, + { + "step_id": 65, + "timestamp": "2026-10-21T17:15:16.659Z", + "source": "agent", + "model_name": "harbor-endpoint/Qwen/Qwen3.8-27B:deepinfra", + "message": "", + "reasoning_content": "This is my final round. Let me validate quickly and submit. But I have 0 model rounds after this, so this round I should both validate (to see) and submit. Since submit freezes, let me just submit now. But I'd like to validate first. However, validation would be a good check but I have no round after to fix. Let me do a quick validate and submit in this round (both tool calls, but they're independent enough \u2014 validate reads current file, submit freezes current file). Let me do both.\n\nActually, if I validate and it shows failures, I can't fix. But submit is required to freeze. Let me just submit to ensure the asset is frozen. I'll submit.", + "tool_calls": [ + { + "tool_call_id": "chatcmpl-tool-b57c804ee67721ac", + "function_name": "mcp__benchmark", + "arguments": { + "tool": "benchmark_validate_candidate", + "args": { + "request_id": "check-final" + } + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "chatcmpl-tool-b57c804ee67721ac", + "content": "{\"request_id\":\"check-final\",\"snapshot_sha256\":\"5f8b396720168f07d550b92f9d6ff292655ce478abacc16b8c8b6d6818ca17bf\",\"validation_calls_used\":1,\"validation_calls_remaining\":4,\"feedback\":{\"schema_version\":\"simready-validator-feedback-v1\",\"snapshot_sha256\":\"5f8b396720168f07d550b92f9d6ff292655ce478abacc16b8c8b6d6818ca17bf\",\"reward\":80.54347826086956,\"simready\":{\"schema\":\"simready-validator-score-v1\",\"policy_id\":\"NVIDIA-Robotics-Prop-4.0.0-mandatory-95-plus-5-v1\",\"status\":\"scored\",\"score_percent\":80.54347826086956,\"base_credit_percent\":80.54347826086956,\"completion_bonus\":0,\"passed_count\":39,\"failed_count\":7,\"unknown_count\":0,\"applicable_count\":46,\"official_conformance\":{\"profile\":{\"id\":\"Robotics-Prop\",\"version\":\"4.0.0\"},\"passed\":false,\"filtered\":false},\"checks\":[{\"requirement_id\":\"com.nvidia.simready.HI.010\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.005\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.008\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.010\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.001\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.SL.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.MAT.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.QCODE.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.TIME.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SR.002\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.SR.004\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.UN.006\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.UN.007\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.VG.008\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VG.025\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VG.MESH.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.MAT.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.PS.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.TEX.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.TEX.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.AA.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.AA.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.004\",\"status\":\"pass\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.usd.RB.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.005\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.009\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.COL.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.002\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.usd.VG.014\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.usd.VG.027\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.028\",\"status\":\"pass\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.usd.VG.029\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VM.BIND.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VM.PS.001\",\"status\":\"pass\",\"finding_count\":0}]},\"nvidia_validator_report\":{\"available\":true,\"report_id\":\"ed30feec4bed0c88fcfbe1d301c138bdacfe475d1013a02d19cd9c9bbcb00b67\",\"sha256\":\"ed30feec4bed0c88fcfbe1d301c138bdacfe475d1013a02d19cd9c9bbcb00b67\",\"bytes\":182013,\"total_characters\":182013,\"issue_counts\":{\"issues\":7,\"soft_issues\":18,\"warnings\":2,\"infos\":0},\"complete_report_available\":true,\"delivery\":\"agent_file\",\"file_path\":\"/tmp/simready-validation-reports/ed30feec4bed0c88fcfbe1d301c138bdacfe475d1013a02d19cd9c9bbcb00b67.json\",\"report\":null,\"retrieval_tool\":\"get_validation_report\",\"offset_unit\":\"Unicode_code_points\",\"search_hint\":\"rg -n -m 20 -M 240 --max-columns-preview -F -e -e ; use sed -n ,p for nearby lines\",\"redactions\":\"private host paths and credential patterns only; original diagnostic wording, suggestions and candidate USD sites retained\",\"file_available\":true,\"validation_calls_consumed\":0}},\"status\":\"completed\"}", + "extra": { + "tool_name": "mcp__benchmark", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 33675, + "completion_tokens": 198, + "cached_tokens": 1568, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 33873 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "1f42637b", + "pi_parent_id": "5fbae363", + "provider": "harbor-endpoint", + "api": "openai-completions", + "response_id": "chatcmpl-RZJYbfaZgZPzM5TfAq0rJvWf", + "response_model": "Qwen/Qwen3.8-27B", + "stop_reason": "toolUse", + "raw_stop_reason": "tool_calls" + } + } + ], + "final_metrics": { + "total_prompt_tokens": 1487863, + "total_completion_tokens": 21911, + "total_cached_tokens": 490784, + "total_steps": 65, + "extra": { + "cache_write_tokens": 0, + "reasoning_tokens": 0, + "pi_total_tokens": 1509774 + } + } +} \ No newline at end of file diff --git a/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/container_bottle_glass_a01/reconstruction-1/nvidia-validator.json b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/container_bottle_glass_a01/reconstruction-1/nvidia-validator.json new file mode 100644 index 0000000000000000000000000000000000000000..4f15498304a5e5ce9a66511ee9e3cd76cf941d49 --- /dev/null +++ b/runs/nv25-qwen38-27b-medium-pi-none-turn64-20261021/evidence/container_bottle_glass_a01/reconstruction-1/nvidia-validator.json @@ -0,0 +1,4131 @@ +{ + "asset_path": "/output/asset.usd", + "asset_sha256": "684c348810d11dc7a7c63b84c4cf3aba95fb5a6685538953cffe985f5e84dbef", + "engine_dispatch_completed": true, + "features_summary": { + "FET_000_MUJOCO": { + "blocking_failure": false, + "dependencies": "[{'FET_000_STANDARD': {'version': '0.1.0'}}]", + "optional requirements": "['com.nvidia.simready.NP.006', 'com.nvidia.simready.RV.007', 'com.nvidia.simready.SR.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_000_NEWTON": { + "blocking_failure": false, + "dependencies": "[{'FET_000_STANDARD': {'version': '0.1.0'}}]", + "optional requirements": "['com.nvidia.simready.NP.006', 'com.nvidia.simready.RV.004', 'com.nvidia.simready.SR.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_000_PHYSX": { + "blocking_failure": false, + "dependencies": "[{'FET_000_STANDARD': {'version': '0.1.0'}}]", + "optional requirements": "['com.nvidia.simready.NP.006', 'com.nvidia.simready.RV.001', 'com.nvidia.simready.SR.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_000_STANDARD": { + "blocking_failure": false, + "dependencies": "[]", + "optional requirements": "['com.nvidia.simready.NP.006', 'com.nvidia.simready.SR.001']", + "passed": false, + "version": "0.2.0" + }, + "FET_001_STANDARD": { + "blocking_failure": true, + "dependencies": "[]", + "failing requirements": "['com.nvidia.simready.UN.006', 'com.nvidia.simready.UN.007', 'com.nvidia.usd.VG.002', 'com.nvidia.usd.VG.014']", + "passed": false, + "requirement_messages": "{\"com.nvidia.simready.UN.006\": [\"Stage has upAxis of 'Y', not 'Z'.\"], \"com.nvidia.simready.UN.007\": [\"Stage has metersPerUnit of 0.01, not 1.0.\"], \"com.nvidia.usd.VG.002\": [\"Prim does not have any extent value\"], \"com.nvidia.usd.VG.014\": [\"Invalid topology found\"]}", + "version": "1.0.1" + }, + "FET_003_MUJOCO": { + "blocking_failure": false, + "dependencies": "[]", + "optional requirements": "['com.nvidia.simready.MUJOCO.COL.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_003_NEWTON": { + "blocking_failure": false, + "dependencies": "[]", + "optional requirements": "['com.nvidia.simready.NEWTON.COL.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_003_PHYSX": { + "blocking_failure": false, + "dependencies": "[]", + "passed": true, + "version": "0.4.0" + }, + "FET_003_STANDARD": { + "blocking_failure": false, + "dependencies": "[]", + "passed": true, + "version": "0.2.0" + }, + "FET_004_MUJOCO": { + "blocking_failure": false, + "dependencies": "[{'FET_003_MUJOCO': {'version': '0.1.0'}}]", + "optional requirements": "['com.nvidia.simready.MUJOCO.COL.001', 'com.nvidia.simready.RB.MB.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_004_NEWTON": { + "blocking_failure": false, + "dependencies": "[{'FET_003_NEWTON': {'version': '0.1.0'}}]", + "optional requirements": "['com.nvidia.simready.NEWTON.COL.001', 'com.nvidia.simready.RB.MB.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_004_PHYSX": { + "blocking_failure": false, + "dependencies": "[{'FET_003_PHYSX': {'version': '0.4.0'}}]", + "optional requirements": "['com.nvidia.simready.RB.MB.001']", + "passed": false, + "version": "0.4.0" + }, + "FET_004_STANDARD": { + "blocking_failure": false, + "dependencies": "[{'FET_003_STANDARD': {'version': '0.2.0'}}]", + "optional requirements": "['com.nvidia.simready.RB.MB.001']", + "passed": false, + "version": "0.2.0" + }, + "FET_005_STANDARD": { + "blocking_failure": false, + "dependencies": "[]", + "optional requirements": "['com.nvidia.simready.GSP.001', 'com.nvidia.simready.PMT.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_006_MDL": { + "blocking_failure": false, + "dependencies": "[]", + "optional requirements": "['com.nvidia.simready.VM.MDL.003']", + "passed": false, + "version": "0.2.0" + }, + "FET_006_OPENPBR": { + "blocking_failure": false, + "dependencies": "[]", + "optional requirements": "['com.nvidia.simready.VM.PBR.001']", + "passed": false, + "version": "0.1.0" + }, + "FET_006_STANDARD": { + "blocking_failure": false, + "dependencies": "[]", + "passed": true, + "version": "0.2.0" + }, + "FET_007_STANDARD": { + "blocking_failure": false, + "dependencies": "[]", + "optional requirements": 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semantics found on the prim, its ancestors, its bound material, or its GeomSubsets.\"]}", + "version": "0.2.0" + }, + "FET_031_STANDARD": { + "blocking_failure": false, + "dependencies": "[]", + "passed": true, + "version": "0.1.0" + }, + "FET_033_STANDARD": { + "blocking_failure": true, + "dependencies": "[{'FET_031_STANDARD': {'version': '0.1.0'}}]", + "failing requirements": "['com.nvidia.simready.SR.002', 'com.nvidia.simready.SR.004']", + "passed": false, + "requirement_messages": "{\"com.nvidia.simready.SR.002\": [\"No thumbnail found at /output/.thumbs/256x256/asset.usd.png for SimReady asset \"], \"com.nvidia.simready.SR.004\": [\"Required metadata fields are missing: author, asset_name, asset_type, asset_license, category, source_file, usd_date_generated, qcode, rigid_body_count, asset_extents, mass. 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'FET_004_ROBOT_PHYSX' version '0.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_PHYSX-0.3.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_ROBOT_PHYSX' version '0.4.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_PHYSX-0.4.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_STANDARD' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": 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feature 'FET_033_STANDARD' version '0.4.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_033_STANDARD-0.4.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_040_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_040_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_041_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_041_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_042_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_042_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_043_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_043_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_044_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_044_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_045_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_045_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_046_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_046_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.3.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.4.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.4.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_101_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_101_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-COCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-Cityscapes' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-ADE20K' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-PascalVOC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-SUNRGBD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-ImageNet1K' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package' version '1.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-NoBOM' version '1.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '3.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '2.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '2.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '2.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '3.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '4.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "WARNING", + "logger": "root", + "message": "DeprecationWarning: Use find() instead" + }, + { + "level": "WARNING", + "logger": "root", + "message": "File /opt/simready/venv/lib/python3.12/site-packages/simready/validate/api.py, line 485, in _build_features_validation_summary" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Failed requirements ['com.nvidia.simready.SL.001'] preclude feature FET_011_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Failed requirements ['com.nvidia.simready.SR.002', 'com.nvidia.simready.SR.004'] preclude feature FET_033_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.VM.PBR.001'] did not pass for feature FET_006_OPENPBR." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NP.006', 'com.nvidia.simready.SR.001'] did not pass for feature FET_000_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NP.006', 'com.nvidia.simready.RV.004', 'com.nvidia.simready.SR.001'] did not pass for feature FET_000_NEWTON." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Failed requirements ['com.nvidia.simready.SL.001'] preclude feature FET_046_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NEWTON.COL.001', 'com.nvidia.simready.RB.MB.001'] did not pass for feature FET_004_NEWTON." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NEWTON.COL.001'] did not pass for feature FET_003_NEWTON." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Failed requirements ['com.nvidia.simready.UN.006', 'com.nvidia.simready.UN.007', 'com.nvidia.usd.VG.002', 'com.nvidia.usd.VG.014'] preclude feature FET_001_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.RB.MB.001'] did not pass for feature FET_004_PHYSX." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.MUJOCO.COL.001', 'com.nvidia.simready.RB.MB.001'] did not pass for feature FET_004_MUJOCO." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.MUJOCO.COL.001'] did not pass for feature FET_003_MUJOCO." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NP.006', 'com.nvidia.simready.RV.001', 'com.nvidia.simready.SR.001'] did not pass for feature FET_000_PHYSX." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.RB.MB.001'] did not pass for feature FET_004_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NVM.001', 'com.nvidia.simready.NVM.002', 'com.nvidia.simready.NVM.003'] did not pass for feature FET_007_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.ISA.001'] did not pass for feature FET_100_ISAAC." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Failed requirements ['com.nvidia.simready.SL.001'] preclude feature FET_011_RTX." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.DISP.001'] did not pass for feature FET_010_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.GSP.001', 'com.nvidia.simready.PMT.001'] did not pass for feature FET_005_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NP.006', 'com.nvidia.simready.RV.007', 'com.nvidia.simready.SR.001'] did not pass for feature FET_000_MUJOCO." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.VM.MDL.003'] did not pass for feature FET_006_MDL." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Clearing requirements registry" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Clearing features registry" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Clearing profiles registry" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Clearing rules registry" + } + ], + "outcome": "failure", + "passed": false, + "profile_id": "Robotics-Prop", + "profile_version": "4.0.0", + "rule_execution": { + "buckets": [ + { + "bucket": "neutral", + "declared_requirement_codes": [ + "com.nvidia.simready.DISP.001", + "com.nvidia.simready.DISP.002", + "com.nvidia.simready.DISP.003", + "com.nvidia.simready.GSP.001", + "com.nvidia.simready.HI.010", + "com.nvidia.simready.ISA.001", + "com.nvidia.simready.JT.001", + "com.nvidia.simready.JT.ART.003", + "com.nvidia.simready.NP.002", + "com.nvidia.simready.NP.003", + "com.nvidia.simready.NP.004", + "com.nvidia.simready.NP.005", + 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"simready.foundation.tier_core.capabilities.core.runtime_variants.validation.RuntimePhysicsIsolationChecker", + "simready.foundation.tier_core.capabilities.core.runtime_variants.validation.RuntimeVariantSectionPurityChecker", + "simready.foundation.tier_core.capabilities.core.sim_ready.validation.MetadataUnion", + "simready.foundation.tier_core.capabilities.core.sim_ready.validation.SimReadyCapabilityChecker", + "simready.foundation.tier_core.capabilities.core.sim_ready.validation.ThumbnailExists", + "simready.foundation.tier_core.capabilities.core.units.validation.MetersPerUnit1Checker", + "simready.foundation.tier_core.capabilities.core.units.validation.UpAxisZChecker", + "simready.foundation.tier_core.capabilities.hierarchy.validation.UndefinedPrimsChecker", + "simready.foundation.tier_core.capabilities.isaac_sim.composition.validation.IsaacCompositionCapabilityChecker", + "simready.foundation.tier_core.capabilities.nonvisual_sensors.nonvisual_materials.validation.NonVisualMaterialsCapabilityChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_graspable.validation.GraspableVectorLineChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_joints.validation.ArticulationChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_joints.validation.PhysicsJointCapabilityChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_materials.validation.PhysicsMaterialsCapabilityChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.InvisibleCollisionMeshHasPurposeGuide", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.MultibodyChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.NestedRigidBodyMassChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.NoNestedRigidBodyWithoutJointChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.RigidBodyCapabilityChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.RigidBodyColliderCapabilityChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.RigidBodyColliderMeshChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.RigidBodyColliderNonUniformScaleChecker", + "simready.foundation.tier_core.capabilities.physics_bodies.physics_rigid_bodies.validation.RigidBodyMassChecker", + "simready.foundation.tier_core.capabilities.semantic_labels.validation.SemanticLabelsCapabilityChecker", + "simready.foundation.tier_core.capabilities.semantic_labels.validation.SemanticLabelsMaterialChecker", + 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"PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=/World/Model/BellBody)", + "message": "GPrim '/World/Model/BellBody' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor", + "prim_path": "/World/Model/BellBody", + "requirement_version": "0.1.0", + "rule": "simready.foundation.tier_core.capabilities.visualization.display_color.validation.DisplayColorCapabilityChecker", + "rule_id": "com.nvidia.simready.DISP.001", + "severity": "failure", + "suggestions": [] + }, + { + "asset": "StageId(root_layer=LayerId(identifier='/output/asset.usd'))", + "location": "PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=/World/Model/BellBody)", + "message": "Prim has a collision API but no material binding through material:binding:physics.", + "prim_path": "/World/Model/BellBody", + "requirement_version": "0.1.0", + "rule": 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"com.nvidia.simready.RV.001", + "severity": "failure", + "suggestions": [] + } + ], + "warnings": [ + { + "asset": "StageId(root_layer=LayerId(identifier='/output/asset.usd'))", + "location": "PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=/World)", + "message": "The prim (/World) is a sibling of the default prim .", + "prim_path": "/World", + "requirement_version": "1.0.0", + "rule": "usd_validation_nvidia.rules._layout.DefaultPrimChecker", + "rule_id": "com.nvidia.usd.HI.004", + "severity": "warning", + "suggestions": [] + }, + { + "asset": "StageId(root_layer=LayerId(identifier='/output/asset.usd'))", + "location": "PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=/World/Model/BellBody)", + "message": "Mesh '/World/Model/BellBody' has non-unit normal (length=0.000000).", + "prim_path": "/World/Model/BellBody", + "requirement_version": "1.0.0", + "rule": "usd_validation_nvidia.rules._geometry.NormalsValidChecker", + "rule_id": "com.nvidia.usd.VG.028", + "severity": "warning", + "suggestions": [] + } + ] +} 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 c03f589e3725ffeaf38077ca5f30ad7821e2e0ae..9aa09ccad331c5b4e32c299a41a52cae09e0151d 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.

1 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)
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_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

\ 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.

2 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)
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

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

\ 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 b6442192bef12484c9c5884a406f1b5f5d6f795a..80baa291f80bc05ec4d264f8d306c7b53371d44e 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": 1, + "completed_conditions": 2, "partial": true, "settings": { "reference_assets": [ @@ -96,6 +96,1893 @@ } }, "results": [ + { + "condition_id": "condition-f0237999d0f3869061985cad42d0fc7d8dca5cde2bc122b7ad38f2a943ce35f1", + "asset_id": "container_bottle_glass_a01", + "requested_model": "Qwen/Qwen3.8-27B:deepinfra", + "harness_id": "pi", + "skill_set_id": "none", + "repetition": 0, + "status": "completed", + "formal_fidelity_percent": 80.54347826086956, + 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+condition-f0237999d0f3869061985cad42d0fc7d8dca5cde2bc122b7ad38f2a943ce35f1,container_bottle_glass_a01,Qwen/Qwen3.8-27B:deepinfra,pi,none,1,completed,80.54347826086956,0.0,,80.54347826086956,39,46,7,0,80.54347826086956,80.54347826086956,0,66.66666666666667,34,17,0,51,51,1.0,66.66666666666667,66.66666666666667,0.0,0.0,,0.0,1.0,1.0,0,0.6666666666666666,complete,measured,39,46,46,1.0,80.54347826086956,80.54347826086956,measured,0.0,2,2,1.0,0.0,0.0,not_applicable,0,0,0,0,,,0.0,measured,0.0,2048,2048,1.0,0.0,0.0,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.0,1,1,measured,0.0,1,1,measured,0,0,0,not_applicable,0,16384,16384,measured,0.0,0.0,2048,0.0,50.0,2,4,0,0,64,1,0,945.3274005204439,906.4118125811219,1487863,21911,1509774,,, condition-d35579adccdd9be0db995225fe9fe1d1fdf955b58d5847ceff846b8084cd9083,food_produce_banana_a01,Qwen/Qwen3.8-27B:deepinfra,pi,none,1,completed,82.6086956521739,0.0,,82.6086956521739,40,46,6,0,82.6086956521739,82.6086956521739,0,78.43137254901961,40,11,0,51,51,1.0,78.43137254901961,78.43137254901961,0.0,0.0,,0.0,1.0,1.0,0,0.8333333333333334,complete,measured,40,46,46,1.0,82.6086956521739,82.6086956521739,measured,0.0,2,2,1.0,0.0,0.0,not_applicable,0,0,0,0,,,0.0,measured,0.0,2048,2048,1.0,0.0,0.0,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.0,1,1,measured,0.0,1,1,measured,0,0,0,not_applicable,0,20480,20480,measured,0.0,0.0,2048,0.0,50.0,2,4,0,0,64,0,0,738.2069523409009,698.7784188082442,1152527,16965,1169492,,, diff --git a/viewer-index.json b/viewer-index.json index 20b96a2e49de577133b303c2ec1e98c996ae1d27..7c4c98ca8ede6b3d69124646eeec8fe34e124dfc 100644 --- a/viewer-index.json +++ b/viewer-index.json @@ -186,9 +186,13 @@ } ], "by_asset": [ + { + "split": 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