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  1. .gitattributes +8 -0
  2. outputs/G059_observatory_pinball/.generation/3d_object/meshy/obj200_meshy_tripo_20261015_v2/asset_task_index.json +52 -0
  3. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/meshy/930290d879f44d9475af2df0f6178dadea87673002164c91afb1655d5ffcef63.meta.json +33 -0
  4. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/meshy/9377ba6d681424c0626264a75c52980292a354e8d8783a375668532b988a4f8e.meta.json +33 -0
  5. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/tripo/3040f769f61230fc8e8401145feb72aef179c6f9d7fd23e1c6800ede841598a8.meta.json +30 -0
  6. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/tripo/84d45009e45f6c50913d8f0dd4e7da796cc7e9980a885e0f25a18e8ed3907e4a.meta.json +30 -0
  7. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/frozen_game_inputs.json +163 -0
  8. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt +273 -0
  9. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/method_selection.md +152 -0
  10. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt +8 -0
  11. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/localization_integrity.json +131 -0
  12. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/provenance/frozen_parent_plan_original.zip +3 -0
  13. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/provenance/records_before_localization_769eb142823f7565.zip +3 -0
  14. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/provenance/records_before_localization_774e0e1cdcec8285.zip +3 -0
  15. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/receipts/meshy/G059_observatory_pinball__G059_observatory_pinball_obj_001.json +88 -0
  16. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/receipts/meshy/G059_observatory_pinball__G059_observatory_pinball_obj_003.json +88 -0
  17. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/receipts/tripo/G059_observatory_pinball__G059_observatory_pinball_obj_001.json +54 -0
  18. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/receipts/tripo/G059_observatory_pinball__G059_observatory_pinball_obj_003.json +54 -0
  19. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/cloud_api.py +557 -0
  20. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/glb_utils.py +578 -0
  21. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/meshy_model.py +463 -0
  22. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/tripo_model.py +532 -0
  23. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/operators/gen_3d_object/operator.py +596 -0
  24. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/paths.py +444 -0
  25. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/record_paths.py +77 -0
  26. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/prompts/stage2_assets.md +95 -0
  27. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/cloud_journal.py +178 -0
  28. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/generate_3d_comparison.py +603 -0
  29. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/package-lock.json +763 -0
  30. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/process_mesh.mjs +77 -0
  31. outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/sources_index.json +128 -0
  32. outputs/G059_observatory_pinball/.generation/3d_object/tripo/obj200_meshy_tripo_20261015_v2/asset_task_index.json +52 -0
  33. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/meshy/import/model.glb +3 -0
  34. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/meshy/meta.json +170 -0
  35. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/meshy/model.glb +3 -0
  36. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/meshy/preview.png +3 -0
  37. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/tripo/import/model.glb +3 -0
  38. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/tripo/meta.json +147 -0
  39. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/tripo/model.glb +3 -0
  40. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/tripo/preview.png +3 -0
  41. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/meshy/import/model.glb +3 -0
  42. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/meshy/meta.json +170 -0
  43. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/meshy/model.glb +3 -0
  44. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/meshy/preview.png +3 -0
  45. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/tripo/import/model.glb +3 -0
  46. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/tripo/meta.json +147 -0
  47. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/tripo/model.glb +3 -0
  48. outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/tripo/preview.png +3 -0
  49. outputs/G059_observatory_pinball/eval/3d_object/G059_observatory_pinball_obj_001/meshy/previews/import/contact_sheet.jpg +3 -0
  50. outputs/G059_observatory_pinball/eval/3d_object/G059_observatory_pinball_obj_001/meshy/previews/import/iso.png +3 -0
.gitattributes CHANGED
@@ -58,3 +58,11 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/meshy/import/model.glb filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/meshy/model.glb filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/tripo/import/model.glb filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_001/tripo/model.glb filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/meshy/import/model.glb filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/meshy/model.glb filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/tripo/import/model.glb filter=lfs diff=lfs merge=lfs -text
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+ outputs/G059_observatory_pinball/assets/3d_object/G059_observatory_pinball_obj_003/tripo/model.glb filter=lfs diff=lfs merge=lfs -text
outputs/G059_observatory_pinball/.generation/3d_object/meshy/obj200_meshy_tripo_20261015_v2/asset_task_index.json ADDED
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+ {
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+ "plan_sha256": "5c287b8399f00fbb0dddf94c9e3f5ffcbcc2e679ff76882bc8fc369d6eae840d",
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+ "game_id": "G059_observatory_pinball",
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+ "provider": "meshy",
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+ "scope": "3d_object_only_not_complete_stage2",
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+ "tasks": [
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+ {
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+ "task": {
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+ "game_id": "G059_observatory_pinball",
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+ "task_id": "G059_observatory_pinball_obj_001",
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+ "asset_name": "star_pinball",
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+ "name_zh": "星屑弹珠",
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+ "role": "prop",
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+ "input_mode": "text_to_3d",
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+ "prompt": "Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
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+ "seed": 1591,
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+ "decimation_target": 2000,
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+ "texture_size": 1024,
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+ "rig": "none",
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+ "animation_strategy": "procedural",
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+ "spec_ref": "L01",
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+ "poly_policy": "low_poly_priority"
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+ },
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+ "shared_prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
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+ "reference": null,
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+ "subject_group": "rigid",
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+ "context_condition": "shared_short_context"
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+ },
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+ {
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+ "task": {
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+ "game_id": "G059_observatory_pinball",
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+ "task_id": "G059_observatory_pinball_obj_003",
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+ "asset_name": "brass_flipper_pair",
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+ "name_zh": "黄铜挡板对",
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+ "role": "mechanism",
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+ "input_mode": "text_to_3d",
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+ "prompt": "Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
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+ "seed": 1593,
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+ "decimation_target": 8000,
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+ "texture_size": 2048,
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+ "rig": "none",
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+ "animation_strategy": "procedural",
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+ "spec_ref": "L01,G02",
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+ "poly_policy": "low_poly_priority"
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+ },
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+ "shared_prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
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+ "reference": null,
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+ "subject_group": "rigid",
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+ "context_condition": "shared_short_context"
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+ }
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+ ]
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+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/meshy/930290d879f44d9475af2df0f6178dadea87673002164c91afb1655d5ffcef63.meta.json ADDED
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+ "ai_model": "meshy-6",
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+ "topology": "triangle",
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+ "target_polycount": 8000,
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+ "should_remesh": true,
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+ "mode": "preview",
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+ "prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
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+ "seed": 1593
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outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/meshy/9377ba6d681424c0626264a75c52980292a354e8d8783a375668532b988a4f8e.meta.json ADDED
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+ "should_remesh": true,
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+ "mode": "preview",
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+ "prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
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+ "seed": 1591
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+ "model": "meshy-6",
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outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/tripo/3040f769f61230fc8e8401145feb72aef179c6f9d7fd23e1c6800ede841598a8.meta.json ADDED
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+ "geometry_quality": "standard",
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+ "smart_low_poly": true,
10
+ "face_limit": 8000,
11
+ "prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
12
+ "model_seed": 1593,
13
+ "texture_seed": 1593
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+ },
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+ "model": "v3.1-20260211",
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+ "elapsed_sec": 249.58,
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+ "credits": 30.0,
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+ "cached": false,
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+ "preview_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/40acc76f-5e92-49d4-b329-c056ad36526a/legacy_mesh.webp?auth_key=1792227876-nlclfhub-0-7f722db68037c533e07cd3b46ab8dacf",
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+ "cache_key": "3040f769f61230fc8e8401145feb72aef179c6f9d7fd23e1c6800ede841598a8"
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+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/cache_metadata/tripo/84d45009e45f6c50913d8f0dd4e7da796cc7e9980a885e0f25a18e8ed3907e4a.meta.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "provider": "tripo",
3
+ "payload": {
4
+ "model": "v3.1-20260211",
5
+ "texture": true,
6
+ "pbr": true,
7
+ "texture_quality": "standard",
8
+ "geometry_quality": "standard",
9
+ "smart_low_poly": true,
10
+ "face_limit": 2000,
11
+ "prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
12
+ "model_seed": 1591,
13
+ "texture_seed": 1591
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+ },
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+ "model": "v3.1-20260211",
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+ "task_id": "8f4c4879-b27c-4976-aff6-f03973daaadc",
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+ "elapsed_sec": 168.46,
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+ "credits": 30.0,
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+ "cached": false,
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+ "preview_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/8f4c4879-b27c-4976-aff6-f03973daaadc/legacy_mesh.webp?auth_key=1792227786-edcmnhdh-0-27653fddcbd59b6157390dabd360bbac",
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+ "nodes": 1,
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+ "generator": "https://tripo3d.ai",
29
+ "cache_key": "84d45009e45f6c50913d8f0dd4e7da796cc7e9980a885e0f25a18e8ed3907e4a"
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+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/frozen_game_inputs.json ADDED
@@ -0,0 +1,163 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "schema_version": "game_delivery_view_not_execution_plan_v1",
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+ "batch_id": "obj200_meshy_tripo_20261015_v2",
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+ "game_id": "G059_observatory_pinball",
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+ "parent_frozen_plan_sha256": "5c287b8399f00fbb0dddf94c9e3f5ffcbcc2e679ff76882bc8fc369d6eae840d",
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+ "parent_frozen_plan_file_sha256": "3c4798c34345ab6f7fc07f850f25deca44051565185a1c8a80058819e1bbd685",
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+ "task_count": 2,
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+ "parent_plan_original": {
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+ "archive": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/provenance/frozen_parent_plan_original.zip",
10
+ "archive_member": "bench/test_data/outputs/_asset_batches/obj200_meshy_tripo_20261015_v2/plan.json",
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+ "original_file_sha256": "3c4798c34345ab6f7fc07f850f25deca44051565185a1c8a80058819e1bbd685",
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+ "plan_sha256": "5c287b8399f00fbb0dddf94c9e3f5ffcbcc2e679ff76882bc8fc369d6eae840d"
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+ },
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+ "scope": "3d_object_only_not_complete_stage2",
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+ "providers": {
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+ "meshy": {
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+ "model": "meshy-6",
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+ "api_base": "https://api.meshy.ai",
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+ "options": {
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+ "low_poly": false,
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+ "texture": true,
22
+ "enable_pbr": true,
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+ "should_remesh": true,
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+ "topology": "triangle"
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+ },
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+ "credits": {
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+ "text_preview": 20,
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+ "text_refine": 10,
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+ "image": 30
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+ }
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+ },
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+ "tripo": {
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+ "model": "v3.1-20260211",
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+ "api_base": "https://openapi.tripo3d.com/v3",
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+ "options": {
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+ "low_poly": true,
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+ "texture": true,
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+ "pbr": true,
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+ "texture_quality": "standard",
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+ "geometry_quality": "standard"
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+ },
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+ "credits": {
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+ "text": 30,
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+ "image": 40
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+ }
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+ }
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+ },
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+ "postprocess": {
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+ "tool": "gltf-transform-4.2.1_meshoptimizer-0.24.0",
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+ "simplify_error": 0.01,
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+ "simplify_passes": 1,
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+ "triangle_budget": "per_task_decimation_target_at_most_8000",
53
+ "texture_budget": "per_task_texture_size_downsize_only",
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+ "preserve_native_output": true
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+ },
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+ "runtime_sources": {
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+ "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/generate_3d_comparison.py": "70f8d79c8596908f7edcd7ff68120f558cea6881f23dc2f0e29ef62f2bab75c4",
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+ "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/cloud_api.py": "a3c363a3439b3864e05e782340eb3059380c4b1c28eccb2524e9cbf9131fe996",
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+ "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/process_mesh.mjs": "b1b6ada273a576083bb167772ec03fee6fe3275470180563722e56687688995c",
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69
+ },
70
+ "mesh_runtime": {
71
+ "status": "ready",
72
+ "node": "20.17.0",
73
+ "dependencies": {
74
+ "@gltf-transform/core": "4.2.1",
75
+ "@gltf-transform/extensions": "4.2.1",
76
+ "@gltf-transform/functions": "4.2.1",
77
+ "draco3dgltf": "1.5.7",
78
+ "meshoptimizer": "0.24.0",
79
+ "sharp": "0.35.5"
80
+ }
81
+ },
82
+ "documents": {
83
+ "general_requirement": {
84
+ "path": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt",
85
+ "sha256": "4b6847098cb1a6e7a930c80af21b14e75771d1d6e9c8326d19439a446ea8a767",
86
+ "source": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt"
87
+ },
88
+ "object_requirement": {
89
+ "path": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt",
90
+ "sha256": "45cbe4cfc38dd23248f1ea2fb3ca15bb14ee7ee095c0d7576f6a9fdfb32d4472",
91
+ "source": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt"
92
+ },
93
+ "context_excerpt": "微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。",
94
+ "context_method": "deterministic title/world/core-loop excerpts; full brief retained locally"
95
+ },
96
+ "tasks": [
97
+ {
98
+ "task": {
99
+ "game_id": "G059_observatory_pinball",
100
+ "task_id": "G059_observatory_pinball_obj_001",
101
+ "asset_name": "star_pinball",
102
+ "name_zh": "星屑弹珠",
103
+ "role": "prop",
104
+ "input_mode": "text_to_3d",
105
+ "prompt": "Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
106
+ "seed": 1591,
107
+ "decimation_target": 2000,
108
+ "texture_size": 1024,
109
+ "rig": "none",
110
+ "animation_strategy": "procedural",
111
+ "spec_ref": "L01",
112
+ "poly_policy": "low_poly_priority"
113
+ },
114
+ "shared_prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
115
+ "reference": null,
116
+ "subject_group": "rigid",
117
+ "context_condition": "shared_short_context"
118
+ },
119
+ {
120
+ "task": {
121
+ "game_id": "G059_observatory_pinball",
122
+ "task_id": "G059_observatory_pinball_obj_003",
123
+ "asset_name": "brass_flipper_pair",
124
+ "name_zh": "黄铜挡板对",
125
+ "role": "mechanism",
126
+ "input_mode": "text_to_3d",
127
+ "prompt": "Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
128
+ "seed": 1593,
129
+ "decimation_target": 8000,
130
+ "texture_size": 2048,
131
+ "rig": "none",
132
+ "animation_strategy": "procedural",
133
+ "spec_ref": "L01,G02",
134
+ "poly_policy": "low_poly_priority"
135
+ },
136
+ "shared_prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
137
+ "reference": null,
138
+ "subject_group": "rigid",
139
+ "context_condition": "shared_short_context"
140
+ }
141
+ ],
142
+ "input_policy": "shared_short_context_and_reference_only",
143
+ "context_limitations": "Text APIs received shared short context plus asset prompt; image APIs received reference only. Full requirements retained as evidence, not sent to APIs.",
144
+ "benchmark_metrics": {
145
+ "C": {
146
+ "status": "UNKNOWN",
147
+ "value": null
148
+ },
149
+ "Q1": {
150
+ "status": "UNKNOWN",
151
+ "value": null
152
+ },
153
+ "Q2": {
154
+ "status": "UNKNOWN",
155
+ "value": null
156
+ },
157
+ "Q3": {
158
+ "status": "UNKNOWN",
159
+ "value": null
160
+ }
161
+ },
162
+ "view_sha256": "f3e3f9c53d46453718d9f0961d7322e8f4220199882a03c58604693ee8063d85"
163
+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt ADDED
@@ -0,0 +1,273 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # 《微缩天文台的物理弹珠》｜机关倍率弹珠机制输入规范
2
+
3
+ ```yaml
4
+ case_id: G059
5
+ base_case_id: G059
6
+ title: 微缩天文台的物理弹珠
7
+ category: Sports / Rhythm / Physics
8
+ tier: M
9
+ engine: unity3d
10
+ report_track: Standard
11
+ paired_conditions: [R, N]
12
+ required_real_clients: 1
13
+ fixed_seed: 1059
14
+ spec_version: v3
15
+ status: DRAFT_LOCAL
16
+ mechanism_source: null
17
+ task_spec_version: null
18
+ task_spec_hash: null
19
+ frozen_by: null
20
+ frozen_at: null
21
+ dependency_hashes: null
22
+ ```
23
+
24
+ ## 0. 标题、版本与使用说明
25
+
26
+ - 作品名：《微缩天文台的物理弹珠》；版本：mechanics-v3（2026-10-11 完整性修订：补同帧多球出界与连续碰撞规则、镜头边界、世界设定、演出反馈、视频与正向范围清单）；运行引擎：**Unity 2022.3（URP 渲染管线）**（spec、rubric 与 asset 任务 JSONL 引擎字段保持一致）；输入方式：键盘与鼠标。
27
+ - 原创边界：本作全部名称、弹珠台、机关、文案与美术必须原创，不使用任何商业作品的名称、主题台或造型。
28
+ - 规则优先级：本文件全局数值与规则 ＞ 机制章节 ＞ 弹珠台实例 ＞ 生成器自由补充；未指定数值可作为明确标注的配置默认值。
29
+ - 本文件用于游戏生成模型；文档存在不等于玩法完成，静态页面或演示视频不能单独证明可玩。
30
+
31
+ ## 1. 定位与完整流程 [S01–S06]
32
+
33
+ - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。
34
+ - S02 核心循环一句话：发射弹射 → 挡板控制 → 机关触发 → 倍率累积 → 多球管理 → 出界回收 → 结算。
35
+ - S03 流程：单球热身段（倍率起步）→ 机关链段（按序提倍率）→ 多球高潮段（解锁多球）→ 球数耗尽结算。
36
+ - S04 最低完整流程：发射、左右挡板、机关靶标、倍率显示、出界回收、结算、重开必须全部存在且有真实入口。
37
+ - S05 失败恢复入口：单球落袋且仍有发球机会→自动发新球继续；球数耗尽一键重开；Esc 暂停。
38
+ - S06 本局耦合边速览：机关顺序系统→倍率计分系统（按序提倍率、乱序重置组链）；多球状态系统→出界回收系统（多球下逐球回收、同帧出界合并耗 1 机会）。
39
+
40
+ ## 2. 完整核心循环与阶段 [S06–S10]
41
+
42
+ 完整循环：启动与标题 → 单球热身 → 机关链 → 多球高潮 → 球数耗尽结算 → 重开/返回。每阶段六要素如下（引用本 spec §3–§7 与 §9 对应规则）：
43
+
44
+ - S06 启动与标题
45
+ - input：系统启动加载完成（触发方：系统）；玩家按 Enter/点击「开始」
46
+ - precondition：构建可启动且台面按 seed=1059 冻结
47
+ - state_change：进入「标题」状态；首次进入按 §10 C01 触发开场视频
48
+ - feedback：标题界面按 §9 F10 呈现（达标线 10000 目标）
49
+ - next_actions：进入「单球热身段」
50
+ - outcome：无跨局状态写入（见 §7 V04）
51
+ - S07 单球热身段
52
+ - input：Space 蓄力发射、左/右 Shift 挡板、滚轮缩放、Esc 暂停（触发方：玩家）
53
+ - precondition：发球机会 >0 且场上无球
54
+ - state_change：发射入台；倍率从 ×1 起步；A/B/C 组链可用
55
+ - feedback：星光尾迹与撞击反馈按 §9 F05 呈现
56
+ - next_actions：按序完成任一组 → 倍率 +1 →「机关链段」节奏
57
+ - outcome：分数与倍率局内累计
58
+ - S08 机关链段
59
+ - input：挡板控制（触发方：玩家）
60
+ - precondition：球在场
61
+ - state_change：A1→A2→A3 / B1→B2 / C1→C2→C3 按序推进；乱序重置该组链（倍率不回退）
62
+ - feedback：组链进度灯与倍率跳变反馈
63
+ - next_actions：完成 C 组 → 解锁多球 →「多球高潮段」（先播 C02）
64
+ - outcome：倍率与分数持续累计
65
+ - S09 多球高潮段
66
+ - input：挡板控制（触发方：玩家）
67
+ - precondition：C 组完成，+2 球入场
68
+ - state_change：各球独立物理与计分；逐球回收带球标识；同帧多球出界按 G07 合并结算
69
+ - feedback：多球星光与机台灯光全亮
70
+ - next_actions：机会归零 →「结算」（先播 C03）
71
+ - outcome：按 V01/V02 判定
72
+ - S10 结算
73
+ - input：Enter＝重开 / Esc＝返回标题（触发方：玩家）
74
+ - precondition：发球机会归零
75
+ - state_change：进入「结算」状态；物理冻结
76
+ - feedback：结算面板显示总分、最高倍率、多球时长
77
+ - next_actions：重开（全量清空）或返回
78
+ - outcome：无跨局写入
79
+
80
+ ## 3. 数值口径与全局规则 [G01–G07]
81
+
82
+ - G01 统一刻度：分数按点、倍率按倍数、球按颗计；时间用游戏模拟秒（暂停冻结）。
83
+ - G02 弹珠台与物理（本包冻结值）：单张天文台弹珠台（倾斜台面、原创造型）；���右挡板各 1、顶部发射弹射轨道；弹珠直径 2.7 cm 等比；重力沿台面分量固定。高速碰撞可靠性红线：任意速度下弹珠不得穿模穿透挡板/靶标/边墙（碰撞采样导出，零穿模事件）；单物理步内连续碰撞 ≥3 次仍须稳定结算（采用连续碰撞检测或子步进，采样导出零穿模零卡死）。
84
+ - G03 机关顺序与倍率（本包冻结值）：3 组机关——A 行星轨道（靶标 A1→A2→A3 按序）、B 星图（B1→B2 按序）、C 彗星（C1→C2→C3 按序）；任一组按序完成 → 倍率 +1（上限 ×5）；组内乱序命中 → 该组链重置（倍率不变）；完成 C 组 → 解锁多球（+2 球）。
85
+ - G04 计分（本包冻结值）：每次靶标命中得基础 100 ×当前倍率；完成组链瞬间另加 500 ×当时倍率；返回通道射入 250 ×倍率；总分＝事件加权和，对账容差 0；达标线 10000 分。
86
+ - G05 球数与出界（本包冻结值）：初始发球机会 3 次；单球落袋（场上无其他球）→ 机会 −1；多球下逐球出界仅回收该球、不耗机会；机会归零且分数未达标 → 失败结算。
87
+ - G06 判定与独立 oracle（本包冻结值）：计分 oracle——按序命中 A1→A2→A3（倍率 ×1 期）：100×3＝300 分，完成链另加 500 → 总 800 分且倍率升 ×2，之后每次命中按 ×2 计；对账任何偏离即 FAIL。多球 oracle——双球在场时 1 球落袋（预期发球机会不变、另一球继续）；单球落袋（预期机会 −1）。发射弹射由 Space 蓄力（蓄力 0.5–1.0 秒线性映射弹射力度）。Esc 暂停冻结物理与计时；fixed_seed=1059 冻结台面扰动序列（可复现弹射）；窗口失焦自动暂停。
88
+ - G07 同帧多球出界（本包冻结值）：同一物理步内多球同时出界——逐球回收并各自记录回收事件（含球标识）；若该步后场上无球且发球机会 >0 → 本步出界合并视为一次「落袋事件」，仅耗 1 次发球机会（不按球数扣减）；oracle：双球同帧出界且无第三球在场 → 机会 −1（非 −2）；任意时刻机会不为负。
89
+
90
+ ## 4. 操作与输入 [I01–I07]
91
+
92
+ - I01 键鼠：左 Shift／Z＝左挡板；右 Shift／／＝右挡板；Space＝发射蓄力；Esc＝暂停；结算界面 Enter＝重开。
93
+ - I02 输入语义边界：无球在发射轨道时蓄力无效；暂停/结算期间输入无效；挡板键为按住状态语义。
94
+ - I03 无手柄需求；分数、倍率、剩余发球机会、组链进度、场上球数须常驻显示。
95
+ - I04 输入优先级：暂停与结算状态阻断全部玩法输入；同帧左右挡板同时有效；发射仅在发射轨道有球时可用。
96
+ - I05 焦点与失焦规则：点击画布捕获输入焦点；面板层阻断点击穿透；窗口失焦自动暂停。
97
+ - I06 UI 必须显示的状态：分数、倍率、发球机会、组链进度（A/B/C 三组）、场上球数；HUD 对照见 rubric。
98
+ - I07 输入延迟目标：挡板按下到抬起反馈 ≤ 30 毫秒（弹珠手感关键）；发射蓄力采样 ≤ 50 毫秒。
99
+
100
+ ## 5. 弹珠台与内容清单 [L01–L04]
101
+
102
+ - L01 生成对象：弹珠台 1（原创造型）、靶标 8（A×3、B×2、C×3）、左右挡板、发射轨道、返回通道、HUD（分数/倍率/机会/组链/球数）。
103
+ - L02 关卡：单张台面；靶标布局固定，台面扰动序列由 seed=1059 冻结，不随机扩展。
104
+ - L03 目标物/交互物/场景/UI 对象：本 spec §3–§9 引用的界面元素（标题/HUD/结算/暂停/视频播放层）与交互物逐类存在且运行时可进入；数量与属性以 L01/L02 与 G 系为准。
105
+ - L04 冻结需求 vs 实现默认 vs 生成自由度：本 spec 明确写出的数值与数量为冻结需求；§9 未冻结的台面装饰与配色为生成自由度，不得评估为缺失；实现默认值必须明确标注且符合核心机制。
106
+
107
+ ## 6. 机制系统 [M01–M05]
108
+
109
+ - M01 挡板与碰撞（主机制）
110
+ - input：左右挡板键
111
+ - precondition：处于游玩状态（非暂停/结算）
112
+ - state_change：挡板抬升改变碰撞反弹；高速碰撞不穿透；单步连续碰撞 ≥3 次稳定结算（G02）
113
+ - observable：碰撞采样流（含球标识、速度、法线、接触点；零穿模事件）
114
+ - invalid_case：暂停期间挡板冻结
115
+ - recovery：—
116
+ - M02 机关顺序与倍率
117
+ - input：弹珠命中靶标（系统）
118
+ - precondition：球与靶标碰撞体接触
119
+ - state_change：组内按序推进、乱序重置；完成组链倍率 +1（≤×5）
120
+ - observable：机关序事件（含球标识与靶标 ID）与倍率状态变更
121
+ - invalid_case：乱序命中不加分不提倍率
122
+ - recovery：该组链重新按序完成
123
+ - M03 多球状态
124
+ - input：完成 C 组机关（系统）
125
+ - precondition：C 组链完成且未处于多球中
126
+ - state_change：+2 球入场，各球独立物理、独立计分、独立球标识
127
+ - observable：多球计数与逐球回收事件（带球标识）
128
+ - invalid_case：重复完成 C 组不重复加球（倍率期外）
129
+ - recovery：逐球回收直至单球/零球
130
+ - M04 出界与计分
131
+ - input：球落袋／球数耗尽（系统）
132
+ - precondition：球越过出界判定线
133
+ - state_change：逐球回收；单球落袋耗发球机会；同帧多球出界按 G07 合并耗 1 机会；机会归零结算
134
+ - observable：计分流水（事件加权和）与发球机会流水（含同帧合并事件字段）
135
+ - invalid_case：机会为 0 时不再发球
136
+ - recovery：判负一键重开
137
+ - M05 镜头与取景
138
+ - input：滚轮缩放（玩家）
139
+ - precondition：处于游玩状态
140
+ - state_change：1.0×/1.3× 两档缩放（台面中心为锚）；台面边界外不可平移；多球期间保持台面全览（不跟随单球）
141
+ - observable：缩放档位事件；全览断言（多球时四角可见）
142
+ - invalid_case：缩放不改变判定与物理
143
+ - recovery：—
144
+
145
+ 系统耦合边（玩法必需、可复现）：
146
+
147
+ - E01 from_system=机关顺序系统 → to_system=倍率计分系统；changed_state=按序完成组链使倍率 +1，随后每次命中按新倍率计分；乱序重置组链但不回退倍率；验证方式=机关序事件→倍率状态→计分流水三联对照（state_before/after）。
148
+ - E02 from_system=多球状态系统 → to_system=出界回收系统；changed_state=场上球数 ≥2 时落袋仅回收该球且发球机会不变，单球落袋才机会 −1，同帧多球出界合并耗 1（G07）；验证方式=多球/单球/同帧三种落袋场景的发球机会流水对照。
149
+
150
+ ## 7. 成功、失败与恢复 [V01–V05]
151
+
152
+ - V01 成功条件：球数耗尽时总分 ≥10000 → 胜利结算（显示总分、最高倍率、多球时长）。
153
+ - V02 失败条件：发球机会归零且总分 <10000 → 失败结算。
154
+ - V03 恢复语义：单球落袋且有剩余机会 → 自动发新球继续（倍率与分数保留）；判负一键重开全量重置（seed 复现）。
155
+ - V04 persistent_state：局内（倍率/球数/分数局内保留；重开全量清空）。
156
+ - V05 persistent_state 生命周期：当前动作级状态即时结算；当前局级状态局内保留、重开清空；无跨局保留状态。
157
+ - V06 软锁与不可达处理：不设软锁——发球机会耗尽必然结算；球卡死（速度近零且非判定区）超 5 秒自动微扰复位（缺陷容错，采样记录）。
158
+
159
+ ## 8. 世界设定与创作基线 [W01–W08]
160
+
161
+ - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。
162
+ - W02 场景所在地：星穹观测台的展示厅——单张天文台主题弹珠台（倾斜台面、星轨灯带、黄铜挡板）。
163
+ - W03 玩家身份与当前任务：玩家是观测台的访客；当前任务：按序点亮行星轨道、星图与彗星三组机关，解锁「群星多球」，冲击观测记录 10000 分。
164
+ - W04 失败代价与结局表达：机会耗尽未达标＝「记录未破」（判负文案）；达标则 C03 呈现群星灯带全亮与观测记录题名。
165
+ - W05 叙事来源：三组机关＝老匠人的三段观测笔记（行星轨道/星图/彗星）；多球＝「群星同辉」时刻；返回通道＝回廊巡星。全部原创。
166
+ - W06 视觉风格与色彩材质：黄铜与深蓝星空的机台风；主色＝黄铜金（#B08D4F 系）＋星空深蓝（#1D2B4A 系）＋彗星青白（#9FD8E8 系）；材质以黄铜、发光灯带、深色台面为主。
167
+ - W07 环境氛围与声音语言：安静展厅中的机台低鸣——常驻展厅环境声；音效语言为「弹射砰＋撞击铛＋靶标叮＋多球合鸣」，全部音效按 §9 F06 冻结清单交付。
168
+ - W08 故事表达方式：开场视频（C01）交代观测台与弹珠机 → 多球视频（C02）在首次解锁多球时呈现「群星同辉」→ 结算视频（C03）收束观测记录；故事只做包装，不改变机制数值。
169
+
170
+ ## 9. 演出、镜头与反馈 [F01–F10]
171
+
172
+ - F01 视角与镜头：侧视固定台面全览（正面视角，台面四角可见）；滚轮两档缩放（1.0×/1.3×，台面中心为锚）；镜头边界＝台面外框，不可平移；多球期间保持全览（防漏球）；重开后镜头复位默认档。
173
+ - F02 关键操作镜头变化：完成组链瞬间轻微震动 0.1 秒；多球入场时机台灯带全亮＋镜头轻微拉远 5%（0.4 秒）后回位；无慢动作。
174
+ - F03 输入与延迟：见 I07（挡板 ≤30 毫秒）。
175
+ - F04 环境常驻效果：星轨灯带缓转、台面星尘微粒、挡板黄铜反光；不遮挡靶标与出界判定线。
176
+ - F05 事件反馈表（事件 → 表现 → 结束条件，全部为冻结需求）：
177
+
178
+ | 事件 | 画面表现 | 音效 | 结束条件 |
179
+ |---|---|---|---|
180
+ | 发射蓄力 | 蓄力弧光沿轨道亮起 | 蓄力嗡声（按住循环） | 发射 |
181
+ | 弹射入台 | 球弹出＋星光尾迹启动 | 弹射砰声 | 尾迹常驻 |
182
+ | 靶标命中 | 靶标星徽点亮＋撞击闪光 | 撞击铛声（按组分档） | 0.3s |
183
+ | 组链推进 | 组链进度灯逐级点亮 | 进度叮声 | 常亮 |
184
+ | 乱序重置 | 该组进度灯熄灭＋红闪一次 | 低沉否定音 | 0.3s |
185
+ | 倍率提升 | 倍率数字放大弹跳＋金光圈 | 倍率上扬音 | 弹跳完成 |
186
+ | 多球解锁 | 灯带全亮＋双球入场星光 | 群星合鸣音 | 入场完成 |
187
+ | 返回通道射入 | 通道流光＋250×倍率飘分 | 通道滑音 | 完成 |
188
+ | 逐球回收 | 球坠出界灰化＋球标识归档 | 落袋闷响 | 完成 |
189
+ | 同帧多球出界 | 双球同时灰化＋「合并计 1」提示 | 双响合并声 | 完成 |
190
+ | 达标线突破 | 分数栏金光爆发＋「记录已破」横幅 | 纪录钟声 | 进入结算淡出 |
191
+ | 判负 | 灯光渐暗 | 低沉收束音 | 进入结算 |
192
+
193
+ - F06 关键音效清单：蓄力嗡声、弹射砰、撞击铛（三组分档）、进度叮、否定音、倍率上扬、群星合鸣、通道滑音、落袋闷响、双响合并、纪录钟声、收束音；环境音：展厅低鸣＋机台运转（常驻循环）；循环音开始/结束：蓄力嗡声按按住起止、环境声随台面载入开始、随结算淡出 0.5s；无配音需求。
194
+ - F07 VFX 信息性与遮挡约束：组链进度灯与倍率数字承担机关信息；球标识（HUD 多球计数）承担多球信息；星光尾迹与星尘粒子单帧 ≤ 45 且不遮挡靶标、挡板与出界判定线。
195
+ - F08 音画同步：撞击铛与碰撞帧同步；倍率上扬与倍率事件帧同步；纪录钟声与达标帧同步。
196
+ - F09 屏幕震动：组链完成 0.1 秒小幅；同帧多球出界 0.15 秒中幅；设置界面提供「镜头震动开/关」（关闭不影响判定）。
197
+ - F10 前端界面：标题（开始/目标提示/设置/退出）→ HUD（分数、倍率、发球机会、A/B/C 组链进度、场上球数）→ 结算（总分/最高倍率/多球时长/达标状态/重开/返回）→ 暂停面板（继续/重开/设置）；关键状态附图标＋文字（组链、多球数、合并计 1 提示），不只靠颜色区分；窗口失焦自动暂停。
198
+
199
+ ## 10. 过场视频 [C01–C03]
200
+
201
+ - C01 开场观测（Opening，10 秒，1280×720@24fps）
202
+ - 触发时机：首次由标题进入台面之前，每局一次
203
+ - 内容与角色场景：星穹观测台展厅夜景，镜头掠过黄铜弹珠台的星轨灯带，一枚弹珠被推上发射轨道
204
+ - 资产对应：弹珠台、星轨灯带、弹珠与游戏内模型同源设计
205
+ - 可跳过：Esc/Enter 跳过 → 直接进入台面；自然播完 → 同
206
+ - 状态一致：播放期间不推进任何计时；进入状态＝机会 3、倍率 ×1
207
+ - C02 群星多球（Event，6 秒，1280×720@24fps）
208
+ - 触发时机：首次完成 C 组解锁多球事件后的下一帧短暂插入（每局一次）
209
+ - 内容与角色场景：彗星靶标三点连成光轨，两枚新弹珠自星轨灯带滑入台面，灯带全亮
210
+ - 资产对应：彗星靶标、弹珠、灯带与游戏内一致
211
+ - 可跳过：Esc 跳过 → 回到台面继续（多球状态已生效）；自然播完 → 同
212
+ - 状态一致：仅在真实解锁后触发，球数与计分不变
213
+ - C03 观测完成（Ending，10 秒，1280×720@24fps）
214
+ - 触发时机：发球机会归零结算前，每局一次
215
+ - 内容与角色场景：台面灯带按最终倍率级数逐级定格；达标时星图在台面上方展开并题写「观测记录」，未达标时灯光温和收暗
216
+ - 资产对应：弹珠台、星图、灯带与游戏内一致
217
+ - 可跳过：Esc/Enter 跳过 → 直接进入结算面板；自然播完 → 同
218
+ - 状态一致：达标/未达标呈现与真实结算一致
219
+
220
+ ## 11. 范围与正向能力清单 [N01–N06]
221
+
222
+ - N01 本测例包含的玩法能力：单台弹珠物理、三组机关链与倍率、多球状态与球标识、同帧多球出界合并结算、连续碰撞稳定、双档全览镜头、蓄力发射。
223
+ - N02 本测例包含的流程与界面：标题、发射与挡板操作、结算与判负、暂停（含失焦自动暂停）、一键重开。
224
+ - N03 本测例包含的演出能力：开场/多球/结算视频（C01–C03）、§9 F04–F09 全部事件反馈与音效、星空机台氛围。
225
+ - N04 输入范围：键盘＋鼠标（Space/左右 Shift 或 Z//、滚轮/Esc/Enter）；无触控、手柄、多人需求。
226
+ - N05 音频范围：§9 F06 冻结音效清单＋展厅环境音；无配音与背景音乐轨需求。
227
+ - N06 表现层自由度：§9 未冻结的台面装饰、配色细节与粒子参数为生成自由度，由 L04 承担，不评估为缺失。
228
+
229
+ ## 12. 参考图绑定 [A01]
230
+
231
+ - 本测例当前无已绑定参考图；规划的参考图（天文台弹珠台全景、三组靶标造型、弹珠与挡板等）已登记于 `asset_tasks/puzzle_survival_rpg_sports/ref_images_manifest.jsonl`（含完整生成 prompt），作为待补前置依赖管理，正式任务 JSONL 不指向不存在文件。
232
+
233
+ ## 13. 复杂度档案
234
+
235
+ ```yaml
236
+ difficulty:
237
+ tier: M
238
+ complexity_profile: {coupling: C2, persistence: P1, recovery: R1, runtime_complexity: B2, hidden_state: H0}
239
+ dominant_dimensions: [coupling]
240
+ rationale: "局内多系统耦合：机关序→倍率计分、多球状态→出界回收（含同帧合并）两条可复现 A→B 边（C2）；多球并发物理与连续碰撞（B2）；分数/倍率/机会局内保留（P1）；判负重开即恢复（R1）；新增同帧出界与镜头规则仍属局内物理规则，不构成跨阶段持久后果"
241
+ downgrade_boundary: "删去机关序与倍率联动及多球状态（固定倍率单球台）后降为 S"
242
+ upgrade_boundary: "若多台连打成绩跨局保留并解锁新台面规则，升 L-Regular"
243
+ stress_axes: []
244
+ ```
245
+
246
+ ## 生成任务明确性补充（2026-10-12）
247
+
248
+ > 本补充只约束游戏生成输入，不引用 rubric。所有生成器必须以本文件规则和下列 JSONL 任务为准；未列出的装饰细节可以自由发挥，但不得省略已列资产或生命周期。
249
+
250
+ ### 故事与流程最低合同
251
+ - **玩家身份与当前冲突**：以 §1、§8 的角色/世界/冲突为唯一叙事入口；开局必须让玩家知道“我是谁、现在要解决什么问题”。
252
+ - **阶段性目标**：必须有可操作的阶段目标、至少一次状态变化/升级，并在 §7 的胜利、失败、重开入口中闭环；不能只生成一个无结果的场景演示。
253
+ - **结果承接**：胜利/失败都要有明确结果文案或演出，并回到可重开、暂停或标题入口；视频、音频和 VFX 不得推进未完成的玩法状态。
254
+
255
+ ### 生成任务清单（JSONL 冻结口径）
256
+ - scene：1 个；必须生成连贯可游玩的空间，不得出现下半部文字、拼贴面板、物体 lineup 或 UI。
257
+ - object：3 个（text-to-3D 2，image-to-3D 1）；object 任务资产为：star_pinball, planet_target_bank, brass_flipper_pair。每项只允许一个物体；组合物必须拆成独立任务。
258
+ - motion：1 个；覆盖动作：ball_launch。
259
+ - video/audio/mechanic/UI：分别为 3/11/1/1 个任务；若某项为 0，只能是本案例明确的 N/A，不得默默遗漏。
260
+
261
+ ### Video / motion / audio 生命周期
262
+ - Video 每项必须写清 `trigger`、`start_condition`、`duration_sec`、`skippable`、`skip_behavior`、`end_condition` 和进入的下一个游戏状态；播放期间不得偷偷消耗计时或改变战斗/任务数值。
263
+ - Motion 每项必须写清 `source_asset`、`trigger`、`start_condition`、`duration_sec`、`loop`、`end_condition` 和 `cancel_behavior`；动作要与对应输入/机制事件绑定，不可只写“walk animation”。
264
+ - Audio 每项必须写清触发事件、时长、`loop`、`stop_condition`、优先级和 ducking；关键命中/提示音必须与事件帧同步，暂停/结算时按 §9 处理。
265
+
266
+ ### Mechanic / UI / 游玩手感
267
+ - Mechanic JSON 与 §1–§7 配对：每个输入都要有 precondition、state_change、feedback、next_state；必须说明失败/禁用分支。
268
+ - UI JSON 与 §9/F10 配对：HUD、菜单、结算、暂停、错误/禁用态要有 state binding；关键状态不能只用颜色表达。
269
+ - 手感冻结：相机跟随/构图、FOV、碰撞/遮挡、镜头调整与镜头震动必须在 §9 说明；震动反馈必须写明触发、强度和持续时间，并提供关闭设置且不改变判定。
270
+
271
+ ### VFX 时机合同
272
+ 每个特效必须写清 `trigger event`、预备/前摇、active window、持续时间、结束条件、被打断/取消条件，以及和相机震动、音效、UI 的同步关系；命中特效、失败特效、胜利特效不能只写“有粒子”。
273
+
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/method_selection.md ADDED
@@ -0,0 +1,152 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # 优先资产：方法选择与执行边界
2
+
3
+ 核对日期：2026-10-15。本文是候选方法建议和开跑前检查，不是实验结果，也不是已验证的
4
+ API 配置。评测口径以 `GameFactory-3A/eval/asset_evaluation_plan.md` 为准；
5
+ 本次没有改动该方案、原始全集或其他五份现有优先生成 JSONL。
6
+
7
+ ## 1. 建议首轮组合
8
+
9
+ | 类别 | 首轮建议 | 放在哪组 | 选择理由 / 限制 |
10
+ |---|---|---|---|
11
+ | 3D Object | Meshy + Tripo + 腾讯云 Hunyuan3D Pro 商用 API | B1 商用生成 API；逐版本核对开放权重状态 | 三家即可；人物/刚体、T2/I2 分组，保持同输入和低模预算 |
12
+ | 3D Scene | 新增 World Labs Marble World API；保留 WorldPlay/HY-World 2.1 Scene → WorldMirror → 导出，以及 LLM 布局/组合 | Marble 为 B2 商用 direct 候选；另两路为组合方法对照 | Marble 提供世界生成和 mesh 导出；不拿仅视频输出替代 3D 交付 |
13
+ | 自然音 / SFX（看情况吧） | ElevenLabs Sound Effects v2 + Stable Audio 3.0 Large 商用 API | B4 Environment / Foley 子组 | 一个面向音效、一个通用音频基线；先用声音事件和环境音 pilot 验证，不跑成音乐任务 |
14
+ | 中文人物语音 | MiniMax Speech（优先验证 `speech-2.8-hd`）+ ElevenLabs TTS 的固定中文支持版本 | B4 Speech 子组 | 当前 38 条都是中文；固定说话人、情绪映射和完整台词 |
15
+ | CG | Seedance + MiniMax Hailuo（优先验证 `MiniMax-Hailuo-2.3`） | B3；T2V 与 I2V 分开 | 先跑两家即可，不急着加入第三家；按 API 的时长/分辨率能力冻结共同条件 |
16
+ | Motion | MoMask + Puppeteer 对比 LLM 直出；可再加 Meshy Text-to-Motion | 前两路是开放模型链 / 系统对照；Meshy 是 B5 商用 API 候选 | 先满足用户要的两路比较；若 B5 必须有闭源专用生成 API，再加第三路 |
17
+ | T-pose | 同一份冻结准备输入 | 不新增主表 | 两个动作方法共享角色输入，不把图像准备差异算成动作模型收益 |
18
+
19
+ 商用 API 不自动等于闭源模型。特别是 Hunyuan3D 必须登记云端实际版本，不能把本地
20
+ 开放权重版本包装成闭源行；MiniMax 的视频实验也要写清 Hailuo 的具体 ID，不能只写品牌。
21
+ MoMask、Puppeteer、WorldPlay、WorldMirror 的源码/模型发布可在官方仓库核对 [R1–R4]。
22
+ 上述 API 的能力入口见文末官方来源；账户权限和实际可用版本仍需 pilot 确认。
23
+
24
+ **规模建议**：B1 三家、CG 两家、音频按两种任务各两家；场景优先补 Marble，而不是
25
+ 为了凑三列加入不能导出场景的模型。B2 暂时只有一个确认能力范围的商用 direct 候选，
26
+ 如需至少两家闭源 direct API，仍须找到并实测第二家，不能用组合方法假充。
27
+
28
+ ## 2. 为什么按这些方法分组
29
+
30
+ 原方案 §1/§4 要求闭源专用生成 API、开放模型与多模型组合分开，首轮主表不混排。
31
+ 因此保留用户提出的系统比较，但不悄悄改掉主表含义：
32
+
33
+ - B1/B3/B4：按相同任务和输入条件比较商用服务，记录模型的权重开放状态。
34
+ - B2：Marble direct 与 WorldPlay + WorldMirror / LLM composition 分 panel 报告。
35
+ - B5：MoMask 生成人形动作，Puppeteer 在本项目链路中主要承担绑骨/蒙皮准备；
36
+ LLM 直出是另一条系统方法。不能把它们标为两个闭源 motion API。
37
+ - 如果研究问题改成“各种资产生成方法谁更适合游戏”，可以增加系统对照表，
38
+ 但需要显式修改协议，而不是沿用 `Closed-source method` 表头。
39
+
40
+ 为了隔离动作生成能力，建议先冻结一套人形骨架和白模，两路动作采用同一个映射、
41
+ retargeter、20 fps 和接触检查；角色网格、绑骨差异另在第三阶段端到端比较。
42
+ LLM 直出必须交付轨迹/骨骼动画文件，只有 Blender 脚本、文字或预览视频不算交付成功。
43
+
44
+ ## 3. 与当前优先清单对齐的阻塞项
45
+
46
+ ### 3D Object：低模与上下文能力
47
+
48
+ 现有 200 条保留低模 prompt，且 `decimation_target` 最高 8000。
49
+ 建议统一保存原始 API mesh 和固定后处理后的导入 mesh，分别报告；不要只给一家减面，
50
+ 也不要把减面后生成的新几何缺陷完全归给原始模型。
51
+
52
+ Hunyuan3D Pro 的普通模式中 `Prompt` 与图像输入互斥，不能假设 I2 能同时传游戏梗概。
53
+ 这类调用按原方案记为 `reference-only` 辅助组；T2 可以拼接冻结的短版梗概。
54
+ 其 3.0/3.1 的 LowPoly 支持不同，先确定使用的版本和后处理政策 [R5]。
55
+ 其他 I2 API 也逐一核对文本上下文能力，不能只在 judge 阶段补梗概。
56
+
57
+ 不要用 `latest` 当作冻结版本。Meshy 文档还提示其 `lowpoly` 模型类型将在
58
+ 2026-10-30 退役；现有清单的 `poly_policy: low_poly_priority` 只是实验政策，
59
+ 不等于必须调用这个即将退役的 API 类型 [R6]。
60
+
61
+ ### 3D Scene：交付要有真实场景
62
+
63
+ 69 条现有场景任���要求 `output_format: glb`。WorldPlay 的视频需经 WorldMirror 重建
64
+ 及场景导出后，才与场景任务对齐；只生成视频不能记 Delivery 成功。
65
+
66
+ Marble 的世界接口返回 splats 和 collider mesh，并另提供高质量带纹理 GLB 导出。
67
+ 建议正式 B2/第三阶段使用后者，保存碰撞网格和世界尺度信息；不要拿无外观的 collider
68
+ mesh 冒充完整美术场景，也不要把 splat 文件简单改后缀作为 GLB [R7]。
69
+ 生成和导出都计入耗时/成本；若导出不可用，保留该任务的未交付状态，不替换成全景图。
70
+
71
+ LLM composition 固定资产池、资产提供者、坐标系统、规划调用数和修补预算；
72
+ 若它额外调用对象生成器，费用和调用全部计入系统方法，不能只记 LLM 的 token 成本。
73
+
74
+ ### Audio：需要按声音任务选方法，不是一种模型跑全部
75
+
76
+ 当前非语音 706 条：623 条 `one_shot`、83 条 `ambient_loop`；语音 38 条，全部中文。
77
+ 这是分类字段统计；实际循环要求仍以每条任务的 `loop` / 生命周期字段为准。
78
+ 非语音时长为 0.15–45 秒，其中 93 条短于 0.5 秒、281 条短于 1 秒、19 条长于 30 秒。
79
+
80
+ ElevenLabs SFX API reference 写 0.5–30 秒，能力总览却写 0.1–30 秒，存在官方文档差异；
81
+ 开跑前应实测短音边界并保存实际请求/响应，不自行认定所有短音都支持 [R8, R9]。
82
+ Stable Audio 的 API 时长范围也应从具体 endpoint 核对。这里建议验证 3.0 Large 商用服务，
83
+ 而不是把已开放权重的 3.0 Medium / Small / Small SFX 当作闭源方法 [R10]。
84
+ 若账户仍使用 2.5 API，则固定并单列 2.5 版本，不混写成 3.0 的结果 [R16]。
85
+ 共同能力子集用于配对排名；其余任务仍留在第三阶段完整清单中，标注能力缺口。
86
+
87
+ 解码、重采样到要求的 48 kHz / 24 kHz 可采用同一确定性工具并保存原件。
88
+ 短音裁切、长音拼接/循环、生成式延长不是无代价格式转换：如要使用，须预先冻结规则，
89
+ 单列 pipeline 结果及成本，不能悄悄改任务时长来让 API 通过。
90
+
91
+ 语音不得把“游戏梗概 + 角色介绍”拼进需要念出的台词。检查 API 是否有独立的
92
+ instruction/style 通道；没有时仅可使用冻结的 voice/emotion 参数映射，单列标准 TTS
93
+ 条件，不宣称模型直接读取了梗概。MiniMax 的 TTS 参数和 ElevenLabs 版本入口见 [R11, R12]。
94
+
95
+ ### CG：现有任务与 reference-image 协议不一致
96
+
97
+ 194 条中 190 条 `text_to_video`、4 条 `image_to_video`，但当前全集和优先清单都没有
98
+ 参考图路径字段。不能用这批数据直接声称完成“194 条 reference-image-to-video”评测。
99
+
100
+ 建议明确选择：保留 T2V 子表、Q1 预声明 N/A；同时为 I2V 冻结真实的共同参考帧，
101
+ 补齐路径和来源后再运行 Q1。若要全部改成 I2V，应生成并冻结共享参考图，然后形成新的
102
+ 任务版本；不能各视频方法自行画图作为自己的参考。
103
+
104
+ 现有时长 4–12 秒、输出 1280×720/24 fps；Hailuo 2.3 文生接口的原生规格是
105
+ 768P 的 6/10 秒或 1080P 的 6 秒，不能把原 JSON 原样发出去 [R13]。
106
+ 先冻结共同能力 pilot 子集；非原生任务保留并标注，不隐式拉伸视频来满足事件时长。
107
+ Seedance 使用已接入的实际 model ID，先验证能力矩阵，不将品牌名当成版本。
108
+
109
+ ### Motion：保留非人形与短动作
110
+
111
+ 新增 78 条中，76 条人形、G040 一条 vehicle、G030 一条 mechanical。
112
+ 两个非人形任务必须保留用于第三阶段，不能因为 MoMask 主要面向人形就删去。
113
+ 按 rig group 单列，不支持时明确记录；需要 procedural 交付时另列方法，不冒充 MoMask 结果。
114
+
115
+ Meshy Text-to-Motion 的官方接口提供自然语言动作和 FBX/BVH，当前时长要求为
116
+ 2–10 秒且按 0.5 秒步长 [R14]。它适合补商用动作 API 对照，但不是现有所有短动作的
117
+ 无缝替换。LLM 直出也固定同一骨架、帧数和时长，不只比较好看的视频。
118
+
119
+ ## 4. 最小执行顺序
120
+
121
+ 1. 先为 13 个 L 级游戏准备第三阶段的全部既有资产任务；完整性与模型共同能力子集是两件事。
122
+ 2. 选 G003/G025/G040 等 3–5 个游戏做 pilot，覆盖中文语音、RTS 压力、机械/载具边界。
123
+ 每类先挑少量代表任务；这不缩减 L 级正式导入清单。
124
+ 3. 冻结游戏梗概、任务/参考输入、适用指标、API 版本、调用次数、超时重试和后处理。
125
+ 4. 报 Delivery、C、Q1/Q2/Q3、Coverage 和成本，按游戏宏平均；不挑 best-of，也不将
126
+ 未测能力缺口伪装成 API 生成失败。正式分母政策在开跑前固定。
127
+ 5. 第三阶段各 repair 方法共享同一冻结资产包。提前固定每类资产的交付来源，不能按
128
+ 单条 judge 最高分挑选，也不能悄悄用 LLM 补产物来遮盖某个生成方法的失败。
129
+ 若比较资产来源，另设因子并保持 repair 方法与预算一致。
130
+
131
+ ## 官方来源
132
+
133
+ - [R1: MoMask](https://github.com/EricGuo5513/momask-codes)
134
+ - [R2: Puppeteer](https://github.com/Seed3D/Puppeteer)
135
+ - [R3: HY-WorldPlay](https://github.com/Tencent-Hunyuan/HY-WorldPlay)
136
+ - [R4: HunyuanWorld-Mirror](https://github.com/Tencent-Hunyuan/HunyuanWorld-Mirror)
137
+ - [R5: Hunyuan3D Pro API](https://intl.cloud.tencent.com/ind/document/product/1284/75540)
138
+ - [R6: Meshy Text-to-3D](https://docs.meshy.ai/en/api/text-to-3d)
139
+ - [R7: World Labs World API](https://docs.worldlabs.ai/api)
140
+ - [R8: ElevenLabs Sound Effects API](https://elevenlabs.io/docs/api-reference/text-to-sound-effects/convert)
141
+ - [R9: ElevenLabs Sound Effects 能力总览](https://elevenlabs.io/docs/overview/capabilities/sound-effects)
142
+ - [R10: Stable Audio 模型及商用 API 入口](https://stability.ai/stable-audio)
143
+ - [R11: MiniMax TTS](https://platform.minimax.io/docs/api-reference/speech-t2a-http)
144
+ - [R12: ElevenLabs 模型](https://elevenlabs.io/docs/overview/models)
145
+ - [R13: MiniMax Hailuo T2V](https://platform.minimax.io/docs/api-reference/video-generation-t2v)
146
+ - [R14: Meshy Text-to-Motion](https://docs.meshy.ai/en/api/text-to-motion)
147
+ - [R15: Tripo 开发者入口](https://developers.tripo3d.ai/)
148
+ - [R16: Stable Audio 2.5 官方发布与 API 入口](https://stability.ai/news-updates/stability-ai-introduces-stable-audio-25-the-first-audio-model-built-for-enterprise-sound-production-at-scale)
149
+
150
+ Seedance 的本地封装 `GameFactory-3A/models/gen_cg_video/seedance_model.py` 已登记
151
+ model ID 和官方文档入口；本次网页抓取未能直接读取该火山引擎文档，因此不在本文
152
+ 宣称已核对其全部时长/分辨率规格，开跑前仍需 API pilot。
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt ADDED
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+ # G059_observatory_pinball / 3D_object requirement
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+
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+ Source of truth: ../general_requirement.txt
4
+
5
+ Frozen task inputs:
6
+ - star_pinball: Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures
7
+ - planet_target_bank: Brass pinball target bank of three domed planet medallions on a curved rail with lamp sockets, brass-and-starlight look, game-ready, PBR textures
8
+ - brass_flipper_pair: Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures
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+ "emission": "https://assets.meshy.ai/8f6e5ce2-d8d8-44a6-a7ed-c92b05e979af/tasks/01a1430c-2973-724b-8173-44c7aaf03d70/output/texture_0_emission.png?Expires=4945708800&Signature=WUiX7H8tcDD0hl85w5sVaYpCKzSbRUh0MK2DpvE1TyOrxgDenUQ~xN-Tl6KTlUQlw1F1YbQITtwBTmVOuBzcB6Osw1u~AyyM0lYmsuMD3tg5otNgBT~jxlVS7BFiHN4pEAwcEV9pJEQEUD5y9CvPT2g0~3Xi7IXf5WSHLYqeoS6C4DFpEV6g6u3gMhH1Ow3JJ0z~iMjFBUiZsHHvWKG15nZs5wXjHcY6QW9alIkEXn6BcpQnnT8uStvljdl6jcs6K~N9ouj94EZC8A1b1rYKOYCo7kzjmPOxy1GYuXq2TO-9s3Kzs8LmsdKfHn628lHw7MgJqpqkwzSx2YnQtp6~8w__&Key-Pair-Id=K1VGYTHIYLM9UM"
82
+ }
83
+ ],
84
+ "remove_lighting": true,
85
+ "consumed_credits": 10
86
+ }
87
+ }
88
+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/receipts/tripo/G059_observatory_pinball__G059_observatory_pinball_obj_001.json ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "submissions": {
3
+ "a45e06f23c2834c080b33f36edc70c52984d27a38f1807ceb81ff92cb1fd9b94": {
4
+ "endpoint": "/generation/text-to-model",
5
+ "reserved_credits": 30,
6
+ "status": "created",
7
+ "remote_id": "8f4c4879-b27c-4976-aff6-f03973daaadc",
8
+ "response": {
9
+ "code": 0,
10
+ "status": "success",
11
+ "data": {
12
+ "type": "text_to_model",
13
+ "status": "queued",
14
+ "task_id": "8f4c4879-b27c-4976-aff6-f03973daaadc"
15
+ }
16
+ },
17
+ "reported_credits": 30.0
18
+ }
19
+ },
20
+ "results": {
21
+ "/tasks/8f4c4879-b27c-4976-aff6-f03973daaadc": {
22
+ "code": 0,
23
+ "status": "success",
24
+ "data": {
25
+ "type": "text_to_model",
26
+ "status": "success",
27
+ "progress": 100,
28
+ "input": {
29
+ "pbr": true,
30
+ "prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Chrome-and-pearl pinball with tiny embedded star flecks, clean brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
31
+ "texture": true,
32
+ "export_uv": true,
33
+ "face_limit": 2000,
34
+ "model_seed": 1591,
35
+ "texture_seed": 1591,
36
+ "model_version": "v3.1-20260211",
37
+ "smart_low_poly": true,
38
+ "texture_quality": "standard",
39
+ "geometry_quality": "standard",
40
+ "texture_alignment": "geometry"
41
+ },
42
+ "output": {
43
+ "model_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/8f4c4879-b27c-4976-aff6-f03973daaadc/tripo_pbr_model_8f4c4879-b27c-4976-aff6-f03973daaadc.glb?auth_key=1792227786-wbcjytij-0-3932707c1fa3e91952d39ea67a10f6ef",
44
+ "rendered_image_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/8f4c4879-b27c-4976-aff6-f03973daaadc/legacy_mesh.webp?auth_key=1792227786-edcmnhdh-0-27653fddcbd59b6157390dabd360bbac",
45
+ "generated_image_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/8f4c4879-b27c-4976-aff6-f03973daaadc/text2image_8f4c4879-b27c-4976-aff6-f03973daaadc.jpeg?auth_key=1792227786-ltclvulc-0-e72d6842fdfc79ea42ce6d9448e47827"
46
+ },
47
+ "task_id": "8f4c4879-b27c-4976-aff6-f03973daaadc",
48
+ "created_at": "2026-10-16T09:00:20.498545Z",
49
+ "completed_at": "2026-10-16T09:03:05.572360Z",
50
+ "credits_consumed": 30.0
51
+ }
52
+ }
53
+ }
54
+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/receipts/tripo/G059_observatory_pinball__G059_observatory_pinball_obj_003.json ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "submissions": {
3
+ "8a9f6ede3e3ff56b6832800ee7e4e9ca29c66507980f5790b5faaba9246cbf0d": {
4
+ "endpoint": "/generation/text-to-model",
5
+ "reserved_credits": 30,
6
+ "status": "created",
7
+ "remote_id": "40acc76f-5e92-49d4-b329-c056ad36526a",
8
+ "response": {
9
+ "code": 0,
10
+ "status": "success",
11
+ "data": {
12
+ "type": "text_to_model",
13
+ "status": "queued",
14
+ "task_id": "40acc76f-5e92-49d4-b329-c056ad36526a"
15
+ }
16
+ },
17
+ "reported_credits": 30.0
18
+ }
19
+ },
20
+ "results": {
21
+ "/tasks/40acc76f-5e92-49d4-b329-c056ad36526a": {
22
+ "code": 0,
23
+ "status": "success",
24
+ "data": {
25
+ "type": "text_to_model",
26
+ "status": "success",
27
+ "progress": 100,
28
+ "input": {
29
+ "pbr": true,
30
+ "prompt": "Game context (excerpt): 微缩天文台的物理弹珠 | - W01 世界与时代背景：架空的黄铜天文时代；「星穹观测台」的老匠人把一生观测的星图搬进了一台弹珠机，让访客用弹珠「运行」他的星空。 | - S01 类型：单台物理弹珠街机。本测例包含的能力：冻结台面布局、三组机关链与倍率、多球状态与球标识、同帧出界合并结算、连续碰撞稳定、双档镜头、开场/多球/结算视频。\nAsset: Pair of brass-capped pinball flipper assemblies with pivot pins and spring mounts, brass-era look, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail",
31
+ "texture": true,
32
+ "export_uv": true,
33
+ "face_limit": 8000,
34
+ "model_seed": 1593,
35
+ "texture_seed": 1593,
36
+ "model_version": "v3.1-20260211",
37
+ "smart_low_poly": true,
38
+ "texture_quality": "standard",
39
+ "geometry_quality": "standard",
40
+ "texture_alignment": "geometry"
41
+ },
42
+ "output": {
43
+ "model_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/40acc76f-5e92-49d4-b329-c056ad36526a/tripo_pbr_model_40acc76f-5e92-49d4-b329-c056ad36526a.glb?auth_key=1792227876-ihoilxyu-0-e2724b55c6d80fa0d40f98dd60f03b48",
44
+ "rendered_image_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/40acc76f-5e92-49d4-b329-c056ad36526a/legacy_mesh.webp?auth_key=1792227876-nlclfhub-0-7f722db68037c533e07cd3b46ab8dacf",
45
+ "generated_image_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/40acc76f-5e92-49d4-b329-c056ad36526a/text2image_40acc76f-5e92-49d4-b329-c056ad36526a.jpeg?auth_key=1792227876-gdrqqewl-0-aa629a736a2b5e3fa21c12568062660d"
46
+ },
47
+ "task_id": "40acc76f-5e92-49d4-b329-c056ad36526a",
48
+ "created_at": "2026-10-16T09:00:28.805609Z",
49
+ "completed_at": "2026-10-16T09:04:31.449860Z",
50
+ "credits_consumed": 30.0
51
+ }
52
+ }
53
+ }
54
+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/cloud_api.py ADDED
@@ -0,0 +1,557 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ models/common/cloud_api.py
3
+
4
+ Shared plumbing for closed-source ("cloud API") model wrappers — the part of
5
+ Tripo / Meshy / Rodin / ElevenLabs / Kling wrappers that is identical no matter
6
+ what the provider generates.
7
+
8
+ Contract: `agent_skills/develop_harness/api_model_require.md` R9.
9
+ This module owns R9.6 (submit → poll → download behind a blocking call),
10
+ R9.7 (API key from the environment, at call time), R9.8 (response cache, so a
11
+ re-run is not re-billed) and R9.9 (retry with backoff, retryable vs. terminal).
12
+
13
+ It knows nothing about 3D, audio or video — only HTTP, money and failure modes.
14
+
15
+ Dependencies: stdlib at import time; `requests` is imported lazily on first use
16
+ so `test/harness/smoke.py` keeps working on a machine that does not have it.
17
+
18
+ Usage:
19
+ from models.common import cloud_api
20
+
21
+ key = cloud_api.require_api_key(None, "TRIPO_API_KEY",
22
+ "https://platform.tripo3d.ai/api-keys")
23
+ client = cloud_api.CloudAPIClient("https://openapi.tripo3d.ai/v3", key)
24
+ data = client.request("POST", "/generation/text-to-model", json={...})
25
+ """
26
+ from __future__ import annotations
27
+
28
+ import hashlib
29
+ import json
30
+ import logging
31
+ import os
32
+ import time
33
+ from pathlib import Path
34
+ from typing import Any, Callable, Iterable, Optional
35
+
36
+ logger = logging.getLogger(__name__)
37
+ logger.addHandler(logging.NullHandler())
38
+
39
+ #: HTTP statuses worth retrying — transient by nature.
40
+ RETRYABLE_STATUS: frozenset[int] = frozenset({408, 409, 425, 429, 500, 502, 503, 504})
41
+
42
+ #: HTTP statuses that will never succeed on retry: bad request, auth, quota.
43
+ TERMINAL_STATUS: frozenset[int] = frozenset({400, 401, 402, 403, 404, 405, 413, 415, 422})
44
+
45
+
46
+ # ── Errors ────────────────────────────────────────────────────────────────────
47
+
48
+
49
+ class CloudAPIError(RuntimeError):
50
+ """
51
+ Base class for every cloud-API failure.
52
+
53
+ Attributes:
54
+ status: HTTP status code, when the failure came from a response.
55
+ task_id: Provider task id, when one had already been created — keep it,
56
+ a timed-out task usually finishes anyway and can be fetched
57
+ later (`api_model_require.md` R9.6).
58
+ payload: Decoded response body, truncated for readability.
59
+ """
60
+
61
+ retryable = False
62
+
63
+ def __init__(self, message: str, *, status: Optional[int] = None,
64
+ task_id: Optional[str] = None, payload: Any = None):
65
+ super().__init__(message)
66
+ self.status = status
67
+ self.task_id = task_id
68
+ self.payload = payload
69
+
70
+
71
+ class CloudAPIAuthError(CloudAPIError):
72
+ """401 / 403 — the key is missing, wrong, or lacks the entitlement."""
73
+
74
+
75
+ class CloudAPIQuotaError(CloudAPIError):
76
+ """402 or a provider-specific "insufficient credits" body. Terminal."""
77
+
78
+
79
+ class CloudAPIRequestError(CloudAPIError):
80
+ """400 / 404 / 422 — the request itself is wrong. Terminal."""
81
+
82
+
83
+ class CloudAPIServerError(CloudAPIError):
84
+ """5xx and connection-level failures. Retryable."""
85
+
86
+ retryable = True
87
+
88
+
89
+ class CloudAPIRateLimitError(CloudAPIServerError):
90
+ """429 — retryable, honour `Retry-After` when present."""
91
+
92
+
93
+ class CloudTaskFailed(CloudAPIError):
94
+ """The provider accepted the task and then reported failure."""
95
+
96
+
97
+ class CloudTaskTimeout(CloudAPIError):
98
+ """The task did not reach a terminal state within `timeout` seconds."""
99
+
100
+
101
+ # ── Credentials ───────────────────────────────────────────────────────────────
102
+
103
+
104
+ def require_api_key(value: Optional[str], env_var: str, signup_url: str,
105
+ *, who: str = "This model") -> str:
106
+ """
107
+ Resolve an API key, failing fast with an actionable message (R1.6 / R9.7).
108
+
109
+ Args:
110
+ value: Explicit key passed to the constructor, or None.
111
+ env_var: Environment variable to fall back to.
112
+ signup_url: Where a human gets a key.
113
+ who: Name used in the error message.
114
+
115
+ Returns:
116
+ The key.
117
+
118
+ Raises:
119
+ CloudAPIAuthError: no key available.
120
+ """
121
+ key = value or os.environ.get(env_var)
122
+ if key:
123
+ return key.strip()
124
+ raise CloudAPIAuthError(
125
+ f"{who} needs an API key and none was found.\n"
126
+ f" 1. get one at {signup_url}\n"
127
+ f" 2. export {env_var}=<your key> # never commit it\n"
128
+ f" (or pass api_key=... to the constructor)"
129
+ )
130
+
131
+
132
+ def redact(key: Optional[str]) -> str:
133
+ """Key fingerprint safe to put in a log line or `meta.json`."""
134
+ if not key:
135
+ return "<unset>"
136
+ return f"{key[:4]}…{key[-2:]} (len {len(key)})"
137
+
138
+
139
+ # ── HTTP ───────���──────────────────────────────────────────────────────────────
140
+
141
+
142
+ def _requests():
143
+ """Import `requests` lazily with an actionable message (R1.5 / R1.6)."""
144
+ try:
145
+ import requests # noqa: PLC0415
146
+ except ImportError as e: # pragma: no cover - environment dependent
147
+ raise ImportError(
148
+ "Cloud-API model wrappers need the `requests` package:\n"
149
+ " bash scripts/asset_env_setup/cloud_api_install.sh\n"
150
+ " # or simply: python -m pip install requests\n"
151
+ "(only needed for the API backends; the local-weight models and "
152
+ "test/harness/smoke.py do not import it.)"
153
+ ) from e
154
+ return requests
155
+
156
+
157
+ def _truncate(payload: Any, limit: int = 600) -> Any:
158
+ text = payload if isinstance(payload, str) else json.dumps(payload, default=str)
159
+ return text if len(text) <= limit else text[:limit] + f"… (+{len(text) - limit} chars)"
160
+
161
+
162
+ def classify_http_error(status: int, body: Any, *,
163
+ task_id: Optional[str] = None) -> CloudAPIError:
164
+ """
165
+ Map an HTTP status onto the right exception class (R9.9).
166
+
167
+ The body is inspected too: providers happily answer 200/400 with a
168
+ "not enough credits" payload, which must not be retried.
169
+ """
170
+ text = _truncate(body)
171
+ low = str(text).lower()
172
+ # Providers phrase "you are out of money" in prose, and the status code alone
173
+ # does not distinguish it from a bad key: Tripo answers **403** with
174
+ # "You don't have enough credit to create this task". Matching the body first
175
+ # is what keeps "wrong key" and "no money" apart for the caller.
176
+ if any(s in low for s in ("insufficient", "enough credit", "enough credits",
177
+ "out of credit", "purchase more credit",
178
+ "quota exceeded", "no credits", "balance")):
179
+ return CloudAPIQuotaError(
180
+ f"HTTP {status}: out of credits — {text}", status=status,
181
+ task_id=task_id, payload=body)
182
+ if status in (401, 403):
183
+ return CloudAPIAuthError(
184
+ f"HTTP {status}: authentication rejected — {text}", status=status,
185
+ task_id=task_id, payload=body)
186
+ if status == 402:
187
+ return CloudAPIQuotaError(
188
+ f"HTTP {status}: payment required — {text}", status=status,
189
+ task_id=task_id, payload=body)
190
+ if status == 429:
191
+ return CloudAPIRateLimitError(
192
+ f"HTTP {status}: rate limited — {text}", status=status,
193
+ task_id=task_id, payload=body)
194
+ if status in TERMINAL_STATUS:
195
+ return CloudAPIRequestError(
196
+ f"HTTP {status}: request rejected — {text}", status=status,
197
+ task_id=task_id, payload=body)
198
+ if status in RETRYABLE_STATUS or status >= 500:
199
+ return CloudAPIServerError(
200
+ f"HTTP {status}: server error — {text}", status=status,
201
+ task_id=task_id, payload=body)
202
+ return CloudAPIError(
203
+ f"HTTP {status}: unexpected response — {text}", status=status,
204
+ task_id=task_id, payload=body)
205
+
206
+
207
+ class CloudAPIClient:
208
+ """
209
+ Thin retrying HTTP client for one provider.
210
+
211
+ Args:
212
+ base_url: Root of the API, without a trailing slash.
213
+ api_key: Bearer token.
214
+ timeout: Per-request socket timeout in seconds (not the task timeout).
215
+ max_retries: Extra attempts after the first one, for retryable failures.
216
+ backoff: Base of the exponential backoff, seconds.
217
+ auth_header: Header name / value template, for providers that do not
218
+ use `Authorization: Bearer <key>`.
219
+ user_agent: Sent as-is; helps providers attribute traffic.
220
+ """
221
+
222
+ def __init__(
223
+ self,
224
+ base_url: str,
225
+ api_key: str,
226
+ *,
227
+ timeout: int = 60,
228
+ max_retries: int = 3,
229
+ backoff: float = 1.5,
230
+ auth_header: str = "Authorization",
231
+ auth_template: str = "Bearer {key}",
232
+ user_agent: str = "3AGameFactory/0.1 (+https://github.com/OpenDCAI/GameFactory-3A)",
233
+ ):
234
+ self.base_url = base_url.rstrip("/")
235
+ self._api_key = api_key
236
+ self.timeout = timeout
237
+ self.max_retries = max_retries
238
+ self.backoff = backoff
239
+ self.auth_header = auth_header
240
+ self.auth_template = auth_template
241
+ self.user_agent = user_agent
242
+ self._session = None
243
+
244
+ # -- session ---------------------------------------------------------------
245
+
246
+ @property
247
+ def session(self):
248
+ """Lazily created `requests.Session` (kept alive across polls)."""
249
+ if self._session is None:
250
+ requests = _requests()
251
+ self._session = requests.Session()
252
+ self._session.headers.update({
253
+ self.auth_header: self.auth_template.format(key=self._api_key),
254
+ "User-Agent": self.user_agent,
255
+ })
256
+ return self._session
257
+
258
+ def close(self) -> None:
259
+ """Idempotent — safe after a failed construction and safe to call twice."""
260
+ if self._session is not None:
261
+ try:
262
+ self._session.close()
263
+ finally:
264
+ self._session = None
265
+
266
+ # -- requests --------------------------------------------------------------
267
+
268
+ def request(
269
+ self,
270
+ method: str,
271
+ path: str,
272
+ *,
273
+ json_body: Optional[dict] = None,
274
+ files: Optional[dict] = None,
275
+ data: Optional[dict] = None,
276
+ params: Optional[dict] = None,
277
+ expect_json: bool = True,
278
+ ) -> Any:
279
+ """
280
+ Perform one API call, retrying retryable failures (R9.9).
281
+
282
+ Args:
283
+ method: "GET" / "POST" / …
284
+ path: Path appended to `base_url`, or a full URL.
285
+ json_body: JSON payload.
286
+ files/data: multipart payload (`requests` semantics).
287
+ params: Query string.
288
+ expect_json: Parse the response as JSON; otherwise return `bytes`.
289
+
290
+ Returns:
291
+ Parsed JSON (dict / list) or raw `bytes`.
292
+
293
+ Raises:
294
+ CloudAPIError subclass — terminal errors immediately, retryable ones
295
+ after `max_retries` attempts.
296
+ """
297
+ requests = _requests()
298
+ url = path if path.startswith("http") else f"{self.base_url}/{path.lstrip('/')}"
299
+
300
+ last: Optional[CloudAPIError] = None
301
+ for attempt in range(self.max_retries + 1):
302
+ try:
303
+ resp = self.session.request(
304
+ method, url, json=json_body, files=files, data=data,
305
+ params=params, timeout=self.timeout,
306
+ )
307
+ except (requests.ConnectionError, requests.Timeout) as e:
308
+ last = CloudAPIServerError(f"{method} {url} failed at transport level: {e}")
309
+ else:
310
+ if resp.ok:
311
+ if not expect_json:
312
+ return resp.content
313
+ try:
314
+ return resp.json()
315
+ except ValueError as e:
316
+ raise CloudAPIError(
317
+ f"{method} {url} returned {resp.status_code} with a "
318
+ f"non-JSON body: {_truncate(resp.text)}"
319
+ ) from e
320
+ try:
321
+ body: Any = resp.json()
322
+ except ValueError:
323
+ body = resp.text
324
+ err = classify_http_error(resp.status_code, body)
325
+ if not err.retryable:
326
+ raise err
327
+ last = err
328
+ retry_after = resp.headers.get("Retry-After")
329
+ if retry_after:
330
+ try:
331
+ time.sleep(min(float(retry_after), 60.0))
332
+ except ValueError:
333
+ pass
334
+
335
+ if attempt < self.max_retries:
336
+ delay = self.backoff * (2 ** attempt)
337
+ logger.warning("[cloud_api] %s %s attempt %d/%d failed (%s); retrying in %.1fs",
338
+ method, url, attempt + 1, self.max_retries + 1, last, delay)
339
+ time.sleep(delay)
340
+
341
+ assert last is not None
342
+ raise last
343
+
344
+ def download(self, url: str, *, max_bytes: Optional[int] = None) -> bytes:
345
+ """
346
+ Fetch a generated artifact. Signed asset URLs are short-lived — call this
347
+ immediately after the task reports success.
348
+
349
+ Args:
350
+ url: Absolute URL from the task output.
351
+ max_bytes: Reject anything larger, so a wrong URL cannot fill a disk.
352
+
353
+ Returns:
354
+ The file content.
355
+ """
356
+ content = self.request("GET", url, expect_json=False)
357
+ if max_bytes is not None and len(content) > max_bytes:
358
+ raise CloudAPIError(
359
+ f"downloaded artifact is {len(content)} bytes, over the "
360
+ f"{max_bytes} byte limit: {url}")
361
+ if not content:
362
+ raise CloudAPIError(f"downloaded artifact is empty: {url}")
363
+ return content
364
+
365
+
366
+ # ── Polling ───────────────────────────────────────────────────────────────────
367
+
368
+
369
+ def poll_task(
370
+ fetch: Callable[[], dict],
371
+ *,
372
+ task_id: str,
373
+ timeout: float = 300.0,
374
+ poll_interval: float = 3.0,
375
+ done_states: Iterable[str],
376
+ failed_states: Iterable[str],
377
+ state_key: str = "status",
378
+ progress_key: str = "progress",
379
+ verbose: bool = False,
380
+ ) -> dict:
381
+ """
382
+ Block until a provider task reaches a terminal state (R9.6).
383
+
384
+ Args:
385
+ fetch: Callable returning the decoded task object.
386
+ task_id: Only used for messages — every error carries it.
387
+ timeout: Wall-clock budget in seconds.
388
+ poll_interval: Seconds between polls.
389
+ done_states: States meaning success (compared case-insensitively).
390
+ failed_states: States meaning failure.
391
+ state_key: Field holding the state.
392
+ progress_key: Field holding 0-100 progress, when the provider sends one.
393
+ verbose: Print progress; otherwise only DEBUG logs (R3.7).
394
+
395
+ Returns:
396
+ The task object in its successful terminal state.
397
+
398
+ Raises:
399
+ CloudTaskFailed: provider reported failure.
400
+ CloudTaskTimeout: budget exhausted; the task may still finish server-side,
401
+ the error carries `task_id` so it can be fetched later.
402
+ """
403
+ done = {s.lower() for s in done_states}
404
+ failed = {s.lower() for s in failed_states}
405
+ deadline = time.time() + timeout
406
+ last_progress = -1
407
+
408
+ while True:
409
+ task = fetch()
410
+ state = str(task.get(state_key, "")).lower()
411
+ progress = task.get(progress_key)
412
+
413
+ if progress != last_progress:
414
+ last_progress = progress
415
+ logger.debug("[cloud_api] task %s: %s (%s%%)", task_id, state, progress)
416
+ if verbose:
417
+ print(f"[cloud_api] task {task_id}: {state} ({progress}%)")
418
+
419
+ if state in done:
420
+ return task
421
+ if state in failed:
422
+ raise CloudTaskFailed(
423
+ f"task {task_id} ended as {state!r}: {_truncate(task)}",
424
+ task_id=task_id, payload=task)
425
+
426
+ remaining = deadline - time.time()
427
+ if remaining <= 0:
428
+ raise CloudTaskTimeout(
429
+ f"task {task_id} still {state!r} after {timeout:.0f}s. It may still "
430
+ f"finish server-side — query it with the task id above, or raise "
431
+ f"`timeout=` on the model.",
432
+ task_id=task_id, payload=task)
433
+ time.sleep(min(poll_interval, remaining))
434
+
435
+
436
+ # ── Response cache ────────────────────────────────────────────────────────────
437
+
438
+
439
+ def request_hash(payload: dict) -> str:
440
+ """
441
+ Stable sha256 over a request description (R9.8).
442
+
443
+ The payload must contain everything that changes the output — model version,
444
+ prompt, image bytes hash, every generation parameter, the output format.
445
+ Never put the API key in it.
446
+ """
447
+ canonical = json.dumps(payload, sort_keys=True, ensure_ascii=False, default=str)
448
+ return hashlib.sha256(canonical.encode("utf-8")).hexdigest()
449
+
450
+
451
+ def bytes_hash(data: bytes) -> str:
452
+ """sha256 of a binary input, e.g. the reference image."""
453
+ return hashlib.sha256(data).hexdigest()
454
+
455
+
456
+ class ResponseCache:
457
+ """
458
+ Content-addressed cache of generated artifacts.
459
+
460
+ A cloud call costs credits, so an identical request must never be sent twice
461
+ (R9.8). Layout::
462
+
463
+ <cache_dir>/<provider>/<hash>.<ext> the artifact
464
+ <cache_dir>/<provider>/<hash>.meta.json request description + task id
465
+
466
+ Args:
467
+ cache_dir: Root directory. `None` disables caching entirely.
468
+ provider: Sub-directory name, so two providers never collide.
469
+ """
470
+
471
+ def __init__(self, cache_dir: Optional[str | Path], provider: str):
472
+ self.root = Path(cache_dir).expanduser() / provider if cache_dir else None
473
+ self.provider = provider
474
+
475
+ @property
476
+ def enabled(self) -> bool:
477
+ return self.root is not None
478
+
479
+ def _paths(self, key: str, ext: str) -> tuple[Path, Path]:
480
+ assert self.root is not None
481
+ return self.root / f"{key}.{ext}", self.root / f"{key}.meta.json"
482
+
483
+ def get(self, key: str, ext: str = "glb") -> Optional[bytes]:
484
+ """Cached artifact bytes, or None. Performs no network I/O, ever."""
485
+ if not self.enabled:
486
+ return None
487
+ blob, _ = self._paths(key, ext)
488
+ if blob.is_file() and blob.stat().st_size > 0:
489
+ logger.info("[cloud_api] cache hit (%s): %s", self.provider, blob.name)
490
+ return blob.read_bytes()
491
+ return None
492
+
493
+ def put(self, key: str, data: bytes, meta: dict, ext: str = "glb") -> Path:
494
+ """Store an artifact plus the request that produced it. Returns its path."""
495
+ if not self.enabled:
496
+ return Path()
497
+ blob, meta_path = self._paths(key, ext)
498
+ blob.parent.mkdir(parents=True, exist_ok=True)
499
+ blob.write_bytes(data)
500
+ meta_path.write_text(
501
+ json.dumps({**meta, "cache_key": key, "bytes": len(data)},
502
+ indent=2, ensure_ascii=False, default=str),
503
+ encoding="utf-8",
504
+ )
505
+ return blob
506
+
507
+
508
+ # ── Input encoding ────────────────────────────────────────────────────────────
509
+
510
+
511
+ def image_to_png_bytes(image: Any) -> bytes:
512
+ """
513
+ Normalize an image input to PNG bytes.
514
+
515
+ Accepts a `PIL.Image.Image`, raw `bytes` (returned unchanged), or a
516
+ `np.ndarray`. Paths are rejected on purpose — `model_require.md` R3.2 says a
517
+ model takes the object, not a path.
518
+
519
+ Returns:
520
+ PNG-encoded bytes (RGBA preserved when present).
521
+ """
522
+ if isinstance(image, (bytes, bytearray)):
523
+ return bytes(image)
524
+ if isinstance(image, (str, Path)):
525
+ raise TypeError(
526
+ "models take an image object, not a path (model_require.md R3.2). "
527
+ "Open it in the operator: Image.open(path).convert('RGBA')"
528
+ )
529
+
530
+ from io import BytesIO # noqa: PLC0415
531
+
532
+ from PIL import Image as PILImage # noqa: PLC0415
533
+
534
+ if not isinstance(image, PILImage.Image):
535
+ try:
536
+ import numpy as np # noqa: PLC0415
537
+ except ImportError:
538
+ np = None # type: ignore[assignment]
539
+ if np is not None and isinstance(image, np.ndarray):
540
+ image = PILImage.fromarray(image)
541
+ else:
542
+ raise TypeError(
543
+ f"unsupported image type {type(image).__name__}; expected "
544
+ f"PIL.Image.Image, numpy.ndarray or bytes"
545
+ )
546
+
547
+ buf = BytesIO()
548
+ image.save(buf, format="PNG")
549
+ return buf.getvalue()
550
+
551
+
552
+ def image_to_data_uri(image: Any, mime: str = "image/png") -> str:
553
+ """PNG data URI (`data:image/png;base64,…`) for providers that take one inline."""
554
+ import base64 # noqa: PLC0415
555
+
556
+ payload = base64.b64encode(image_to_png_bytes(image)).decode("ascii")
557
+ return f"data:{mime};base64,{payload}"
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/glb_utils.py ADDED
@@ -0,0 +1,578 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ models/common/glb_utils.py
3
+
4
+ Dependency-free inspection of binary glTF (`.glb`) buffers.
5
+
6
+ Why this exists instead of `trimesh.load(...)`: the API wrappers must report the
7
+ triangle count of what they just paid for (`api_model_require.md` R9.8), and
8
+ that number has to be available on a CPU-only box with nothing but the stdlib
9
+ installed. Parsing the JSON chunk of a GLB is enough for counting.
10
+
11
+ `glb_summary` and `glb_triangle_count` read the JSON chunk only. `read_glb_mesh`
12
+ decodes vertex data as well, because a generated part has to be *composed* with
13
+ primitives rather than merely counted, and that needs its triangles in the same
14
+ coordinate frame as everything else.
15
+
16
+ Usage:
17
+ from models.common.glb_utils import glb_summary, read_glb_mesh
18
+ info = glb_summary(open("model.glb", "rb").read())
19
+ print(info["triangles"], info["materials"])
20
+
21
+ mesh = read_glb_mesh(open("part.glb", "rb").read())
22
+ print(len(mesh["positions"]), mesh["low"], mesh["high"])
23
+ """
24
+ from __future__ import annotations
25
+
26
+ import json
27
+ import math
28
+ import struct
29
+ from typing import Any, Optional, Sequence
30
+
31
+ GLB_MAGIC = b"glTF"
32
+
33
+ #: glTF primitive mode 4 == TRIANGLES. Only triangle primitives are counted.
34
+ _MODE_TRIANGLES = 4
35
+
36
+ #: glTF componentType -> (struct format, byte size). Indices are allowed to be
37
+ #: any of the unsigned types; positions are float in every file worth reading.
38
+ _COMPONENT_TYPES: dict[int, tuple[str, int]] = {
39
+ 5120: ("b", 1), # BYTE
40
+ 5121: ("B", 1), # UNSIGNED_BYTE
41
+ 5122: ("h", 2), # SHORT
42
+ 5123: ("H", 2), # UNSIGNED_SHORT
43
+ 5125: ("I", 4), # UNSIGNED_INT
44
+ 5126: ("f", 4), # FLOAT
45
+ }
46
+
47
+ #: glTF accessor type -> component count.
48
+ _TYPE_COUNTS: dict[str, int] = {
49
+ "SCALAR": 1, "VEC2": 2, "VEC3": 3, "VEC4": 4,
50
+ "MAT2": 4, "MAT3": 9, "MAT4": 16,
51
+ }
52
+
53
+
54
+ class GLBParseError(ValueError):
55
+ """The buffer is not a GLB we can read."""
56
+
57
+
58
+ def is_glb(data: bytes) -> bool:
59
+ """True when `data` starts with the 12-byte GLB header."""
60
+ return len(data) >= 12 and data[:4] == GLB_MAGIC
61
+
62
+
63
+ def glb_json_chunk(data: bytes) -> dict[str, Any]:
64
+ """
65
+ Return the parsed JSON chunk of a GLB.
66
+
67
+ Args:
68
+ data: Whole `.glb` file content.
69
+
70
+ Returns:
71
+ The glTF document as a dict.
72
+
73
+ Raises:
74
+ GLBParseError: bad magic, truncated file, or a missing JSON chunk.
75
+ """
76
+ if not is_glb(data):
77
+ raise GLBParseError(
78
+ f"not a GLB: expected magic {GLB_MAGIC!r}, got {data[:4]!r}"
79
+ )
80
+ if len(data) < 20:
81
+ raise GLBParseError(f"GLB truncated: {len(data)} bytes")
82
+
83
+ _magic, version, total_len = struct.unpack_from("<4sII", data, 0)
84
+ if total_len > len(data):
85
+ raise GLBParseError(
86
+ f"GLB header claims {total_len} bytes, buffer holds {len(data)}"
87
+ )
88
+
89
+ offset = 12
90
+ while offset + 8 <= len(data):
91
+ chunk_len, chunk_type = struct.unpack_from("<I4s", data, offset)
92
+ offset += 8
93
+ chunk = data[offset:offset + chunk_len]
94
+ offset += chunk_len
95
+ if chunk_type == b"JSON":
96
+ try:
97
+ return json.loads(chunk.decode("utf-8"))
98
+ except (UnicodeDecodeError, json.JSONDecodeError) as e:
99
+ raise GLBParseError(f"GLB JSON chunk is not valid JSON: {e}") from e
100
+ raise GLBParseError(f"GLB (version {version}) has no JSON chunk")
101
+
102
+
103
+ def glb_triangle_count(data: bytes) -> Optional[int]:
104
+ """
105
+ Triangle count of a GLB, or None when it cannot be determined.
106
+
107
+ Counts every triangle-mode primitive of every mesh once, i.e. the *asset's*
108
+ triangle budget, not the per-instance count after node duplication.
109
+
110
+ Returns:
111
+ int triangles, or None if the JSON chunk is unreadable.
112
+ """
113
+ try:
114
+ doc = glb_json_chunk(data)
115
+ except GLBParseError:
116
+ return None
117
+
118
+ accessors = doc.get("accessors", [])
119
+ total = 0
120
+ for mesh in doc.get("meshes", []):
121
+ for prim in mesh.get("primitives", []):
122
+ if prim.get("mode", _MODE_TRIANGLES) != _MODE_TRIANGLES:
123
+ continue
124
+ idx = prim.get("indices")
125
+ if idx is not None and idx < len(accessors):
126
+ count = accessors[idx].get("count", 0)
127
+ else:
128
+ pos = prim.get("attributes", {}).get("POSITION")
129
+ count = accessors[pos].get("count", 0) if pos is not None and pos < len(accessors) else 0
130
+ total += count // 3
131
+ return total
132
+
133
+
134
+ def glb_summary(data: bytes) -> dict[str, Any]:
135
+ """
136
+ Cheap description of a GLB, for logs and `meta.json`.
137
+
138
+ Returns:
139
+ dict with keys:
140
+ bytes (int) — buffer size
141
+ triangles (int | None) — see `glb_triangle_count`
142
+ meshes, materials, textures, images, nodes (int)
143
+ generator (str | None) — glTF `asset.generator`
144
+ error (str) — present only when the JSON chunk is unreadable
145
+ """
146
+ out: dict[str, Any] = {"bytes": len(data)}
147
+ try:
148
+ doc = glb_json_chunk(data)
149
+ except GLBParseError as e:
150
+ out.update({"triangles": None, "error": str(e)})
151
+ return out
152
+
153
+ out.update({
154
+ "triangles": glb_triangle_count(data),
155
+ "meshes": len(doc.get("meshes", [])),
156
+ "materials": len(doc.get("materials", [])),
157
+ "textures": len(doc.get("textures", [])),
158
+ "images": len(doc.get("images", [])),
159
+ "nodes": len(doc.get("nodes", [])),
160
+ "generator": (doc.get("asset") or {}).get("generator"),
161
+ })
162
+ return out
163
+
164
+
165
+ # --------------------------------------------------------------------------
166
+ # Vertex decoding
167
+ #
168
+ # Needed to *compose* a generated part with primitives, as opposed to merely
169
+ # reporting on it: composition means putting its triangles into the same
170
+ # coordinate frame as the rest, and that requires reading them.
171
+ # --------------------------------------------------------------------------
172
+
173
+
174
+ def glb_binary_chunk(data: bytes) -> bytes:
175
+ """Return the BIN chunk of a GLB, or b"" when there is none."""
176
+ if not is_glb(data):
177
+ raise GLBParseError(f"not a GLB: got magic {data[:4]!r}")
178
+ offset = 12
179
+ while offset + 8 <= len(data):
180
+ chunk_len, chunk_type = struct.unpack_from("<I4s", data, offset)
181
+ offset += 8
182
+ if chunk_type == b"BIN\x00":
183
+ return data[offset:offset + chunk_len]
184
+ offset += chunk_len
185
+ return b""
186
+
187
+
188
+ def _read_accessor(doc: dict[str, Any], binary: bytes, index: int) -> list[tuple]:
189
+ """Decode one accessor into a list of component tuples.
190
+
191
+ Honours ``byteStride``. Interleaved buffers are normal out of an
192
+ exporter, and reading one as tightly packed yields positions that are a
193
+ silent mixture of coordinates and normals — it parses, it renders, it is
194
+ garbage.
195
+ """
196
+
197
+ accessor = doc["accessors"][index]
198
+ component_type = accessor["componentType"]
199
+ if component_type not in _COMPONENT_TYPES:
200
+ raise GLBParseError(f"unsupported componentType {component_type}")
201
+ fmt, component_size = _COMPONENT_TYPES[component_type]
202
+ per_element = _TYPE_COUNTS[accessor["type"]]
203
+ count = accessor["count"]
204
+
205
+ view_index = accessor.get("bufferView")
206
+ if view_index is None:
207
+ # A sparse or zero-filled accessor. Legal, and not something a mesh
208
+ # we are about to weld into another asset should be relying on.
209
+ return [tuple([0] * per_element)] * count
210
+
211
+ view = doc["bufferViews"][view_index]
212
+ if view.get("buffer", 0) != 0:
213
+ raise GLBParseError("only single-buffer GLBs are supported")
214
+ base = view.get("byteOffset", 0) + accessor.get("byteOffset", 0)
215
+ packed = component_size * per_element
216
+ stride = view.get("byteStride") or packed
217
+
218
+ out: list[tuple] = []
219
+ element_format = "<" + fmt * per_element
220
+ for element in range(count):
221
+ start = base + element * stride
222
+ if start + packed > len(binary):
223
+ raise GLBParseError(
224
+ f"accessor {index} reads past the {len(binary)}-byte buffer"
225
+ )
226
+ out.append(struct.unpack_from(element_format, binary, start))
227
+ return out
228
+
229
+
230
+ def _node_matrix(node: dict[str, Any]) -> list[float]:
231
+ """A node's local transform as a 16-float column-major matrix.
232
+
233
+ Handles both an explicit ``matrix`` and a TRS triple, since a file may use
234
+ either. Ignoring the transform looks like a modelling error: a mesh
235
+ authored Z-up whose node carries the -90 that stands it upright arrives on
236
+ its side, and the natural reaction is to rotate it back in the spec —
237
+ hard-coding a correction for something the file already stated.
238
+ """
239
+
240
+ if "matrix" in node:
241
+ return [float(value) for value in node["matrix"]]
242
+
243
+ tx, ty, tz = [float(value) for value in node.get("translation", (0, 0, 0))]
244
+ qx, qy, qz, qw = [float(value) for value in node.get("rotation", (0, 0, 0, 1))]
245
+ sx, sy, sz = [float(value) for value in node.get("scale", (1, 1, 1))]
246
+
247
+ # Quaternion to rotation matrix.
248
+ xx, yy, zz = qx * qx, qy * qy, qz * qz
249
+ xy, xz, yz = qx * qy, qx * qz, qy * qz
250
+ wx, wy, wz = qw * qx, qw * qy, qw * qz
251
+ rotation = (
252
+ (1 - 2 * (yy + zz), 2 * (xy + wz), 2 * (xz - wy)),
253
+ (2 * (xy - wz), 1 - 2 * (xx + zz), 2 * (yz + wx)),
254
+ (2 * (xz + wy), 2 * (yz - wx), 1 - 2 * (xx + yy)),
255
+ )
256
+ scale = (sx, sy, sz)
257
+ return [
258
+ rotation[0][0] * scale[0], rotation[0][1] * scale[0], rotation[0][2] * scale[0], 0.0,
259
+ rotation[1][0] * scale[1], rotation[1][1] * scale[1], rotation[1][2] * scale[1], 0.0,
260
+ rotation[2][0] * scale[2], rotation[2][1] * scale[2], rotation[2][2] * scale[2], 0.0,
261
+ tx, ty, tz, 1.0,
262
+ ]
263
+
264
+
265
+ def _multiply(a: Sequence[float], b: Sequence[float]) -> list[float]:
266
+ """Column-major 4x4 product, applying `b` then `a`."""
267
+ out = [0.0] * 16
268
+ for column in range(4):
269
+ for row in range(4):
270
+ out[column * 4 + row] = sum(
271
+ a[k * 4 + row] * b[column * 4 + k] for k in range(4)
272
+ )
273
+ return out
274
+
275
+
276
+ _IDENTITY = [1.0, 0, 0, 0, 0, 1.0, 0, 0, 0, 0, 1.0, 0, 0, 0, 0, 1.0]
277
+
278
+
279
+ def read_glb_mesh(data: bytes) -> dict[str, Any]:
280
+ """Decode every triangle of a GLB into one flat, world-space mesh.
281
+
282
+ Walks the scene graph and applies each node's accumulated transform, so
283
+ the result is in the file's own world coordinates rather than in the
284
+ local frame of whichever mesh happened to be first.
285
+
286
+ The node hierarchy is deliberately *not* preserved. A part fetched from
287
+ a generator is one object as far as the composition is concerned — the
288
+ thing worth keeping addressable is the spec's part id, which the writer
289
+ attaches, and a generator's internal node names ("mesh_0", "Object_2")
290
+ are not names anything downstream can use.
291
+
292
+ Returns:
293
+ dict with ``positions`` and ``normals`` as lists of 3-tuples,
294
+ ``uvs`` as 2-tuples, ``indices`` as a flat list, ``low``/``high`` as
295
+ the axis-aligned bounds, and ``images`` / ``material_runs`` carrying
296
+ whatever textures the file brought with it. Normals are generated
297
+ per-face when the file omits them.
298
+
299
+ Textures come across because a generated part's whole contribution is
300
+ surface. Dropping them and letting the part inherit the spec's flat PBR
301
+ factors is consistent but throws away the thing that was paid for: the
302
+ stippling on a grip, the panel creases and decals on a car shell. That
303
+ needs three things travelling together — UVs per vertex, the image
304
+ bytes, and which triangles use which image — so ``material_runs``
305
+ records index ranges rather than a single material for the part.
306
+ """
307
+
308
+ doc = glb_json_chunk(data)
309
+ binary = glb_binary_chunk(data)
310
+ if not binary:
311
+ raise GLBParseError(
312
+ "the GLB has no BIN chunk, so its vertex data is external; "
313
+ "only self-contained GLBs can be composed"
314
+ )
315
+
316
+ positions: list[tuple[float, float, float]] = []
317
+ normals: list[tuple[float, float, float]] = []
318
+ uvs: list[tuple[float, float]] = []
319
+ indices: list[int] = []
320
+ material_runs: list[dict[str, Any]] = []
321
+
322
+ def add_mesh(mesh_index: int, matrix: Sequence[float]) -> None:
323
+ # The inverse transpose of the upper 3x3, for the normals. A non-uniform
324
+ # node scale makes the forward matrix wrong for them, and the symptom is
325
+ # lighting that reads as a modelling error rather than as a bad import.
326
+ normal_matrix = _inverse_transpose_3x3(matrix)
327
+
328
+ for primitive in doc["meshes"][mesh_index].get("primitives", []):
329
+ if primitive.get("mode", _MODE_TRIANGLES) != _MODE_TRIANGLES:
330
+ continue
331
+ attributes = primitive.get("attributes", {})
332
+ if "POSITION" not in attributes:
333
+ continue
334
+
335
+ local = _read_accessor(doc, binary, attributes["POSITION"])
336
+ base = len(positions)
337
+ for x, y, z in local:
338
+ positions.append((
339
+ matrix[0] * x + matrix[4] * y + matrix[8] * z + matrix[12],
340
+ matrix[1] * x + matrix[5] * y + matrix[9] * z + matrix[13],
341
+ matrix[2] * x + matrix[6] * y + matrix[10] * z + matrix[14],
342
+ ))
343
+
344
+ if "NORMAL" in attributes:
345
+ for nx, ny, nz in _read_accessor(doc, binary, attributes["NORMAL"]):
346
+ tx = normal_matrix[0] * nx + normal_matrix[3] * ny + normal_matrix[6] * nz
347
+ ty = normal_matrix[1] * nx + normal_matrix[4] * ny + normal_matrix[7] * nz
348
+ tz = normal_matrix[2] * nx + normal_matrix[5] * ny + normal_matrix[8] * nz
349
+ length = math.sqrt(tx * tx + ty * ty + tz * tz) or 1.0
350
+ normals.append((tx / length, ty / length, tz / length))
351
+ else:
352
+ normals.extend([(0.0, 0.0, 0.0)] * len(local))
353
+
354
+ # UVs are per-vertex and must stay aligned with positions, so a
355
+ # primitive without them still contributes placeholders — a short
356
+ # UV list would silently shift every following part's texturing.
357
+ if "TEXCOORD_0" in attributes:
358
+ uvs.extend(
359
+ (float(u), float(v))
360
+ for u, v in _read_accessor(doc, binary, attributes["TEXCOORD_0"])
361
+ )
362
+ else:
363
+ uvs.extend([(0.0, 0.0)] * len(local))
364
+
365
+ if "indices" in primitive and primitive["indices"] is not None:
366
+ local_indices = [
367
+ value[0] for value in
368
+ _read_accessor(doc, binary, primitive["indices"])
369
+ ]
370
+ else:
371
+ local_indices = list(range(len(local)))
372
+
373
+ run_start = len(indices)
374
+ indices.extend(base + value for value in local_indices)
375
+ material_runs.append({
376
+ "start": run_start,
377
+ "count": len(local_indices),
378
+ "material": primitive.get("material"),
379
+ })
380
+
381
+ def walk(node_index: int, parent: Sequence[float]) -> None:
382
+ node = doc["nodes"][node_index]
383
+ matrix = _multiply(parent, _node_matrix(node))
384
+ if node.get("mesh") is not None:
385
+ add_mesh(node["mesh"], matrix)
386
+ for child in node.get("children", ()):
387
+ walk(child, matrix)
388
+
389
+ scenes = doc.get("scenes") or []
390
+ scene = scenes[doc.get("scene", 0)] if scenes else None
391
+ roots = scene.get("nodes", ()) if scene else range(len(doc.get("nodes", [])))
392
+ for root in roots:
393
+ walk(root, _IDENTITY)
394
+
395
+ if not positions:
396
+ raise GLBParseError("the GLB contains no triangle geometry")
397
+
398
+ # Fill in any face normals the file left out, so a consumer never has to
399
+ # ask whether normals are present.
400
+ _fill_missing_normals(positions, normals, indices)
401
+
402
+ low = tuple(min(point[axis] for point in positions) for axis in range(3))
403
+ high = tuple(max(point[axis] for point in positions) for axis in range(3))
404
+ return {
405
+ "positions": positions,
406
+ "normals": normals,
407
+ "uvs": uvs,
408
+ "indices": indices,
409
+ "triangles": len(indices) // 3,
410
+ "low": low,
411
+ "high": high,
412
+ "material_runs": material_runs,
413
+ "materials": _read_materials(doc, binary),
414
+ "has_uvs": any(u != 0.0 or v != 0.0 for u, v in uvs),
415
+ }
416
+
417
+
418
+ def _read_materials(doc: dict[str, Any], binary: bytes) -> list[dict[str, Any]]:
419
+ """Each material's PBR factors, its base-colour image and its MR image.
420
+
421
+ Base colour and metallic-roughness. Not the normal or occlusion maps:
422
+ those would give the composed asset a texture set the primitives beside it
423
+ lack, and a car body with a normal map next to a flat-shaded spoiler reads
424
+ as two assets. Metallic-roughness is different in kind — it is not detail
425
+ on top of a surface, it is *which surface it is*.
426
+
427
+ Taking the map is what makes the factors trustworthy. An exporter that puts
428
+ those channels in a texture leaves the factors at glTF's default ``1.0`` to
429
+ multiply it, so the two only mean anything together. This function used to
430
+ take the colour alone and substitute dielectric defaults (``0.0``/``0.55``)
431
+ on the grounds that inherited factors would render a polymer grip as
432
+ sandblasted steel — true, but it threw away the answer to keep from
433
+ guessing wrong. Plate armour came out as grey plastic: every generated
434
+ piece of the knight had ``metallicFactor 1.0`` and an MR map in the file,
435
+ and both were discarded.
436
+
437
+ ``factors_from`` is still recorded, because a material with no map at all
438
+ still has to fall back and a caller needs to know which happened.
439
+ """
440
+
441
+ out: list[dict[str, Any]] = []
442
+ images = doc.get("images", [])
443
+ textures = doc.get("textures", [])
444
+ views = doc.get("bufferViews", [])
445
+
446
+ def image_bytes(reference: dict[str, Any]) -> tuple[bytes | None, str | None]:
447
+ index = reference.get("index")
448
+ if index is None or index >= len(textures):
449
+ return None, None
450
+ image_index = textures[index].get("source")
451
+ if image_index is None or image_index >= len(images):
452
+ return None, None
453
+ image = images[image_index]
454
+ view_index = image.get("bufferView")
455
+ if view_index is not None and view_index < len(views):
456
+ view = views[view_index]
457
+ start = view.get("byteOffset", 0)
458
+ return (
459
+ bytes(binary[start:start + view["byteLength"]]),
460
+ image.get("mimeType") or "image/png",
461
+ )
462
+ if str(image.get("uri", "")).startswith("data:"):
463
+ # A data URI is legal and some exporters emit one even in a GLB.
464
+ # Decoded here so the caller never has to care which form was used.
465
+ import base64
466
+
467
+ header, _, payload = image["uri"].partition(",")
468
+ return (
469
+ base64.b64decode(payload),
470
+ header.split(":")[1].split(";")[0] if ":" in header
471
+ else "image/png",
472
+ )
473
+ return None, None
474
+
475
+ for material in doc.get("materials", []):
476
+ pbr = material.get("pbrMetallicRoughness") or {}
477
+ colour_image, colour_mime = image_bytes(pbr.get("baseColorTexture") or {})
478
+ mr_image, mr_mime = image_bytes(
479
+ pbr.get("metallicRoughnessTexture") or {})
480
+
481
+ if mr_image is not None:
482
+ # The map is coming with us, so the factors mean what they say:
483
+ # they scale it. glTF's default is 1.0 for exactly this case.
484
+ metallic = float(pbr.get("metallicFactor", 1.0))
485
+ roughness = float(pbr.get("roughnessFactor", 1.0))
486
+ provenance = "file"
487
+ elif (pbr.get("metallicRoughnessTexture") or {}).get("index") is not None:
488
+ # A map is declared but its bytes could not be read. Falling back
489
+ # to dielectric defaults, because inheriting factors written to
490
+ # scale a map we do not have renders a polymer grip as steel.
491
+ metallic, roughness, provenance = 0.0, 0.55, "assumed"
492
+ else:
493
+ metallic = float(pbr.get("metallicFactor", 1.0))
494
+ roughness = float(pbr.get("roughnessFactor", 1.0))
495
+ provenance = "file"
496
+
497
+ out.append({
498
+ "name": material.get("name") or "",
499
+ "baseColor": [
500
+ float(value)
501
+ for value in pbr.get("baseColorFactor", [1.0, 1.0, 1.0, 1.0])
502
+ ],
503
+ "metallic": metallic,
504
+ "roughness": roughness,
505
+ "factors_from": provenance,
506
+ "image": colour_image,
507
+ "mimeType": colour_mime,
508
+ "mrImage": mr_image,
509
+ "mrMimeType": mr_mime,
510
+ })
511
+ return out
512
+
513
+
514
+ def _inverse_transpose_3x3(matrix: Sequence[float]) -> list[float]:
515
+ """Inverse transpose of a column-major 4x4's rotation/scale block."""
516
+ a = (matrix[0], matrix[1], matrix[2])
517
+ b = (matrix[4], matrix[5], matrix[6])
518
+ c = (matrix[8], matrix[9], matrix[10])
519
+ determinant = (
520
+ a[0] * (b[1] * c[2] - b[2] * c[1])
521
+ - a[1] * (b[0] * c[2] - b[2] * c[0])
522
+ + a[2] * (b[0] * c[1] - b[1] * c[0])
523
+ )
524
+ if abs(determinant) < 1e-20:
525
+ return [1.0, 0, 0, 0, 1.0, 0, 0, 0, 1.0]
526
+ # cofactor / determinant, already the inverse transpose.
527
+ return [
528
+ (b[1] * c[2] - b[2] * c[1]) / determinant,
529
+ (b[2] * c[0] - b[0] * c[2]) / determinant,
530
+ (b[0] * c[1] - b[1] * c[0]) / determinant,
531
+ (a[2] * c[1] - a[1] * c[2]) / determinant,
532
+ (a[0] * c[2] - a[2] * c[0]) / determinant,
533
+ (a[1] * c[0] - a[0] * c[1]) / determinant,
534
+ (a[1] * b[2] - a[2] * b[1]) / determinant,
535
+ (a[2] * b[0] - a[0] * b[2]) / determinant,
536
+ (a[0] * b[1] - a[1] * b[0]) / determinant,
537
+ ]
538
+
539
+
540
+ def _fill_missing_normals(
541
+ positions: list[tuple[float, float, float]],
542
+ normals: list[tuple[float, float, float]],
543
+ indices: list[int],
544
+ ) -> None:
545
+ """Replace zero-length normals with the area-weighted face average."""
546
+
547
+ missing = [
548
+ index for index, normal in enumerate(normals)
549
+ if normal[0] == 0.0 and normal[1] == 0.0 and normal[2] == 0.0
550
+ ]
551
+ if not missing:
552
+ return
553
+
554
+ accumulated = {index: [0.0, 0.0, 0.0] for index in missing}
555
+ needed = set(missing)
556
+ for triangle in range(len(indices) // 3):
557
+ ia, ib, ic = indices[triangle * 3:triangle * 3 + 3]
558
+ if not (ia in needed or ib in needed or ic in needed):
559
+ continue
560
+ pa, pb, pc = positions[ia], positions[ib], positions[ic]
561
+ e1 = (pb[0] - pa[0], pb[1] - pa[1], pb[2] - pa[2])
562
+ e2 = (pc[0] - pa[0], pc[1] - pa[1], pc[2] - pa[2])
563
+ cross = (
564
+ e1[1] * e2[2] - e1[2] * e2[1],
565
+ e1[2] * e2[0] - e1[0] * e2[2],
566
+ e1[0] * e2[1] - e1[1] * e2[0],
567
+ )
568
+ for index in (ia, ib, ic):
569
+ if index in accumulated:
570
+ for axis in range(3):
571
+ accumulated[index][axis] += cross[axis]
572
+
573
+ for index, vector in accumulated.items():
574
+ length = math.sqrt(sum(value * value for value in vector))
575
+ normals[index] = (
576
+ (vector[0] / length, vector[1] / length, vector[2] / length)
577
+ if length > 1e-20 else (0.0, 1.0, 0.0)
578
+ )
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/meshy_model.py ADDED
@@ -0,0 +1,463 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ models/gen_3d_object/meshy_model.py
3
+
4
+ MeshyModel — wrapper around Meshy's cloud 3D-generation API (image-to-3D and
5
+ text-to-3D), producing GLB / FBX / OBJ / USDZ / STL.
6
+
7
+ Reference: https://docs.meshy.ai/ (base https://api.meshy.ai)
8
+
9
+ Second backend for the `gen_3d_object` slot. Its `infer` / `infer_and_save`
10
+ signatures are identical to `TripoModel`'s and positionally identical to
11
+ `Trellis2Model`'s, so `Gen3DObjectOperator` dispatches on class name alone
12
+ (model_require.md R6).
13
+
14
+ CONTRACT DEVIATIONS (model_require.md targets local-weight models; the rules that
15
+ replace it live in agent_skills/develop_harness/api_model_require.md):
16
+ C1 R2.1/R2.2 → R9.1 `model_path` carries a *model version id* ("meshy-6").
17
+ C2 R2.3 → R9.2 `device` accepted for interface parity and ignored.
18
+ C3 R3.6/R5.5 → R9.3 no @torch.no_grad(); torch is not involved.
19
+ C4 R4.1-R4.3 → R9.4 `unload()` is a no-op that closes the HTTP session.
20
+ C5 R3.3/R3.4 → R9.5 `seed` is forwarded for text-to-3D only, where the API
21
+ accepts it; image-to-3D has no seed. Reproducibility is
22
+ NOT guaranteed server-side and is never faked locally.
23
+ C6 R3.1 → R9.6 task-based API (submit → poll → download); `infer()`
24
+ blocks until completion or `timeout` (default 300 s).
25
+ Text-to-3D runs two tasks (preview → refine) when a
26
+ texture is requested; both ids are logged.
27
+ C7 R1.2 uses the documented `infer_and_save(..., output_path)`
28
+ exception; the bytes-returning `infer()` exists alongside.
29
+ C8 (new) → R9.8 `cache_dir` prevents re-billing an identical request.
30
+ C9 (new) → R9.9 `max_retries` + exponential backoff; retryable and
31
+ terminal failures are split.
32
+
33
+ Environment:
34
+ MESHY_API_KEY required at the first infer() call, not at construction.
35
+ Get one at https://www.meshy.ai/api (a `msy_dummy_...`
36
+ test-mode key returns canned assets without spending credits).
37
+ MESHY_API_BASE optional override of the API root.
38
+ `pip install requests` is needed for the API backends only.
39
+
40
+ Usage:
41
+ from models.gen_3d_object.meshy_model import MeshyModel
42
+ model = MeshyModel(model_path="meshy-6", output_format="fbx")
43
+ path = model.infer_and_save(image, output_path="out/model.fbx", seed=42)
44
+ """
45
+ from __future__ import annotations
46
+
47
+ import logging
48
+ import os
49
+ import time
50
+ from pathlib import Path
51
+ from typing import Any, Optional
52
+
53
+ from models.common import cloud_api
54
+ from models.common.glb_utils import glb_summary
55
+
56
+ logger = logging.getLogger(__name__)
57
+
58
+ SIGNUP_URL = "https://www.meshy.ai/api"
59
+
60
+ DEFAULT_API_BASE = "https://api.meshy.ai"
61
+
62
+ #: Short names accepted for `model_path`. Unknown values pass through untouched.
63
+ MODEL_ALIASES: dict[str, str] = {
64
+ "meshy": "meshy-6",
65
+ "meshy-6-text-to-3d": "meshy-6",
66
+ "meshy-6-image-to-3d": "meshy-6",
67
+ "meshy-5-text-to-3d": "meshy-5",
68
+ "meshy-5-image-to-3d": "meshy-5",
69
+ }
70
+
71
+ DEFAULT_MODEL = "meshy-6"
72
+
73
+ DONE_STATES = ("succeeded", "success", "completed")
74
+ FAILED_STATES = ("failed", "canceled", "cancelled", "expired")
75
+
76
+ #: Meshy rejects a target_polycount outside this range with a 400 (terminal).
77
+ POLYCOUNT_RANGE = (100, 300_000)
78
+
79
+ #: Formats the API can return directly, i.e. keys of `model_urls`.
80
+ SUPPORTED_FORMATS = ("glb", "fbx", "obj", "usdz", "stl", "mtl", "3mf")
81
+
82
+
83
+ class MeshyModel:
84
+ """
85
+ Cloud image-to-3D / text-to-3D through Meshy.
86
+
87
+ Args:
88
+ model_path: [C1] Meshy `ai_model` id ("meshy-6", "meshy-5", "latest"),
89
+ or an alias from `MODEL_ALIASES`.
90
+ device: [C2] Accepted for interface parity, ignored. "cpu" is fine.
91
+ api_key: Explicit key; defaults to `$MESHY_API_KEY`, read at first call.
92
+ timeout: [C6] Seconds to wait for one generation task (each stage of
93
+ the text-to-3D preview → refine chain gets the full budget).
94
+ poll_interval: Seconds between status polls.
95
+ max_retries: [C9] Extra attempts for retryable HTTP failures.
96
+ cache_dir: [C8] Directory for the response cache. None disables it.
97
+ output_format: Any of `SUPPORTED_FORMATS`; picked out of `model_urls`.
98
+ low_poly: [B4.3] Sets `model_type="lowpoly"`, i.e. the service produces
99
+ a low-poly mesh instead of us decimating one locally.
100
+ texture / enable_pbr / topology / should_remesh:
101
+ Forwarded to the generation endpoints.
102
+ refine: Text-to-3D only. Meshy's preview stage returns an untextured
103
+ mesh; the refine stage textures it and costs extra credits.
104
+ Ignored when `texture=False`.
105
+ api_base: Override the API root (defaults to `$MESHY_API_BASE`).
106
+ verbose: Print task progress; off by default (R3.7).
107
+ """
108
+
109
+ PROVIDER = "meshy"
110
+
111
+ def __init__(
112
+ self,
113
+ model_path: str = DEFAULT_MODEL,
114
+ device: str = "cuda",
115
+ *,
116
+ api_key: Optional[str] = None,
117
+ # Measured: one image-to-3D with PBR textures took 283 s here, and the
118
+ # Tripo backend took 601 s for the same job. Timing out does not refund
119
+ # the credits, so the default errs long; the error carries the task_id.
120
+ timeout: int = 1800,
121
+ poll_interval: float = 3.0,
122
+ max_retries: int = 3,
123
+ cache_dir: Optional[str] = None,
124
+ output_format: str = "glb",
125
+ low_poly: bool = False,
126
+ texture: bool = True,
127
+ enable_pbr: bool = True,
128
+ topology: str = "triangle",
129
+ should_remesh: Optional[bool] = None,
130
+ refine: bool = True,
131
+ api_base: Optional[str] = None,
132
+ http_timeout: int = 60,
133
+ verbose: bool = False,
134
+ **model_specific: Any,
135
+ ):
136
+ # [CONTRACT-DEVIATION C1] model_path is a version id, not a weight location.
137
+ # [CONTRACT-DEVIATION C2] device accepted for interface parity, ignored.
138
+ self.model_path = MODEL_ALIASES.get(str(model_path).lower(), model_path)
139
+ self.device = device
140
+
141
+ # R2.4 — store everything before anything loads.
142
+ self.api_key = api_key
143
+ self.timeout = timeout
144
+ self.poll_interval = poll_interval
145
+ self.max_retries = max_retries
146
+ self.cache_dir = cache_dir
147
+ self.output_format = output_format.lower().lstrip(".")
148
+ self.low_poly = low_poly
149
+ self.texture = texture
150
+ self.enable_pbr = enable_pbr
151
+ self.topology = topology
152
+ self.should_remesh = should_remesh
153
+ self.refine = refine
154
+ self.api_base = (api_base or os.environ.get("MESHY_API_BASE")
155
+ or DEFAULT_API_BASE)
156
+ self.http_timeout = http_timeout
157
+ self.verbose = verbose
158
+ self.model_specific = model_specific
159
+
160
+ if self.output_format not in SUPPORTED_FORMATS:
161
+ raise ValueError(
162
+ f"output_format={self.output_format!r} is not one of "
163
+ f"{SUPPORTED_FORMATS}. Meshy returns these directly in model_urls."
164
+ )
165
+
166
+ self._client: Optional[cloud_api.CloudAPIClient] = None
167
+ self._cache = cloud_api.ResponseCache(cache_dir, self.PROVIDER)
168
+
169
+ #: Record of the most recent **real** call — see `TripoModel.last_call_info`.
170
+ self.last_call_info: dict[str, Any] = {}
171
+
172
+ # ── plumbing ──────────────────────────────────────────────────────────────
173
+
174
+ @property
175
+ def client(self) -> cloud_api.CloudAPIClient:
176
+ """HTTP client, created on first use. [R9.7] The key is resolved here."""
177
+ if self._client is None:
178
+ key = cloud_api.require_api_key(
179
+ self.api_key, "MESHY_API_KEY", SIGNUP_URL, who="MeshyModel")
180
+ self._client = cloud_api.CloudAPIClient(
181
+ self.api_base, key,
182
+ timeout=self.http_timeout,
183
+ max_retries=self.max_retries,
184
+ )
185
+ return self._client
186
+
187
+ def unload(self) -> None:
188
+ """[C4] Close the HTTP session. Idempotent, and safe before any call."""
189
+ if self._client is not None:
190
+ self._client.close()
191
+ self._client = None
192
+
193
+ close = unload
194
+
195
+ @staticmethod
196
+ def _task_id_of(resp: Any) -> str:
197
+ """Meshy answers a creation call with `{"result": "<task id>"}`."""
198
+ if isinstance(resp, dict):
199
+ for key in ("result", "id", "task_id"):
200
+ value = resp.get(key)
201
+ if isinstance(value, str) and value:
202
+ return value
203
+ raise cloud_api.CloudAPIError(
204
+ f"Meshy accepted the request but returned no task id: {resp!r}")
205
+
206
+ def _fetch_task(self, endpoint: str, task_id: str) -> dict:
207
+ task = self.client.request("GET", f"{endpoint}/{task_id}")
208
+ if not isinstance(task, dict):
209
+ raise cloud_api.CloudAPIError(
210
+ f"unexpected task payload for {task_id}: {task!r}", task_id=task_id)
211
+ return task
212
+
213
+ def _model_url(self, task: dict) -> str:
214
+ """URL of the requested format, with an actionable message when absent."""
215
+ urls = task.get("model_urls") or {}
216
+ url = urls.get(self.output_format)
217
+ if isinstance(url, str) and url.startswith("http"):
218
+ return url
219
+ raise cloud_api.CloudAPIError(
220
+ f"task {task.get('id')} finished but has no {self.output_format!r} "
221
+ f"URL. Available: {sorted(urls)}. Set output_format to one of those.",
222
+ task_id=task.get("id"), payload=task)
223
+
224
+ def _clamp_polycount(self, value: Optional[int]) -> Optional[int]:
225
+ """
226
+ Keep `target_polycount` inside the documented range.
227
+
228
+ `Gen3DObjectOperator` forwards TRELLIS.2's default of 1_000_000, which
229
+ Meshy rejects with a terminal 400. Clamping (loudly) keeps the operator
230
+ interchangeable (R6) instead of making the caller special-case backends.
231
+ """
232
+ if value is None:
233
+ return None
234
+ low, high = POLYCOUNT_RANGE
235
+ clamped = max(low, min(int(value), high))
236
+ if clamped != int(value):
237
+ logger.warning("[meshy] target_polycount %s clamped to %s (API range %s-%s)",
238
+ value, clamped, low, high)
239
+ return clamped
240
+
241
+ # ── inference ─────────────────────────────────────────────────────────────
242
+
243
+ def infer(
244
+ self,
245
+ image: Any = None,
246
+ seed: int = 42,
247
+ decimation_target: Optional[int] = None,
248
+ texture_size: Optional[int] = None,
249
+ *,
250
+ prompt: Optional[str] = None,
251
+ negative_prompt: Optional[str] = None,
252
+ image_url: Optional[str] = None,
253
+ verbose: Optional[bool] = None,
254
+ **provider_kwargs: Any,
255
+ ) -> bytes:
256
+ """
257
+ Generate one 3D asset and return the model file bytes.
258
+
259
+ Args:
260
+ image: Reference image as `PIL.Image.Image`, `np.ndarray` or PNG
261
+ `bytes` — sent inline as a base64 data URI. Not a path (R3.2).
262
+ seed: [C5] Forwarded for text-to-3D only; image-to-3D has no seed
263
+ parameter. Reproducibility is not guaranteed.
264
+ decimation_target: Target face count → `target_polycount`, clamped to
265
+ the API's 100-300000 range.
266
+ texture_size: Accepted for signature parity with `Trellis2Model` and
267
+ **ignored** — Meshy exposes no texture resolution parameter.
268
+ prompt: Text prompt for text-to-3D. [A4 decision] Same rationale as
269
+ `TripoModel`: keeps text-to-3D reachable without a second slot.
270
+ negative_prompt: Sent as `texture_prompt`'s counterpart is absent in
271
+ the API — rejected explicitly rather than silently dropped.
272
+ image_url: Publicly reachable image URL, used instead of the data URI.
273
+ verbose: Override the constructor's verbosity for this call.
274
+ **provider_kwargs: Merged into the request body verbatim.
275
+
276
+ Returns:
277
+ The model file as `bytes`, in `output_format`.
278
+
279
+ Raises:
280
+ CloudAPIAuthError / CloudAPIQuotaError / CloudTaskFailed /
281
+ CloudTaskTimeout — see `models/common/cloud_api.py`.
282
+ """
283
+ verbose = self.verbose if verbose is None else verbose
284
+ if image is None and image_url is None and not prompt:
285
+ raise ValueError(
286
+ "MeshyModel.infer needs an image (`image=` / `image_url=`) or a "
287
+ "text `prompt=`; got neither.")
288
+ if negative_prompt:
289
+ raise ValueError(
290
+ "Meshy has no negative_prompt parameter. Fold the constraint into "
291
+ "`prompt`, or use TripoModel which supports it.")
292
+ if texture_size is not None:
293
+ logger.debug("[meshy] texture_size=%s ignored; the API has no equivalent",
294
+ texture_size)
295
+
296
+ polycount = self._clamp_polycount(decimation_target)
297
+ use_image = image is not None or image_url is not None
298
+
299
+ payload: dict[str, Any] = {
300
+ "ai_model": self.model_path,
301
+ "model_type": "lowpoly" if self.low_poly else "standard",
302
+ "topology": self.topology,
303
+ }
304
+ if polycount is not None:
305
+ payload["target_polycount"] = polycount
306
+ if self.should_remesh is not None:
307
+ payload["should_remesh"] = self.should_remesh
308
+
309
+ if use_image:
310
+ payload["should_texture"] = self.texture
311
+ payload["enable_pbr"] = self.enable_pbr
312
+ else:
313
+ payload["mode"] = "preview"
314
+ payload["prompt"] = prompt
315
+ # [CONTRACT-DEVIATION C5] accepted by the text endpoint only.
316
+ payload["seed"] = int(seed)
317
+ payload.update(provider_kwargs)
318
+
319
+ # [C8] Everything that changes the output goes into the key; the image is
320
+ # represented by its hash, and the API key never appears.
321
+ png = cloud_api.image_to_png_bytes(image) if image is not None else None
322
+ cache_key = cloud_api.request_hash({
323
+ "provider": self.PROVIDER,
324
+ "payload": payload,
325
+ "image_sha256": cloud_api.bytes_hash(png) if png else None,
326
+ "image_url": image_url,
327
+ "refine": self.refine and self.texture and not use_image,
328
+ "output_format": self.output_format,
329
+ })
330
+ cached = self._cache.get(cache_key, ext=self.output_format)
331
+ if cached is not None:
332
+ self.last_call_info = {
333
+ "provider": self.PROVIDER, "cached": True, "cache_key": cache_key,
334
+ "bytes": len(cached),
335
+ **(glb_summary(cached) if self.output_format == "glb" else {}),
336
+ }
337
+ return cached
338
+
339
+ t0 = time.time()
340
+ task_ids: list[str] = []
341
+
342
+ if use_image:
343
+ endpoint = "/openapi/v1/image-to-3d"
344
+ payload["image_url"] = (
345
+ image_url if png is None else cloud_api.image_to_data_uri(image))
346
+ task = self._submit_and_wait(endpoint, payload, verbose=verbose,
347
+ task_ids=task_ids)
348
+ else:
349
+ endpoint = "/openapi/v2/text-to-3d"
350
+ task = self._submit_and_wait(endpoint, payload, verbose=verbose,
351
+ task_ids=task_ids)
352
+ if self.texture and self.refine:
353
+ # [C6] Preview geometry is untextured; refine is a second billed
354
+ # task that paints it. Skip with texture=False or refine=False.
355
+ refine_payload = {
356
+ "mode": "refine",
357
+ "preview_task_id": task_ids[-1],
358
+ "ai_model": self.model_path,
359
+ "enable_pbr": self.enable_pbr,
360
+ }
361
+ task = self._submit_and_wait(endpoint, refine_payload,
362
+ verbose=verbose, task_ids=task_ids)
363
+
364
+ data = self.client.download(self._model_url(task))
365
+ elapsed = time.time() - t0
366
+
367
+ info = glb_summary(data) if self.output_format == "glb" else {"bytes": len(data)}
368
+ self.last_call_info = {
369
+ "provider": self.PROVIDER,
370
+ "model": self.model_path,
371
+ "task_id": task_ids[-1],
372
+ "task_ids": task_ids,
373
+ "elapsed_sec": round(elapsed, 2),
374
+ "credits": task.get("credits_consumed", task.get("credits")),
375
+ "cached": False,
376
+ "cache_key": cache_key,
377
+ "format": self.output_format,
378
+ # The provider's own render of what it produced. Recording the URL
379
+ # (rather than downloading it here) keeps the model out of artifact
380
+ # placement (R1.2) while giving the caller a free visual check —
381
+ # "the asset exists" and "the asset is what was asked for" are
382
+ # different claims, and only a picture settles the second one.
383
+ "preview_url": task.get("thumbnail_url"),
384
+ **info,
385
+ }
386
+ # R9.8 — one line per billed call.
387
+ logger.info(
388
+ "[meshy] task=%s model=%s %.1fs credits=%s triangles=%s bytes=%s",
389
+ task_ids[-1], self.model_path, elapsed, self.last_call_info.get("credits"),
390
+ info.get("triangles"), len(data),
391
+ )
392
+ if verbose:
393
+ print(f"[meshy] {self.last_call_info}")
394
+
395
+ self._cache.put(cache_key, data, {
396
+ "provider": self.PROVIDER, "payload": payload,
397
+ **{k: v for k, v in self.last_call_info.items() if k != "cache_key"},
398
+ }, ext=self.output_format)
399
+ return data
400
+
401
+ def _submit_and_wait(self, endpoint: str, payload: dict, *,
402
+ verbose: bool, task_ids: list[str]) -> dict:
403
+ """Create one task on `endpoint`, poll it to a terminal state, return it."""
404
+ created = self.client.request("POST", endpoint, json_body=payload)
405
+ task_id = self._task_id_of(created)
406
+ task_ids.append(task_id)
407
+ if verbose:
408
+ print(f"[meshy] task {task_id} submitted ({endpoint}, "
409
+ f"mode={payload.get('mode', 'image')})")
410
+ return cloud_api.poll_task(
411
+ lambda: self._fetch_task(endpoint, task_id),
412
+ task_id=task_id,
413
+ timeout=self.timeout,
414
+ poll_interval=self.poll_interval,
415
+ done_states=DONE_STATES,
416
+ failed_states=FAILED_STATES,
417
+ verbose=verbose,
418
+ )
419
+
420
+ def infer_and_save(
421
+ self,
422
+ image: Any = None,
423
+ output_path: Optional[str] = None,
424
+ seed: int = 42,
425
+ decimation_target: Optional[int] = None,
426
+ texture_size: Optional[int] = None,
427
+ *,
428
+ prompt: Optional[str] = None,
429
+ negative_prompt: Optional[str] = None,
430
+ image_url: Optional[str] = None,
431
+ verbose: Optional[bool] = None,
432
+ **provider_kwargs: Any,
433
+ ) -> str:
434
+ """
435
+ [C7] The documented R1.2 exception: run `infer()` and write the result.
436
+
437
+ The path comes **in** from the caller and is never derived here.
438
+
439
+ Args:
440
+ output_path: Destination file. Parent directories are created.
441
+ (everything else: see `infer`)
442
+
443
+ Returns:
444
+ `str(output_path)`.
445
+ """
446
+ if not output_path:
447
+ raise ValueError("output_path is required (model_require.md R1.2)")
448
+ data = self.infer(
449
+ image, seed, decimation_target, texture_size,
450
+ prompt=prompt, negative_prompt=negative_prompt, image_url=image_url,
451
+ verbose=verbose, **provider_kwargs,
452
+ )
453
+ out = Path(output_path)
454
+ out.parent.mkdir(parents=True, exist_ok=True)
455
+ out.write_bytes(data)
456
+ return str(out)
457
+
458
+ # ── account ───────────────────────────────────────────────────────────────
459
+
460
+ def balance(self) -> dict:
461
+ """Remaining credits: ``{"balance": int}``. Cheap and unbilled."""
462
+ resp = self.client.request("GET", "/openapi/v1/balance")
463
+ return resp if isinstance(resp, dict) else {"balance": resp}
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/tripo_model.py ADDED
@@ -0,0 +1,532 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ models/gen_3d_object/tripo_model.py
3
+
4
+ TripoModel — wrapper around Tripo3D's cloud 3D-generation API (image-to-3D and
5
+ text-to-3D), producing a GLB.
6
+
7
+ Reference: https://developers.tripo3d.ai/ (v3 API, base https://openapi.tripo3d.ai/v3)
8
+
9
+ CONTRACT DEVIATIONS (model_require.md targets local-weight models; the rules that
10
+ replace it live in agent_skills/develop_harness/api_model_require.md):
11
+ C1 R2.1/R2.2 → R9.1 `model_path` carries a *model version id*
12
+ ("v3.1-20260211"), not a weight location.
13
+ C2 R2.3 → R9.2 `device` accepted for interface parity and ignored.
14
+ C3 R3.6/R5.5 → R9.3 no @torch.no_grad(); torch is not involved.
15
+ C4 R4.1-R4.3 → R9.4 `unload()` is a no-op that closes the HTTP session.
16
+ C5 R3.3/R3.4 → R9.5 `seed` is forwarded as model_seed/texture_seed when the
17
+ provider accepts it; server-side reproducibility is NOT
18
+ guaranteed and is never faked locally.
19
+ C6 R3.1 → R9.6 task-based API (submit → poll → download); `infer()`
20
+ blocks until completion or `timeout` (default 300 s).
21
+ A timeout error carries the `task_id`.
22
+ C7 R1.2 uses the documented `infer_and_save(..., output_path)`
23
+ exception; the bytes-returning `infer()` exists alongside.
24
+ C8 (new) → R9.8 `cache_dir` prevents re-billing an identical request.
25
+ C9 (new) → R9.9 `max_retries` + exponential backoff; retryable (5xx/429/
26
+ transport) and terminal (400/401/402) failures are split.
27
+
28
+ Environment:
29
+ TRIPO_API_KEY required at the first infer() call, not at construction.
30
+ Get one at https://platform.tripo3d.ai/api-keys
31
+ TRIPO_API_BASE optional override of the API root.
32
+ `pip install requests` is needed for the API backends only.
33
+
34
+ Usage:
35
+ from models.gen_3d_object.tripo_model import TripoModel
36
+ model = TripoModel(model_path="v3.1-20260211")
37
+ path = model.infer_and_save(image, output_path="out/model.glb", seed=42)
38
+ print(model.last_call_info) # task_id, elapsed, credits, triangles
39
+ """
40
+ from __future__ import annotations
41
+
42
+ import logging
43
+ import os
44
+ import time
45
+ from pathlib import Path
46
+ from typing import Any, Optional
47
+
48
+ from models.common import cloud_api
49
+ from models.common.glb_utils import glb_summary
50
+
51
+ logger = logging.getLogger(__name__)
52
+
53
+ #: Where a human gets a key. Quoted verbatim in the fail-fast message (R1.6).
54
+ SIGNUP_URL = "https://platform.tripo3d.ai/api-keys"
55
+
56
+ DEFAULT_API_BASE = "https://openapi.tripo3d.ai/v3"
57
+
58
+ #: Short names accepted for `model_path`, mapped to the ids the API expects.
59
+ #: Unknown values are passed through untouched, so a version released after this
60
+ #: file was written still works without a code change.
61
+ MODEL_ALIASES: dict[str, str] = {
62
+ "tripo": "v3.1-20260211",
63
+ "tripo-v3.1": "v3.1-20260211",
64
+ "v3.1": "v3.1-20260211",
65
+ "tripo-v3.0": "v3.0-20250812",
66
+ "v3.0": "v3.0-20250812",
67
+ "tripo-v2.5": "v2.5-20250123",
68
+ "v2.5": "v2.5-20250123",
69
+ # P series — natively low-poly, the cheap option for mesh particles (B4.2).
70
+ "tripo-p1": "P1-20260311",
71
+ "p1": "P1-20260311",
72
+ }
73
+
74
+ DEFAULT_MODEL = "v3.1-20260211"
75
+
76
+ #: Terminal task states. Tripo reports lower-case; compared case-insensitively.
77
+ DONE_STATES = ("success", "succeeded", "finished", "completed")
78
+ FAILED_STATES = ("failed", "cancelled", "canceled", "banned", "expired", "unknown")
79
+
80
+ #: Output fields that have carried the download URL across API versions.
81
+ _MODEL_URL_KEYS = ("model_url", "pbr_model", "model", "base_model", "glb", "gltf")
82
+
83
+ #: `face_limit` range the service accepts **while `smart_low_poly` is on**.
84
+ #: Outside it the request is rejected with a terminal 400:
85
+ #: "when smart_low_poly is enabled, face_limit must be between 500 and 20000
86
+ #: (triangle mesh), got 30000"
87
+ #: Not in the public docs; found by calling it.
88
+ LOW_POLY_FACE_LIMIT_RANGE = (500, 20_000)
89
+
90
+
91
+ class TripoModel:
92
+ """
93
+ Cloud image-to-3D / text-to-3D through Tripo3D.
94
+
95
+ Interchangeable with `Trellis2Model` in `Gen3DObjectOperator`: the
96
+ `infer_and_save(image, output_path, seed, decimation_target, texture_size)`
97
+ call signature is positionally identical (model_require.md R6).
98
+
99
+ Args:
100
+ model_path: [C1] Tripo model version id, or an alias from `MODEL_ALIASES`.
101
+ device: [C2] Accepted for interface parity, ignored. "cpu" is fine.
102
+ api_key: Explicit key; defaults to `$TRIPO_API_KEY`, read at first call.
103
+ timeout: [C6] Seconds to wait for one generation task.
104
+ poll_interval: Seconds between status polls.
105
+ max_retries: [C9] Extra attempts for retryable HTTP failures.
106
+ cache_dir: [C8] Directory for the response cache. None disables it.
107
+ output_format: "glb" is produced natively. Any other format needs the
108
+ conversion endpoint — see `convert_path`.
109
+ convert_path: API path of the format-conversion endpoint. Left as None
110
+ because it is not pinned down in the public v3 docs; set it
111
+ to enable `output_format="fbx"` without touching this file.
112
+ low_poly: [B4.3] Ask the service for clean low-poly topology
113
+ (`smart_low_poly`) instead of decimating locally.
114
+ texture / pbr / quad / texture_quality / geometry_quality:
115
+ Forwarded verbatim to the generation endpoint.
116
+ api_base: Override the API root (defaults to `$TRIPO_API_BASE`).
117
+ verbose: Print task progress; off by default (R3.7).
118
+ """
119
+
120
+ #: Provider name, used for cache namespacing and log lines.
121
+ PROVIDER = "tripo"
122
+
123
+ def __init__(
124
+ self,
125
+ model_path: str = DEFAULT_MODEL,
126
+ device: str = "cuda",
127
+ *,
128
+ api_key: Optional[str] = None,
129
+ # Measured: image-to-3D with smart_low_poly took **601 s**, i.e. it would
130
+ # have died one second past a 600 s budget. Timing out does not refund
131
+ # the credits — the task finishes server-side and only the download is
132
+ # lost — so the default errs long. The error carries the task_id.
133
+ timeout: int = 1800,
134
+ poll_interval: float = 3.0,
135
+ max_retries: int = 3,
136
+ cache_dir: Optional[str] = None,
137
+ output_format: str = "glb",
138
+ convert_path: Optional[str] = None,
139
+ low_poly: bool = False,
140
+ texture: bool = True,
141
+ pbr: bool = True,
142
+ quad: bool = False,
143
+ texture_quality: str = "standard",
144
+ geometry_quality: str = "standard",
145
+ api_base: Optional[str] = None,
146
+ http_timeout: int = 60,
147
+ verbose: bool = False,
148
+ **model_specific: Any,
149
+ ):
150
+ # [CONTRACT-DEVIATION C1] model_path is a version id, not a weight location.
151
+ # [CONTRACT-DEVIATION C2] device accepted for interface parity, ignored.
152
+ self.model_path = MODEL_ALIASES.get(str(model_path).lower(), model_path)
153
+ self.device = device
154
+
155
+ # R2.4 — every constructor argument lands on self before anything loads,
156
+ # so unload()/reload round-trips without losing configuration.
157
+ self.api_key = api_key
158
+ self.timeout = timeout
159
+ self.poll_interval = poll_interval
160
+ self.max_retries = max_retries
161
+ self.cache_dir = cache_dir
162
+ self.output_format = output_format.lower().lstrip(".")
163
+ self.convert_path = convert_path
164
+ self.low_poly = low_poly
165
+ self.texture = texture
166
+ self.pbr = pbr
167
+ self.quad = quad
168
+ self.texture_quality = texture_quality
169
+ self.geometry_quality = geometry_quality
170
+ self.api_base = (api_base or os.environ.get("TRIPO_API_BASE")
171
+ or DEFAULT_API_BASE)
172
+ self.http_timeout = http_timeout
173
+ self.verbose = verbose
174
+ self.model_specific = model_specific
175
+
176
+ self._client: Optional[cloud_api.CloudAPIClient] = None
177
+ self._cache = cloud_api.ResponseCache(cache_dir, self.PROVIDER)
178
+
179
+ #: Record of the most recent **real** call: task_id, elapsed_sec, credits,
180
+ #: triangles, bytes, cached. Operators copy it into meta.json (R9.8).
181
+ self.last_call_info: dict[str, Any] = {}
182
+
183
+ # ── plumbing ──────────────────────────────────────────────────────────────
184
+
185
+ @property
186
+ def client(self) -> cloud_api.CloudAPIClient:
187
+ """
188
+ HTTP client, created on first use.
189
+
190
+ [C6/R9.7] The API key is resolved here rather than in `__init__`, so the
191
+ wrapper can be imported and constructed on a machine with no credentials
192
+ (which is exactly what `test/harness/smoke.py` does).
193
+ """
194
+ if self._client is None:
195
+ key = cloud_api.require_api_key(
196
+ self.api_key, "TRIPO_API_KEY", SIGNUP_URL, who="TripoModel")
197
+ self._client = cloud_api.CloudAPIClient(
198
+ self.api_base, key,
199
+ timeout=self.http_timeout,
200
+ max_retries=self.max_retries,
201
+ )
202
+ return self._client
203
+
204
+ def unload(self) -> None:
205
+ """[C4] Close the HTTP session. Idempotent, and safe before any call."""
206
+ if self._client is not None:
207
+ self._client.close()
208
+ self._client = None
209
+
210
+ close = unload
211
+
212
+ @staticmethod
213
+ def _unwrap(resp: Any) -> dict:
214
+ """
215
+ Strip Tripo's `{"code": 0, "data": {...}}` envelope.
216
+
217
+ A non-zero `code` on an HTTP 200 is a terminal application error — the
218
+ same request will fail the same way, so it must not be retried (R9.9).
219
+ """
220
+ if not isinstance(resp, dict):
221
+ raise cloud_api.CloudAPIError(f"unexpected response type {type(resp).__name__}: {resp!r}")
222
+ code = resp.get("code")
223
+ if code not in (None, 0):
224
+ message = resp.get("message") or resp.get("msg") or resp
225
+ suggestion = resp.get("suggestion")
226
+ raise cloud_api.CloudAPIRequestError(
227
+ f"Tripo API error code={code}: {message}"
228
+ + (f" — {suggestion}" if suggestion else ""),
229
+ payload=resp,
230
+ )
231
+ data = resp.get("data")
232
+ return data if isinstance(data, dict) else resp
233
+
234
+ def _upload_image(self, png: bytes) -> str:
235
+ """Upload PNG bytes, return the `file_token` used as generation input."""
236
+ data = self._unwrap(self.client.request(
237
+ "POST", "/files",
238
+ files={"file": ("input.png", png, "image/png")},
239
+ ))
240
+ token = data.get("file_token") or data.get("image_token") or data.get("token")
241
+ if not token:
242
+ raise cloud_api.CloudAPIError(
243
+ f"upload succeeded but no file_token in the response: {data}")
244
+ return str(token)
245
+
246
+ @staticmethod
247
+ def _extract_model_url(task: dict) -> str:
248
+ """Find the artifact URL in a finished task, across output field names."""
249
+ output = task.get("output") or task.get("result") or {}
250
+ for key in _MODEL_URL_KEYS:
251
+ value = output.get(key)
252
+ if isinstance(value, str) and value.startswith("http"):
253
+ return value
254
+ if isinstance(value, dict) and isinstance(value.get("url"), str):
255
+ return value["url"]
256
+ raise cloud_api.CloudAPIError(
257
+ f"task {task.get('task_id')} reported success but carries no model URL. "
258
+ f"output={output!r}",
259
+ task_id=task.get("task_id"), payload=task)
260
+
261
+ def _fetch_task(self, task_id: str) -> dict:
262
+ return self._unwrap(self.client.request("GET", f"/tasks/{task_id}"))
263
+
264
+ # ── payload ───────────────────────────────────────────────────────────────
265
+
266
+ def _clamp_face_limit(self, value: int) -> int:
267
+ """
268
+ Keep `face_limit` inside the range the service accepts.
269
+
270
+ `Gen3DObjectOperator` forwards TRELLIS.2's default of 1 000 000, and with
271
+ `low_poly=True` anything outside 500-20 000 is a terminal 400. Clamping
272
+ (loudly) keeps the backends interchangeable (R6) rather than making the
273
+ caller special-case each provider.
274
+ """
275
+ value = int(value)
276
+ if not self.low_poly:
277
+ return value
278
+ low, high = LOW_POLY_FACE_LIMIT_RANGE
279
+ clamped = max(low, min(value, high))
280
+ if clamped != value:
281
+ logger.warning("[tripo] face_limit %s clamped to %s "
282
+ "(smart_low_poly range %s-%s)", value, clamped, low, high)
283
+ return clamped
284
+
285
+ def _build_payload(
286
+ self,
287
+ *,
288
+ prompt: Optional[str],
289
+ negative_prompt: Optional[str],
290
+ seed: Optional[int],
291
+ decimation_target: Optional[int],
292
+ provider_kwargs: dict,
293
+ ) -> dict:
294
+ """Generation parameters shared by the image and text endpoints."""
295
+ payload: dict[str, Any] = {
296
+ "model": self.model_path,
297
+ "texture": self.texture,
298
+ "pbr": self.pbr,
299
+ "texture_quality": self.texture_quality,
300
+ "geometry_quality": self.geometry_quality,
301
+ }
302
+ if self.quad:
303
+ payload["quad"] = True
304
+ if self.low_poly:
305
+ # [B4.3] Ask the service for low-poly topology. Decimating a 2M-face
306
+ # mesh locally wrecks UVs and normals; generating low-poly does not.
307
+ payload["smart_low_poly"] = True
308
+ if decimation_target:
309
+ payload["face_limit"] = self._clamp_face_limit(decimation_target)
310
+ if prompt:
311
+ payload["prompt"] = prompt
312
+ if negative_prompt:
313
+ payload["negative_prompt"] = negative_prompt
314
+ if seed is not None:
315
+ # [CONTRACT-DEVIATION C5] forwarded, but the service does not promise
316
+ # that the same seed reproduces the same mesh. Never faked locally.
317
+ payload["model_seed"] = int(seed)
318
+ payload["texture_seed"] = int(seed)
319
+ payload.update(provider_kwargs)
320
+ return payload
321
+
322
+ # ── inference ─────────────────────────────────────────────────────────────
323
+
324
+ def infer(
325
+ self,
326
+ image: Any = None,
327
+ seed: int = 42,
328
+ decimation_target: Optional[int] = None,
329
+ texture_size: Optional[int] = None,
330
+ *,
331
+ prompt: Optional[str] = None,
332
+ negative_prompt: Optional[str] = None,
333
+ image_url: Optional[str] = None,
334
+ verbose: Optional[bool] = None,
335
+ **provider_kwargs: Any,
336
+ ) -> bytes:
337
+ """
338
+ Generate one 3D asset and return the model file bytes.
339
+
340
+ [C6] Submits the task, polls until it finishes, downloads the artifact —
341
+ all inside this call. Typical wall time is 20 s to 4 min.
342
+
343
+ Args:
344
+ image: Reference image as `PIL.Image.Image`, `np.ndarray` or PNG
345
+ `bytes`. Not a path (R3.2). Give `image`, `image_url` or
346
+ `prompt`; image wins when several are present.
347
+ seed: [C5] Forwarded as `model_seed` / `texture_seed`. Reproducibility
348
+ is not guaranteed server-side.
349
+ decimation_target: Target face count, forwarded as `face_limit`.
350
+ None leaves it to the service.
351
+ texture_size: Accepted for signature parity with `Trellis2Model` and
352
+ **ignored** — Tripo exposes `texture_quality`, not a
353
+ resolution. Pass `texture_quality=` to the constructor.
354
+ prompt: Text prompt for text-to-3D. [A4 decision] The operator slot is
355
+ image-to-3D today; accepting `prompt` here keeps text-to-3D
356
+ available without a second wrapper.
357
+ negative_prompt: Text-to-3D only.
358
+ image_url: Publicly reachable image URL, used instead of uploading.
359
+ verbose: Override the constructor's verbosity for this call.
360
+ **provider_kwargs: Merged into the request body verbatim, so a new
361
+ API parameter needs no change here.
362
+
363
+ Returns:
364
+ The model file as `bytes` — GLB unless `output_format`/`convert_path`
365
+ say otherwise.
366
+
367
+ Raises:
368
+ CloudAPIAuthError: no or invalid `TRIPO_API_KEY`.
369
+ CloudAPIQuotaError: out of credits (terminal, never retried).
370
+ CloudTaskTimeout: not finished within `timeout`; carries `task_id`.
371
+ CloudTaskFailed: the service rejected or failed the task.
372
+ """
373
+ verbose = self.verbose if verbose is None else verbose
374
+ if image is None and image_url is None and not prompt:
375
+ raise ValueError(
376
+ "TripoModel.infer needs an image (`image=` / `image_url=`) or a "
377
+ "text `prompt=`; got neither.")
378
+ if texture_size is not None:
379
+ # [CONTRACT-DEVIATION C2-style] accepted for parity, ignored.
380
+ logger.debug("[tripo] texture_size=%s ignored; use texture_quality",
381
+ texture_size)
382
+ if self.output_format != "glb" and not self.convert_path:
383
+ raise NotImplementedError(
384
+ f"TripoModel produces GLB; output_format={self.output_format!r} needs "
385
+ f"Tripo's conversion endpoint, whose path is not pinned in the public "
386
+ f"v3 docs. Either set convert_path=... on the constructor, use "
387
+ f"MeshyModel(output_format='fbx') which returns FBX natively, or "
388
+ f"convert the GLB with engine_adapters/blender/."
389
+ )
390
+
391
+ png = cloud_api.image_to_png_bytes(image) if image is not None else None
392
+ use_image = png is not None or bool(image_url)
393
+ payload = self._build_payload(
394
+ # The image endpoint has no prompt field — sending one is a terminal
395
+ # 400. An image plus a prompt means "use the image".
396
+ prompt=None if use_image else prompt,
397
+ negative_prompt=None if use_image else negative_prompt,
398
+ seed=seed,
399
+ decimation_target=decimation_target, provider_kwargs=provider_kwargs,
400
+ )
401
+
402
+ # [C8] Cache key covers everything that changes the output. The image is
403
+ # represented by its hash, never its bytes, and the key never sees the API key.
404
+ cache_key = cloud_api.request_hash({
405
+ "provider": self.PROVIDER,
406
+ "payload": payload,
407
+ "image_sha256": cloud_api.bytes_hash(png) if png else None,
408
+ "image_url": image_url,
409
+ "output_format": self.output_format,
410
+ })
411
+ cached = self._cache.get(cache_key, ext=self.output_format)
412
+ if cached is not None:
413
+ self.last_call_info = {
414
+ "provider": self.PROVIDER, "cached": True, "cache_key": cache_key,
415
+ "bytes": len(cached), **glb_summary(cached),
416
+ }
417
+ return cached
418
+
419
+ t0 = time.time()
420
+ if png is not None:
421
+ # `input` takes a file_token, a public URL or a previous task id.
422
+ payload["input"] = self._upload_image(png)
423
+ endpoint = "/generation/image-to-model"
424
+ elif image_url:
425
+ payload["input"] = image_url
426
+ endpoint = "/generation/image-to-model"
427
+ else:
428
+ endpoint = "/generation/text-to-model"
429
+
430
+ created = self._unwrap(self.client.request("POST", endpoint, json_body=payload))
431
+ task_id = str(created.get("task_id") or created.get("id") or "")
432
+ if not task_id:
433
+ raise cloud_api.CloudAPIError(
434
+ f"{endpoint} accepted the request but returned no task_id: {created}")
435
+ if verbose:
436
+ print(f"[tripo] task {task_id} submitted ({endpoint})")
437
+
438
+ # Some responses already carry a finished task; only poll when they do not.
439
+ state = str(created.get("status", "")).lower()
440
+ if state in DONE_STATES:
441
+ task = created
442
+ else:
443
+ task = cloud_api.poll_task(
444
+ lambda: self._fetch_task(task_id),
445
+ task_id=task_id,
446
+ timeout=self.timeout,
447
+ poll_interval=self.poll_interval,
448
+ done_states=DONE_STATES,
449
+ failed_states=FAILED_STATES,
450
+ verbose=verbose,
451
+ )
452
+
453
+ data = self.client.download(self._extract_model_url(task))
454
+ elapsed = time.time() - t0
455
+
456
+ info = glb_summary(data) if self.output_format == "glb" else {"bytes": len(data)}
457
+ self.last_call_info = {
458
+ "provider": self.PROVIDER,
459
+ "model": self.model_path,
460
+ "task_id": task_id,
461
+ "elapsed_sec": round(elapsed, 2),
462
+ "credits": task.get("credits_consumed", task.get("credits")),
463
+ "cached": False,
464
+ "cache_key": cache_key,
465
+ # The provider's own render — see the note in meshy_model.py.
466
+ "preview_url": (task.get("output") or {}).get("rendered_image_url"),
467
+ **info,
468
+ }
469
+ # R9.8 — one line per billed call: what it cost and what it produced.
470
+ logger.info(
471
+ "[tripo] task=%s model=%s %.1fs credits=%s triangles=%s bytes=%s",
472
+ task_id, self.model_path, elapsed, self.last_call_info.get("credits"),
473
+ info.get("triangles"), len(data),
474
+ )
475
+ if verbose:
476
+ print(f"[tripo] {self.last_call_info}")
477
+
478
+ self._cache.put(cache_key, data, {
479
+ "provider": self.PROVIDER, "payload": payload,
480
+ **{k: v for k, v in self.last_call_info.items() if k != "cache_key"},
481
+ }, ext=self.output_format)
482
+ return data
483
+
484
+ def infer_and_save(
485
+ self,
486
+ image: Any = None,
487
+ output_path: Optional[str] = None,
488
+ seed: int = 42,
489
+ decimation_target: Optional[int] = None,
490
+ texture_size: Optional[int] = None,
491
+ *,
492
+ prompt: Optional[str] = None,
493
+ negative_prompt: Optional[str] = None,
494
+ image_url: Optional[str] = None,
495
+ verbose: Optional[bool] = None,
496
+ **provider_kwargs: Any,
497
+ ) -> str:
498
+ """
499
+ [C7] The documented R1.2 exception: run `infer()` and write the result.
500
+
501
+ The path comes **in** from the caller and is never derived here — the
502
+ operator owns artifact placement.
503
+
504
+ Args:
505
+ output_path: Destination file. Parent directories are created.
506
+ (everything else: see `infer`)
507
+
508
+ Returns:
509
+ `str(output_path)`.
510
+ """
511
+ if not output_path:
512
+ raise ValueError("output_path is required (model_require.md R1.2)")
513
+ data = self.infer(
514
+ image, seed, decimation_target, texture_size,
515
+ prompt=prompt, negative_prompt=negative_prompt, image_url=image_url,
516
+ verbose=verbose, **provider_kwargs,
517
+ )
518
+ out = Path(output_path)
519
+ out.parent.mkdir(parents=True, exist_ok=True)
520
+ out.write_bytes(data)
521
+ return str(out)
522
+
523
+ # ── account ───────────────────────────────────────────────────────────────
524
+
525
+ def balance(self) -> dict:
526
+ """
527
+ Remaining credits: ``{"balance": float, "frozen": float}``.
528
+
529
+ Cheap and unbilled — call it before a batch to check the budget (C4 note:
530
+ this is the only method that talks to the API without generating).
531
+ """
532
+ return self._unwrap(self.client.request("GET", "/account/balance"))
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/operators/gen_3d_object/operator.py ADDED
@@ -0,0 +1,596 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ operators/gen_3d_object/operator.py
3
+
4
+ Gen3DObjectOperator — accepts a loaded model and processes an input dict into a
5
+ 3D output (GLB file on disk).
6
+
7
+ The operator is intentionally model-agnostic: you inject any object that
8
+ implements the same interface as Trellis2Model. New model wrappers can be
9
+ swapped in without touching this file.
10
+
11
+ Output layout — two modes, chosen by whether `output_dir` is given:
12
+
13
+ * **per-game (default, `output_dir=None`)** — resolved by
14
+ `pipeline.common.paths`, so artifacts are grouped by generated game project::
15
+
16
+ test_data/outputs/<game_id>/<run_id>/assets/3d_object/<task_id>/
17
+ ├── model.glb
18
+ └── meta.json
19
+
20
+ * **flat (legacy, `output_dir="..."`)** — writes `<output_dir>/<task_id>.glb`,
21
+ byte-for-byte the historical behaviour. Existing callers are unaffected.
22
+
23
+ Usage:
24
+ from models.gen_3d_object.trellis_2_model import Trellis2Model
25
+ from operators.gen_3d_object.operator import Gen3DObjectOperator
26
+
27
+ model = Trellis2Model(model_path="...")
28
+
29
+ # per-game layout
30
+ op = Gen3DObjectOperator(model=model, run_id="20260731_1032")
31
+
32
+ # legacy flat layout (unchanged)
33
+ op = Gen3DObjectOperator(model=model, output_dir="outputs/3d_object")
34
+
35
+ result = op.run({
36
+ "game_id": "gameA_cyberpunk_shooter", # optional, inferred when omitted
37
+ "task_id": "sword_001",
38
+ "image_path": "path/to/image.png", # or "image": PIL.Image
39
+ "seed": 42,
40
+ })
41
+ print(result["glb_path"])
42
+
43
+ Two optional extras, both additive and off unless asked for:
44
+
45
+ * naming an ``asset_id`` in the task hands the finished mesh to the
46
+ three.js adapter — staged, oriented, manifest rewritten;
47
+ * ``run_art_plan(game_id, image_model)`` generates a whole game's
48
+ recorded art plan (``funcs/art_plan.py``) that way in one call.
49
+
50
+ ``funcs/asset_pack.py`` covers the other case: three CC0 models,
51
+ downloaded and imported in seconds, for when generating is overkill.
52
+
53
+ A third route skips inference entirely. Passing ``spec`` instead of an
54
+ image builds the mesh from a declarative part list
55
+ (``funcs/code_asset.py``), which suits anything exactly describable — a
56
+ crate, a sign, a wheel, a rifle. It needs no model and no GPU, states its
57
+ own facing and size instead of leaving them to be guessed, and keeps its
58
+ parts as named glTF nodes so gameplay can still move them::
59
+
60
+ op = Gen3DObjectOperator(model=None, run_id="20260826_1400")
61
+ op.run({
62
+ "game_id": "gameA_cyberpunk_shooter",
63
+ "task_id": "crate_001",
64
+ "spec": {
65
+ "subject": "wooden supply crate",
66
+ "units": "metres", "forward": "+z",
67
+ "asset_type": "prop", "height_metres": 0.6,
68
+ "parts": [{"id": "body", "kind": "box",
69
+ "size": [0.6, 0.6, 0.6], "at": [0, 0.3, 0]}],
70
+ },
71
+ })
72
+
73
+ The two can be mixed, which is usually the best available answer for a
74
+ detailed hard-surface asset. A ``mesh`` part reads a GLB off disk — one
75
+ component generated by a cloud model — and is placed, measured and gated
76
+ exactly like a primitive. What each side contributes is not
77
+ interchangeable: the generator supplies shapes no formula states (a
78
+ moulded grip's finger swells), and the spec supplies the dimensions and
79
+ placement a prompt cannot specify (a rail's 30 mm slot pitch). Spending
80
+ generation on something a lathe states exactly buys an approximation at a
81
+ hundred times the triangles, and the approximation is the part that can no
82
+ longer be adjusted by editing a number — so the ``provenance`` gate
83
+ reports what was delegated and at what cost::
84
+
85
+ op.run({
86
+ "game_id": "gameA_cyberpunk_shooter",
87
+ "task_id": "rifle_001",
88
+ "spec": {
89
+ "subject": "assault rifle",
90
+ "units": "metres", "forward": "+z",
91
+ "asset_type": "weapon", "height_metres": 0.24,
92
+ "parts": [
93
+ # exact dimensions: stated
94
+ {"id": "receiver", "kind": "box",
95
+ "size": [0.04, 0.048, 0.30], "at": [0, 0.139, -0.03]},
96
+ # moulded surface: fetched, with a uniform `size` so the
97
+ # mesh keeps the proportions it was generated with
98
+ {"id": "grip", "kind": "mesh",
99
+ "source": "parts/grip.glb",
100
+ "size": [0.116, 0.116, 0.116], "at": [0, 0.045, -0.104]},
101
+ ],
102
+ },
103
+ })
104
+ """
105
+ from __future__ import annotations
106
+
107
+ import time
108
+ from pathlib import Path
109
+ from typing import Any, Optional
110
+
111
+ from PIL import Image
112
+
113
+ #: Registered task kind for this operator (see pipeline/common/paths.py).
114
+ TASK_KIND = "3d_object"
115
+
116
+ #: Artifact filename used by the per-game layout.
117
+ GLB_FILENAME = "model.glb"
118
+
119
+
120
+ class Gen3DObjectOperator:
121
+ """
122
+ Operator for 3D object generation.
123
+
124
+ Args:
125
+ model: A loaded model with an `infer_and_save(image, output_path, ...)` method.
126
+ Currently supports Trellis2Model; any model with the same interface works.
127
+ output_dir (str, optional): **Legacy flat mode.** When given, every GLB is
128
+ written as `<output_dir>/<task_id>.glb`, exactly as before. When
129
+ omitted (default), the per-game layout under
130
+ `test_data/outputs/<game_id>/<run_id>/assets/3d_object/<task_id>/`
131
+ is used instead.
132
+ run_id (str): Groups all artifacts of one generation run. Per-game mode only.
133
+ default_game_id (str, optional): Fallback game project for tasks that carry
134
+ no `game_id` and whose input paths reveal none. Per-game mode only.
135
+ """
136
+
137
+ def __init__(
138
+ self,
139
+ model: Any,
140
+ output_dir: Optional[str] = None,
141
+ run_id: str = "default",
142
+ default_game_id: Optional[str] = None,
143
+ ):
144
+ self.model = model
145
+ self.run_id = run_id
146
+ self.default_game_id = default_game_id
147
+ # Legacy flat mode is active only when an explicit output_dir is supplied.
148
+ self.output_dir = Path(output_dir) if output_dir else None
149
+ if self.output_dir is not None:
150
+ self.output_dir.mkdir(parents=True, exist_ok=True)
151
+
152
+ # --------------------------------------------------------------------------
153
+
154
+ def _load_image(self, inp: dict) -> Image.Image:
155
+ """Return a PIL image from an input dict that has 'image_path' or 'image'."""
156
+ if "image" in inp and isinstance(inp["image"], Image.Image):
157
+ return inp["image"]
158
+ if "image_path" in inp:
159
+ p = Path(inp["image_path"])
160
+ if not p.is_absolute() and not p.exists():
161
+ # resolve relative to repo root (codes_official/)
162
+ repo_root = Path(__file__).resolve().parents[2]
163
+ p = repo_root / inp["image_path"]
164
+ return Image.open(str(p)).convert("RGBA")
165
+ raise ValueError("Input must contain 'image_path' (str) or 'image' (PIL.Image).")
166
+
167
+ # --------------------------------------------------------------------------
168
+
169
+ def _artifact_suffix(self) -> str:
170
+ """
171
+ File extension for the artifact — GLB unless the injected model says
172
+ otherwise (the cloud backends can emit FBX / OBJ / USDZ).
173
+
174
+ The result dict keeps the ``glb_path`` key whatever the extension is:
175
+ renaming a returned key breaks `eval.py` and `test/`.
176
+ """
177
+ fmt = getattr(self.model, "output_format", None)
178
+ return str(fmt).lower().lstrip(".") if fmt else "glb"
179
+
180
+ def _resolve_out_path(self, inp: dict, task_id: str) -> tuple[str, Path, Path]:
181
+ """
182
+ Return ``(game_id, task_dir, glb_path)`` for either output mode.
183
+
184
+ Legacy flat mode keeps the historical `<output_dir>/<task_id>.glb`.
185
+ """
186
+ suffix = self._artifact_suffix()
187
+ if self.output_dir is not None:
188
+ game_id = str(inp.get("game_id") or inp.get("game") or "")
189
+ return game_id, self.output_dir, self.output_dir / f"{task_id}.{suffix}"
190
+
191
+ from pipeline.common import paths
192
+ game_id = paths.infer_game_id(inp, fallback=self.default_game_id)
193
+ task_dir = paths.task_output_dir(game_id, TASK_KIND, task_id, run_id=self.run_id)
194
+ filename = GLB_FILENAME if suffix == "glb" else f"model.{suffix}"
195
+ return game_id, task_dir, task_dir / filename
196
+
197
+ # --------------------------------------------------------------------------
198
+
199
+ def run(self, inp: dict) -> dict:
200
+ """
201
+ Generate a 3D object from an image prompt, or build one from a spec.
202
+
203
+ Args:
204
+ inp (dict):
205
+ - image_path (str): path to the reference / concept image
206
+ OR image (PIL.Image): pre-loaded image
207
+ OR spec (dict): a part spec, which builds the mesh instead
208
+ of inferring it (see `funcs/code_asset.py`)
209
+ - compose (dict): combine_avatar arguments, including caller-defined
210
+ socket_definitions, grip_templates and optional slot_definitions
211
+ - game_id (str, optional): game project this task belongs to;
212
+ inferred from `image_path` when omitted
213
+ - task_id (str, optional): used to name the output file / directory
214
+ - seed (int, optional): random seed (default 42)
215
+ - decimation_target (int, optional)
216
+ - texture_size (int, optional)
217
+
218
+ Returns:
219
+ dict:
220
+ - task_id (str)
221
+ - glb_path (str): absolute path to the saved GLB file
222
+ - elapsed_sec (float)
223
+ - game_id (str), task_kind (str), output_dir (str) ← additive
224
+ """
225
+ if inp.get("compose") is not None:
226
+ if inp.get("spec") is not None:
227
+ raise ValueError("provide compose or spec, not both")
228
+ return self._run_compose(inp)
229
+ if inp.get("spec") is not None:
230
+ return self._run_spec(inp)
231
+
232
+ task_id = inp.get("task_id", f"task_{int(time.time())}")
233
+ seed = inp.get("seed", 42)
234
+ decimation_target = inp.get("decimation_target", 1_000_000)
235
+ texture_size = inp.get("texture_size", 4096)
236
+
237
+ game_id, task_dir, out_path = self._resolve_out_path(inp, task_id)
238
+
239
+ text_mode = inp.get("input_mode") == "text_to_3d"
240
+ if text_mode and not str(inp.get("prompt") or "").strip():
241
+ raise ValueError("text_to_3d requires a non-empty prompt")
242
+ image = None if text_mode else self._load_image(inp)
243
+ inference_kwargs = {"prompt": inp["prompt"]} if text_mode else {}
244
+
245
+ t0 = time.time()
246
+ glb_path = self.model.infer_and_save(
247
+ image,
248
+ output_path=str(out_path),
249
+ seed=seed,
250
+ decimation_target=decimation_target,
251
+ texture_size=texture_size,
252
+ **inference_kwargs,
253
+ )
254
+ elapsed = time.time() - t0
255
+
256
+ result = {
257
+ "task_id": task_id,
258
+ "glb_path": glb_path,
259
+ "elapsed_sec": round(elapsed, 2),
260
+ "game_id": game_id,
261
+ "task_kind": TASK_KIND,
262
+ "output_dir": str(task_dir),
263
+ }
264
+
265
+ # Image-to-3D infers a floor under a subject that stands on the edge
266
+ # of its own crop, and it is never wanted: measured at a fifth of the
267
+ # triangle budget, and a grey pancake under the character in the
268
+ # scene. Removing it here means every consumer of this task output
269
+ # gets a clean mesh, rather than each game discovering the slab.
270
+ if inp.get("strip_ground_plate", True):
271
+ from .funcs.mesh_cleanup import strip_ground_plate
272
+
273
+ cleanup = strip_ground_plate(glb_path)
274
+ result["ground_plate"] = cleanup
275
+ if cleanup.get("applied"):
276
+ result.setdefault("warnings", []).append(
277
+ f"removed an inferred floor: {cleanup['plate_count']} "
278
+ f"sheets and {cleanup['debris_count']} loose lumps, "
279
+ f"{cleanup['removed_fraction']:.0%} of the mesh"
280
+ )
281
+ elif cleanup.get("reason") and "nothing" not in cleanup["reason"]:
282
+ result.setdefault("warnings", []).append(
283
+ f"left the mesh alone: {cleanup['reason']}"
284
+ )
285
+
286
+ # meta.json only in per-game mode, so legacy output dirs stay untouched.
287
+ if self.output_dir is None:
288
+ from pipeline.common import paths
289
+ meta = {
290
+ **result,
291
+ "run_id": self.run_id,
292
+ "prompt": inp.get("prompt"),
293
+ "source_image": inp.get("image_path"),
294
+ "seed": seed,
295
+ "decimation_target": decimation_target,
296
+ "texture_size": texture_size,
297
+ "model": type(self.model).__name__,
298
+ }
299
+ for key in ("asset_id", "asset_type", "forward_axis",
300
+ "scale_hint_metres", "notes"):
301
+ if inp.get(key) is not None:
302
+ meta[key] = inp[key]
303
+ # Cloud backends expose what the call cost and produced — task id,
304
+ # credits, triangle count (api_model_require.md R9.8). Recording it
305
+ # here is what makes a billed run reproducible after the fact.
306
+ call_info = getattr(self.model, "last_call_info", None)
307
+ if call_info:
308
+ meta["model_call"] = dict(call_info)
309
+ paths.write_task_meta(task_dir, meta)
310
+
311
+ # Optional handover to the engine adapter, active only when the task
312
+ # names an asset. A generated mesh is not part of a game until the
313
+ # adapter has staged it and recorded which way it faces.
314
+ if inp.get("asset_id") and self.output_dir is None:
315
+ from .funcs.asset_import import import_asset
316
+ result.update(
317
+ import_asset(
318
+ game_id,
319
+ task_id,
320
+ asset_id=str(inp["asset_id"]),
321
+ asset_type=str(inp.get("asset_type") or "prop"),
322
+ run_id=self.run_id,
323
+ forward_axis=str(inp.get("forward_axis") or ""),
324
+ scale_hint_metres=inp.get("scale_hint_metres"),
325
+ verified_by=str(inp.get("verified_by") or "heuristic"),
326
+ notes=str(inp.get("notes") or ""),
327
+ project_hint=str(inp.get("project_hint") or ""),
328
+ preview=bool(inp.get("preview", True)),
329
+ )
330
+ )
331
+
332
+ return result
333
+
334
+ # --------------------------------------------------------------------------
335
+
336
+ def _run_compose(self, inp: dict) -> dict:
337
+ """Resolve caller-configured attachments, then build through the spec route."""
338
+ import json
339
+ from .funcs.code_asset_templates.human_template.combine import (
340
+ combine_avatar, write_report,
341
+ )
342
+
343
+ task_id = inp.get("task_id", f"task_{int(time.time())}")
344
+ _, _, out_path = self._resolve_out_path(inp, task_id)
345
+ directory = out_path.parent / f"{out_path.stem}_compose"
346
+ config = dict(inp["compose"])
347
+ config.setdefault("parts_dir", directory / "parts")
348
+ started = time.time()
349
+ combined = combine_avatar(**config)
350
+ result = self._run_spec({**inp, "task_id": task_id, "spec": combined["spec"]})
351
+ report_path = write_report(combined["report"], directory / "report.json")
352
+ sockets_path = directory / "sockets.json"
353
+ sockets_path.write_text(json.dumps(combined["report"]["sockets"], indent=2),
354
+ encoding="utf-8")
355
+ result["compose"] = {**combined["report"], "report_path": report_path,
356
+ "sockets_path": str(sockets_path)}
357
+ result["elapsed_sec"] = round(time.time() - started, 2)
358
+ return result
359
+
360
+ def _run_spec(self, inp: dict) -> dict:
361
+ """Build the asset from a declarative spec rather than an image.
362
+
363
+ Taken when the task carries a ``spec``. No model is loaded and no
364
+ image is read, so this path works with ``model=None`` — a crate
365
+ does not need a GPU, and requiring one to build a box is what makes
366
+ primitives feel like a defeat rather than a choice.
367
+
368
+ Three things come out of the spec that the generated path can only
369
+ guess at, which is the reason to prefer it wherever it applies:
370
+
371
+ * ``forward_axis`` is *stated*, so the import is recorded as
372
+ ``verified_by="spec"`` rather than ``"heuristic"``. Facing is
373
+ the one property `orientation_review` exists to establish, and
374
+ here there is nothing to establish.
375
+ * ``scale_hint_metres`` is stated, so the mesh has a real size
376
+ instead of a unit box someone has to scale by eye.
377
+ * parts keep their ids as glTF node names, so a wheel can be spun
378
+ after import. A reconstructed mesh is one fused body.
379
+
380
+ ``strip_ground_plate`` is deliberately not run: it removes a floor
381
+ that image-to-3D *invented*, and a spec cannot invent one. Running
382
+ it here would risk deleting a plinth that was asked for.
383
+
384
+ A spec may also carry ``mesh`` parts, which read a GLB off disk —
385
+ typically one component from a cloud model, composed in where no
386
+ formula states the shape. Those change one thing here and nothing
387
+ else: ``verified_by`` drops to ``"spec+generated"``, because a
388
+ generated part's facing was *asserted* by whoever placed it and not
389
+ established by anything. Claiming ``"spec"`` for a composition that
390
+ is largely fetched geometry would put an unverified facing behind the
391
+ one label that is supposed to mean it was not guessed.
392
+ """
393
+ from .funcs.code_asset import MESH_KIND, build_code_asset
394
+
395
+ task_id = inp.get("task_id", f"task_{int(time.time())}")
396
+ game_id, task_dir, out_path = self._resolve_out_path(inp, task_id)
397
+ # A spec always yields glTF, whatever output_format an injected
398
+ # model happens to advertise.
399
+ out_path = out_path.with_suffix(".glb")
400
+ task_dir.mkdir(parents=True, exist_ok=True)
401
+
402
+ t0 = time.time()
403
+ report = build_code_asset(
404
+ inp["spec"],
405
+ str(out_path),
406
+ revise=inp.get("revise"),
407
+ strict=bool(inp.get("strict", True)),
408
+ )
409
+ elapsed = time.time() - t0
410
+
411
+ # Which parts were fetched rather than derived. Carried on the result
412
+ # because after export the two are indistinguishable, and only one of
413
+ # them can still be changed by editing a number: a reviewer who wants
414
+ # the grip 4 mm thicker needs to know that means regenerating it.
415
+ # `long_axis` travels too, since a regenerated part is a new set of
416
+ # axes and the rotation that placed the old one will not place it.
417
+ generated_parts = [
418
+ {
419
+ "id": part["id"],
420
+ "source": part["source"],
421
+ "long_axis": part.get("long_axis"),
422
+ }
423
+ for part in report["spec"]["parts"]
424
+ if part.get("kind") == MESH_KIND
425
+ ]
426
+
427
+ result: dict[str, Any] = {
428
+ "task_id": task_id,
429
+ "glb_path": report["glb_path"],
430
+ "elapsed_sec": round(elapsed, 2),
431
+ "game_id": game_id,
432
+ "task_kind": TASK_KIND,
433
+ "output_dir": str(task_dir),
434
+ "source": "code_asset+generated" if generated_parts else "code_asset",
435
+ "spec_ok": report["ok"],
436
+ "gates": report["gates"],
437
+ "triangles": report["triangles"],
438
+ "bounds": report["bounds"],
439
+ "part_ids": report["part_ids"],
440
+ "generated_parts": generated_parts,
441
+ "stop_reason": report["stop_reason"],
442
+ "attempts": report["attempts"],
443
+ }
444
+ if report["warnings"]:
445
+ result.setdefault("warnings", []).extend(report["warnings"])
446
+ if report["failures"]:
447
+ # Surfaced as warnings on the result *and* kept in `gates`: a
448
+ # gate failure that only appears in a nested dict is the silent
449
+ # early return this whole module is shaped against.
450
+ result.setdefault("warnings", []).extend(
451
+ f"gate: {message}" for message in report["failures"]
452
+ )
453
+
454
+ if self.output_dir is None:
455
+ from pipeline.common import paths
456
+
457
+ meta = {
458
+ **result,
459
+ "run_id": self.run_id,
460
+ "spec": report["spec"],
461
+ "forward_axis": report["forward_axis"],
462
+ "scale_hint_metres": report["scale_hint_metres"],
463
+ "model": "code_asset",
464
+ }
465
+ for key in ("asset_id", "asset_type", "notes"):
466
+ if inp.get(key) is not None:
467
+ meta[key] = inp[key]
468
+ paths.write_task_meta(task_dir, meta)
469
+
470
+ # A failed spec is not handed to the engine. An asset that exists
471
+ # gets used, so a gate failure has to stop it becoming an asset.
472
+ if inp.get("asset_id") and self.output_dir is None and report["ok"]:
473
+ from .funcs.asset_import import import_asset
474
+
475
+ result.update(
476
+ import_asset(
477
+ game_id,
478
+ task_id,
479
+ asset_id=str(inp["asset_id"]),
480
+ asset_type=str(
481
+ inp.get("asset_type")
482
+ or report["spec"].get("asset_type")
483
+ or "prop"
484
+ ),
485
+ run_id=self.run_id,
486
+ # Stated by the spec, not inferred from a view.
487
+ forward_axis=report["forward_axis"],
488
+ scale_hint_metres=report["scale_hint_metres"],
489
+ # "spec" means the facing was stated rather than guessed.
490
+ # With generated parts in the composition that is only
491
+ # half true: the *placement* is stated, but the mesh
492
+ # inside it came from a generator with no facing of its
493
+ # own, and whoever wrote the rotation asserted one. Said
494
+ # distinctly so a reviewer knows an orientation check is
495
+ # still worth a look, instead of trusting a label that
496
+ # was earned by a different route.
497
+ verified_by="spec+generated" if generated_parts else "spec",
498
+ notes=str(inp.get("notes") or "")
499
+ or (
500
+ f"Built from a spec: {report['subject']}."
501
+ + (
502
+ f" {len(generated_parts)} generated part(s): "
503
+ f"{', '.join(part['id'] for part in generated_parts)}."
504
+ if generated_parts else ""
505
+ )
506
+ ),
507
+ project_hint=str(inp.get("project_hint") or ""),
508
+ preview=bool(inp.get("preview", True)),
509
+ )
510
+ )
511
+ return result
512
+
513
+ # --------------------------------------------------------------------------
514
+
515
+ def run_art_plan(
516
+ self,
517
+ game_id: str,
518
+ image_model: Any = None,
519
+ plan: Optional[list[dict]] = None,
520
+ assets: tuple[str, ...] = (),
521
+ ) -> list[dict]:
522
+ """
523
+ Generate a game's recorded art plan and import each asset.
524
+
525
+ The plan lives in `funcs/art_plan.py`; it names a subject, an asset
526
+ type and a **height in metres**, because a mesh normalised into a
527
+ unit box has no size of its own. Concept images come from
528
+ `image_model` unless an entry points at one.
529
+
530
+ Facing is recorded as `heuristic`, never as verified: single-image
531
+ reconstruction puts the input view on a predictable axis, but a
532
+ guess labelled as checked stops anyone checking. Each import leaves
533
+ a review sheet for `agent_skills/asset_qa/`.
534
+ """
535
+ from .funcs.art_plan import concept_image, plan_for_game
536
+
537
+ entries = plan if plan is not None else plan_for_game(game_id)
538
+ if not entries:
539
+ raise ValueError(
540
+ f"No art plan for {game_id!r}; add one to "
541
+ "operators/gen_3d_object/funcs/art_plan.py"
542
+ )
543
+
544
+ results: list[dict] = []
545
+ for entry in entries:
546
+ if assets and entry["asset_id"] not in assets:
547
+ continue
548
+ image, provenance, framing = concept_image(entry, image_model)
549
+ task_dir = Path(
550
+ self._resolve_out_path(
551
+ {"game_id": game_id}, entry["task_id"]
552
+ )[1]
553
+ )
554
+ task_dir.mkdir(parents=True, exist_ok=True)
555
+ # Keep the concept image beside the mesh it produced: a bad
556
+ # asset is almost always a bad concept image, and that is not
557
+ # diagnosable after the fact if the input was thrown away.
558
+ image.save(task_dir / "concept.png")
559
+ result = self.run(
560
+ {
561
+ "game_id": game_id,
562
+ "task_id": entry["task_id"],
563
+ "image": image,
564
+ "prompt": entry["full_prompt"],
565
+ "seed": entry.get("seed", 42),
566
+ "decimation_target": entry["triangles"],
567
+ "texture_size": entry["texture"],
568
+ "asset_id": entry["asset_id"],
569
+ "asset_type": entry["type"],
570
+ "forward_axis": entry["faces"],
571
+ "scale_hint_metres": entry["height"],
572
+ "verified_by": "heuristic",
573
+ "notes": entry["notes"]
574
+ or f"Generated from: {provenance}. Facing assumed "
575
+ "from the input view.",
576
+ }
577
+ )
578
+ result["asset_id"] = entry["asset_id"]
579
+ result["concept_source"] = provenance
580
+ result["framing"] = framing
581
+ if framing.get("touched_border"):
582
+ # The subject ran off the edge of the generated image, so
583
+ # part of it was never drawn. Cropping cannot invent it.
584
+ result.setdefault("warnings", []).append(
585
+ "the concept image was cropped at the border, so the "
586
+ "mesh is probably truncated: regenerate with another "
587
+ "seed"
588
+ )
589
+ results.append(result)
590
+ return results
591
+
592
+ # --------------------------------------------------------------------------
593
+
594
+ def run_batch(self, inputs: list[dict]) -> list[dict]:
595
+ """Run a list of input dicts sequentially and return results."""
596
+ return [self.run(inp) for inp in inputs]
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/paths.py ADDED
@@ -0,0 +1,444 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ pipeline/common/paths.py
3
+
4
+ Single source of truth for every input / output path in 3AGameFactory.
5
+
6
+ The benchmark is authored **per game project**, so outputs are organized the same
7
+ way. An artifact is uniquely addressed by ``(game_id, run_id, task_kind, task_id)``::
8
+
9
+ test_data/test_samples/<game_id>/<TaskDir>/... # inputs (read-only)
10
+ test_data/outputs/<game_id>/<run_id>/<layer>/<task_kind>/<task_id>/ # outputs
11
+
12
+ Full output tree::
13
+
14
+ test_data/outputs/ # OUTPUT_ROOT ($AAAGF_OUTPUT_ROOT)
15
+ └── gameA_cyberpunk_shooter/ # one dir per generated game project
16
+ ├── latest -> 20260731_1032/ # symlink to the most recent run
17
+ └── <run_id>/ # "default", or a timestamp
18
+ ├── run_meta.json # ckpts · seeds · git sha · argv
19
+ ├── assets/
20
+ │ ├── 3d_object/<task_id>/ # model.glb + meta.json
21
+ │ ├── tpose/<task_id>/ # tpose_fg.png + meta.json
22
+ │ ├── 3d_scene/<task_id>/
23
+ │ ├── motion/<task_id>/
24
+ │ ├── cg_video/<task_id>/
25
+ │ └── audio/<task_id>/ # dialogue / sound-effect audio + meta.json
26
+ ├── mechanic/<task_id>/ # engine project + demo_outputs/ + launch.sh
27
+ ├── ui/<task_id>/
28
+ ├── pipeline/<task_id>/ # end-to-end game-slice artifacts
29
+ └── eval/
30
+ ├── <task_kind>/<task_id>/ # metrics.json · build.log · judge_log.json
31
+ └── summary.json # aggregate over the whole run
32
+
33
+ The root stays next to the test set so any evaluator finds inputs and outputs side
34
+ by side. Generated artifacts get large — point ``$AAAGF_OUTPUT_ROOT`` at a scratch
35
+ disk to relocate the whole tree without touching code.
36
+
37
+ This module has **no third-party dependencies** and imports no models, so it is
38
+ safe to import from anywhere (including CPU-only tooling and tests).
39
+ """
40
+ from __future__ import annotations
41
+
42
+ import json
43
+ import os
44
+ import subprocess
45
+ import sys
46
+ from datetime import datetime
47
+ from pathlib import Path
48
+ from typing import Any, Optional
49
+
50
+ # ── Roots ─────────────────────────────────────────────────────────────────────
51
+
52
+ REPO_ROOT = Path(__file__).resolve().parents[2]
53
+
54
+ TEST_DATA_ROOT = REPO_ROOT / "test_data"
55
+ TEST_SAMPLES_ROOT = TEST_DATA_ROOT / "test_samples"
56
+
57
+ #: Output root. Override with ``export AAAGF_OUTPUT_ROOT=/scratch/aaagf_outputs``.
58
+ OUTPUT_ROOT = Path(
59
+ os.environ.get("AAAGF_OUTPUT_ROOT", TEST_DATA_ROOT / "outputs")
60
+ ).expanduser()
61
+
62
+ #: Used when a task carries no game association (ad-hoc single-image demos).
63
+ UNASSIGNED_GAME = "_scratch"
64
+
65
+ #: Run id used when the caller does not ask for a fresh timestamped one.
66
+ DEFAULT_RUN_ID = "default"
67
+
68
+ LATEST_LINK = "latest"
69
+
70
+
71
+ # ── Task kinds ────────────────────────────────────────────────────────────────
72
+
73
+ #: task_kind -> layer directory. Layer A = assets, B = mechanic, C = ui.
74
+ TASK_LAYER: dict[str, str] = {
75
+ # Layer A — asset generation
76
+ "3d_object": "assets",
77
+ "tpose": "assets",
78
+ "3d_scene": "assets",
79
+ "motion": "assets",
80
+ "cg_video": "assets",
81
+ "audio": "assets",
82
+ # Game design (story / chapters / asset & screen plan) — A-layer diagnostic only
83
+ "design": "design",
84
+ # Layer B / C — code generation
85
+ "mechanic": "mechanic",
86
+ "ui": "ui",
87
+ # End-to-end vertical slice
88
+ "pipeline": "pipeline",
89
+ # Whitebox-stage game evaluation (stage-1 LLM/Agent whitebox rubric) —
90
+ # an eval-only kind: results land under ``eval/whitebox/<task_id>/``
91
+ "whitebox": "whitebox",
92
+ }
93
+
94
+ #: task_kind -> directory name inside ``test_samples/<game_id>/``.
95
+ TASK_INPUT_DIR: dict[str, str] = {
96
+ "3d_object": "3D_object",
97
+ "tpose": "tpose",
98
+ "3d_scene": "3D_scene",
99
+ "motion": "motion",
100
+ "cg_video": "cg_video",
101
+ "audio": "audio",
102
+ "design": "design",
103
+ "mechanic": "mechanic",
104
+ "ui": "ui",
105
+ "pipeline": "pipeline",
106
+ # whitebox case inputs (game_spec/rubric/references) live under
107
+ # ``test_bench_example/<case>/``; this dir keeps the registration
108
+ # complete for the shared task-input helpers.
109
+ "whitebox": "whitebox",
110
+ }
111
+
112
+ #: task_kind -> per-game task list filename inside ``TASK_INPUT_DIR``.
113
+ TASK_JSONL: dict[str, str] = {
114
+ "3d_object": "object_tasks.jsonl",
115
+ "tpose": "tpose_tasks.jsonl",
116
+ "3d_scene": "scene_tasks.jsonl",
117
+ "motion": "motion_tasks.jsonl",
118
+ "cg_video": "cg_tasks.jsonl",
119
+ "audio": "audio_tasks.jsonl",
120
+ "design": "design_tasks.jsonl",
121
+ "mechanic": "mechanic_tasks.jsonl",
122
+ "ui": "ui_tasks.jsonl",
123
+ "pipeline": "pipeline_task.jsonl",
124
+ "whitebox": "whitebox_tasks.jsonl",
125
+ }
126
+
127
+ #: task_kind -> cross-game aggregate jsonl under ``test_samples/``.
128
+ TASK_COLLECT_JSONL: dict[str, str] = {
129
+ "3d_object": "3D_object_gen_collect.jsonl",
130
+ "tpose": "tpose_gen_collect.jsonl",
131
+ "3d_scene": "3D_scene_gen_collect.jsonl",
132
+ "motion": "motion_gen_collect.jsonl",
133
+ "cg_video": "cg_video_collect.jsonl",
134
+ "audio": "audio_gen_collect.jsonl",
135
+ "design": "design_collect.jsonl",
136
+ "mechanic": "mechanic_collect.jsonl",
137
+ "ui": "ui_collect.jsonl",
138
+ "pipeline": "pipeline_collect.jsonl",
139
+ "whitebox": "whitebox_collect.jsonl",
140
+ }
141
+
142
+ #: Layer-A kinds only — what ``pipeline/assets_gen/`` covers.
143
+ ASSET_TASK_KINDS = tuple(k for k, v in TASK_LAYER.items() if v == "assets")
144
+
145
+
146
+ def check_kind(task_kind: str) -> str:
147
+ """Raise a helpful error for an unregistered task kind."""
148
+ if task_kind not in TASK_LAYER:
149
+ raise ValueError(
150
+ f"Unknown task_kind {task_kind!r}. Register it in "
151
+ f"pipeline/common/paths.py first. Known: {sorted(TASK_LAYER)}"
152
+ )
153
+ return task_kind
154
+
155
+
156
+ # ── Input paths ───────────────────────────────────────────────────────────────
157
+
158
+ def game_input_dir(game_id: str) -> Path:
159
+ """``test_data/test_samples/<game_id>/``"""
160
+ return TEST_SAMPLES_ROOT / game_id
161
+
162
+
163
+ def task_input_dir(game_id: str, task_kind: str) -> Path:
164
+ """``test_data/test_samples/<game_id>/<TaskDir>/``"""
165
+ return game_input_dir(game_id) / TASK_INPUT_DIR[check_kind(task_kind)]
166
+
167
+
168
+ def task_jsonl(game_id: str, task_kind: str) -> Path:
169
+ """``test_data/test_samples/<game_id>/<TaskDir>/<kind>_tasks.jsonl``"""
170
+ return task_input_dir(game_id, task_kind) / TASK_JSONL[check_kind(task_kind)]
171
+
172
+
173
+ def collect_jsonl(task_kind: str) -> Path:
174
+ """``test_data/test_samples/<kind>_collect.jsonl`` — cross-game task list."""
175
+ return TEST_SAMPLES_ROOT / TASK_COLLECT_JSONL[check_kind(task_kind)]
176
+
177
+
178
+ def resolve_tasks_path(task_kind: str, tasks: str | None = None,
179
+ game_id: str | None = None) -> Path:
180
+ """
181
+ Standard task-list resolution shared by every ``run.py`` / ``eval.py``:
182
+
183
+ explicit ``--tasks`` → the game's own ``*_tasks.jsonl`` (if non-empty)
184
+ → the cross-game ``*_collect.jsonl``.
185
+ """
186
+ if tasks:
187
+ return resolve_input_path(tasks)
188
+ if game_id:
189
+ per_game = task_jsonl(game_id, task_kind)
190
+ if per_game.exists() and per_game.stat().st_size > 0:
191
+ return per_game
192
+ return collect_jsonl(task_kind)
193
+
194
+
195
+ def list_games() -> list[str]:
196
+ """Every game project directory present in the test set."""
197
+ if not TEST_SAMPLES_ROOT.is_dir():
198
+ return []
199
+ return sorted(
200
+ p.name
201
+ for p in TEST_SAMPLES_ROOT.iterdir()
202
+ if p.is_dir() and not p.name.startswith((".", "_"))
203
+ )
204
+
205
+
206
+ def infer_game_id(task: dict, fallback: Optional[str] = None) -> str:
207
+ """
208
+ Resolve which game project a task belongs to.
209
+
210
+ Priority: explicit ``game_id`` / ``game`` field → any path-like field that
211
+ sits under ``test_samples/<game_id>/`` → ``fallback`` → ``UNASSIGNED_GAME``.
212
+ """
213
+ for key in ("game_id", "game"):
214
+ if task.get(key):
215
+ return str(task[key])
216
+
217
+ for value in task.values():
218
+ if not isinstance(value, str) or "test_samples" not in value:
219
+ continue
220
+ parts = Path(value).parts
221
+ if "test_samples" in parts:
222
+ idx = parts.index("test_samples")
223
+ if idx + 1 < len(parts):
224
+ return parts[idx + 1]
225
+
226
+ return fallback or UNASSIGNED_GAME
227
+
228
+
229
+ def iter_tasks(tasks_path: str | Path, game_filter: str | None = None):
230
+ """
231
+ Yield ``(task_dict, game_id)`` from a jsonl, skipping blanks and comments.
232
+
233
+ Every runner should iterate through this so `game_id` resolution and the
234
+ `--game` filter behave identically across tasks.
235
+ """
236
+ with open(tasks_path) as f:
237
+ for lineno, line in enumerate(f, 1):
238
+ line = line.strip()
239
+ if not line or line.startswith("//"):
240
+ continue
241
+ try:
242
+ task = json.loads(line)
243
+ except json.JSONDecodeError as e:
244
+ raise ValueError(f"{tasks_path}:{lineno} is not valid JSON: {e}") from e
245
+ game_id = infer_game_id(task)
246
+ if game_filter and game_id != game_filter:
247
+ continue
248
+ yield task, game_id
249
+
250
+
251
+ # ── Output paths ──────────────────────────────────────────────────────────────
252
+
253
+ def new_run_id(prefix: str = "") -> str:
254
+ """Timestamped run id, e.g. ``20260731_103200`` or ``qwen3b_20260731_103200``."""
255
+ stamp = datetime.now().strftime("%Y%m%d_%H%M%S")
256
+ return f"{prefix}_{stamp}" if prefix else stamp
257
+
258
+
259
+ def game_output_dir(game_id: str) -> Path:
260
+ """``test_data/outputs/<game_id>/``"""
261
+ return OUTPUT_ROOT / game_id
262
+
263
+
264
+ def run_dir(game_id: str, run_id: str = DEFAULT_RUN_ID) -> Path:
265
+ """``test_data/outputs/<game_id>/<run_id>/`` — root of one generation run."""
266
+ return game_output_dir(game_id) / run_id
267
+
268
+
269
+ def task_output_dir(
270
+ game_id: str,
271
+ task_kind: str,
272
+ task_id: str,
273
+ run_id: str = DEFAULT_RUN_ID,
274
+ create: bool = True,
275
+ ) -> Path:
276
+ """
277
+ ``test_data/outputs/<game_id>/<run_id>/<layer>/[<task_kind>/]<task_id>/``
278
+
279
+ One directory per task, so an artifact ships alongside its preview,
280
+ intermediates and ``meta.json`` without filename mangling.
281
+ """
282
+ check_kind(task_kind)
283
+ layer = TASK_LAYER[task_kind]
284
+ base = run_dir(game_id, run_id) / layer
285
+ # assets/ is further split by kind; mechanic/ ui/ pipeline/ *are* the kind.
286
+ if layer == "assets":
287
+ base = base / task_kind
288
+ path = base / task_id
289
+ if create:
290
+ path.mkdir(parents=True, exist_ok=True)
291
+ return path
292
+
293
+
294
+ def eval_output_dir(
295
+ game_id: str,
296
+ task_kind: str,
297
+ task_id: str,
298
+ run_id: str = DEFAULT_RUN_ID,
299
+ create: bool = True,
300
+ ) -> Path:
301
+ """``test_data/outputs/<game_id>/<run_id>/eval/<task_kind>/<task_id>/``"""
302
+ check_kind(task_kind)
303
+ path = run_dir(game_id, run_id) / "eval" / task_kind / task_id
304
+ if create:
305
+ path.mkdir(parents=True, exist_ok=True)
306
+ return path
307
+
308
+
309
+ def eval_summary_path(game_id: str, run_id: str = DEFAULT_RUN_ID) -> Path:
310
+ """``test_data/outputs/<game_id>/<run_id>/eval/summary.json``"""
311
+ return run_dir(game_id, run_id) / "eval" / "summary.json"
312
+
313
+
314
+ def results_summary_path(game_id: str, task_kind: str,
315
+ run_id: str = DEFAULT_RUN_ID) -> Path:
316
+ """``test_data/outputs/<game_id>/<run_id>/<task_kind>_results_summary.json``"""
317
+ check_kind(task_kind)
318
+ return run_dir(game_id, run_id) / f"{task_kind}_results_summary.json"
319
+
320
+
321
+ def run_meta_path(game_id: str, run_id: str = DEFAULT_RUN_ID) -> Path:
322
+ """``test_data/outputs/<game_id>/<run_id>/run_meta.json``"""
323
+ return run_dir(game_id, run_id) / "run_meta.json"
324
+
325
+
326
+ # ── Run bookkeeping ───────────────────────────────────────────────────────────
327
+
328
+ def _git_sha() -> Optional[str]:
329
+ try:
330
+ out = subprocess.run(
331
+ ["git", "-C", str(REPO_ROOT), "rev-parse", "--short", "HEAD"],
332
+ capture_output=True, text=True, timeout=5,
333
+ )
334
+ return out.stdout.strip() or None
335
+ except Exception:
336
+ return None
337
+
338
+
339
+ def update_latest_link(game_id: str, run_id: str) -> None:
340
+ """Repoint ``<game_id>/latest`` at ``run_id`` (best effort, never fatal)."""
341
+ if run_id == LATEST_LINK:
342
+ return
343
+ link = game_output_dir(game_id) / LATEST_LINK
344
+ try:
345
+ link.parent.mkdir(parents=True, exist_ok=True)
346
+ if link.is_symlink() or link.exists():
347
+ link.unlink()
348
+ link.symlink_to(run_id, target_is_directory=True)
349
+ except OSError:
350
+ pass # filesystem without symlink support — not fatal
351
+
352
+
353
+ def write_run_meta(
354
+ game_id: str,
355
+ run_id: str = DEFAULT_RUN_ID,
356
+ *,
357
+ task_kind: Optional[str] = None,
358
+ extra: Optional[dict[str, Any]] = None,
359
+ ) -> Path:
360
+ """Record how a run was produced, so results stay reproducible."""
361
+ path = run_meta_path(game_id, run_id)
362
+ path.parent.mkdir(parents=True, exist_ok=True)
363
+
364
+ meta: dict[str, Any] = {
365
+ "game_id": game_id,
366
+ "run_id": run_id,
367
+ "task_kind": task_kind,
368
+ "created_at": datetime.now().isoformat(timespec="seconds"),
369
+ "git_sha": _git_sha(),
370
+ "argv": sys.argv,
371
+ }
372
+ if extra:
373
+ meta.update(extra)
374
+
375
+ if path.exists(): # merge with an earlier task_kind in the same run
376
+ try:
377
+ prev = json.loads(path.read_text(encoding="utf-8"))
378
+ history = prev.pop("history", [])
379
+ history.append(prev)
380
+ meta["history"] = history
381
+ except (json.JSONDecodeError, OSError):
382
+ pass
383
+
384
+ path.write_text(json.dumps(meta, indent=2, ensure_ascii=False), encoding="utf-8")
385
+ return path
386
+
387
+
388
+ def write_task_meta(task_dir: str | Path, meta: dict[str, Any]) -> Path:
389
+ """Write ``<task_dir>/meta.json`` next to the artifacts."""
390
+ d = Path(task_dir)
391
+ d.mkdir(parents=True, exist_ok=True)
392
+ path = d / "meta.json"
393
+ from .record_paths import portable_value
394
+ path.write_text(json.dumps(portable_value(meta, d), indent=2, ensure_ascii=False, default=str),
395
+ encoding="utf-8")
396
+ return path
397
+
398
+
399
+ def write_results_summary(results: list[dict], task_kind: str,
400
+ run_id: str = DEFAULT_RUN_ID) -> list[Path]:
401
+ """
402
+ Group ``run()`` results by ``game_id`` and write one summary per game,
403
+ refresh ``run_meta.json`` and the ``latest`` symlink.
404
+
405
+ Returns the summary paths written.
406
+ """
407
+ check_kind(task_kind)
408
+ grouped: dict[str, list[dict]] = {}
409
+ for r in results:
410
+ grouped.setdefault(r.get("game_id") or UNASSIGNED_GAME, []).append(r)
411
+
412
+ written = []
413
+ for game_id, items in grouped.items():
414
+ path = results_summary_path(game_id, task_kind, run_id)
415
+ path.parent.mkdir(parents=True, exist_ok=True)
416
+ path.write_text(json.dumps(items, indent=2, ensure_ascii=False, default=str),
417
+ encoding="utf-8")
418
+ write_run_meta(game_id, run_id, task_kind=task_kind,
419
+ extra={"num_tasks": len(items)})
420
+ update_latest_link(game_id, run_id)
421
+ written.append(path)
422
+ return written
423
+
424
+
425
+ # ── Misc ──────────────────────────────────────────────────────────────────────
426
+
427
+ def resolve_input_path(path_like: str | Path) -> Path:
428
+ """Resolve a possibly repo-relative input path (jsonl paths are repo-relative)."""
429
+ if str(path_like).replace("\\", "/").startswith("bench/"):
430
+ from .record_paths import resolve_path
431
+ return resolve_path(path_like)
432
+ p = Path(path_like)
433
+ if p.is_absolute() or p.exists():
434
+ return p
435
+ return REPO_ROOT / p
436
+
437
+
438
+ def rel_to_repo(path: str | Path) -> str:
439
+ """Repo-relative string if possible, else the absolute path — for logs / meta."""
440
+ p = Path(path).resolve()
441
+ try:
442
+ return str(p.relative_to(REPO_ROOT))
443
+ except ValueError:
444
+ return str(p)
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/record_paths.py ADDED
@@ -0,0 +1,77 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """Portable workspace paths for persisted records; resolve only when doing I/O."""
2
+ from __future__ import annotations
3
+
4
+ from pathlib import Path
5
+ import re
6
+
7
+ BENCH = Path(__file__).resolve().parents[3]
8
+ _PREFIXES = ("test_data/", "GameFactory-3A/", "scripts/", "prompts/", "config/", "reports/")
9
+ _ROOT = BENCH.as_posix()
10
+ _INLINE_ROOT = re.compile(re.escape(_ROOT).replace("/", r"[\\/]"), re.IGNORECASE)
11
+
12
+
13
+ def resolve_path(value: str | Path) -> Path:
14
+ text = str(value).replace("\\", "/")
15
+ if text == "bench" or text.startswith("bench/"):
16
+ path = (BENCH.parent / text).resolve()
17
+ path.relative_to(BENCH.resolve())
18
+ return path
19
+ path = Path(value)
20
+ return path if path.is_absolute() else BENCH / path
21
+
22
+
23
+ def portable_path(value: str | Path, base: Path | None = None) -> str:
24
+ original = str(value)
25
+ text = original.replace("\\", "/")
26
+ if re.match(r"^[A-Za-z][A-Za-z0-9+.-]*:", text) and not re.match(r"^[A-Za-z]:/", text):
27
+ return original # URLs, API URIs and dependency descriptors retain their meaning.
28
+ if text.casefold() == _ROOT.casefold() or text.casefold().startswith(_ROOT.casefold() + "/"):
29
+ return "bench" + text[len(_ROOT):]
30
+ if text == "bench" or text.startswith("bench/"):
31
+ path = resolve_path(text)
32
+ suffix = path.relative_to(BENCH.resolve()).as_posix()
33
+ return "bench" if suffix == "." else "bench/" + suffix
34
+ if text.startswith(_PREFIXES):
35
+ path = (BENCH / text).resolve()
36
+ path.relative_to(BENCH.resolve())
37
+ return "bench/" + path.relative_to(BENCH.resolve()).as_posix()
38
+ if base is not None and "/" in text and "\n" not in text and not text.startswith("/"):
39
+ candidate = base / text
40
+ try:
41
+ if candidate.exists():
42
+ return "bench/" + candidate.resolve().relative_to(BENCH.resolve()).as_posix()
43
+ except (OSError, ValueError):
44
+ pass
45
+ return original
46
+
47
+
48
+ def portable_text(value: str) -> str:
49
+ """Convert workspace paths embedded in log/error text, leaving URLs intact."""
50
+ pattern = re.compile(r"(?:https?://[^\s<>]+)|(" + _INLINE_ROOT.pattern + r"(?:[\\/][^\r\n\"'<>|;,)]*)?)", re.IGNORECASE)
51
+ return pattern.sub(lambda match: portable_path(match.group(1)) if match.group(1) else match.group(0), value)
52
+
53
+
54
+ def portable_value(value, base: Path | None = None):
55
+ if isinstance(value, dict):
56
+ return {portable_path(key) if isinstance(key, str) else key: portable_value(item, base)
57
+ for key, item in value.items()}
58
+ if isinstance(value, (list, tuple)):
59
+ return [portable_value(item, base) for item in value]
60
+ if isinstance(value, Path):
61
+ return portable_path(value, base)
62
+ if isinstance(value, str):
63
+ result = portable_path(value, base)
64
+ return portable_text(result)
65
+ return value
66
+
67
+
68
+ def runtime_value(value):
69
+ """Hydrate a verified frozen plan for runtime use; never use before hashing."""
70
+ if isinstance(value, dict):
71
+ return {str(resolve_path(key)) if isinstance(key, str) and (key == "bench" or key.startswith("bench/")) else key:
72
+ runtime_value(item) for key, item in value.items()}
73
+ if isinstance(value, list):
74
+ return [runtime_value(item) for item in value]
75
+ if isinstance(value, str) and (value == "bench" or value.startswith("bench/")):
76
+ return str(resolve_path(value))
77
+ return value
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/prompts/stage2_assets.md ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # GameFactory-3A Stage 2 — asset generation
2
+
3
+ 你正在执行同一个游戏测例的第二阶段资产生成。**开始前必须先阅读 `{SETTING_OVERVIEW}`，并严格遵循其中的 asset refinement、asset QA 和 validation 流程。**
4
+
5
+ ## 测例输入
6
+
7
+ - 游戏测例：`{GAME_ID}`
8
+ - 测例目录：`{CASE_ROOT}`
9
+ - GameFactory-3A 根目录：`{FRAMEWORK_ROOT}`
10
+ - 总入口文档：`{SETTING_OVERVIEW}`
11
+ - 目标引擎：`{ENGINE}`
12
+ - 完整游戏需求：`{GENERAL_REQUIREMENT}`
13
+ - 当前 run 根目录：`{RUN_ROOT}`
14
+ - runner 控制面（冻结索引、prompt/packet/log）：`{GENERATION_CONTROL_ROOT}`
15
+ - 第一阶段白模 run：`{WHITEBOX_RUN_ROOT}`
16
+ - 第一阶段白模 workspace：`{WHITEBOX_WORKSPACE}`
17
+ - 第一阶段资产接口：`{ASSET_SLOTS}`
18
+ - 第一阶段计划/TODO：`{GENERATION_PLAN}`
19
+ - 外部冻结的资产任务索引：`{ASSET_TASK_INDEX}`
20
+ - 资产输出根目录：`{ASSET_OUTPUT_ROOT}`
21
+ - 当前阶段 pipeline task 目录：`{STAGE_WORKSPACE}`
22
+ - 资产 QA 证据根：`{RUN_ROOT}/eval/<task_kind>/<task_id>/`
23
+
24
+ 请读取游戏完整梗概和玩法，再读取 `{ASSET_TASK_INDEX}` 中列出的**每一条**资产任务、对应的 requirement、JSONL 和参考图片。**每一个资产生成任务都必须使用完整游戏梗概作为上下文**，不能只把孤立的资产 prompt 交给生成流程。
25
+
26
+ ## 本阶段任务
27
+
28
+ 1. 根据第一阶段的任务拆解、TODO 和 `asset_slots.json` 确认资产用途、生命周期、比例、朝向、挂点和风格；
29
+ 2. 按 `setting_overview.md` 路由到对应的 T-pose、3D object、3D scene、Motion、Audio、CG video 或其他资产 Skill；
30
+ 3. 逐项生成冻结任务索引中的所有资产，并执行对应的结构/视觉 QA；
31
+ 4. 保持第一阶段定义的 asset ID 和游戏/UI/mechanic contract 不变；
32
+ 5. 记录资产来源、配置、参考图、QA 和后续导入要求；
33
+ 6. 生成完整的资产 manifest，供第三阶段导入使用。
34
+
35
+ ## 限制
36
+
37
+ - 不修改第一阶段核心游戏机制和需求；
38
+ - 不擅自删除、合并或跳过资产任务；
39
+ - 资产失败必须记录为失败，不能伪造成功；
40
+ - 不将资产生成 QA 当成游戏已经完成；
41
+ - 本阶段默认不执行 Agent repair。
42
+
43
+ ## 输出位置和 Layer 规则
44
+
45
+ 资产必须按框架标准布局写入：
46
+
47
+ - `{ASSET_OUTPUT_ROOT}/tpose/<task_id>/`；
48
+ - `{ASSET_OUTPUT_ROOT}/3d_object/<task_id>/`；
49
+ - `{ASSET_OUTPUT_ROOT}/3d_scene/<task_id>/`；
50
+ - `{ASSET_OUTPUT_ROOT}/motion/<task_id>/`；
51
+ - `{ASSET_OUTPUT_ROOT}/audio/<task_id>/`；
52
+ - `{ASSET_OUTPUT_ROOT}/cg_video/<task_id>/`。
53
+
54
+ 每个任务目录至少应有资产文件、`meta.json`、预览（若适用）和 QA 证据。资产 manifest 和阶段产物说明写入 `{ASSET_MANIFEST}`（位于标准 `pipeline/<task_id>/` task 目录）；冻结索引只读自 `{ASSET_TASK_INDEX}`，runner 控制文件写入 `{GENERATION_CONTROL_ROOT}`。每个资产任务的 QA 证据写入 `{RUN_ROOT}/eval/<task_kind>/<task_id>/`。至少生成：
55
+
56
+ - `asset_manifest.json`；
57
+ - `asset_generation_report.json`；
58
+ - `asset_task_index.json`（由外部入口生成，不得删改任务）；
59
+ - 失败任务及其失败原因。
60
+
61
+ 不要写入 case 输入目录、不要覆盖白模 run，也不要创建 `pipeline/assets/` stage 目录；真实资产必须按 `assets/<task_kind>/<task_id>/` 放置，不能把所有文件平铺在 pipeline task 目录。
62
+
63
+ ## 已确认的优先 3D Object 双服务对比
64
+
65
+ 当用户明确选择优先 200 条对象任务的 Meshy / Tripo API 对比时，使用
66
+ `scripts/asset/generate_3d_comparison.py` 与 `config/asset_3d_comparison.json`，
67
+ 具体命令和费用见 `scripts/asset/README_3d_comparison.md`。这是跨游戏的对象生成实验；
68
+ 各游戏只包含 3D Object 子集，不能将其标为六类资产齐全的完整 Stage 2。
69
+
70
+ - 输入以 `test_data/priority_gen/3d_object_priority_lowpoly_collect.jsonl` 的全部 200 条为准，
71
+ 保留原 task ID、prompt、seed、参考图及最高 8000 三角面的既定政策。
72
+ - 完整游戏需求保留在冻结输入包；两家文生调用使用完全相同的短梗概和原资产 prompt，
73
+ 合计不超过 800 字符。API 未接收完整正文这一事实必须记录，不能宣称正文已送入模型。
74
+ - 两家图生均使用同一冻结参考图，列入 `reference_only` 辅助组；不要为了补文字上下文
75
+ 悄悄改图、另画参考图、改变原任务的输入模式或仅给一家添加贴图提示词。
76
+ - 每家分别运行全部 200 条。按人物/刚体、文生/图生及上下文条件分组；Hunyuan3D Pro
77
+ 仅保留后续接入口，本轮不启用、不消耗第三家额度。
78
+ - 固定具体模型版本，不使用 `latest`；Meshy 本轮使用 standard + remesh，
79
+ 不依赖将于 2026-10-30 退役的 `model_type=lowpoly`。
80
+ - 原始 API mesh 写为 `model.glb`，统一后处理的导入 mesh 写为 `import/model.glb`。
81
+ 两家使用同一固定工具、参数与贴���上限；分别记录原始和后处理 QA、耗时及缺陷。
82
+ 减面未达到预算应如实记录失败，不增加生成次数、不换模型补齐或挑选 best-of。
83
+ - 付费调用前需要用户确认预算并在环境中配置密钥。提交后立刻落盘任务 ID；
84
+ 已知远端任务只续查结果，提交结果不确定时停下核对，不自动重发付费任务。
85
+ - 本轮按游戏级共享资产目录落盘，在任务目录下加厂商一级：
86
+ `test_data/outputs/<game_id>/assets/3d_object/<task_id>/<provider>/`，
87
+ `<provider>` 为 `meshy` / `tripo`，不使用 `asset_comparison` 输出目录。
88
+ 原始 `model.glb`、`import/model.glb`、`meta.json`、服务端预览均放在厂商目录内；
89
+ QA 写入 `test_data/outputs/<game_id>/eval/3d_object/<task_id>/<provider>/`。
90
+ manifest/阶段报告按游戏、批次、厂商放在
91
+ `test_data/outputs/<game_id>/pipeline/<game_id>_pipeline/<batch_id>/<provider>/`，
92
+ 冻结输入、计费回执与跨游戏预览保存在 `test_data/outputs/_asset_batches/<batch_id>/`。
93
+ 不覆盖不同批次已有的厂商资产，也不覆盖白模工程。
94
+ 结构检查通过不等于视觉 QA 通过；C、Q1/Q2/Q3 的正式评分缺少证据时保持 UNKNOWN。
95
+ 第三阶段的资产来源需要另行固定，不能按逐条最高评分混选两家产物。
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/cloud_journal.py ADDED
@@ -0,0 +1,178 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """Durable submit receipts for the comparison runner; no automatic POST retry.
2
+
3
+ Uses the framework's HTTP plumbing. A lost create response is ambiguous: retain
4
+ the credit reservation and require reconciliation instead of buying a new task.
5
+ The runner holds one batch lock while using this client.
6
+ """
7
+ from __future__ import annotations
8
+
9
+ import json
10
+ import math
11
+ import os
12
+ from pathlib import Path
13
+ from typing import Any
14
+
15
+ from models.common import cloud_api
16
+ from pipeline.common.record_paths import portable_value, portable_text
17
+
18
+
19
+ def read_json(path: Path, default=None):
20
+ return json.loads(path.read_text(encoding="utf-8")) if path.is_file() else default
21
+
22
+
23
+ def write_json(path: Path, value: Any, *, portable: bool = True) -> None:
24
+ path.parent.mkdir(parents=True, exist_ok=True)
25
+ temporary = path.with_name(path.name + ".tmp")
26
+ with temporary.open("w", encoding="utf-8", newline="\n") as stream:
27
+ json.dump(portable_value(value, path.parent) if portable else value,
28
+ stream, ensure_ascii=False, indent=2)
29
+ stream.write("\n")
30
+ stream.flush()
31
+ os.fsync(stream.fileno())
32
+ os.replace(temporary, path)
33
+
34
+
35
+ def safe_error(exc: Exception) -> str:
36
+ value = str(exc)
37
+ for name in ("MESHY_API_KEY", "TRIPO_API_KEY"):
38
+ secret = os.environ.get(name)
39
+ if secret:
40
+ value = value.replace(secret, "[REDACTED]")
41
+ return portable_text(value)[:1600]
42
+
43
+
44
+ class BudgetExceeded(RuntimeError):
45
+ pass
46
+
47
+
48
+ class AmbiguousSubmission(RuntimeError):
49
+ pass
50
+
51
+
52
+ def reserved_credits(directory: Path) -> int:
53
+ return sum(
54
+ int(item["reserved_credits"])
55
+ for path in directory.glob("*.json")
56
+ for item in read_json(path, {}).get("submissions", {}).values()
57
+ if item["status"] != "rejected"
58
+ )
59
+
60
+
61
+ class JournalClient:
62
+ """Replay successful create receipts and query the same remote task on resume."""
63
+
64
+ def __init__(self, base: str, key: str, journal: Path, cap: int,
65
+ prices: dict[str, int], provider: str, transport=None, resume_refused=False):
66
+ self.journal = journal
67
+ self.cap = cap
68
+ self.prices = prices
69
+ self.provider = provider
70
+ self.resume_refused = resume_refused
71
+ # GET is safe to retry. A billed POST gets exactly one transport attempt.
72
+ self.reader = transport or cloud_api.CloudAPIClient(base, key, max_retries=3)
73
+ self.writer = transport or cloud_api.CloudAPIClient(base, key, max_retries=0)
74
+ self.public = None
75
+
76
+ def _cost(self, endpoint: str, body: dict) -> int:
77
+ if endpoint == "/files":
78
+ return 0
79
+ if self.provider == "meshy":
80
+ if endpoint == "/openapi/v2/text-to-3d":
81
+ return self.prices["text_refine" if body.get("mode") == "refine" else "text_preview"]
82
+ if endpoint == "/openapi/v1/image-to-3d":
83
+ return self.prices["image"]
84
+ elif endpoint in ("/generation/text-to-model", "/generation/image-to-model"):
85
+ return self.prices["text" if "text-to" in endpoint else "image"]
86
+ raise ValueError(f"Unpriced POST endpoint: {endpoint}")
87
+
88
+ def request(self, method: str, endpoint: str, **kwargs):
89
+ state = read_json(self.journal, {"submissions": {}, "results": {}})
90
+ if method != "POST":
91
+ result = self.reader.request(method, endpoint, **kwargs)
92
+ if method == "GET" and isinstance(result, dict):
93
+ state["results"][endpoint] = result
94
+ payload = result.get("data", result)
95
+ if isinstance(payload, dict):
96
+ remote_id = payload.get("task_id") or payload.get("id")
97
+ reported = payload.get("credits_consumed", payload.get("credits"))
98
+ for record in state["submissions"].values():
99
+ if remote_id and record.get("remote_id") == remote_id and isinstance(reported, (int, float)):
100
+ record["reported_credits"] = reported
101
+ record["reserved_credits"] = max(record["reserved_credits"], math.ceil(reported))
102
+ write_json(self.journal, state)
103
+ return result
104
+
105
+ # Hash binary inputs; never persist image bytes or credentials in receipts.
106
+ descriptor = {"endpoint": endpoint, "body": kwargs.get("json_body"),
107
+ "files": {name: cloud_api.bytes_hash(value[1])
108
+ for name, value in (kwargs.get("files") or {}).items()}}
109
+ fingerprint = cloud_api.request_hash(descriptor)
110
+ previous = state["submissions"].get(fingerprint)
111
+ if previous:
112
+ if previous["status"] == "created":
113
+ return previous["response"]
114
+ if previous["status"] == "rejected" and not (self.resume_refused and previous.get("resource_refusal")):
115
+ raise cloud_api.CloudAPIRequestError(previous["error"])
116
+ if previous["status"] != "rejected":
117
+ raise AmbiguousSubmission(
118
+ f"Unconfirmed submission {fingerprint} in {self.journal}. "
119
+ "Reconcile its remote task ID; no automatic resubmission.")
120
+
121
+ cost = self._cost(endpoint, kwargs.get("json_body") or {})
122
+ used = reserved_credits(self.journal.parent)
123
+ if used + cost > self.cap:
124
+ raise BudgetExceeded(f"{self.provider}: {used} reserved + {cost} exceeds cap {self.cap}")
125
+ record = {"endpoint": endpoint, "reserved_credits": cost, "status": "submitting"}
126
+ if previous:
127
+ record["rejection_history"] = [*previous.get("rejection_history", []),
128
+ {k: v for k, v in previous.items() if k != "rejection_history"}]
129
+ state["submissions"][fingerprint] = record
130
+ write_json(self.journal, state) # commit before the request can incur a charge
131
+ try:
132
+ response = self.writer.request(method, endpoint, **kwargs)
133
+ except cloud_api.CloudAPIError as exc:
134
+ # These are explicit refusals. 5xx/timeouts may have created a task.
135
+ if exc.status in (400, 401, 402, 403, 404, 405, 413, 415, 422, 429):
136
+ record.update(status="rejected", error=safe_error(exc), resource_refusal=isinstance(
137
+ exc, (cloud_api.CloudAPIAuthError, cloud_api.CloudAPIQuotaError, cloud_api.CloudAPIRateLimitError)))
138
+ else:
139
+ record.update(status="uncertain", error=safe_error(exc))
140
+ write_json(self.journal, state)
141
+ if record["status"] == "uncertain":
142
+ raise AmbiguousSubmission(f"Unconfirmed POST {fingerprint}; {safe_error(exc)}") from exc
143
+ raise
144
+
145
+ rejected = isinstance(response, dict) and response.get("code") not in (None, 0)
146
+ envelope = response.get("data", response) if isinstance(response, dict) else {}
147
+ remote_id = (envelope.get("task_id") or envelope.get("id") or envelope.get("result")
148
+ or envelope.get("file_token") or envelope.get("token")) if isinstance(envelope, dict) else None
149
+ if rejected:
150
+ rejection = cloud_api.classify_http_error(400, response)
151
+ record.update(status="rejected", error=safe_error(rejection), resource_refusal=isinstance(
152
+ rejection, (cloud_api.CloudAPIAuthError, cloud_api.CloudAPIQuotaError)))
153
+ elif not remote_id:
154
+ record.update(status="uncertain", error="Response contained no remote task/file ID")
155
+ else:
156
+ record.update(status="created", remote_id=remote_id, response=response)
157
+ write_json(self.journal, state)
158
+ if rejected:
159
+ raise rejection
160
+ if record["status"] == "uncertain":
161
+ raise AmbiguousSubmission(f"Unconfirmed POST {fingerprint}: missing task/file ID")
162
+ return response
163
+
164
+ def download(self, url: str, **kwargs) -> bytes:
165
+ # Signed CDN downloads must not receive the provider's Authorization key.
166
+ if not url.startswith("https://"):
167
+ raise ValueError("Artifact download must use HTTPS")
168
+ if self.public is None:
169
+ self.public = cloud_api.CloudAPIClient("", "", max_retries=3)
170
+ self.public.session.headers.pop("Authorization", None)
171
+ return self.public.download(url, **kwargs)
172
+
173
+ def close(self):
174
+ self.reader.close()
175
+ if self.writer is not self.reader:
176
+ self.writer.close()
177
+ if self.public is not None:
178
+ self.public.close()
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/generate_3d_comparison.py ADDED
@@ -0,0 +1,603 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/usr/bin/env python3
2
+ """Prepare, run and resume the frozen Meshy/Tripo 200-object comparison.
3
+
4
+ Prepare/status are offline. Run requires explicit spending caps and API keys.
5
+ Native generation outputs remain unmodified. A shared postprocessor produces
6
+ separate import meshes; visual acceptance is a separate review.
7
+ """
8
+ from __future__ import annotations
9
+
10
+ import argparse
11
+ from collections import Counter, defaultdict
12
+ from contextlib import contextmanager
13
+ from datetime import datetime, timezone
14
+ import hashlib
15
+ import io
16
+ import json
17
+ import math
18
+ import os
19
+ from pathlib import Path
20
+ import re
21
+ import shutil
22
+ import struct
23
+ import subprocess
24
+ import sys
25
+
26
+ BENCH = Path(__file__).resolve().parents[2]
27
+ FRAMEWORK = BENCH / "GameFactory-3A"
28
+ sys.path.insert(0, str(FRAMEWORK))
29
+ from pipeline.common import paths
30
+ from pipeline.common.record_paths import portable_value, resolve_path, runtime_value
31
+ from models.common import cloud_api
32
+ from models.common.glb_utils import glb_json_chunk, glb_summary
33
+ from cloud_journal import (AmbiguousSubmission, BudgetExceeded, JournalClient,
34
+ read_json, reserved_credits, safe_error, write_json)
35
+
36
+ DEFAULT_CONFIG = BENCH / "config/asset_3d_comparison.json"
37
+ IDENTIFIER = re.compile(r"^[A-Za-z0-9][A-Za-z0-9_-]{0,160}$")
38
+ RUNTIME_FILES = [Path(__file__), Path(__file__).with_name("cloud_journal.py"),
39
+ FRAMEWORK / "pipeline/common/record_paths.py",
40
+ FRAMEWORK / "pipeline/common/paths.py",
41
+ BENCH / "prompts/stage2_assets.md",
42
+ FRAMEWORK / "operators/gen_3d_object/operator.py",
43
+ FRAMEWORK / "models/gen_3d_object/meshy_model.py",
44
+ FRAMEWORK / "models/gen_3d_object/tripo_model.py",
45
+ FRAMEWORK / "models/common/cloud_api.py",
46
+ FRAMEWORK / "models/common/glb_utils.py",
47
+ Path(__file__).with_name("mesh_tools") / "process_mesh.mjs",
48
+ Path(__file__).with_name("mesh_tools") / "package-lock.json"]
49
+ MESH_TOOL = Path(__file__).with_name("mesh_tools") / "process_mesh.mjs"
50
+
51
+
52
+ def now():
53
+ return datetime.now(timezone.utc).isoformat(timespec="seconds")
54
+
55
+
56
+ def digest(path: Path):
57
+ return hashlib.sha256(path.read_bytes()).hexdigest()
58
+
59
+
60
+ def checked_id(value: str):
61
+ if not IDENTIFIER.fullmatch(value):
62
+ raise ValueError(f"Invalid path identifier: {value!r}")
63
+ return value
64
+
65
+
66
+ def bench_path(value: str):
67
+ result = resolve_path(value).resolve()
68
+ result.relative_to(BENCH.resolve())
69
+ return result
70
+
71
+
72
+ def batch_directory(config: dict, batch_id: str):
73
+ return bench_path(config["output_root"]) / "_asset_batches" / checked_id(batch_id)
74
+
75
+
76
+ @contextmanager
77
+ def exclusive_batch(directory: Path):
78
+ """OS lock releases on process exit, including an interrupted run."""
79
+ directory.mkdir(parents=True, exist_ok=True)
80
+ with (directory / "batch.lock").open("a+b") as stream:
81
+ stream.seek(0, 2)
82
+ if stream.tell() == 0:
83
+ stream.write(b"0")
84
+ stream.flush()
85
+ stream.seek(0)
86
+ if os.name == "nt":
87
+ import msvcrt
88
+ msvcrt.locking(stream.fileno(), msvcrt.LK_NBLCK, 1)
89
+ else:
90
+ import fcntl
91
+ fcntl.flock(stream, fcntl.LOCK_EX | fcntl.LOCK_NB)
92
+ try:
93
+ yield
94
+ finally:
95
+ stream.seek(0)
96
+ if os.name == "nt":
97
+ msvcrt.locking(stream.fileno(), msvcrt.LK_UNLCK, 1)
98
+ else:
99
+ fcntl.flock(stream, fcntl.LOCK_UN)
100
+
101
+
102
+ def game_directory(plan: dict, game: str):
103
+ return Path(plan["output_root"]) / checked_id(game)
104
+
105
+
106
+ def pipeline_directory(plan: dict, provider: str, game: str):
107
+ return (game_directory(plan, game) / "pipeline" / (game + "_pipeline")
108
+ / checked_id(plan["batch_id"]) / checked_id(provider))
109
+
110
+
111
+ def generation_index(plan: dict, provider: str, game: str):
112
+ return (game_directory(plan, game) / ".generation/3d_object" / checked_id(provider)
113
+ / checked_id(plan["batch_id"]) / "asset_task_index.json")
114
+
115
+
116
+ def short_context(text: str, limit: int):
117
+ """Declared deterministic excerpts, not a claim that the model read the brief."""
118
+ title = re.search(r"^title:\s*(.+)$", text, re.M)
119
+ lines = [line.strip() for line in text.splitlines() if line.strip()]
120
+ title_text = title.group(1) if title else next((s.lstrip("# ") for s in lines if s.startswith("#")), "")
121
+ world = next((line for line in lines if re.match(r"-\s*W01\b", line)), "")
122
+ loop = next((line for line in lines if any(word in line for word in ("核心循环：", "核心循环:", "核心玩法：", "核心玩法:"))), "")
123
+ if not loop:
124
+ loop = next((line for line in lines if re.match(r"-\s*S01\b", line)), "")
125
+ if not loop:
126
+ heading = re.search(r"^##[^\n]*(?:核心循环|一句话定位)[^\n]*\n([^#]+)", text, re.M)
127
+ loop = heading.group(1) if heading else ""
128
+ pieces = [re.sub(r"\s+", " ", value).strip()[:size]
129
+ for value, size in ((title_text, 70), (world, 110), (loop, 110)) if value]
130
+ value = " | ".join(pieces)
131
+ if not value:
132
+ raise ValueError("Cannot extract game context; provide a reviewed short context")
133
+ return value[:limit]
134
+
135
+
136
+ def frozen_copy(source: Path, destination: Path):
137
+ if destination.exists() and digest(destination) != digest(source):
138
+ raise ValueError(f"Frozen input changed; use a new batch ID: {destination}")
139
+ destination.parent.mkdir(parents=True, exist_ok=True)
140
+ if not destination.exists():
141
+ shutil.copyfile(source, destination)
142
+ return {"path": str(destination.resolve()), "sha256": digest(destination),
143
+ "source": str(source.resolve())}
144
+
145
+
146
+ def node_process(arguments: list[str], timeout: int):
147
+ node = shutil.which("node")
148
+ if not node:
149
+ raise ValueError("Node.js is required for the fixed mesh pipeline")
150
+ environment = os.environ.copy()
151
+ for key in ("MESHY_API_KEY", "TRIPO_API_KEY"):
152
+ environment.pop(key, None)
153
+ if os.name == "nt":
154
+ # Conda's DLLs can shadow sharp's libvips dependencies in child processes.
155
+ environment["PATH"] = str(Path(node).parent) + os.pathsep + str(Path(os.environ["SystemRoot"]) / "System32")
156
+ return subprocess.run([node, str(MESH_TOOL), *arguments], capture_output=True,
157
+ text=True, encoding="utf-8", timeout=timeout, env=environment)
158
+
159
+
160
+ def mesh_runtime():
161
+ result = node_process(["--check"], timeout=60)
162
+ if result.returncode:
163
+ raise ValueError("Mesh postprocessor unavailable; run npm ci in scripts/asset/mesh_tools. " + result.stderr[-500:])
164
+ return json.loads(result.stdout)
165
+
166
+
167
+ def subject_group(task: dict):
168
+ role = task.get("role", "")
169
+ return "character" if task.get("rig", "none") != "none" or role in (
170
+ "character", "player", "event_figure", "npc", "creature", "unit_special") or role.startswith("enemy") else "rigid"
171
+
172
+
173
+ def prepare(config: dict, batch_id: str):
174
+ if config["input_policy"] != "shared_short_context_and_reference_only" or not config["input_policy_confirmed"]:
175
+ raise ValueError("The input protocol must be confirmed before preparing this comparison")
176
+ directory = batch_directory(config, batch_id)
177
+ plan_file = directory / "plan.json"
178
+ if plan_file.exists():
179
+ raise ValueError(f"Batch is already frozen: {plan_file}. Use status/run or a new batch ID.")
180
+ source = bench_path(config["tasks"])
181
+ tasks = [json.loads(line) for line in source.read_text(encoding="utf-8-sig").splitlines() if line.strip()]
182
+ if len(tasks) != config["expected_tasks"]:
183
+ raise ValueError(f"Expected {config['expected_tasks']} tasks; got {len(tasks)}")
184
+ for task in tasks:
185
+ for provider in config["providers"]:
186
+ output = (bench_path(config["output_root"]) / checked_id(task["game_id"])
187
+ / "assets/3d_object" / checked_id(task["task_id"]) / checked_id(provider))
188
+ if output.is_dir() and any(p.name != ".gitkeep" for p in output.iterdir()):
189
+ raise ValueError(f"Provider directory already contains assets; resume its batch: {output}")
190
+ seen = set()
191
+ frozen_tasks = []
192
+ documents = {}
193
+ tool_runtime = mesh_runtime()
194
+ for task in tasks:
195
+ game = checked_id(task["game_id"])
196
+ task_id = checked_id(task["task_id"])
197
+ identity = (game, task_id)
198
+ if identity in seen:
199
+ raise ValueError(f"Duplicate task: {identity}")
200
+ seen.add(identity)
201
+ case = BENCH / "test_data/test_samples" / game
202
+ if game not in documents:
203
+ requirement = case / "general_requirement.txt"
204
+ full_text = requirement.read_text(encoding="utf-8")
205
+ doc_root = directory / "inputs" / game
206
+ documents[game] = {
207
+ "general_requirement": frozen_copy(requirement, doc_root / "general_requirement.txt"),
208
+ "object_requirement": frozen_copy(case / "3D_object/requirement.txt", doc_root / "object_requirement.txt"),
209
+ "context_excerpt": short_context(full_text, config["context_excerpt_max_chars"]),
210
+ "context_method": "deterministic title/world/core-loop excerpts; full brief retained locally",
211
+ }
212
+ mode = task["input_mode"]
213
+ prompt = None
214
+ reference = None
215
+ if mode == "text_to_3d":
216
+ # Never shorten the asset prompt. Both providers receive this exact string.
217
+ prompt = f"Game context (excerpt): {documents[game]['context_excerpt']}\nAsset: {task['prompt']}"
218
+ if len(prompt) > config["shared_prompt_max_chars"]:
219
+ raise ValueError(f"Shared prompt exceeds limit: {task_id} ({len(prompt)} chars)")
220
+ elif mode == "image_to_3d":
221
+ source_image = bench_path(task["image_path"])
222
+ reference = frozen_copy(source_image, directory / "references" / (digest(source_image) + source_image.suffix.lower()))
223
+ else:
224
+ raise ValueError(f"Unsupported input mode: {mode}")
225
+ if not 500 <= task["decimation_target"] <= 8000:
226
+ raise ValueError(f"Unexpected triangle target: {task_id}")
227
+ frozen_tasks.append({"task": task, "shared_prompt": prompt, "reference": reference,
228
+ "subject_group": subject_group(task),
229
+ "context_condition": "shared_short_context" if prompt else "reference_only"})
230
+ output_root = bench_path(config["output_root"])
231
+ plan = {"schema_version": "asset_3d_comparison_plan_v1", "batch_id": batch_id,
232
+ "created_at": now(), "scope": "3d_object_only_not_complete_stage2",
233
+ "config": config, "output_root": str(output_root), "directory": str(directory),
234
+ "source": frozen_copy(source, directory / "inputs/source_tasks.jsonl"),
235
+ "method_reference": frozen_copy(bench_path(config["method_reference"]), directory / "inputs/method_selection.md"),
236
+ "documents": documents, "tasks": frozen_tasks,
237
+ "runtime_sources": {str(p.resolve()): digest(p) for p in RUNTIME_FILES},
238
+ "estimated_credits": {}, "recommended_credit_caps": {},
239
+ "qa_policy": "basic structural checks + pending visual review; no automatic acceptance",
240
+ "texture_policy": "preserve native output; same deterministic downsize for both import meshes",
241
+ "postprocess": config["postprocess"], "mesh_runtime": tool_runtime,
242
+ "deferred_providers": {"hunyuan3d_pro": {"status": "not_enabled", "adapter_contract":
243
+ "infer_and_save(image, output_path, seed, decimation_target, texture_size, *, prompt); requires pinned cloud version and input capability check"}}}
244
+ for provider, settings in config["providers"].items():
245
+ prices = settings["credits"]
246
+ estimate = sum((prices["text_preview"] + prices["text_refine"] if provider == "meshy" else prices["text"])
247
+ if item["shared_prompt"] else prices["image"] for item in frozen_tasks)
248
+ plan["estimated_credits"][provider] = estimate
249
+ plan["recommended_credit_caps"][provider] = (estimate * 11 + 9) // 10
250
+ plan["plan_sha256"] = cloud_api.request_hash(portable_value(plan))
251
+ write_json(plan_file, plan)
252
+ write_json(directory / "asset_task_index.json", {"plan_sha256": plan["plan_sha256"],
253
+ "task_count": len(frozen_tasks), "tasks": frozen_tasks})
254
+ for provider in config["providers"]:
255
+ for game in documents:
256
+ write_json(generation_index(plan, provider, game), {
257
+ "plan_sha256": plan["plan_sha256"], "game_id": game, "provider": provider,
258
+ "scope": plan["scope"], "tasks": [item for item in frozen_tasks if item["task"]["game_id"] == game]})
259
+ refresh_reports(plan)
260
+ return plan
261
+
262
+
263
+ def load_plan(config: dict, batch_id: str):
264
+ plan = read_json(batch_directory(config, batch_id) / "plan.json")
265
+ if not plan:
266
+ raise ValueError("Prepare this batch first")
267
+ claimed = plan["plan_sha256"]
268
+ if cloud_api.request_hash({k: v for k, v in plan.items() if k != "plan_sha256"}) != claimed:
269
+ raise ValueError("Frozen plan was modified")
270
+ return runtime_value(plan)
271
+
272
+
273
+ def validate_inputs(plan: dict):
274
+ if mesh_runtime() != plan["mesh_runtime"]:
275
+ raise ValueError("Mesh runtime differs from the frozen version")
276
+ for filename, expected in plan["runtime_sources"].items():
277
+ if digest(Path(filename)) != expected:
278
+ raise ValueError(f"Runtime changed after freeze: {filename}; prepare a new batch")
279
+ files = [plan["source"], plan["method_reference"]]
280
+ files.extend(doc[field] for doc in plan["documents"].values()
281
+ for field in ("general_requirement", "object_requirement"))
282
+ files.extend(item["reference"] for item in plan["tasks"] if item["reference"])
283
+ for entry in files:
284
+ if digest(Path(entry["path"])) != entry["sha256"]:
285
+ raise ValueError(f"Frozen input changed: {entry['path']}")
286
+
287
+
288
+ def basic_qa(filename: Path, task: dict):
289
+ data = filename.read_bytes()
290
+ summary = glb_summary(data)
291
+ checks = {"parseable_glb": "error" not in summary}
292
+ if checks["parseable_glb"]:
293
+ doc = glb_json_chunk(data)
294
+ checks["glb_v2_exact_length"] = struct.unpack_from("<II", data, 4) == (2, len(data))
295
+ checks["positive_triangle_count"] = bool(summary["triangles"])
296
+ checks["triangle_budget"] = 0 < summary["triangles"] <= task["decimation_target"]
297
+ checks["materials_present"] = summary["materials"] > 0
298
+ checks["textures_present"] = summary["textures"] > 0 and summary["images"] > 0
299
+ primitives = [p for m in doc.get("meshes", []) for p in m.get("primitives", [])]
300
+ checks["uv_present"] = bool(primitives) and all("TEXCOORD_0" in p.get("attributes", {}) for p in primitives)
301
+ checks["self_contained"] = all("uri" not in b or b["uri"].startswith("data:") for b in doc.get("buffers", [])) and all(
302
+ "bufferView" in image or str(image.get("uri", "")).startswith("data:") for image in doc.get("images", []))
303
+ return {"status": "PASS" if all(checks.values()) else "FAIL", "checks": checks,
304
+ "summary": summary, "triangle_target": task["decimation_target"],
305
+ "requested_texture_size": task.get("texture_size"),
306
+ "texture_budget_verified": False, "visual_status": "PENDING",
307
+ "limitations": ["No visual, orientation, scale, rigging or engine acceptance yet",
308
+ "Native texture resolution retained; task texture_size is not enforced",
309
+ "Basic checks do not validate every accessor, topology defect or PBR channel"]}
310
+
311
+
312
+ def process_import_mesh(source: Path, task: dict):
313
+ destination = source.parent / "import/model.glb"
314
+ result = node_process([str(source), str(destination), str(task["decimation_target"]),
315
+ str(task["texture_size"])], timeout=300)
316
+ if result.returncode:
317
+ raise RuntimeError("Postprocessing failed: " + result.stderr[-1200:])
318
+ report = json.loads(result.stdout)
319
+ return destination, report
320
+
321
+
322
+ def task_directories(plan: dict, provider: str, task: dict):
323
+ root = game_directory(plan, task["game_id"])
324
+ task_id, provider = checked_id(task["task_id"]), checked_id(provider)
325
+ output = root / "assets/3d_object" / task_id / provider
326
+ evaluation = root / "eval/3d_object" / task_id / provider
327
+ return output, evaluation
328
+
329
+
330
+ def refresh_reports(plan: dict):
331
+ summary = {"batch_id": plan["batch_id"], "plan_sha256": plan["plan_sha256"],
332
+ "updated_at": now(), "expected_assets": len(plan["tasks"]) * len(plan["config"]["providers"]),
333
+ "estimated_credits": plan["estimated_credits"], "providers": {}}
334
+ for provider in plan["config"]["providers"]:
335
+ by_game = defaultdict(list)
336
+ for item in plan["tasks"]:
337
+ task = item["task"]
338
+ output, evaluation = task_directories(plan, provider, task)
339
+ meta = read_json(output / "meta.json", {})
340
+ by_game[task["game_id"]].append({"task_id": task["task_id"], "asset_name": task["asset_name"],
341
+ "task_kind": "3d_object", "status": meta.get("status", "prepared"),
342
+ "artifact": str(output / "import/model.glb"), "native_artifact": str(output / "model.glb"),
343
+ "meta": str(output / "meta.json"), "native_structural_qa": meta.get("native_structural_qa"),
344
+ "import_structural_qa": meta.get("import_structural_qa"),
345
+ "native_delivered": meta.get("native_delivered", False),
346
+ "import_delivered": meta.get("import_delivered", False),
347
+ "qa": str(evaluation / "qa.json"), "visual_status": "PENDING",
348
+ "context_condition": item["context_condition"], "subject_group": item["subject_group"],
349
+ "input_mode": task["input_mode"], "error": meta.get("error")})
350
+ all_entries = [entry for entries in by_game.values() for entry in entries]
351
+ summary["providers"][provider] = {"task_count": len(all_entries),
352
+ "status_counts": dict(Counter(entry["status"] for entry in all_entries)),
353
+ "reserved_credits": reserved_credits(Path(plan["directory"]) / "submissions" / provider),
354
+ "visual_accepted": 0, "method_group": plan["config"]["method_group"],
355
+ "benchmark_metrics": {name: {"status": "UNKNOWN", "value": None}
356
+ for name in ("C", "Q1", "Q2", "Q3")},
357
+ "subgroups": {key: dict(Counter(e[key] for e in all_entries))
358
+ for key in ("subject_group", "input_mode", "context_condition")},
359
+ "game_macro_delivery": sum(sum(e["status"] == "delivered" for e in entries) / len(entries)
360
+ for entries in by_game.values()) / len(by_game),
361
+ "game_macro_native_delivery": sum(sum(e["native_delivered"] for e in entries) / len(entries)
362
+ for entries in by_game.values()) / len(by_game),
363
+ "native_structural_pass": sum(e["native_structural_qa"] == "PASS" for e in all_entries),
364
+ "import_structural_pass": sum(e["import_structural_qa"] == "PASS" for e in all_entries),
365
+ "delivery_metric_status": "NOT_RUN" if all(e["status"] == "prepared" for e in all_entries) else "PARTIAL"}
366
+ for game, entries in by_game.items():
367
+ pipeline = pipeline_directory(plan, provider, game)
368
+ manifest = {"game_id": game, "provider": provider, "batch_id": plan["batch_id"],
369
+ "plan_sha256": plan["plan_sha256"], "scope": plan["scope"], "assets": entries,
370
+ "full_context": plan["documents"][game], "status": "pending_visual_review"}
371
+ write_json(pipeline / "asset_manifest.json", manifest)
372
+ write_json(pipeline / "asset_generation_report.json", {
373
+ "task_count": len(entries), "status_counts": dict(Counter(e["status"] for e in entries)),
374
+ "failures": [e for e in entries if e["error"]], "visual_accepted": 0})
375
+ paths.write_task_meta(pipeline, {"game_id": game, "task_id": game + "_pipeline",
376
+ "task_kind": "pipeline", "run_id": plan["batch_id"], "status": "comparison_only",
377
+ "provider": provider, "scope": plan["scope"]})
378
+ write_json(Path(plan["directory"]) / "asset_generation_report.json", summary)
379
+ return summary
380
+
381
+
382
+ def make_model(plan: dict, provider: str, task: dict, cap: int):
383
+ from models.gen_3d_object.meshy_model import MeshyModel
384
+ from models.gen_3d_object.tripo_model import TripoModel
385
+ settings = plan["config"]["providers"][provider]
386
+ cls = MeshyModel if provider == "meshy" else TripoModel
387
+ control = Path(plan["directory"])
388
+ model = cls(model_path=settings["model"], device="cpu", api_base=settings["api_base"],
389
+ cache_dir=str(control / "cache" / task["game_id"] / task["task_id"]),
390
+ timeout=1800, poll_interval=5, **settings["options"])
391
+ key = cloud_api.require_api_key(None, provider.upper() + "_API_KEY", "See the comparison README")
392
+ journal = control / "submissions" / provider / (task["game_id"] + "__" + task["task_id"] + ".json")
393
+ model._client = JournalClient(settings["api_base"], key, journal, cap, settings["credits"], provider,
394
+ resume_refused=True)
395
+ return model
396
+
397
+
398
+ def download_preview(model, output: Path):
399
+ from PIL import Image
400
+ url = model.last_call_info.get("preview_url")
401
+ if not url:
402
+ return {"status": "unavailable"}
403
+ try:
404
+ data = model.client.download(url)
405
+ with Image.open(io.BytesIO(data)) as preview:
406
+ preview.verify()
407
+ extension = {"PNG": ".png", "JPEG": ".jpg", "WEBP": ".webp"}.get(preview.format)
408
+ if not extension:
409
+ return {"status": "unsupported_image_format"}
410
+ path = output / ("preview" + extension)
411
+ path.write_bytes(data)
412
+ return {"status": "downloaded", "path": str(path), "visual_review": "PENDING"}
413
+ except Exception as exc:
414
+ return {"status": "failed", "error": safe_error(exc)}
415
+
416
+
417
+ def run(plan: dict, args):
418
+ from operators.gen_3d_object.operator import Gen3DObjectOperator
419
+
420
+ class SharedStoreOperator(Gen3DObjectOperator):
421
+ def _resolve_out_path(self, inp, task_id):
422
+ output, _ = task_directories(plan, provider, inp)
423
+ output.mkdir(parents=True, exist_ok=True)
424
+ return inp["game_id"], output, output / "model.glb"
425
+
426
+ if not args.allow_paid:
427
+ raise ValueError("Paid generation requires --allow-paid and explicit provider credit caps")
428
+ validate_inputs(plan)
429
+ selected = list(dict.fromkeys(args.provider or list(plan["config"]["providers"])))
430
+ caps = {p: getattr(args, p + "_credit_cap") for p in selected}
431
+ for provider in selected:
432
+ if not caps[provider] or caps[provider] < reserved_credits(Path(plan["directory"]) / "submissions" / provider):
433
+ raise ValueError(f"Supply a positive --{provider}-credit-cap covering existing reservations")
434
+ cloud_api.require_api_key(None, provider.upper() + "_API_KEY", "See scripts/asset/README_3d_comparison.md")
435
+ selection = set(args.task_id or [])
436
+ known = {item["task"]["task_id"] for item in plan["tasks"]}
437
+ if selection - known:
438
+ raise ValueError(f"Unknown task IDs: {sorted(selection - known)}")
439
+ jobs = [item for item in plan["tasks"] if not selection or item["task"]["task_id"] in selection]
440
+ if args.limit is not None:
441
+ if args.limit < 1:
442
+ raise ValueError("--limit must be positive")
443
+ jobs = jobs[:args.limit]
444
+ write_json(Path(plan["directory"]) / "spending_authorization.json", {
445
+ "plan_sha256": plan["plan_sha256"], "credit_caps": caps, "recorded_at": now(),
446
+ "selected_task_ids": [item["task"]["task_id"] for item in jobs],
447
+ "note": "Caps reserve estimated credits; account-side limits remain authoritative"})
448
+ interrupted = False
449
+ for provider in selected:
450
+ failures = 0
451
+ for item in jobs:
452
+ task = item["task"]
453
+ output, evaluation = task_directories(plan, provider, task)
454
+ previous = read_json(output / "meta.json", {})
455
+ if previous and previous.get("plan_sha256") != plan["plan_sha256"]:
456
+ raise ValueError(f"Another batch owns this provider directory; do not overwrite: {output}")
457
+ if not previous and output.is_dir() and any(p.name != ".gitkeep" for p in output.iterdir()):
458
+ raise ValueError(f"Untracked provider artifacts must not be overwritten: {output}")
459
+ if previous.get("status") == "delivered" and (output / "model.glb").is_file():
460
+ imported = output / "import/model.glb"
461
+ if previous.get("artifact_sha256") == digest(output / "model.glb") and imported.is_file() and previous.get("import_sha256") == digest(imported):
462
+ continue
463
+ if previous.get("status") == "failed":
464
+ continue # one generation attempt, no cherry-picking on rerun
465
+ output.mkdir(parents=True, exist_ok=True)
466
+ meta = {"game_id": task["game_id"], "task_id": task["task_id"], "asset_name": task["asset_name"],
467
+ "task_kind": "3d_object", "run_id": plan["batch_id"], "provider": provider,
468
+ "plan_sha256": plan["plan_sha256"], "context_condition": item["context_condition"],
469
+ "full_context": plan["documents"][task["game_id"]], "source_task": task,
470
+ "shared_prompt": item["shared_prompt"], "reference": item["reference"],
471
+ "status": "running", "updated_at": now(), "visual_status": "PENDING"}
472
+ write_json(output / "meta.json", meta)
473
+ model = None
474
+ stop = False
475
+ try:
476
+ model = make_model(plan, provider, task, caps[provider])
477
+ # Preserve native output for a fair comparison. No automatic mesh cleanup/import.
478
+ inp = {**task, "strip_ground_plate": False}
479
+ inp.pop("asset_id", None)
480
+ if item["reference"]:
481
+ inp["image_path"] = item["reference"]["path"]
482
+ else:
483
+ inp["prompt"] = item["shared_prompt"]
484
+ result = SharedStoreOperator(model, run_id=plan["batch_id"]).run(inp)
485
+ raw_qa = basic_qa(Path(result["glb_path"]), task)
486
+ meta.update(native_delivered=raw_qa["checks"]["parseable_glb"], result=result,
487
+ native_structural_qa=raw_qa["status"], model_call=model.last_call_info,
488
+ artifact_sha256=digest(output / "model.glb"))
489
+ write_json(evaluation / "qa.json", {"native": raw_qa, "import": {"status": "PENDING"},
490
+ "visual_status": "PENDING"})
491
+ imported, postprocess = process_import_mesh(Path(result["glb_path"]), task)
492
+ import_qa = basic_qa(imported, task)
493
+ import_qa["texture_budget_verified"] = all(max(t["after"]) <= task["texture_size"] for t in postprocess["textures"])
494
+ import_qa["checks"]["texture_budget"] = import_qa["texture_budget_verified"]
495
+ import_qa["status"] = "PASS" if all(import_qa["checks"].values()) else "FAIL"
496
+ write_json(evaluation / "qa.json", {"native": raw_qa, "import": import_qa,
497
+ "postprocess": postprocess, "visual_status": "PENDING"})
498
+ meta.update(status="delivered", result=result, model_call=model.last_call_info,
499
+ import_delivered=import_qa["checks"]["parseable_glb"],
500
+ artifact_sha256=digest(output / "model.glb"), import_sha256=digest(imported),
501
+ native_structural_qa=raw_qa["status"], import_structural_qa=import_qa["status"],
502
+ postprocess=postprocess,
503
+ preview=download_preview(model, output))
504
+ failures = 0
505
+ except Exception as exc:
506
+ status = "failed"
507
+ if isinstance(exc, cloud_api.CloudTaskTimeout):
508
+ status = "remote_pending"
509
+ elif isinstance(exc, AmbiguousSubmission):
510
+ status, stop = "submission_uncertain", True
511
+ elif isinstance(exc, (BudgetExceeded, cloud_api.CloudAPIAuthError, cloud_api.CloudAPIQuotaError)):
512
+ status, stop = "blocked", True
513
+ elif isinstance(exc, cloud_api.CloudAPIServerError):
514
+ status = "resume_required" # known receipts survive poll/download failures
515
+ elif not isinstance(exc, (cloud_api.CloudTaskFailed, cloud_api.CloudAPIRequestError, ValueError)):
516
+ status = "resume_required" # retain a downloaded asset after local/tool failures
517
+ meta.update(status=status, error=safe_error(exc), error_type=type(exc).__name__)
518
+ failures += 1
519
+ stop = stop or failures >= 3
520
+ finally:
521
+ if model is not None:
522
+ model.unload()
523
+ meta["updated_at"] = now()
524
+ journal = read_json(Path(plan["directory"]) / "submissions" / provider /
525
+ (task["game_id"] + "__" + task["task_id"] + ".json"), {})
526
+ meta["generation_cost"] = [{"endpoint": record["endpoint"], "remote_id": record.get("remote_id"),
527
+ "reservation": record["reserved_credits"], "reported_credits": record.get("reported_credits"),
528
+ "status": record["status"]} for record in journal.get("submissions", {}).values()]
529
+ write_json(output / "meta.json", meta)
530
+ refresh_reports(plan)
531
+ print(json.dumps({"provider": provider, "task_id": task["task_id"], "status": meta["status"],
532
+ "error": meta.get("error")}, ensure_ascii=False), flush=True)
533
+ if stop:
534
+ interrupted = True
535
+ break
536
+ if interrupted:
537
+ break
538
+ incomplete = any(read_json(task_directories(plan, p, item["task"])[0] / "meta.json", {}).get("status") != "delivered"
539
+ for p in selected for item in jobs)
540
+ return 2 if interrupted or incomplete else 0
541
+
542
+
543
+ def recover(plan: dict, args):
544
+ """Attach an inspected remote ID to an ambiguous receipt; never submit here."""
545
+ checked_id(args.remote_task_id)
546
+ matches = [item["task"] for item in plan["tasks"] if item["task"]["task_id"] == args.task_id]
547
+ if len(matches) != 1:
548
+ raise ValueError("Recover requires exactly one known task")
549
+ task = matches[0]
550
+ journal = Path(plan["directory"]) / "submissions" / args.provider / (task["game_id"] + "__" + task["task_id"] + ".json")
551
+ state = read_json(journal, {})
552
+ record = state.get("submissions", {}).get(args.request_hash)
553
+ if not record or record["status"] not in ("submitting", "uncertain") or record["endpoint"] == "/files":
554
+ raise ValueError("Receipt is not an ambiguous generation submission")
555
+ record.update(status="created", remote_id=args.remote_task_id, reconciled_at=now(),
556
+ response={"result": args.remote_task_id} if args.provider == "meshy" else
557
+ {"code": 0, "data": {"task_id": args.remote_task_id}})
558
+ write_json(journal, state)
559
+ return {"recovered_task_id": args.remote_task_id, "network_requests": 0}
560
+
561
+
562
+ def main(argv=None):
563
+ parser = argparse.ArgumentParser(description=__doc__)
564
+ parser.add_argument("--config", type=Path, default=DEFAULT_CONFIG)
565
+ sub = parser.add_subparsers(dest="command", required=True)
566
+ for name in ("prepare", "status", "run", "recover"):
567
+ command = sub.add_parser(name)
568
+ command.add_argument("--batch-id", required=True)
569
+ if name == "run":
570
+ command.add_argument("--allow-paid", action="store_true")
571
+ command.add_argument("--meshy-credit-cap", type=int)
572
+ command.add_argument("--tripo-credit-cap", type=int)
573
+ command.add_argument("--provider", action="append", choices=("meshy", "tripo"))
574
+ command.add_argument("--task-id", action="append")
575
+ command.add_argument("--limit", type=int, help="Limit tasks per selected provider; full inventory is retained")
576
+ elif name == "recover":
577
+ command.add_argument("--provider", required=True, choices=("meshy", "tripo"))
578
+ command.add_argument("--task-id", required=True)
579
+ command.add_argument("--request-hash", required=True)
580
+ command.add_argument("--remote-task-id", required=True)
581
+ args = parser.parse_args(argv)
582
+ config = read_json(args.config)
583
+ with exclusive_batch(batch_directory(config, args.batch_id)):
584
+ if args.command == "prepare":
585
+ plan = prepare(config, args.batch_id)
586
+ print(json.dumps(portable_value({"plan": str(Path(plan["directory"]) / "plan.json"),
587
+ "tasks_per_provider": len(plan["tasks"]), "estimated_credits": plan["estimated_credits"],
588
+ "recommended_credit_caps": plan["recommended_credit_caps"]}), indent=2))
589
+ else:
590
+ plan = load_plan(config, args.batch_id)
591
+ if args.command == "run":
592
+ return run(plan, args)
593
+ value = recover(plan, args) if args.command == "recover" else refresh_reports(plan)
594
+ print(json.dumps(portable_value(value), indent=2, ensure_ascii=False))
595
+ return 0
596
+
597
+
598
+ if __name__ == "__main__":
599
+ try:
600
+ raise SystemExit(main())
601
+ except (ValueError, OSError, cloud_api.CloudAPIError) as exc:
602
+ print(safe_error(exc), file=sys.stderr)
603
+ raise SystemExit(2)
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/package-lock.json ADDED
@@ -0,0 +1,763 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "name": "bench-asset-comparison-mesh-tools",
3
+ "version": "1.0.0",
4
+ "lockfileVersion": 3,
5
+ "requires": true,
6
+ "packages": {
7
+ "": {
8
+ "name": "bench-asset-comparison-mesh-tools",
9
+ "version": "1.0.0",
10
+ "dependencies": {
11
+ "@gltf-transform/core": "4.2.1",
12
+ "@gltf-transform/extensions": "4.2.1",
13
+ "@gltf-transform/functions": "4.2.1",
14
+ "draco3dgltf": "1.5.7",
15
+ "meshoptimizer": "0.24.0",
16
+ "sharp": "0.35.5"
17
+ }
18
+ },
19
+ "node_modules/@emnapi/runtime": {
20
+ "version": "1.11.3",
21
+ "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.11.3.tgz",
22
+ "integrity": "sha512-Xz4Tpyki7XyrpbUK1jR1AhdAdaXyhhY4lZ3neLodmhpuWfy2PAQN5B46sAiU4liOXGLkHypn/qU+jvfWSCYYLA==",
23
+ "license": "MIT",
24
+ "optional": true,
25
+ "dependencies": {
26
+ "tslib": "^2.4.0"
27
+ }
28
+ },
29
+ "node_modules/@gltf-transform/core": {
30
+ "version": "4.2.1",
31
+ "resolved": "https://registry.npmjs.org/@gltf-transform/core/-/core-4.2.1.tgz",
32
+ "integrity": "sha512-qKhrQ29KJ9K6sz7xGoGRllqPBlROjPJMQPvCLBOfgMPH3S/Ph5E0e6fD5WmwTY5QPyBsDMRqKd1Vl0ncThTXGw==",
33
+ "license": "MIT",
34
+ "dependencies": {
35
+ "property-graph": "^3.0.0"
36
+ },
37
+ "funding": {
38
+ "url": "https://github.com/sponsors/donmccurdy"
39
+ }
40
+ },
41
+ "node_modules/@gltf-transform/extensions": {
42
+ "version": "4.2.1",
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+ }
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+ }
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+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/process_mesh.mjs ADDED
@@ -0,0 +1,77 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ // One fixed pipeline for both services; keep the original GLB separately.
2
+ import {readFileSync, mkdirSync} from 'node:fs';
3
+ import {dirname} from 'node:path';
4
+ import {performance} from 'node:perf_hooks';
5
+ import {NodeIO, Logger} from '@gltf-transform/core';
6
+ import {ALL_EXTENSIONS} from '@gltf-transform/extensions';
7
+ import {simplify, weld} from '@gltf-transform/functions';
8
+ import {MeshoptDecoder, MeshoptSimplifier} from 'meshoptimizer';
9
+ import draco from 'draco3dgltf';
10
+ import sharp from 'sharp';
11
+
12
+ const settings = JSON.parse(readFileSync(new URL('./package.json', import.meta.url)));
13
+ await Promise.all([MeshoptDecoder.ready, MeshoptSimplifier.ready]);
14
+ const runtime = {node: process.versions.node, dependencies: settings.dependencies};
15
+ if (process.argv[2] === '--check') {
16
+ console.log(JSON.stringify({status: 'ready', ...runtime}));
17
+ } else {
18
+ const [source, destination, triangleArg, textureArg] = process.argv.slice(2);
19
+ const triangleTarget = Number(triangleArg), textureTarget = Number(textureArg);
20
+ if (!source || !destination || !Number.isInteger(triangleTarget) || triangleTarget <= 0
21
+ || !Number.isInteger(textureTarget) || textureTarget <= 0) {
22
+ throw new Error('Expected: source.glb destination.glb triangle_target texture_size');
23
+ }
24
+ const started = performance.now();
25
+ const io = new NodeIO().registerExtensions(ALL_EXTENSIONS).registerDependencies({
26
+ 'draco3d.decoder': await draco.createDecoderModule(),
27
+ 'meshopt.decoder': MeshoptDecoder,
28
+ });
29
+ const document = await io.read(source);
30
+ document.setLogger(new Logger(Logger.Verbosity.SILENT));
31
+ // The decoded import GLB is not dependent on the provider's mesh codec.
32
+ for (const extension of document.getRoot().listExtensionsUsed()) {
33
+ if (['KHR_draco_mesh_compression', 'EXT_meshopt_compression'].includes(extension.extensionName)) {
34
+ extension.dispose();
35
+ }
36
+ }
37
+ function triangleCount() {
38
+ let count = 0;
39
+ for (const mesh of document.getRoot().listMeshes()) {
40
+ for (const primitive of mesh.listPrimitives()) {
41
+ if (primitive.getMode() !== 4) throw new Error('Only triangle primitives are supported');
42
+ const n = (primitive.getIndices() || primitive.getAttribute('POSITION')).getCount();
43
+ count += n / 3;
44
+ }
45
+ }
46
+ return count;
47
+ }
48
+ const before = triangleCount();
49
+ if (before > triangleTarget) {
50
+ await document.transform(weld(), simplify({simplifier: MeshoptSimplifier,
51
+ ratio: triangleTarget / before, error: 0.01, lockBorder: false}));
52
+ }
53
+ const textures = [];
54
+ for (const texture of document.getRoot().listTextures()) {
55
+ const image = texture.getImage();
56
+ if (!image) throw new Error('Texture has no decoded image');
57
+ const input = Buffer.from(image);
58
+ const info = await sharp(input).metadata();
59
+ let sizeAfter = [info.width, info.height];
60
+ if (Math.max(...sizeAfter) > textureTarget) {
61
+ const {data, info: resized} = await sharp(input).resize({width: textureTarget, height: textureTarget,
62
+ fit: 'inside', withoutEnlargement: true, kernel: 'lanczos3'}).png({compressionLevel: 9}).toBuffer({resolveWithObject: true});
63
+ texture.setImage(new Uint8Array(data)).setMimeType('image/png').setURI('');
64
+ sizeAfter = [resized.width, resized.height];
65
+ }
66
+ textures.push({name: texture.getName(), before: [info.width, info.height], after: sizeAfter});
67
+ }
68
+ const after = triangleCount();
69
+ mkdirSync(dirname(destination), {recursive: true});
70
+ await io.write(destination, document);
71
+ console.log(JSON.stringify({status: after <= triangleTarget ? 'PASS' : 'FAIL',
72
+ triangles_before: before, triangles_after: after, triangle_target: triangleTarget,
73
+ texture_target: textureTarget, textures, runtime,
74
+ policy: 'weld; one simplify pass at error 0.01 when over budget; downsize textures only; preserve UV/material/node data',
75
+ elapsed_sec: Math.round((performance.now() - started) / 10) / 100,
76
+ visual_review: 'PENDING'}));
77
+ }
outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/sources_index.json ADDED
@@ -0,0 +1,128 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "files": [
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+ {
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+ "path": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt",
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+ "sha256": "4b6847098cb1a6e7a930c80af21b14e75771d1d6e9c8326d19439a446ea8a767",
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+ "bytes": 23996
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+ },
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+ {
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+ "path": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt",
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+ "sha256": "45cbe4cfc38dd23248f1ea2fb3ca15bb14ee7ee095c0d7576f6a9fdfb32d4472",
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+ "bytes": 559
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+ },
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+ {
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+ "path": "bench/test_data/outputs/G059_observatory_pinball/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/method_selection.md",
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+ "sha256": "d9b0471f4c0e0f1e70c76e2bba676d3275d10530451435dc625972dbcea9abbe",
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+ "bytes": 11846
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+ },
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+ {
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