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filter=lfs diff=lfs merge=lfs -text +outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_003/meshy/model.glb filter=lfs diff=lfs merge=lfs -text +outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_003/tripo/import/model.glb filter=lfs diff=lfs merge=lfs -text +outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_003/tripo/model.glb filter=lfs diff=lfs merge=lfs -text diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/meshy/obj200_meshy_tripo_20261015_v2/asset_task_index.json b/outputs/G056_garden_minigolf/.generation/3d_object/meshy/obj200_meshy_tripo_20261015_v2/asset_task_index.json new file mode 100644 index 0000000000000000000000000000000000000000..1741bfcee68c9a89ad7197c2f58cfeca41602c05 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/meshy/obj200_meshy_tripo_20261015_v2/asset_task_index.json @@ -0,0 +1,52 @@ +{ + "plan_sha256": 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"0f0bfafd73cbfed0d3216f4a2c5a8031b9ad81621ae6abfa2eaf6b8d656e4051", + "source": "bench/test_data/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt" + }, + "object_requirement": { + "path": "bench/test_data/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt", + "sha256": "2f0f65f7b7349df66d1724a8d96d19577c23ae9555326dedfbf353dac4550aa0", + "source": "bench/test_data/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt" + }, + "context_excerpt": "漂浮花园的迷你高尔夫 | - W01 世界与时代背景：架空云海时代的「浮屿花园」——园艺师们在漂浮于云海的花屿上经营三洞试炼球场，庆祝春分的推杆大会今夜开杆。 | - S01 类型：3D 俯视迷你高尔夫（单人杆数制）。本测例包含的能力：三洞冻结球场、蓄力击球物理、坡面反弹摩擦、瞄准线与轨迹残影反馈、界外复位与罚杆、双镜头模式、开场/结算视频。", + "context_method": "deterministic title/world/core-loop excerpts; full brief retained locally" + }, + "tasks": [ + { + "task": { + "game_id": "G056_garden_minigolf", + "task_id": "G056_garden_minigolf_obj_002", + "asset_name": "golf_ball", + "name_zh": "高尔夫球", + "role": "prop", + "input_mode": "text_to_3d", + "prompt": "Single dimpled golf ball with a soft pearl sheen, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "seed": 1562, + "decimation_target": 3000, + "texture_size": 1024, + "rig": "none", + "animation_strategy": "procedural", + "spec_ref": "L01", + "poly_policy": "low_poly_priority" + }, + "shared_prompt": "Game context (excerpt): 漂浮花园的迷你高尔夫 | - W01 世界与时代背景：架空云海时代的「浮屿花园」——园艺师们在漂浮于云海的花屿上经营三洞试炼球场，庆祝春分的推杆大会今夜开杆。 | - S01 类型：3D 俯视迷你高尔夫（单人杆数制）。本测例包含的能力：三洞冻结球场、蓄力击球物理、坡面反弹摩擦、瞄准线与轨迹残影反馈、界外复位与罚杆、双镜头模式、开场/结算视频。\nAsset: Single dimpled golf ball with a soft pearl sheen, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "reference": null, + "subject_group": "rigid", + "context_condition": "shared_short_context" + }, + { + "task": { + "game_id": "G056_garden_minigolf", + "task_id": "G056_garden_minigolf_obj_003", + "asset_name": "hole_flag", + "name_zh": "球洞与旗杆", + "role": "prop", + "input_mode": "text_to_3d", + "prompt": "Miniature golf hole cup with a slender striped pennant flag and a subtle glow rim, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "seed": 1563, + "decimation_target": 6000, + "texture_size": 2048, + "rig": "none", + "animation_strategy": "procedural", + "spec_ref": "L01", + "poly_policy": "low_poly_priority" + }, + "shared_prompt": "Game context (excerpt): 漂浮花园的迷你高尔夫 | - W01 世界与时代背景：架空云海时代的「浮屿花园」——园艺师们在漂浮于云海的花屿上经营三洞试炼球场，庆祝春分的推杆大会今夜开杆。 | - S01 类型：3D 俯视迷你高尔夫（单人杆数制）。本测例包含的能力：三洞冻结球场、蓄力击球物理、坡面反弹摩擦、瞄准线与轨迹残影反馈、界外复位与罚杆、双镜头模式、开场/结算视频。\nAsset: Miniature golf hole cup with a slender striped pennant flag and a subtle glow rim, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "reference": null, + "subject_group": "rigid", + "context_condition": "shared_short_context" + } + ], + "input_policy": "shared_short_context_and_reference_only", + "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.", + "benchmark_metrics": { + "C": { + "status": "UNKNOWN", + "value": null + }, + "Q1": { + "status": "UNKNOWN", + "value": null + }, + "Q2": { + "status": "UNKNOWN", + "value": null + }, + "Q3": { + "status": "UNKNOWN", + "value": null + } + }, + "view_sha256": "edac27f7770d58b09e2e2ec238bef2b4a7cf6b03cc883dea90771e8a24002d3c" +} diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt new file mode 100644 index 0000000000000000000000000000000000000000..8191248194c09c9f5ebb331688280175d3c97afc --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/general_requirement.txt @@ -0,0 +1,264 @@ +# 《漂浮花园的迷你高尔夫》｜推杆物理机制输入规范 + +```yaml +case_id: G056 +base_case_id: G056 +title: 漂浮花园的迷你高尔夫 +category: Sports / Rhythm / Physics +tier: S +engine: godot +report_track: Standard +paired_conditions: [R, N] +required_real_clients: 1 +fixed_seed: 1056 +spec_version: v3 +status: DRAFT_LOCAL +mechanism_source: null +task_spec_version: null +task_spec_hash: null +frozen_by: null +frozen_at: null +dependency_hashes: null +``` + +## 0. 标题、版本与使用说明 + +- 作品名：《漂浮花园的迷你高尔夫》；版本：mechanics-v3（2026-10-11 完整性修订：补瞄准线/力度条/轨迹残影、镜头规则、世界设定、演出反馈、视频与正向范围清单）；运行引擎：**Godot 4.x（Windows 桌面构建）**（spec、rubric 与 asset 任务 JSONL 引擎字段保持一致）；输入方式：键盘与鼠标。 +- 原创边界：迷你高尔夫属公有领域玩法；本作全部名称、球场、文案与美术必须原创，不使用任何商业作品的球场设计、角色或造型。 +- 规则优先级：本文件全局数值与规则 ＞ 机制章节 ＞ 球洞实例 ＞ 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。 +- 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。 + +## 1. 定位与完整流程 [S01–S06] + +- S01 类型：3D 俯视迷你高尔夫（单人杆数制）。本测例包含的能力：三洞冻结球场、蓄力击球物理、坡面反弹摩擦、瞄准线与轨迹残影反馈、界外复位与罚杆、双镜头模式、开场/结算视频。 +- S02 核心循环一句话：瞄定力度方向 → 击球 → 物理滚动 → 进洞或补杆 → 结算杆数。 +- S03 流程：标题 → 球洞1 → 球洞2 → 球洞3 → 总结算（杆数对比标准杆）；每洞自动开球。 +- S04 最低完整流程：标题、三洞球场、每洞 HUD（当前杆数）、总结算、重开必须全部存在且有真实入口。 +- S05 失败恢复入口：界外自动复位回上一杆位＋罚 1 杆；总结算界面一键重开；Esc 暂停。 +- S06 与种子卡差异：种子卡杆数为「规则化高尔夫全流程」；本包冻结为三洞切片（标准杆 12），P0 局内口径不变。 + +## 2. 完整核心循环与阶段 [S06–S11] + +完整循环：启动与标题 → 球洞1 → 球洞2 → 球洞3 → 总结算 → 重开/返回。每阶段六要素如下（引用本 spec §3–§7 与 §9 对应规则）： + +- S06 启动与标题 + - input：系统启动加载完成（触发方：系统）；玩家按 Enter/点击「开始」 + - precondition：构建可启动且球场按 seed=1056 生成完成 + - state_change：进入「标题」状态；首次进入按 §10 C01 触发开场视频 + - feedback：标题界面按 §9 F10 呈现 + - next_actions：进入「球洞1」 + - outcome：无跨局状态写入（见 §7 V04） +- S07 球洞1（直道平地，标准杆 3） + - input：鼠标瞄准、按住左键蓄力、松开击球、R 重打、C 镜头切换、Esc 暂停（触发方：玩家） + - precondition：洞1 载入完成且球静止于发球点 + - state_change：击球按 G02 公式生成初速 → 物理结算 + - feedback：瞄准线/蓄力条/轨迹残影按 §9 F05 呈现 + - next_actions：入洞 →「球洞2」；8 杆上限 → 强制完成进下一洞 + - outcome：本洞杆数累计局内 +- S08 球洞2（缓上坡＋单挡板折返，标准杆 4） + - input：同 S07（触发方：玩家） + - precondition：洞1 完成（入洞或达上限） + - state_change：载入洞2；坡面与挡板按 L02 冻结 + - feedback：坡面瞄准线变浅提示减速 + - next_actions：入洞 →「球洞3」 + - outcome：杆数累计 +- S09 球洞3（阶梯坡＋双挡板，标准杆 5） + - input：同 S07（触发方：玩家） + - precondition：洞2 完成 + - state_change：载入洞3；阶梯坡与双挡板生效 + - feedback：反弹火花与入洞反馈 + - next_actions：入洞或达上限 →「总结算」（先播 C02） + - outcome：按 V01 结算 +- S10 总结算 + - input：Enter＝重开 / Esc＝返回标题（触发方：玩家） + - precondition：三洞全部完成 + - state_change：进入「总结算」状态 + - feedback：总结算面板显示总杆数、对比标准杆 12、罚杆数 + - next_actions：重开或返回 + - outcome：无跨局写入 +- S11 暂停 + - input：Esc（触发方：玩家） + - precondition：处于任一洞 + - state_change：暂停覆盖层打开；球、物理与蓄力冻结 + - feedback：暂停面板（继续/本洞重打/返回标题/设置） + - next_actions：Esc 或「继续」→ 恢复 + - outcome：恢复后无状态漂移（G04） + +## 3. 数值口径与全局规则 [G01–G05] + +- G01 统一刻度：距离米制；力度为 0–100% 蓄力条（数值常显）；杆数为整数。 +- G02 物理与公式（本包冻结值）：击球初速 v＝蓄力比例 × 12 米/秒；平地滚动摩擦减速度 1.5 米/秒²；坡道沿坡向加速度分量 3.0 米/秒²；碰撞恢复系数 0.6。独立 oracle 数例：平地直线满蓄力 50% 击球 v＝6 米/秒，纯滚动距离＝v²/(2×1.5)＝**12 米**；蓄力 100% 为 48 米。 +- G03 杆数与罚则（本包冻结值）：三洞标准杆 3/4/5（总标准杆 12）；界外复位每次罚 1 杆；每洞杆数上限 8 杆，达上限自动按 8 杆＋累计罚杆记入并进入下一洞（无硬失败）。 +- G04 暂停与随机：Esc 暂停冻结球与物理；窗口失焦自动暂停；fixed_seed=1056 冻结三洞地形布置；本作物理为确定公式，无概率判定。 +- G05 瞄准与轨迹反馈（本包冻结值）：击球准备时显示瞄准虚线——长度＝按当前蓄力的预计纯滚动距离 × 60%，不显示反弹/坡面后路径，坡面段虚线透明度降低 40% 提示减速；蓄力条 0–100% 数值与当前蓄力同步；球滚动中显示轨迹残影（0.5 秒渐隐，仅保留最近一条）。 + +## 4. 操作与输入 [I01–I07] + +- I01 键鼠：鼠标移动＝瞄准方向；按住左键蓄力、松开击球；C＝俯视全览/击球视角切换；R＝本洞重打（罚 1 杆）；Esc＝暂停；结算界面 Enter＝重开。 +- I02 输入语义边界：球滚动中击球无效；蓄力不足 5% 松开视为取消（不耗杆）；暂停/结算期间输入无效；被拒输入不产生杆数变化。 +- I03 无手柄需求。 +- I04 输入优先级：暂停与结算状态阻断全部玩法输入；俯视全览模式下击球无效（须切回击球视角）；同帧多输入按瞄准→蓄力→击球顺序结算。 +- 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。 +- I06 UI 必须显示的状态：当前洞号、本洞已用杆数与上限、蓄力条数值、罚杆数、镜头模式提示；HUD 对照见 rubric。 +- I07 输入延迟目标：蓄力/击球按键到画面反馈 ≤ 50 毫秒（手感关键）；镜头切换 ≤ 150 毫秒。 + +## 5. 关卡与内容清单 [L01–L04] + +- L01 生成对象：高尔夫球 1、三洞（洞杯、旗杆、发球点）、坡面与挡板若干、瞄准线与蓄力条 UI、轨迹残影；花园装饰为表现层。 +- L02 球洞（seed=1056 冻结地形）：洞1 直道平地 12 米（标准杆 3）；洞2 缓上坡＋单挡板折返（标准杆 4）；洞3 阶梯坡＋双挡板（标准杆 5）。 +- 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。 +- 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 未冻结的花园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。 + +## 6. 机制系统 [M01–M05] + +- M01 力度方向与物理（主机制） + - input：瞄准＋蓄力击球 + - precondition：球静止且处于击球准备状态（非俯视全览） + - state_change：按 G02 公式生成初速向量 → 球滚动/反弹 + - observable：逐帧球位置采样与初速、距离事件（见 G02 oracle）；`stroke` 事件（含初速与角度） + - invalid_case：滚动中击球、全览模式击球 → 拒绝且不耗杆 + - recovery：球静止即恢复击球准备 +- M02 坡面反弹与摩擦 + - input：地形接触（系统） + - precondition：球与坡面/挡板碰撞 + - state_change：坡面改变速度分量（沿坡 3.0 米/秒²）；碰撞按恢复系数 0.6 反弹 + - observable：接触/反弹事件与速度分量差分 + - invalid_case：无碰撞则纯摩擦结算 + - recovery：— +- M03 界外复位 + - input：球坠出球场边界（系统） + - precondition：球越过 L02 边界 + - state_change：回上一杆位＋罚 1 杆；连续界外不叠加惩罚上限以外的额外状态；镜头回上一杆位 + - observable：`out_of_bounds` 事件（含罚杆字段） + - invalid_case：贴边滚动不触发 + - recovery：复位即恢复击球 +- M04 杆数判定 + - input：球入洞（系统）/ 达上限（系统） + - precondition：球与洞杯判定重叠且速度低于阈值 + - state_change：本洞完成 → 下一洞；达 8 杆上限强制完成；三洞完成 → 总结算 + - observable：`hole_complete` 事件与杆数流水（含罚杆） + - invalid_case：高速掠过洞杯不判入洞（速度阈值） + - recovery：— +- M05 瞄准与轨迹反馈 + - input：瞄准移动／蓄力变化（玩家） + - precondition：击球准备状态 + - state_change：瞄准虚线长度与坡面透明度按 G05 更新；蓄力条数值同步；击球后生成轨迹残影（0.5 秒渐隐，替换旧残影） + - observable：虚线长度采样与预计距离的 60% 对账；残影出现/渐隐事件 + - invalid_case：全览模式不显示虚线（切回即恢复） + - recovery：— + +## 7. 成功、失败与恢复 [V01–V05] + +- V01 成功条件：完成三洞 → 总结算（显示总杆数、对比标准杆 12 与罚杆数）。 +- V02 失败条件：无硬失败态；每洞 8 杆上限强制推进（记为上限完成）。 +- V03 恢复语义：界外自动复位＋罚 1 杆；R 重打本洞（罚 1 杆、回发球点）；结算后一键重开。 +- V04 persistent_state：无（重开全量清空；累计杆数仅本局内保留）。 +- V05 persistent_state 生命周期：当前动作级状态即时结算；当前局级状态（杆数/洞进度）局内保留、重开清空；无跨局保留状态。 +- V06 软锁与不可达处理：不设永久软锁——8 杆上限保证推进；界外复位兜底；任意洞可完成。 + +## 8. 世界设定与创作基线 [W01–W08] + +- W01 世界与时代背景：架空云海时代的「浮屿花园」——园艺师们在漂浮于云海的花屿上经营三洞试炼球场，庆祝春分的推杆大会今夜开杆。 +- W02 场景所在地：浮屿花园的三座花洞——直道花径（洞1）、上坡藤架（洞2）、阶梯石台（洞3），云海在球场边缘流动。 +- W03 玩家身份与当前任务：玩家是见习园艺师「芽衣」；当前任务：在推杆大会上以不超过标准杆的成绩完成三洞，取得正式园丁资格。 +- W04 失败代价与结局表达：本作无失败态；超标准杆仅影响成绩表达；完成则 C02 呈现大会颁奖与花灯升空。 +- W05 叙事来源：三洞＝园艺师资格考试的三个科目（直道基本功/坡度控球/复杂地形）；旗杆与洞杯＝试炼花器；云海边界＝浮屿边界（界外即坠云）。全部原创。 +- W06 视觉风格与色彩材质：明快风格化 3D 花园；主色＝草甸绿（#7CB26B 系）＋花瓣粉（#E8A0B8 系）＋云海白蓝（#C9DCE8 系）；材质以草坪、木挡板、石台为主，光线为春日暖光。 +- W07 环境氛围与声音语言：云海微风的春日花园——常驻风拂草浪与远处鸟鸣；音效语言为「击球脆响＋滚动沙沙＋碰撞闷响＋入洞清脆」，全部音效按 §9 F06 冻结清单交付。 +- W08 故事表达方式：开场视频（C01）交代浮屿与大会 → 三洞推进承载试炼节奏 → 结算视频（C02）收束颁奖；故事只做包装，不改变机制数值。 + +## 9. 演出、镜头与反馈 [F01–F10] + +- F01 视角与镜头（冻结需求）：默认击球视角＝发球/停球点后方第三人称（俯角 45°，距离 5 米），瞄准方向随鼠标旋转；球滚动时镜头平滑跟随球（0.2 秒插值，速度上限 12 米/秒避免甩镜）；球静止 1 秒后镜头回击球准备位；C 键切换「俯视全览」（整洞 60° 俯视，不参与击球）；镜头边界＝球场外框外扩 10%；界外复位/换洞时镜头直接落位（无漂移）。 +- F02 关键操作镜头变化：入洞瞬间镜头轻微推近洞杯 5%（0.5 秒）；出界瞬间镜头短暂拉高 10%（0.4 秒）；无慢动作。 +- F03 输入与延迟：见 I07（击球手感为 S 档核心，≤50 毫秒）。 +- F04 环境常驻效果：花瓣随风飘落（低频）、云海缓慢流动、旗杆旗面摆动；不遮挡瞄准线与洞杯。 +- F05 事件反馈表（事件 → 表现 → 结束条件，全部为冻结需求）： + +| 事件 | 画面表现 | 音效 | 结束条件 | +|---|---|---|---| +| 蓄力开始 | 蓄力条展开＋数值跳动 | 蓄力低鸣（按住循环，音调随力度升高） | 松开或取消 | +| 击球 | 球推出＋草地小尘环＋轨迹残影启动 | 击球脆响 | 残影 0.5s 渐隐 | +| 球滚动 | 轨迹残影跟随＋草浪压痕 | 滚动沙沙（滚动中循环） | 球停 | +| 碰撞挡板 | 火花小粒子＋球体挤压回弹 | 碰撞闷响 | 回弹完成 | +| 上坡减速 | 瞄准线透明度提示（击球前）/球速渐减 | 沙沙声减弱 | 坡段结束 | +| 出界 | 球坠云＋镜头拉高＋「界外＋1 杆」提示 | 坠落风声 | 复位完成 | +| 入洞 | 球旋入洞杯＋旗杆亮灯＋花瓣迸溅 | 入洞清脆音 | 进入下一洞 | +| 达杆数上限 | 「本洞按 8 杆计」横幅 | 低提示音 | 推进下一洞 | +| 三洞完成 | 花灯升空粒子 | 结算上扬音 | 进入总结算 | + +- F06 关键音效清单：蓄力低鸣、击球脆响、滚动沙沙、碰撞闷响、坠落风声、入洞清脆音、低提示音、上扬音；环境音：风拂草浪＋云海低鸣＋远处鸟鸣（常驻循环）；循环音开始/结束：滚动沙沙按滚动起止、蓄力低鸣按按住起止、环境声随球场载入开始、随结算淡出 0.5s；无配音需求。 +- F07 VFX 信息性与遮挡约束：瞄准虚线与蓄力条承担击球信息；轨迹残影承担落点复盘信息；花瓣与草浪粒子单帧 ≤ 35 且不遮挡瞄准线、洞杯与 HUD。 +- F08 音画同步：击球脆响与击球帧同步；碰撞闷响与接触帧同步；入洞清脆音与入洞事件帧同步。 +- F09 屏幕震动：入洞 0.1 秒小幅；碰撞 0.05 秒微幅；设置界面提供「镜头震动开/关」（关闭不影响判定）。 +- F10 前端界面：标题（开始/设置/退出）→ HUD（洞号、杆数/上限、蓄力条数值、罚杆、镜头模式提示）→ 总结算（总杆数/对比标准杆 12/罚杆/重开/返回）→ 暂停面板（继续/本洞重打/返回标题/设置）；关键状态附图标＋文字（镜头模式、界外提示），不只靠颜色区分；窗口失焦自动暂停。 + +## 10. 过场视频 [C01–C02] + +- C01 开场花园（Opening，10 秒，1280×720@24fps） + - 触发时机：首次由标题进入球洞1 之前，每局一次 + - 内容与角色场景：云海之上的浮屿花园全景，花灯次第点亮，见习园艺师「芽衣」握杆走向三洞试炼球场的第一洞发球点 + - 资产对应：浮屿花园、旗杆、高尔夫球与游戏内模型同源设计 + - 可跳过：Esc/Enter 跳过 → 直接进入球洞1；自然播完 → 同 + - 状态一致：播放期间不推进任何计时；进入状态＝0/3 洞 +- C02 推杆大会结算（Ending，10 秒，1280×720@24fps） + - 触发时机：三洞全部完成后、总结算面板之前，每局一次 + - 内容与角色场景：三座花洞灯带依次亮起，花灯升空汇成春分图案，「芽衣」举起推杆向观众席致意 + - 资产对应：球场、花灯、角色与游戏内一致 + - 可跳过：Esc/Enter 跳过 → 直接进入总结算面板；自然播完 → 同 + - 状态一致：仅在真实完成三洞后触发 + +## 11. 范围与正向能力清单 [N01–N06] + +- N01 本测例包含的玩法能力：三洞冻结球场、蓄力击球物理、坡面反弹与摩擦、瞄准线/蓄力条/轨迹残影反馈、界外复位与罚杆、8 杆上限推进、双镜头模式（击球/俯视全览）。 +- N02 本测例包含的流程与界面：标题、三洞推进、总结算、暂停（含失焦自动暂停）、重打与重开。 +- N03 本测例包含的演出能力：开场/结算视频（C01/C02）、§9 F04–F09 全部事件反馈与音效、云海花园氛围。 +- N04 输入范围：键盘＋鼠标（鼠标瞄准/左键蓄力/C/R/Esc/Enter）；无触控、手柄、多人需求。 +- N05 音频范围：§9 F06 冻结音效清单＋花园环境音；无配音与背景音乐轨需求。 +- N06 表现层自由度：§9 未冻结的花卉装饰、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。 + +## 12. 参考图绑定 [A01] + +- 本测例当前无已绑定参考图；规划的参考图（见习园艺师「芽衣」、高尔夫球与旗杆、三洞球场布局等）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。 + +## 13. 复杂度档案 + +```yaml +difficulty: + tier: S + complexity_profile: {coupling: C1, persistence: P0, recovery: R1, runtime_complexity: B1, hidden_state: H0} + dominant_dimensions: [recovery] + rationale: "单主闭环（瞄准→蓄力→击球→物理→进洞/补杆）；坡面与反弹均为物理系统内部规则，无跨系统因果链；多球物理与镜头插值并发（B1）；无失败态，界外复位与重打为恢复路径；新增瞄准反馈与镜头模式不改变难度档" + downgrade_boundary: "去掉坡面与挡板（纯平地直道）后仍为 S（更简）" + upgrade_boundary: "若杆数成绩跨洞/跨局保留并解锁新球场规则，升 M/L" + stress_axes: [] +``` + +## 生成任务明确性补充（2026-10-12） + +> 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。 + +### 故事与流程最低合同 +- **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”。 +- **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。 +- **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。 + +### 生成任务清单（JSONL 冻结口径） +- 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。 +- object：3 个（text-to-3D 2，image-to-3D 1）；object 任务资产为：gardener_mei, golf_ball, hole_flag。每项只允许一个物体；组合物必须拆成独立任务。 +- motion：2 个；覆盖动作：idle, putt_swing。 +- video/audio/mechanic/UI：分别为 2/9/1/1 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。 + +### Video / motion / audio 生命周期 +- 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。 +- 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”。 +- 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。 + +### Mechanic / UI / 游玩手感 +- 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。 +- 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。 +- 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。 + +### VFX 时机合同 +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”。 + diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/method_selection.md b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/method_selection.md new file mode 100644 index 0000000000000000000000000000000000000000..869ae1f54e0eaf8706c0b2865a76c19c00190ee0 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/method_selection.md @@ -0,0 +1,152 @@ +# 优先资产：方法选择与执行边界 + +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 +API 配置。评测口径以 `GameFactory-3A/eval/asset_evaluation_plan.md` 为准； +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。 + +## 1. 建议首轮组合 + +| 类别 | 首轮建议 | 放在哪组 | 选择理由 / 限制 | +|---|---|---|---| +| 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 | +| 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 | +| 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 | +| 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 | +| 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 | +| 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 | +| 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 | + +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 +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。 +MoMask、Puppeteer、WorldPlay、WorldMirror 的源码/模型发布可在官方仓库核对 [R1–R4]。 +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。 + +**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 +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， +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。 + +## 2. 为什么按这些方法分组 + +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。 +因此保留用户提出的系统比较，但不悄悄改掉主表含义： + +- 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。 +- B2：Marble direct 与 WorldPlay + WorldMirror / LLM composition 分 panel 报告。 +- 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； + LLM 直出是另一条系统方法。不能把它们标为两个闭源 motion API。 +- 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， + 但需要显式修改协议，而不是沿用 `Closed-source method` 表头。 + +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、 +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。 +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。 + +## 3. 与当前优先清单对齐的阻塞项 + +### 3D Object：低模与上下文能力 + +现有 200 条保留低模 prompt，且 `decimation_target` 最高 8000。 +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， +也不要把减面后生成的新几何缺陷完全归给原始模型。 + +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。 +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。 +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]。 +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。 + +不要用 `latest` 当作冻结版本。Meshy 文档还提示其 `lowpoly` 模型类型将在 +2026-10-30 退役；现有清单的 `poly_policy: low_poly_priority` 只是实验政策， +不等于必须调用这个即将退役的 API 类型 [R6]。 + +### 3D Scene：交付要有真实场景 + +69 条现有场景任务要求 `output_format: glb`。WorldPlay 的视频需经 WorldMirror 重建 +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。 + +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。 +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 +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]。 +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。 + +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； +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。 + +### Audio：需要按声音任务选方法，不是一种模型跑全部 + +当前非语音 706 条：623 条 `one_shot`、83 条 `ambient_loop`；语音 38 条，全部中文。 +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。 +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。 + +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； +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]。 +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， +而不是把已开放权重的 3.0 Medium / Small / Small SFX 当作闭源方法 [R10]。 +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]。 +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。 + +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。 +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， +单列 pipeline 结果及成本，不能悄悄改任务时长来让 API 通过。 + +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 +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 +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]。 + +### CG：现有任务与 reference-image 协议不一致 + +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 +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。 + +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， +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 +任务版本；不能各视频方法自行画图作为自己的参考。 + +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 +768P 的 6/10 秒或 1080P 的 6 秒，不能把原 JSON 原样发出去 [R13]。 +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。 +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。 + +### Motion：保留非人形与短动作 + +新增 78 条中，76 条人形、G040 一条 vehicle、G030 一条 mechanical。 +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。 +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。 + +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 +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 +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。 + +## 4. 最小执行顺序 + +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。 +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。 + 每类先挑少量代表任务；这不缩减 L 级正式导入清单。 +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。 +4. 报 Delivery、C、Q1/Q2/Q3、Coverage 和成本，按游戏宏平均；不挑 best-of，也不将 + 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。 +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 + 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。 + 若比较资产来源，另设因子并保持 repair 方法与预算一致。 + +## 官方来源 + +- [R1: MoMask](https://github.com/EricGuo5513/momask-codes) +- [R2: Puppeteer](https://github.com/Seed3D/Puppeteer) +- [R3: HY-WorldPlay](https://github.com/Tencent-Hunyuan/HY-WorldPlay) +- [R4: HunyuanWorld-Mirror](https://github.com/Tencent-Hunyuan/HunyuanWorld-Mirror) +- [R5: Hunyuan3D Pro API](https://intl.cloud.tencent.com/ind/document/product/1284/75540) +- [R6: Meshy Text-to-3D](https://docs.meshy.ai/en/api/text-to-3d) +- [R7: World Labs World API](https://docs.worldlabs.ai/api) +- [R8: ElevenLabs Sound Effects API](https://elevenlabs.io/docs/api-reference/text-to-sound-effects/convert) +- [R9: ElevenLabs Sound Effects 能力总览](https://elevenlabs.io/docs/overview/capabilities/sound-effects) +- [R10: Stable Audio 模型及商用 API 入口](https://stability.ai/stable-audio) +- [R11: MiniMax TTS](https://platform.minimax.io/docs/api-reference/speech-t2a-http) +- [R12: ElevenLabs 模型](https://elevenlabs.io/docs/overview/models) +- [R13: MiniMax Hailuo T2V](https://platform.minimax.io/docs/api-reference/video-generation-t2v) +- [R14: Meshy Text-to-Motion](https://docs.meshy.ai/en/api/text-to-motion) +- [R15: Tripo 开发者入口](https://developers.tripo3d.ai/) +- [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) + +Seedance 的本地封装 `GameFactory-3A/models/gen_cg_video/seedance_model.py` 已登记 +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 +宣称已核对其全部时长/分辨率规格，开跑前仍需 API pilot。 diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt new file mode 100644 index 0000000000000000000000000000000000000000..208ebd0016d36f7d818a97f57900f811ef3679c1 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/inputs/object_requirement.txt @@ -0,0 +1,8 @@ +# G056_garden_minigolf / 3D_object requirement + +Source of truth: ../general_requirement.txt + 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(excerpt): 漂浮花园的迷你高尔夫 | - W01 世界与时代背景：架空云海时代的「浮屿花园」——园艺师们在漂浮于云海的花屿上经营三洞试炼球场，庆祝春分的推杆大会今夜开杆。 | - S01 类型：3D 俯视迷你高尔夫（单人杆数制）。本测例包含的能力：三洞冻结球场、蓄力击球物理、坡面反弹摩擦、瞄准线与轨迹残影反馈、界外复位与罚杆、双镜头模式、开场/结算视频。\nAsset: Miniature golf hole cup with a slender striped pennant flag and a subtle glow rim, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "texture": true, + "export_uv": true, + "face_limit": 6000, + "model_seed": 1563, + "texture_seed": 1563, + "model_version": "v3.1-20260211", + "smart_low_poly": true, + "texture_quality": "standard", + "geometry_quality": "standard", + "texture_alignment": "geometry" + }, + "output": { + "model_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/ee4bb38a-96e3-49ef-bf95-f53907b9eb7d/tripo_pbr_model_ee4bb38a-96e3-49ef-bf95-f53907b9eb7d.glb?auth_key=1792227868-fkyitdjc-0-b992f55786163732ed8ff507330a63ba", + "rendered_image_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/ee4bb38a-96e3-49ef-bf95-f53907b9eb7d/legacy_mesh.webp?auth_key=1792227868-harozuco-0-e116d3767acf491181038fb1de8c3792", + "generated_image_url": "https://openapi.cdn.tripo3d.com/tcli_8a234d301b1e472ebe10d73adcd43336/20261016/ee4bb38a-96e3-49ef-bf95-f53907b9eb7d/text2image_ee4bb38a-96e3-49ef-bf95-f53907b9eb7d.jpeg?auth_key=1792227868-uxcslqgf-0-fd81a6201129738568416b6314fd8089" + }, + "task_id": "ee4bb38a-96e3-49ef-bf95-f53907b9eb7d", + "created_at": "2026-10-16T09:00:01.824096Z", + "completed_at": "2026-10-16T09:04:23.778878Z", + "credits_consumed": 30.0 + } + } + } +} diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/cloud_api.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/cloud_api.py new file mode 100644 index 0000000000000000000000000000000000000000..0553c4d55352bbb3fb5ade7c38c53d246484e33f --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/cloud_api.py @@ -0,0 +1,557 @@ +""" +models/common/cloud_api.py + +Shared plumbing for closed-source ("cloud API") model wrappers — the part of +Tripo / Meshy / Rodin / ElevenLabs / Kling wrappers that is identical no matter +what the provider generates. + +Contract: `agent_skills/develop_harness/api_model_require.md` R9. +This module owns R9.6 (submit → poll → download behind a blocking call), +R9.7 (API key from the environment, at call time), R9.8 (response cache, so a +re-run is not re-billed) and R9.9 (retry with backoff, retryable vs. terminal). + +It knows nothing about 3D, audio or video — only HTTP, money and failure modes. + +Dependencies: stdlib at import time; `requests` is imported lazily on first use +so `test/harness/smoke.py` keeps working on a machine that does not have it. + +Usage: + from models.common import cloud_api + + key = cloud_api.require_api_key(None, "TRIPO_API_KEY", + "https://platform.tripo3d.ai/api-keys") + client = cloud_api.CloudAPIClient("https://openapi.tripo3d.ai/v3", key) + data = client.request("POST", "/generation/text-to-model", json={...}) +""" +from __future__ import annotations + +import hashlib +import json +import logging +import os +import time +from pathlib import Path +from typing import Any, Callable, Iterable, Optional + +logger = logging.getLogger(__name__) +logger.addHandler(logging.NullHandler()) + +#: HTTP statuses worth retrying — transient by nature. +RETRYABLE_STATUS: frozenset[int] = frozenset({408, 409, 425, 429, 500, 502, 503, 504}) + +#: HTTP statuses that will never succeed on retry: bad request, auth, quota. +TERMINAL_STATUS: frozenset[int] = frozenset({400, 401, 402, 403, 404, 405, 413, 415, 422}) + + +# ── Errors ──────────────────────────────────────────────────────────────────── + + +class CloudAPIError(RuntimeError): + """ + Base class for every cloud-API failure. + + Attributes: + status: HTTP status code, when the failure came from a response. + task_id: Provider task id, when one had already been created — keep it, + a timed-out task usually finishes anyway and can be fetched + later (`api_model_require.md` R9.6). + payload: Decoded response body, truncated for readability. + """ + + retryable = False + + def __init__(self, message: str, *, status: Optional[int] = None, + task_id: Optional[str] = None, payload: Any = None): + super().__init__(message) + self.status = status + self.task_id = task_id + self.payload = payload + + +class CloudAPIAuthError(CloudAPIError): + """401 / 403 — the key is missing, wrong, or lacks the entitlement.""" + + +class CloudAPIQuotaError(CloudAPIError): + """402 or a provider-specific "insufficient credits" body. Terminal.""" + + +class CloudAPIRequestError(CloudAPIError): + """400 / 404 / 422 — the request itself is wrong. Terminal.""" + + +class CloudAPIServerError(CloudAPIError): + """5xx and connection-level failures. Retryable.""" + + retryable = True + + +class CloudAPIRateLimitError(CloudAPIServerError): + """429 — retryable, honour `Retry-After` when present.""" + + +class CloudTaskFailed(CloudAPIError): + """The provider accepted the task and then reported failure.""" + + +class CloudTaskTimeout(CloudAPIError): + """The task did not reach a terminal state within `timeout` seconds.""" + + +# ── Credentials ─────────────────────────────────────────────────────────────── + + +def require_api_key(value: Optional[str], env_var: str, signup_url: str, + *, who: str = "This model") -> str: + """ + Resolve an API key, failing fast with an actionable message (R1.6 / R9.7). + + Args: + value: Explicit key passed to the constructor, or None. + env_var: Environment variable to fall back to. + signup_url: Where a human gets a key. + who: Name used in the error message. + + Returns: + The key. + + Raises: + CloudAPIAuthError: no key available. + """ + key = value or os.environ.get(env_var) + if key: + return key.strip() + raise CloudAPIAuthError( + f"{who} needs an API key and none was found.\n" + f" 1. get one at {signup_url}\n" + f" 2. export {env_var}= # never commit it\n" + f" (or pass api_key=... to the constructor)" + ) + + +def redact(key: Optional[str]) -> str: + """Key fingerprint safe to put in a log line or `meta.json`.""" + if not key: + return "" + return f"{key[:4]}…{key[-2:]} (len {len(key)})" + + +# ── HTTP ────────────────────────────────────────────────────────────────────── + + +def _requests(): + """Import `requests` lazily with an actionable message (R1.5 / R1.6).""" + try: + import requests # noqa: PLC0415 + except ImportError as e: # pragma: no cover - environment dependent + raise ImportError( + "Cloud-API model wrappers need the `requests` package:\n" + " bash scripts/asset_env_setup/cloud_api_install.sh\n" + " # or simply: python -m pip install requests\n" + "(only needed for the API backends; the local-weight models and " + "test/harness/smoke.py do not import it.)" + ) from e + return requests + + +def _truncate(payload: Any, limit: int = 600) -> Any: + text = payload if isinstance(payload, str) else json.dumps(payload, default=str) + return text if len(text) <= limit else text[:limit] + f"… (+{len(text) - limit} chars)" + + +def classify_http_error(status: int, body: Any, *, + task_id: Optional[str] = None) -> CloudAPIError: + """ + Map an HTTP status onto the right exception class (R9.9). + + The body is inspected too: providers happily answer 200/400 with a + "not enough credits" payload, which must not be retried. + """ + text = _truncate(body) + low = str(text).lower() + # Providers phrase "you are out of money" in prose, and the status code alone + # does not distinguish it from a bad key: Tripo answers **403** with + # "You don't have enough credit to create this task". Matching the body first + # is what keeps "wrong key" and "no money" apart for the caller. + if any(s in low for s in ("insufficient", "enough credit", "enough credits", + "out of credit", "purchase more credit", + "quota exceeded", "no credits", "balance")): + return CloudAPIQuotaError( + f"HTTP {status}: out of credits — {text}", status=status, + task_id=task_id, payload=body) + if status in (401, 403): + return CloudAPIAuthError( + f"HTTP {status}: authentication rejected — {text}", status=status, + task_id=task_id, payload=body) + if status == 402: + return CloudAPIQuotaError( + f"HTTP {status}: payment required — {text}", status=status, + task_id=task_id, payload=body) + if status == 429: + return CloudAPIRateLimitError( + f"HTTP {status}: rate limited — {text}", status=status, + task_id=task_id, payload=body) + if status in TERMINAL_STATUS: + return CloudAPIRequestError( + f"HTTP {status}: request rejected — {text}", status=status, + task_id=task_id, payload=body) + if status in RETRYABLE_STATUS or status >= 500: + return CloudAPIServerError( + f"HTTP {status}: server error — {text}", status=status, + task_id=task_id, payload=body) + return CloudAPIError( + f"HTTP {status}: unexpected response — {text}", status=status, + task_id=task_id, payload=body) + + +class CloudAPIClient: + """ + Thin retrying HTTP client for one provider. + + Args: + base_url: Root of the API, without a trailing slash. + api_key: Bearer token. + timeout: Per-request socket timeout in seconds (not the task timeout). + max_retries: Extra attempts after the first one, for retryable failures. + backoff: Base of the exponential backoff, seconds. + auth_header: Header name / value template, for providers that do not + use `Authorization: Bearer `. + user_agent: Sent as-is; helps providers attribute traffic. + """ + + def __init__( + self, + base_url: str, + api_key: str, + *, + timeout: int = 60, + max_retries: int = 3, + backoff: float = 1.5, + auth_header: str = "Authorization", + auth_template: str = "Bearer {key}", + user_agent: str = "3AGameFactory/0.1 (+https://github.com/OpenDCAI/GameFactory-3A)", + ): + self.base_url = base_url.rstrip("/") + self._api_key = api_key + self.timeout = timeout + self.max_retries = max_retries + self.backoff = backoff + self.auth_header = auth_header + self.auth_template = auth_template + self.user_agent = user_agent + self._session = None + + # -- session --------------------------------------------------------------- + + @property + def session(self): + """Lazily created `requests.Session` (kept alive across polls).""" + if self._session is None: + requests = _requests() + self._session = requests.Session() + self._session.headers.update({ + self.auth_header: self.auth_template.format(key=self._api_key), + "User-Agent": self.user_agent, + }) + return self._session + + def close(self) -> None: + """Idempotent — safe after a failed construction and safe to call twice.""" + if self._session is not None: + try: + self._session.close() + finally: + self._session = None + + # -- requests -------------------------------------------------------------- + + def request( + self, + method: str, + path: str, + *, + json_body: Optional[dict] = None, + files: Optional[dict] = None, + data: Optional[dict] = None, + params: Optional[dict] = None, + expect_json: bool = True, + ) -> Any: + """ + Perform one API call, retrying retryable failures (R9.9). + + Args: + method: "GET" / "POST" / … + path: Path appended to `base_url`, or a full URL. + json_body: JSON payload. + files/data: multipart payload (`requests` semantics). + params: Query string. + expect_json: Parse the response as JSON; otherwise return `bytes`. + + Returns: + Parsed JSON (dict / list) or raw `bytes`. + + Raises: + CloudAPIError subclass — terminal errors immediately, retryable ones + after `max_retries` attempts. + """ + requests = _requests() + url = path if path.startswith("http") else f"{self.base_url}/{path.lstrip('/')}" + + last: Optional[CloudAPIError] = None + for attempt in range(self.max_retries + 1): + try: + resp = self.session.request( + method, url, json=json_body, files=files, data=data, + params=params, timeout=self.timeout, + ) + except (requests.ConnectionError, requests.Timeout) as e: + last = CloudAPIServerError(f"{method} {url} failed at transport level: {e}") + else: + if resp.ok: + if not expect_json: + return resp.content + try: + return resp.json() + except ValueError as e: + raise CloudAPIError( + f"{method} {url} returned {resp.status_code} with a " + f"non-JSON body: {_truncate(resp.text)}" + ) from e + try: + body: Any = resp.json() + except ValueError: + body = resp.text + err = classify_http_error(resp.status_code, body) + if not err.retryable: + raise err + last = err + retry_after = resp.headers.get("Retry-After") + if retry_after: + try: + time.sleep(min(float(retry_after), 60.0)) + except ValueError: + pass + + if attempt < self.max_retries: + delay = self.backoff * (2 ** attempt) + logger.warning("[cloud_api] %s %s attempt %d/%d failed (%s); retrying in %.1fs", + method, url, attempt + 1, self.max_retries + 1, last, delay) + time.sleep(delay) + + assert last is not None + raise last + + def download(self, url: str, *, max_bytes: Optional[int] = None) -> bytes: + """ + Fetch a generated artifact. Signed asset URLs are short-lived — call this + immediately after the task reports success. + + Args: + url: Absolute URL from the task output. + max_bytes: Reject anything larger, so a wrong URL cannot fill a disk. + + Returns: + The file content. + """ + content = self.request("GET", url, expect_json=False) + if max_bytes is not None and len(content) > max_bytes: + raise CloudAPIError( + f"downloaded artifact is {len(content)} bytes, over the " + f"{max_bytes} byte limit: {url}") + if not content: + raise CloudAPIError(f"downloaded artifact is empty: {url}") + return content + + +# ── Polling ─────────────────────────────────────────────────────────────────── + + +def poll_task( + fetch: Callable[[], dict], + *, + task_id: str, + timeout: float = 300.0, + poll_interval: float = 3.0, + done_states: Iterable[str], + failed_states: Iterable[str], + state_key: str = "status", + progress_key: str = "progress", + verbose: bool = False, +) -> dict: + """ + Block until a provider task reaches a terminal state (R9.6). + + Args: + fetch: Callable returning the decoded task object. + task_id: Only used for messages — every error carries it. + timeout: Wall-clock budget in seconds. + poll_interval: Seconds between polls. + done_states: States meaning success (compared case-insensitively). + failed_states: States meaning failure. + state_key: Field holding the state. + progress_key: Field holding 0-100 progress, when the provider sends one. + verbose: Print progress; otherwise only DEBUG logs (R3.7). + + Returns: + The task object in its successful terminal state. + + Raises: + CloudTaskFailed: provider reported failure. + CloudTaskTimeout: budget exhausted; the task may still finish server-side, + the error carries `task_id` so it can be fetched later. + """ + done = {s.lower() for s in done_states} + failed = {s.lower() for s in failed_states} + deadline = time.time() + timeout + last_progress = -1 + + while True: + task = fetch() + state = str(task.get(state_key, "")).lower() + progress = task.get(progress_key) + + if progress != last_progress: + last_progress = progress + logger.debug("[cloud_api] task %s: %s (%s%%)", task_id, state, progress) + if verbose: + print(f"[cloud_api] task {task_id}: {state} ({progress}%)") + + if state in done: + return task + if state in failed: + raise CloudTaskFailed( + f"task {task_id} ended as {state!r}: {_truncate(task)}", + task_id=task_id, payload=task) + + remaining = deadline - time.time() + if remaining <= 0: + raise CloudTaskTimeout( + f"task {task_id} still {state!r} after {timeout:.0f}s. It may still " + f"finish server-side — query it with the task id above, or raise " + f"`timeout=` on the model.", + task_id=task_id, payload=task) + time.sleep(min(poll_interval, remaining)) + + +# ── Response cache ──────────────────────────────────────────────────────────── + + +def request_hash(payload: dict) -> str: + """ + Stable sha256 over a request description (R9.8). + + The payload must contain everything that changes the output — model version, + prompt, image bytes hash, every generation parameter, the output format. + Never put the API key in it. + """ + canonical = json.dumps(payload, sort_keys=True, ensure_ascii=False, default=str) + return hashlib.sha256(canonical.encode("utf-8")).hexdigest() + + +def bytes_hash(data: bytes) -> str: + """sha256 of a binary input, e.g. the reference image.""" + return hashlib.sha256(data).hexdigest() + + +class ResponseCache: + """ + Content-addressed cache of generated artifacts. + + A cloud call costs credits, so an identical request must never be sent twice + (R9.8). Layout:: + + //. the artifact + //.meta.json request description + task id + + Args: + cache_dir: Root directory. `None` disables caching entirely. + provider: Sub-directory name, so two providers never collide. + """ + + def __init__(self, cache_dir: Optional[str | Path], provider: str): + self.root = Path(cache_dir).expanduser() / provider if cache_dir else None + self.provider = provider + + @property + def enabled(self) -> bool: + return self.root is not None + + def _paths(self, key: str, ext: str) -> tuple[Path, Path]: + assert self.root is not None + return self.root / f"{key}.{ext}", self.root / f"{key}.meta.json" + + def get(self, key: str, ext: str = "glb") -> Optional[bytes]: + """Cached artifact bytes, or None. Performs no network I/O, ever.""" + if not self.enabled: + return None + blob, _ = self._paths(key, ext) + if blob.is_file() and blob.stat().st_size > 0: + logger.info("[cloud_api] cache hit (%s): %s", self.provider, blob.name) + return blob.read_bytes() + return None + + def put(self, key: str, data: bytes, meta: dict, ext: str = "glb") -> Path: + """Store an artifact plus the request that produced it. Returns its path.""" + if not self.enabled: + return Path() + blob, meta_path = self._paths(key, ext) + blob.parent.mkdir(parents=True, exist_ok=True) + blob.write_bytes(data) + meta_path.write_text( + json.dumps({**meta, "cache_key": key, "bytes": len(data)}, + indent=2, ensure_ascii=False, default=str), + encoding="utf-8", + ) + return blob + + +# ── Input encoding ──────────────────────────────────────────────────────────── + + +def image_to_png_bytes(image: Any) -> bytes: + """ + Normalize an image input to PNG bytes. + + Accepts a `PIL.Image.Image`, raw `bytes` (returned unchanged), or a + `np.ndarray`. Paths are rejected on purpose — `model_require.md` R3.2 says a + model takes the object, not a path. + + Returns: + PNG-encoded bytes (RGBA preserved when present). + """ + if isinstance(image, (bytes, bytearray)): + return bytes(image) + if isinstance(image, (str, Path)): + raise TypeError( + "models take an image object, not a path (model_require.md R3.2). " + "Open it in the operator: Image.open(path).convert('RGBA')" + ) + + from io import BytesIO # noqa: PLC0415 + + from PIL import Image as PILImage # noqa: PLC0415 + + if not isinstance(image, PILImage.Image): + try: + import numpy as np # noqa: PLC0415 + except ImportError: + np = None # type: ignore[assignment] + if np is not None and isinstance(image, np.ndarray): + image = PILImage.fromarray(image) + else: + raise TypeError( + f"unsupported image type {type(image).__name__}; expected " + f"PIL.Image.Image, numpy.ndarray or bytes" + ) + + buf = BytesIO() + image.save(buf, format="PNG") + return buf.getvalue() + + +def image_to_data_uri(image: Any, mime: str = "image/png") -> str: + """PNG data URI (`data:image/png;base64,…`) for providers that take one inline.""" + import base64 # noqa: PLC0415 + + payload = base64.b64encode(image_to_png_bytes(image)).decode("ascii") + return f"data:{mime};base64,{payload}" diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/glb_utils.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/glb_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..61d86409097747264cabddb0301edc925f4f1ff7 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/common/glb_utils.py @@ -0,0 +1,578 @@ +""" +models/common/glb_utils.py + +Dependency-free inspection of binary glTF (`.glb`) buffers. + +Why this exists instead of `trimesh.load(...)`: the API wrappers must report the +triangle count of what they just paid for (`api_model_require.md` R9.8), and +that number has to be available on a CPU-only box with nothing but the stdlib +installed. Parsing the JSON chunk of a GLB is enough for counting. + +`glb_summary` and `glb_triangle_count` read the JSON chunk only. `read_glb_mesh` +decodes vertex data as well, because a generated part has to be *composed* with +primitives rather than merely counted, and that needs its triangles in the same +coordinate frame as everything else. + +Usage: + from models.common.glb_utils import glb_summary, read_glb_mesh + info = glb_summary(open("model.glb", "rb").read()) + print(info["triangles"], info["materials"]) + + mesh = read_glb_mesh(open("part.glb", "rb").read()) + print(len(mesh["positions"]), mesh["low"], mesh["high"]) +""" +from __future__ import annotations + +import json +import math +import struct +from typing import Any, Optional, Sequence + +GLB_MAGIC = b"glTF" + +#: glTF primitive mode 4 == TRIANGLES. Only triangle primitives are counted. +_MODE_TRIANGLES = 4 + +#: glTF componentType -> (struct format, byte size). Indices are allowed to be +#: any of the unsigned types; positions are float in every file worth reading. +_COMPONENT_TYPES: dict[int, tuple[str, int]] = { + 5120: ("b", 1), # BYTE + 5121: ("B", 1), # UNSIGNED_BYTE + 5122: ("h", 2), # SHORT + 5123: ("H", 2), # UNSIGNED_SHORT + 5125: ("I", 4), # UNSIGNED_INT + 5126: ("f", 4), # FLOAT +} + +#: glTF accessor type -> component count. +_TYPE_COUNTS: dict[str, int] = { + "SCALAR": 1, "VEC2": 2, "VEC3": 3, "VEC4": 4, + "MAT2": 4, "MAT3": 9, "MAT4": 16, +} + + +class GLBParseError(ValueError): + """The buffer is not a GLB we can read.""" + + +def is_glb(data: bytes) -> bool: + """True when `data` starts with the 12-byte GLB header.""" + return len(data) >= 12 and data[:4] == GLB_MAGIC + + +def glb_json_chunk(data: bytes) -> dict[str, Any]: + """ + Return the parsed JSON chunk of a GLB. + + Args: + data: Whole `.glb` file content. + + Returns: + The glTF document as a dict. + + Raises: + GLBParseError: bad magic, truncated file, or a missing JSON chunk. + """ + if not is_glb(data): + raise GLBParseError( + f"not a GLB: expected magic {GLB_MAGIC!r}, got {data[:4]!r}" + ) + if len(data) < 20: + raise GLBParseError(f"GLB truncated: {len(data)} bytes") + + _magic, version, total_len = struct.unpack_from("<4sII", data, 0) + if total_len > len(data): + raise GLBParseError( + f"GLB header claims {total_len} bytes, buffer holds {len(data)}" + ) + + offset = 12 + while offset + 8 <= len(data): + chunk_len, chunk_type = struct.unpack_from(" Optional[int]: + """ + Triangle count of a GLB, or None when it cannot be determined. + + Counts every triangle-mode primitive of every mesh once, i.e. the *asset's* + triangle budget, not the per-instance count after node duplication. + + Returns: + int triangles, or None if the JSON chunk is unreadable. + """ + try: + doc = glb_json_chunk(data) + except GLBParseError: + return None + + accessors = doc.get("accessors", []) + total = 0 + for mesh in doc.get("meshes", []): + for prim in mesh.get("primitives", []): + if prim.get("mode", _MODE_TRIANGLES) != _MODE_TRIANGLES: + continue + idx = prim.get("indices") + if idx is not None and idx < len(accessors): + count = accessors[idx].get("count", 0) + else: + pos = prim.get("attributes", {}).get("POSITION") + count = accessors[pos].get("count", 0) if pos is not None and pos < len(accessors) else 0 + total += count // 3 + return total + + +def glb_summary(data: bytes) -> dict[str, Any]: + """ + Cheap description of a GLB, for logs and `meta.json`. + + Returns: + dict with keys: + bytes (int) — buffer size + triangles (int | None) — see `glb_triangle_count` + meshes, materials, textures, images, nodes (int) + generator (str | None) — glTF `asset.generator` + error (str) — present only when the JSON chunk is unreadable + """ + out: dict[str, Any] = {"bytes": len(data)} + try: + doc = glb_json_chunk(data) + except GLBParseError as e: + out.update({"triangles": None, "error": str(e)}) + return out + + out.update({ + "triangles": glb_triangle_count(data), + "meshes": len(doc.get("meshes", [])), + "materials": len(doc.get("materials", [])), + "textures": len(doc.get("textures", [])), + "images": len(doc.get("images", [])), + "nodes": len(doc.get("nodes", [])), + "generator": (doc.get("asset") or {}).get("generator"), + }) + return out + + +# -------------------------------------------------------------------------- +# Vertex decoding +# +# Needed to *compose* a generated part with primitives, as opposed to merely +# reporting on it: composition means putting its triangles into the same +# coordinate frame as the rest, and that requires reading them. +# -------------------------------------------------------------------------- + + +def glb_binary_chunk(data: bytes) -> bytes: + """Return the BIN chunk of a GLB, or b"" when there is none.""" + if not is_glb(data): + raise GLBParseError(f"not a GLB: got magic {data[:4]!r}") + offset = 12 + while offset + 8 <= len(data): + chunk_len, chunk_type = struct.unpack_from(" list[tuple]: + """Decode one accessor into a list of component tuples. + + Honours ``byteStride``. Interleaved buffers are normal out of an + exporter, and reading one as tightly packed yields positions that are a + silent mixture of coordinates and normals — it parses, it renders, it is + garbage. + """ + + accessor = doc["accessors"][index] + component_type = accessor["componentType"] + if component_type not in _COMPONENT_TYPES: + raise GLBParseError(f"unsupported componentType {component_type}") + fmt, component_size = _COMPONENT_TYPES[component_type] + per_element = _TYPE_COUNTS[accessor["type"]] + count = accessor["count"] + + view_index = accessor.get("bufferView") + if view_index is None: + # A sparse or zero-filled accessor. Legal, and not something a mesh + # we are about to weld into another asset should be relying on. + return [tuple([0] * per_element)] * count + + view = doc["bufferViews"][view_index] + if view.get("buffer", 0) != 0: + raise GLBParseError("only single-buffer GLBs are supported") + base = view.get("byteOffset", 0) + accessor.get("byteOffset", 0) + packed = component_size * per_element + stride = view.get("byteStride") or packed + + out: list[tuple] = [] + element_format = "<" + fmt * per_element + for element in range(count): + start = base + element * stride + if start + packed > len(binary): + raise GLBParseError( + f"accessor {index} reads past the {len(binary)}-byte buffer" + ) + out.append(struct.unpack_from(element_format, binary, start)) + return out + + +def _node_matrix(node: dict[str, Any]) -> list[float]: + """A node's local transform as a 16-float column-major matrix. + + Handles both an explicit ``matrix`` and a TRS triple, since a file may use + either. Ignoring the transform looks like a modelling error: a mesh + authored Z-up whose node carries the -90 that stands it upright arrives on + its side, and the natural reaction is to rotate it back in the spec — + hard-coding a correction for something the file already stated. + """ + + if "matrix" in node: + return [float(value) for value in node["matrix"]] + + tx, ty, tz = [float(value) for value in node.get("translation", (0, 0, 0))] + qx, qy, qz, qw = [float(value) for value in node.get("rotation", (0, 0, 0, 1))] + sx, sy, sz = [float(value) for value in node.get("scale", (1, 1, 1))] + + # Quaternion to rotation matrix. + xx, yy, zz = qx * qx, qy * qy, qz * qz + xy, xz, yz = qx * qy, qx * qz, qy * qz + wx, wy, wz = qw * qx, qw * qy, qw * qz + rotation = ( + (1 - 2 * (yy + zz), 2 * (xy + wz), 2 * (xz - wy)), + (2 * (xy - wz), 1 - 2 * (xx + zz), 2 * (yz + wx)), + (2 * (xz + wy), 2 * (yz - wx), 1 - 2 * (xx + yy)), + ) + scale = (sx, sy, sz) + return [ + rotation[0][0] * scale[0], rotation[0][1] * scale[0], rotation[0][2] * scale[0], 0.0, + rotation[1][0] * scale[1], rotation[1][1] * scale[1], rotation[1][2] * scale[1], 0.0, + rotation[2][0] * scale[2], rotation[2][1] * scale[2], rotation[2][2] * scale[2], 0.0, + tx, ty, tz, 1.0, + ] + + +def _multiply(a: Sequence[float], b: Sequence[float]) -> list[float]: + """Column-major 4x4 product, applying `b` then `a`.""" + out = [0.0] * 16 + for column in range(4): + for row in range(4): + out[column * 4 + row] = sum( + a[k * 4 + row] * b[column * 4 + k] for k in range(4) + ) + return out + + +_IDENTITY = [1.0, 0, 0, 0, 0, 1.0, 0, 0, 0, 0, 1.0, 0, 0, 0, 0, 1.0] + + +def read_glb_mesh(data: bytes) -> dict[str, Any]: + """Decode every triangle of a GLB into one flat, world-space mesh. + + Walks the scene graph and applies each node's accumulated transform, so + the result is in the file's own world coordinates rather than in the + local frame of whichever mesh happened to be first. + + The node hierarchy is deliberately *not* preserved. A part fetched from + a generator is one object as far as the composition is concerned — the + thing worth keeping addressable is the spec's part id, which the writer + attaches, and a generator's internal node names ("mesh_0", "Object_2") + are not names anything downstream can use. + + Returns: + dict with ``positions`` and ``normals`` as lists of 3-tuples, + ``uvs`` as 2-tuples, ``indices`` as a flat list, ``low``/``high`` as + the axis-aligned bounds, and ``images`` / ``material_runs`` carrying + whatever textures the file brought with it. Normals are generated + per-face when the file omits them. + + Textures come across because a generated part's whole contribution is + surface. Dropping them and letting the part inherit the spec's flat PBR + factors is consistent but throws away the thing that was paid for: the + stippling on a grip, the panel creases and decals on a car shell. That + needs three things travelling together — UVs per vertex, the image + bytes, and which triangles use which image — so ``material_runs`` + records index ranges rather than a single material for the part. + """ + + doc = glb_json_chunk(data) + binary = glb_binary_chunk(data) + if not binary: + raise GLBParseError( + "the GLB has no BIN chunk, so its vertex data is external; " + "only self-contained GLBs can be composed" + ) + + positions: list[tuple[float, float, float]] = [] + normals: list[tuple[float, float, float]] = [] + uvs: list[tuple[float, float]] = [] + indices: list[int] = [] + material_runs: list[dict[str, Any]] = [] + + def add_mesh(mesh_index: int, matrix: Sequence[float]) -> None: + # The inverse transpose of the upper 3x3, for the normals. A non-uniform + # node scale makes the forward matrix wrong for them, and the symptom is + # lighting that reads as a modelling error rather than as a bad import. + normal_matrix = _inverse_transpose_3x3(matrix) + + for primitive in doc["meshes"][mesh_index].get("primitives", []): + if primitive.get("mode", _MODE_TRIANGLES) != _MODE_TRIANGLES: + continue + attributes = primitive.get("attributes", {}) + if "POSITION" not in attributes: + continue + + local = _read_accessor(doc, binary, attributes["POSITION"]) + base = len(positions) + for x, y, z in local: + positions.append(( + matrix[0] * x + matrix[4] * y + matrix[8] * z + matrix[12], + matrix[1] * x + matrix[5] * y + matrix[9] * z + matrix[13], + matrix[2] * x + matrix[6] * y + matrix[10] * z + matrix[14], + )) + + if "NORMAL" in attributes: + for nx, ny, nz in _read_accessor(doc, binary, attributes["NORMAL"]): + tx = normal_matrix[0] * nx + normal_matrix[3] * ny + normal_matrix[6] * nz + ty = normal_matrix[1] * nx + normal_matrix[4] * ny + normal_matrix[7] * nz + tz = normal_matrix[2] * nx + normal_matrix[5] * ny + normal_matrix[8] * nz + length = math.sqrt(tx * tx + ty * ty + tz * tz) or 1.0 + normals.append((tx / length, ty / length, tz / length)) + else: + normals.extend([(0.0, 0.0, 0.0)] * len(local)) + + # UVs are per-vertex and must stay aligned with positions, so a + # primitive without them still contributes placeholders — a short + # UV list would silently shift every following part's texturing. + if "TEXCOORD_0" in attributes: + uvs.extend( + (float(u), float(v)) + for u, v in _read_accessor(doc, binary, attributes["TEXCOORD_0"]) + ) + else: + uvs.extend([(0.0, 0.0)] * len(local)) + + if "indices" in primitive and primitive["indices"] is not None: + local_indices = [ + value[0] for value in + _read_accessor(doc, binary, primitive["indices"]) + ] + else: + local_indices = list(range(len(local))) + + run_start = len(indices) + indices.extend(base + value for value in local_indices) + material_runs.append({ + "start": run_start, + "count": len(local_indices), + "material": primitive.get("material"), + }) + + def walk(node_index: int, parent: Sequence[float]) -> None: + node = doc["nodes"][node_index] + matrix = _multiply(parent, _node_matrix(node)) + if node.get("mesh") is not None: + add_mesh(node["mesh"], matrix) + for child in node.get("children", ()): + walk(child, matrix) + + scenes = doc.get("scenes") or [] + scene = scenes[doc.get("scene", 0)] if scenes else None + roots = scene.get("nodes", ()) if scene else range(len(doc.get("nodes", []))) + for root in roots: + walk(root, _IDENTITY) + + if not positions: + raise GLBParseError("the GLB contains no triangle geometry") + + # Fill in any face normals the file left out, so a consumer never has to + # ask whether normals are present. + _fill_missing_normals(positions, normals, indices) + + low = tuple(min(point[axis] for point in positions) for axis in range(3)) + high = tuple(max(point[axis] for point in positions) for axis in range(3)) + return { + "positions": positions, + "normals": normals, + "uvs": uvs, + "indices": indices, + "triangles": len(indices) // 3, + "low": low, + "high": high, + "material_runs": material_runs, + "materials": _read_materials(doc, binary), + "has_uvs": any(u != 0.0 or v != 0.0 for u, v in uvs), + } + + +def _read_materials(doc: dict[str, Any], binary: bytes) -> list[dict[str, Any]]: + """Each material's PBR factors, its base-colour image and its MR image. + + Base colour and metallic-roughness. Not the normal or occlusion maps: + those would give the composed asset a texture set the primitives beside it + lack, and a car body with a normal map next to a flat-shaded spoiler reads + as two assets. Metallic-roughness is different in kind — it is not detail + on top of a surface, it is *which surface it is*. + + Taking the map is what makes the factors trustworthy. An exporter that puts + those channels in a texture leaves the factors at glTF's default ``1.0`` to + multiply it, so the two only mean anything together. This function used to + take the colour alone and substitute dielectric defaults (``0.0``/``0.55``) + on the grounds that inherited factors would render a polymer grip as + sandblasted steel — true, but it threw away the answer to keep from + guessing wrong. Plate armour came out as grey plastic: every generated + piece of the knight had ``metallicFactor 1.0`` and an MR map in the file, + and both were discarded. + + ``factors_from`` is still recorded, because a material with no map at all + still has to fall back and a caller needs to know which happened. + """ + + out: list[dict[str, Any]] = [] + images = doc.get("images", []) + textures = doc.get("textures", []) + views = doc.get("bufferViews", []) + + def image_bytes(reference: dict[str, Any]) -> tuple[bytes | None, str | None]: + index = reference.get("index") + if index is None or index >= len(textures): + return None, None + image_index = textures[index].get("source") + if image_index is None or image_index >= len(images): + return None, None + image = images[image_index] + view_index = image.get("bufferView") + if view_index is not None and view_index < len(views): + view = views[view_index] + start = view.get("byteOffset", 0) + return ( + bytes(binary[start:start + view["byteLength"]]), + image.get("mimeType") or "image/png", + ) + if str(image.get("uri", "")).startswith("data:"): + # A data URI is legal and some exporters emit one even in a GLB. + # Decoded here so the caller never has to care which form was used. + import base64 + + header, _, payload = image["uri"].partition(",") + return ( + base64.b64decode(payload), + header.split(":")[1].split(";")[0] if ":" in header + else "image/png", + ) + return None, None + + for material in doc.get("materials", []): + pbr = material.get("pbrMetallicRoughness") or {} + colour_image, colour_mime = image_bytes(pbr.get("baseColorTexture") or {}) + mr_image, mr_mime = image_bytes( + pbr.get("metallicRoughnessTexture") or {}) + + if mr_image is not None: + # The map is coming with us, so the factors mean what they say: + # they scale it. glTF's default is 1.0 for exactly this case. + metallic = float(pbr.get("metallicFactor", 1.0)) + roughness = float(pbr.get("roughnessFactor", 1.0)) + provenance = "file" + elif (pbr.get("metallicRoughnessTexture") or {}).get("index") is not None: + # A map is declared but its bytes could not be read. Falling back + # to dielectric defaults, because inheriting factors written to + # scale a map we do not have renders a polymer grip as steel. + metallic, roughness, provenance = 0.0, 0.55, "assumed" + else: + metallic = float(pbr.get("metallicFactor", 1.0)) + roughness = float(pbr.get("roughnessFactor", 1.0)) + provenance = "file" + + out.append({ + "name": material.get("name") or "", + "baseColor": [ + float(value) + for value in pbr.get("baseColorFactor", [1.0, 1.0, 1.0, 1.0]) + ], + "metallic": metallic, + "roughness": roughness, + "factors_from": provenance, + "image": colour_image, + "mimeType": colour_mime, + "mrImage": mr_image, + "mrMimeType": mr_mime, + }) + return out + + +def _inverse_transpose_3x3(matrix: Sequence[float]) -> list[float]: + """Inverse transpose of a column-major 4x4's rotation/scale block.""" + a = (matrix[0], matrix[1], matrix[2]) + b = (matrix[4], matrix[5], matrix[6]) + c = (matrix[8], matrix[9], matrix[10]) + determinant = ( + a[0] * (b[1] * c[2] - b[2] * c[1]) + - a[1] * (b[0] * c[2] - b[2] * c[0]) + + a[2] * (b[0] * c[1] - b[1] * c[0]) + ) + if abs(determinant) < 1e-20: + return [1.0, 0, 0, 0, 1.0, 0, 0, 0, 1.0] + # cofactor / determinant, already the inverse transpose. + return [ + (b[1] * c[2] - b[2] * c[1]) / determinant, + (b[2] * c[0] - b[0] * c[2]) / determinant, + (b[0] * c[1] - b[1] * c[0]) / determinant, + (a[2] * c[1] - a[1] * c[2]) / determinant, + (a[0] * c[2] - a[2] * c[0]) / determinant, + (a[1] * c[0] - a[0] * c[1]) / determinant, + (a[1] * b[2] - a[2] * b[1]) / determinant, + (a[2] * b[0] - a[0] * b[2]) / determinant, + (a[0] * b[1] - a[1] * b[0]) / determinant, + ] + + +def _fill_missing_normals( + positions: list[tuple[float, float, float]], + normals: list[tuple[float, float, float]], + indices: list[int], +) -> None: + """Replace zero-length normals with the area-weighted face average.""" + + missing = [ + index for index, normal in enumerate(normals) + if normal[0] == 0.0 and normal[1] == 0.0 and normal[2] == 0.0 + ] + if not missing: + return + + accumulated = {index: [0.0, 0.0, 0.0] for index in missing} + needed = set(missing) + for triangle in range(len(indices) // 3): + ia, ib, ic = indices[triangle * 3:triangle * 3 + 3] + if not (ia in needed or ib in needed or ic in needed): + continue + pa, pb, pc = positions[ia], positions[ib], positions[ic] + e1 = (pb[0] - pa[0], pb[1] - pa[1], pb[2] - pa[2]) + e2 = (pc[0] - pa[0], pc[1] - pa[1], pc[2] - pa[2]) + cross = ( + e1[1] * e2[2] - e1[2] * e2[1], + e1[2] * e2[0] - e1[0] * e2[2], + e1[0] * e2[1] - e1[1] * e2[0], + ) + for index in (ia, ib, ic): + if index in accumulated: + for axis in range(3): + accumulated[index][axis] += cross[axis] + + for index, vector in accumulated.items(): + length = math.sqrt(sum(value * value for value in vector)) + normals[index] = ( + (vector[0] / length, vector[1] / length, vector[2] / length) + if length > 1e-20 else (0.0, 1.0, 0.0) + ) diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/meshy_model.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/meshy_model.py new file mode 100644 index 0000000000000000000000000000000000000000..5363310e6271f7c9f8dadc1c0d2a4b595a43517c --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/meshy_model.py @@ -0,0 +1,463 @@ +""" +models/gen_3d_object/meshy_model.py + +MeshyModel — wrapper around Meshy's cloud 3D-generation API (image-to-3D and +text-to-3D), producing GLB / FBX / OBJ / USDZ / STL. + +Reference: https://docs.meshy.ai/ (base https://api.meshy.ai) + +Second backend for the `gen_3d_object` slot. Its `infer` / `infer_and_save` +signatures are identical to `TripoModel`'s and positionally identical to +`Trellis2Model`'s, so `Gen3DObjectOperator` dispatches on class name alone +(model_require.md R6). + +CONTRACT DEVIATIONS (model_require.md targets local-weight models; the rules that +replace it live in agent_skills/develop_harness/api_model_require.md): + C1 R2.1/R2.2 → R9.1 `model_path` carries a *model version id* ("meshy-6"). + C2 R2.3 → R9.2 `device` accepted for interface parity and ignored. + C3 R3.6/R5.5 → R9.3 no @torch.no_grad(); torch is not involved. + C4 R4.1-R4.3 → R9.4 `unload()` is a no-op that closes the HTTP session. + C5 R3.3/R3.4 → R9.5 `seed` is forwarded for text-to-3D only, where the API + accepts it; image-to-3D has no seed. Reproducibility is + NOT guaranteed server-side and is never faked locally. + C6 R3.1 → R9.6 task-based API (submit → poll → download); `infer()` + blocks until completion or `timeout` (default 300 s). + Text-to-3D runs two tasks (preview → refine) when a + texture is requested; both ids are logged. + C7 R1.2 uses the documented `infer_and_save(..., output_path)` + exception; the bytes-returning `infer()` exists alongside. + C8 (new) → R9.8 `cache_dir` prevents re-billing an identical request. + C9 (new) → R9.9 `max_retries` + exponential backoff; retryable and + terminal failures are split. + +Environment: + MESHY_API_KEY required at the first infer() call, not at construction. + Get one at https://www.meshy.ai/api (a `msy_dummy_...` + test-mode key returns canned assets without spending credits). + MESHY_API_BASE optional override of the API root. + `pip install requests` is needed for the API backends only. + +Usage: + from models.gen_3d_object.meshy_model import MeshyModel + model = MeshyModel(model_path="meshy-6", output_format="fbx") + path = model.infer_and_save(image, output_path="out/model.fbx", seed=42) +""" +from __future__ import annotations + +import logging +import os +import time +from pathlib import Path +from typing import Any, Optional + +from models.common import cloud_api +from models.common.glb_utils import glb_summary + +logger = logging.getLogger(__name__) + +SIGNUP_URL = "https://www.meshy.ai/api" + +DEFAULT_API_BASE = "https://api.meshy.ai" + +#: Short names accepted for `model_path`. Unknown values pass through untouched. +MODEL_ALIASES: dict[str, str] = { + "meshy": "meshy-6", + "meshy-6-text-to-3d": "meshy-6", + "meshy-6-image-to-3d": "meshy-6", + "meshy-5-text-to-3d": "meshy-5", + "meshy-5-image-to-3d": "meshy-5", +} + +DEFAULT_MODEL = "meshy-6" + +DONE_STATES = ("succeeded", "success", "completed") +FAILED_STATES = ("failed", "canceled", "cancelled", "expired") + +#: Meshy rejects a target_polycount outside this range with a 400 (terminal). +POLYCOUNT_RANGE = (100, 300_000) + +#: Formats the API can return directly, i.e. keys of `model_urls`. +SUPPORTED_FORMATS = ("glb", "fbx", "obj", "usdz", "stl", "mtl", "3mf") + + +class MeshyModel: + """ + Cloud image-to-3D / text-to-3D through Meshy. + + Args: + model_path: [C1] Meshy `ai_model` id ("meshy-6", "meshy-5", "latest"), + or an alias from `MODEL_ALIASES`. + device: [C2] Accepted for interface parity, ignored. "cpu" is fine. + api_key: Explicit key; defaults to `$MESHY_API_KEY`, read at first call. + timeout: [C6] Seconds to wait for one generation task (each stage of + the text-to-3D preview → refine chain gets the full budget). + poll_interval: Seconds between status polls. + max_retries: [C9] Extra attempts for retryable HTTP failures. + cache_dir: [C8] Directory for the response cache. None disables it. + output_format: Any of `SUPPORTED_FORMATS`; picked out of `model_urls`. + low_poly: [B4.3] Sets `model_type="lowpoly"`, i.e. the service produces + a low-poly mesh instead of us decimating one locally. + texture / enable_pbr / topology / should_remesh: + Forwarded to the generation endpoints. + refine: Text-to-3D only. Meshy's preview stage returns an untextured + mesh; the refine stage textures it and costs extra credits. + Ignored when `texture=False`. + api_base: Override the API root (defaults to `$MESHY_API_BASE`). + verbose: Print task progress; off by default (R3.7). + """ + + PROVIDER = "meshy" + + def __init__( + self, + model_path: str = DEFAULT_MODEL, + device: str = "cuda", + *, + api_key: Optional[str] = None, + # Measured: one image-to-3D with PBR textures took 283 s here, and the + # Tripo backend took 601 s for the same job. Timing out does not refund + # the credits, so the default errs long; the error carries the task_id. + timeout: int = 1800, + poll_interval: float = 3.0, + max_retries: int = 3, + cache_dir: Optional[str] = None, + output_format: str = "glb", + low_poly: bool = False, + texture: bool = True, + enable_pbr: bool = True, + topology: str = "triangle", + should_remesh: Optional[bool] = None, + refine: bool = True, + api_base: Optional[str] = None, + http_timeout: int = 60, + verbose: bool = False, + **model_specific: Any, + ): + # [CONTRACT-DEVIATION C1] model_path is a version id, not a weight location. + # [CONTRACT-DEVIATION C2] device accepted for interface parity, ignored. + self.model_path = MODEL_ALIASES.get(str(model_path).lower(), model_path) + self.device = device + + # R2.4 — store everything before anything loads. + self.api_key = api_key + self.timeout = timeout + self.poll_interval = poll_interval + self.max_retries = max_retries + self.cache_dir = cache_dir + self.output_format = output_format.lower().lstrip(".") + self.low_poly = low_poly + self.texture = texture + self.enable_pbr = enable_pbr + self.topology = topology + self.should_remesh = should_remesh + self.refine = refine + self.api_base = (api_base or os.environ.get("MESHY_API_BASE") + or DEFAULT_API_BASE) + self.http_timeout = http_timeout + self.verbose = verbose + self.model_specific = model_specific + + if self.output_format not in SUPPORTED_FORMATS: + raise ValueError( + f"output_format={self.output_format!r} is not one of " + f"{SUPPORTED_FORMATS}. Meshy returns these directly in model_urls." + ) + + self._client: Optional[cloud_api.CloudAPIClient] = None + self._cache = cloud_api.ResponseCache(cache_dir, self.PROVIDER) + + #: Record of the most recent **real** call — see `TripoModel.last_call_info`. + self.last_call_info: dict[str, Any] = {} + + # ── plumbing ────────────────────────────────────────────────────────────── + + @property + def client(self) -> cloud_api.CloudAPIClient: + """HTTP client, created on first use. [R9.7] The key is resolved here.""" + if self._client is None: + key = cloud_api.require_api_key( + self.api_key, "MESHY_API_KEY", SIGNUP_URL, who="MeshyModel") + self._client = cloud_api.CloudAPIClient( + self.api_base, key, + timeout=self.http_timeout, + max_retries=self.max_retries, + ) + return self._client + + def unload(self) -> None: + """[C4] Close the HTTP session. Idempotent, and safe before any call.""" + if self._client is not None: + self._client.close() + self._client = None + + close = unload + + @staticmethod + def _task_id_of(resp: Any) -> str: + """Meshy answers a creation call with `{"result": ""}`.""" + if isinstance(resp, dict): + for key in ("result", "id", "task_id"): + value = resp.get(key) + if isinstance(value, str) and value: + return value + raise cloud_api.CloudAPIError( + f"Meshy accepted the request but returned no task id: {resp!r}") + + def _fetch_task(self, endpoint: str, task_id: str) -> dict: + task = self.client.request("GET", f"{endpoint}/{task_id}") + if not isinstance(task, dict): + raise cloud_api.CloudAPIError( + f"unexpected task payload for {task_id}: {task!r}", task_id=task_id) + return task + + def _model_url(self, task: dict) -> str: + """URL of the requested format, with an actionable message when absent.""" + urls = task.get("model_urls") or {} + url = urls.get(self.output_format) + if isinstance(url, str) and url.startswith("http"): + return url + raise cloud_api.CloudAPIError( + f"task {task.get('id')} finished but has no {self.output_format!r} " + f"URL. Available: {sorted(urls)}. Set output_format to one of those.", + task_id=task.get("id"), payload=task) + + def _clamp_polycount(self, value: Optional[int]) -> Optional[int]: + """ + Keep `target_polycount` inside the documented range. + + `Gen3DObjectOperator` forwards TRELLIS.2's default of 1_000_000, which + Meshy rejects with a terminal 400. Clamping (loudly) keeps the operator + interchangeable (R6) instead of making the caller special-case backends. + """ + if value is None: + return None + low, high = POLYCOUNT_RANGE + clamped = max(low, min(int(value), high)) + if clamped != int(value): + logger.warning("[meshy] target_polycount %s clamped to %s (API range %s-%s)", + value, clamped, low, high) + return clamped + + # ── inference ───────────────────────────────────────────────────────────── + + def infer( + self, + image: Any = None, + seed: int = 42, + decimation_target: Optional[int] = None, + texture_size: Optional[int] = None, + *, + prompt: Optional[str] = None, + negative_prompt: Optional[str] = None, + image_url: Optional[str] = None, + verbose: Optional[bool] = None, + **provider_kwargs: Any, + ) -> bytes: + """ + Generate one 3D asset and return the model file bytes. + + Args: + image: Reference image as `PIL.Image.Image`, `np.ndarray` or PNG + `bytes` — sent inline as a base64 data URI. Not a path (R3.2). + seed: [C5] Forwarded for text-to-3D only; image-to-3D has no seed + parameter. Reproducibility is not guaranteed. + decimation_target: Target face count → `target_polycount`, clamped to + the API's 100-300000 range. + texture_size: Accepted for signature parity with `Trellis2Model` and + **ignored** — Meshy exposes no texture resolution parameter. + prompt: Text prompt for text-to-3D. [A4 decision] Same rationale as + `TripoModel`: keeps text-to-3D reachable without a second slot. + negative_prompt: Sent as `texture_prompt`'s counterpart is absent in + the API — rejected explicitly rather than silently dropped. + image_url: Publicly reachable image URL, used instead of the data URI. + verbose: Override the constructor's verbosity for this call. + **provider_kwargs: Merged into the request body verbatim. + + Returns: + The model file as `bytes`, in `output_format`. + + Raises: + CloudAPIAuthError / CloudAPIQuotaError / CloudTaskFailed / + CloudTaskTimeout — see `models/common/cloud_api.py`. + """ + verbose = self.verbose if verbose is None else verbose + if image is None and image_url is None and not prompt: + raise ValueError( + "MeshyModel.infer needs an image (`image=` / `image_url=`) or a " + "text `prompt=`; got neither.") + if negative_prompt: + raise ValueError( + "Meshy has no negative_prompt parameter. Fold the constraint into " + "`prompt`, or use TripoModel which supports it.") + if texture_size is not None: + logger.debug("[meshy] texture_size=%s ignored; the API has no equivalent", + texture_size) + + polycount = self._clamp_polycount(decimation_target) + use_image = image is not None or image_url is not None + + payload: dict[str, Any] = { + "ai_model": self.model_path, + "model_type": "lowpoly" if self.low_poly else "standard", + "topology": self.topology, + } + if polycount is not None: + payload["target_polycount"] = polycount + if self.should_remesh is not None: + payload["should_remesh"] = self.should_remesh + + if use_image: + payload["should_texture"] = self.texture + payload["enable_pbr"] = self.enable_pbr + else: + payload["mode"] = "preview" + payload["prompt"] = prompt + # [CONTRACT-DEVIATION C5] accepted by the text endpoint only. + payload["seed"] = int(seed) + payload.update(provider_kwargs) + + # [C8] Everything that changes the output goes into the key; the image is + # represented by its hash, and the API key never appears. + png = cloud_api.image_to_png_bytes(image) if image is not None else None + cache_key = cloud_api.request_hash({ + "provider": self.PROVIDER, + "payload": payload, + "image_sha256": cloud_api.bytes_hash(png) if png else None, + "image_url": image_url, + "refine": self.refine and self.texture and not use_image, + "output_format": self.output_format, + }) + cached = self._cache.get(cache_key, ext=self.output_format) + if cached is not None: + self.last_call_info = { + "provider": self.PROVIDER, "cached": True, "cache_key": cache_key, + "bytes": len(cached), + **(glb_summary(cached) if self.output_format == "glb" else {}), + } + return cached + + t0 = time.time() + task_ids: list[str] = [] + + if use_image: + endpoint = "/openapi/v1/image-to-3d" + payload["image_url"] = ( + image_url if png is None else cloud_api.image_to_data_uri(image)) + task = self._submit_and_wait(endpoint, payload, verbose=verbose, + task_ids=task_ids) + else: + endpoint = "/openapi/v2/text-to-3d" + task = self._submit_and_wait(endpoint, payload, verbose=verbose, + task_ids=task_ids) + if self.texture and self.refine: + # [C6] Preview geometry is untextured; refine is a second billed + # task that paints it. Skip with texture=False or refine=False. + refine_payload = { + "mode": "refine", + "preview_task_id": task_ids[-1], + "ai_model": self.model_path, + "enable_pbr": self.enable_pbr, + } + task = self._submit_and_wait(endpoint, refine_payload, + verbose=verbose, task_ids=task_ids) + + data = self.client.download(self._model_url(task)) + elapsed = time.time() - t0 + + info = glb_summary(data) if self.output_format == "glb" else {"bytes": len(data)} + self.last_call_info = { + "provider": self.PROVIDER, + "model": self.model_path, + "task_id": task_ids[-1], + "task_ids": task_ids, + "elapsed_sec": round(elapsed, 2), + "credits": task.get("credits_consumed", task.get("credits")), + "cached": False, + "cache_key": cache_key, + "format": self.output_format, + # The provider's own render of what it produced. Recording the URL + # (rather than downloading it here) keeps the model out of artifact + # placement (R1.2) while giving the caller a free visual check — + # "the asset exists" and "the asset is what was asked for" are + # different claims, and only a picture settles the second one. + "preview_url": task.get("thumbnail_url"), + **info, + } + # R9.8 — one line per billed call. + logger.info( + "[meshy] task=%s model=%s %.1fs credits=%s triangles=%s bytes=%s", + task_ids[-1], self.model_path, elapsed, self.last_call_info.get("credits"), + info.get("triangles"), len(data), + ) + if verbose: + print(f"[meshy] {self.last_call_info}") + + self._cache.put(cache_key, data, { + "provider": self.PROVIDER, "payload": payload, + **{k: v for k, v in self.last_call_info.items() if k != "cache_key"}, + }, ext=self.output_format) + return data + + def _submit_and_wait(self, endpoint: str, payload: dict, *, + verbose: bool, task_ids: list[str]) -> dict: + """Create one task on `endpoint`, poll it to a terminal state, return it.""" + created = self.client.request("POST", endpoint, json_body=payload) + task_id = self._task_id_of(created) + task_ids.append(task_id) + if verbose: + print(f"[meshy] task {task_id} submitted ({endpoint}, " + f"mode={payload.get('mode', 'image')})") + return cloud_api.poll_task( + lambda: self._fetch_task(endpoint, task_id), + task_id=task_id, + timeout=self.timeout, + poll_interval=self.poll_interval, + done_states=DONE_STATES, + failed_states=FAILED_STATES, + verbose=verbose, + ) + + def infer_and_save( + self, + image: Any = None, + output_path: Optional[str] = None, + seed: int = 42, + decimation_target: Optional[int] = None, + texture_size: Optional[int] = None, + *, + prompt: Optional[str] = None, + negative_prompt: Optional[str] = None, + image_url: Optional[str] = None, + verbose: Optional[bool] = None, + **provider_kwargs: Any, + ) -> str: + """ + [C7] The documented R1.2 exception: run `infer()` and write the result. + + The path comes **in** from the caller and is never derived here. + + Args: + output_path: Destination file. Parent directories are created. + (everything else: see `infer`) + + Returns: + `str(output_path)`. + """ + if not output_path: + raise ValueError("output_path is required (model_require.md R1.2)") + data = self.infer( + image, seed, decimation_target, texture_size, + prompt=prompt, negative_prompt=negative_prompt, image_url=image_url, + verbose=verbose, **provider_kwargs, + ) + out = Path(output_path) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_bytes(data) + return str(out) + + # ── account ─────────────────────────────────────────────────────────────── + + def balance(self) -> dict: + """Remaining credits: ``{"balance": int}``. Cheap and unbilled.""" + resp = self.client.request("GET", "/openapi/v1/balance") + return resp if isinstance(resp, dict) else {"balance": resp} diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/tripo_model.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/tripo_model.py new file mode 100644 index 0000000000000000000000000000000000000000..483e185ff7ca75d4c4a592fec4e2acd3bcd251aa --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/models/gen_3d_object/tripo_model.py @@ -0,0 +1,532 @@ +""" +models/gen_3d_object/tripo_model.py + +TripoModel — wrapper around Tripo3D's cloud 3D-generation API (image-to-3D and +text-to-3D), producing a GLB. + +Reference: https://developers.tripo3d.ai/ (v3 API, base https://openapi.tripo3d.ai/v3) + +CONTRACT DEVIATIONS (model_require.md targets local-weight models; the rules that +replace it live in agent_skills/develop_harness/api_model_require.md): + C1 R2.1/R2.2 → R9.1 `model_path` carries a *model version id* + ("v3.1-20260211"), not a weight location. + C2 R2.3 → R9.2 `device` accepted for interface parity and ignored. + C3 R3.6/R5.5 → R9.3 no @torch.no_grad(); torch is not involved. + C4 R4.1-R4.3 → R9.4 `unload()` is a no-op that closes the HTTP session. + C5 R3.3/R3.4 → R9.5 `seed` is forwarded as model_seed/texture_seed when the + provider accepts it; server-side reproducibility is NOT + guaranteed and is never faked locally. + C6 R3.1 → R9.6 task-based API (submit → poll → download); `infer()` + blocks until completion or `timeout` (default 300 s). + A timeout error carries the `task_id`. + C7 R1.2 uses the documented `infer_and_save(..., output_path)` + exception; the bytes-returning `infer()` exists alongside. + C8 (new) → R9.8 `cache_dir` prevents re-billing an identical request. + C9 (new) → R9.9 `max_retries` + exponential backoff; retryable (5xx/429/ + transport) and terminal (400/401/402) failures are split. + +Environment: + TRIPO_API_KEY required at the first infer() call, not at construction. + Get one at https://platform.tripo3d.ai/api-keys + TRIPO_API_BASE optional override of the API root. + `pip install requests` is needed for the API backends only. + +Usage: + from models.gen_3d_object.tripo_model import TripoModel + model = TripoModel(model_path="v3.1-20260211") + path = model.infer_and_save(image, output_path="out/model.glb", seed=42) + print(model.last_call_info) # task_id, elapsed, credits, triangles +""" +from __future__ import annotations + +import logging +import os +import time +from pathlib import Path +from typing import Any, Optional + +from models.common import cloud_api +from models.common.glb_utils import glb_summary + +logger = logging.getLogger(__name__) + +#: Where a human gets a key. Quoted verbatim in the fail-fast message (R1.6). +SIGNUP_URL = "https://platform.tripo3d.ai/api-keys" + +DEFAULT_API_BASE = "https://openapi.tripo3d.ai/v3" + +#: Short names accepted for `model_path`, mapped to the ids the API expects. +#: Unknown values are passed through untouched, so a version released after this +#: file was written still works without a code change. +MODEL_ALIASES: dict[str, str] = { + "tripo": "v3.1-20260211", + "tripo-v3.1": "v3.1-20260211", + "v3.1": "v3.1-20260211", + "tripo-v3.0": "v3.0-20250812", + "v3.0": "v3.0-20250812", + "tripo-v2.5": "v2.5-20250123", + "v2.5": "v2.5-20250123", + # P series — natively low-poly, the cheap option for mesh particles (B4.2). + "tripo-p1": "P1-20260311", + "p1": "P1-20260311", +} + +DEFAULT_MODEL = "v3.1-20260211" + +#: Terminal task states. Tripo reports lower-case; compared case-insensitively. +DONE_STATES = ("success", "succeeded", "finished", "completed") +FAILED_STATES = ("failed", "cancelled", "canceled", "banned", "expired", "unknown") + +#: Output fields that have carried the download URL across API versions. +_MODEL_URL_KEYS = ("model_url", "pbr_model", "model", "base_model", "glb", "gltf") + +#: `face_limit` range the service accepts **while `smart_low_poly` is on**. +#: Outside it the request is rejected with a terminal 400: +#: "when smart_low_poly is enabled, face_limit must be between 500 and 20000 +#: (triangle mesh), got 30000" +#: Not in the public docs; found by calling it. +LOW_POLY_FACE_LIMIT_RANGE = (500, 20_000) + + +class TripoModel: + """ + Cloud image-to-3D / text-to-3D through Tripo3D. + + Interchangeable with `Trellis2Model` in `Gen3DObjectOperator`: the + `infer_and_save(image, output_path, seed, decimation_target, texture_size)` + call signature is positionally identical (model_require.md R6). + + Args: + model_path: [C1] Tripo model version id, or an alias from `MODEL_ALIASES`. + device: [C2] Accepted for interface parity, ignored. "cpu" is fine. + api_key: Explicit key; defaults to `$TRIPO_API_KEY`, read at first call. + timeout: [C6] Seconds to wait for one generation task. + poll_interval: Seconds between status polls. + max_retries: [C9] Extra attempts for retryable HTTP failures. + cache_dir: [C8] Directory for the response cache. None disables it. + output_format: "glb" is produced natively. Any other format needs the + conversion endpoint — see `convert_path`. + convert_path: API path of the format-conversion endpoint. Left as None + because it is not pinned down in the public v3 docs; set it + to enable `output_format="fbx"` without touching this file. + low_poly: [B4.3] Ask the service for clean low-poly topology + (`smart_low_poly`) instead of decimating locally. + texture / pbr / quad / texture_quality / geometry_quality: + Forwarded verbatim to the generation endpoint. + api_base: Override the API root (defaults to `$TRIPO_API_BASE`). + verbose: Print task progress; off by default (R3.7). + """ + + #: Provider name, used for cache namespacing and log lines. + PROVIDER = "tripo" + + def __init__( + self, + model_path: str = DEFAULT_MODEL, + device: str = "cuda", + *, + api_key: Optional[str] = None, + # Measured: image-to-3D with smart_low_poly took **601 s**, i.e. it would + # have died one second past a 600 s budget. Timing out does not refund + # the credits — the task finishes server-side and only the download is + # lost — so the default errs long. The error carries the task_id. + timeout: int = 1800, + poll_interval: float = 3.0, + max_retries: int = 3, + cache_dir: Optional[str] = None, + output_format: str = "glb", + convert_path: Optional[str] = None, + low_poly: bool = False, + texture: bool = True, + pbr: bool = True, + quad: bool = False, + texture_quality: str = "standard", + geometry_quality: str = "standard", + api_base: Optional[str] = None, + http_timeout: int = 60, + verbose: bool = False, + **model_specific: Any, + ): + # [CONTRACT-DEVIATION C1] model_path is a version id, not a weight location. + # [CONTRACT-DEVIATION C2] device accepted for interface parity, ignored. + self.model_path = MODEL_ALIASES.get(str(model_path).lower(), model_path) + self.device = device + + # R2.4 — every constructor argument lands on self before anything loads, + # so unload()/reload round-trips without losing configuration. + self.api_key = api_key + self.timeout = timeout + self.poll_interval = poll_interval + self.max_retries = max_retries + self.cache_dir = cache_dir + self.output_format = output_format.lower().lstrip(".") + self.convert_path = convert_path + self.low_poly = low_poly + self.texture = texture + self.pbr = pbr + self.quad = quad + self.texture_quality = texture_quality + self.geometry_quality = geometry_quality + self.api_base = (api_base or os.environ.get("TRIPO_API_BASE") + or DEFAULT_API_BASE) + self.http_timeout = http_timeout + self.verbose = verbose + self.model_specific = model_specific + + self._client: Optional[cloud_api.CloudAPIClient] = None + self._cache = cloud_api.ResponseCache(cache_dir, self.PROVIDER) + + #: Record of the most recent **real** call: task_id, elapsed_sec, credits, + #: triangles, bytes, cached. Operators copy it into meta.json (R9.8). + self.last_call_info: dict[str, Any] = {} + + # ── plumbing ────────────────────────────────────────────────────────────── + + @property + def client(self) -> cloud_api.CloudAPIClient: + """ + HTTP client, created on first use. + + [C6/R9.7] The API key is resolved here rather than in `__init__`, so the + wrapper can be imported and constructed on a machine with no credentials + (which is exactly what `test/harness/smoke.py` does). + """ + if self._client is None: + key = cloud_api.require_api_key( + self.api_key, "TRIPO_API_KEY", SIGNUP_URL, who="TripoModel") + self._client = cloud_api.CloudAPIClient( + self.api_base, key, + timeout=self.http_timeout, + max_retries=self.max_retries, + ) + return self._client + + def unload(self) -> None: + """[C4] Close the HTTP session. Idempotent, and safe before any call.""" + if self._client is not None: + self._client.close() + self._client = None + + close = unload + + @staticmethod + def _unwrap(resp: Any) -> dict: + """ + Strip Tripo's `{"code": 0, "data": {...}}` envelope. + + A non-zero `code` on an HTTP 200 is a terminal application error — the + same request will fail the same way, so it must not be retried (R9.9). + """ + if not isinstance(resp, dict): + raise cloud_api.CloudAPIError(f"unexpected response type {type(resp).__name__}: {resp!r}") + code = resp.get("code") + if code not in (None, 0): + message = resp.get("message") or resp.get("msg") or resp + suggestion = resp.get("suggestion") + raise cloud_api.CloudAPIRequestError( + f"Tripo API error code={code}: {message}" + + (f" — {suggestion}" if suggestion else ""), + payload=resp, + ) + data = resp.get("data") + return data if isinstance(data, dict) else resp + + def _upload_image(self, png: bytes) -> str: + """Upload PNG bytes, return the `file_token` used as generation input.""" + data = self._unwrap(self.client.request( + "POST", "/files", + files={"file": ("input.png", png, "image/png")}, + )) + token = data.get("file_token") or data.get("image_token") or data.get("token") + if not token: + raise cloud_api.CloudAPIError( + f"upload succeeded but no file_token in the response: {data}") + return str(token) + + @staticmethod + def _extract_model_url(task: dict) -> str: + """Find the artifact URL in a finished task, across output field names.""" + output = task.get("output") or task.get("result") or {} + for key in _MODEL_URL_KEYS: + value = output.get(key) + if isinstance(value, str) and value.startswith("http"): + return value + if isinstance(value, dict) and isinstance(value.get("url"), str): + return value["url"] + raise cloud_api.CloudAPIError( + f"task {task.get('task_id')} reported success but carries no model URL. " + f"output={output!r}", + task_id=task.get("task_id"), payload=task) + + def _fetch_task(self, task_id: str) -> dict: + return self._unwrap(self.client.request("GET", f"/tasks/{task_id}")) + + # ── payload ─────────────────────────────────────────────────────────────── + + def _clamp_face_limit(self, value: int) -> int: + """ + Keep `face_limit` inside the range the service accepts. + + `Gen3DObjectOperator` forwards TRELLIS.2's default of 1 000 000, and with + `low_poly=True` anything outside 500-20 000 is a terminal 400. Clamping + (loudly) keeps the backends interchangeable (R6) rather than making the + caller special-case each provider. + """ + value = int(value) + if not self.low_poly: + return value + low, high = LOW_POLY_FACE_LIMIT_RANGE + clamped = max(low, min(value, high)) + if clamped != value: + logger.warning("[tripo] face_limit %s clamped to %s " + "(smart_low_poly range %s-%s)", value, clamped, low, high) + return clamped + + def _build_payload( + self, + *, + prompt: Optional[str], + negative_prompt: Optional[str], + seed: Optional[int], + decimation_target: Optional[int], + provider_kwargs: dict, + ) -> dict: + """Generation parameters shared by the image and text endpoints.""" + payload: dict[str, Any] = { + "model": self.model_path, + "texture": self.texture, + "pbr": self.pbr, + "texture_quality": self.texture_quality, + "geometry_quality": self.geometry_quality, + } + if self.quad: + payload["quad"] = True + if self.low_poly: + # [B4.3] Ask the service for low-poly topology. Decimating a 2M-face + # mesh locally wrecks UVs and normals; generating low-poly does not. + payload["smart_low_poly"] = True + if decimation_target: + payload["face_limit"] = self._clamp_face_limit(decimation_target) + if prompt: + payload["prompt"] = prompt + if negative_prompt: + payload["negative_prompt"] = negative_prompt + if seed is not None: + # [CONTRACT-DEVIATION C5] forwarded, but the service does not promise + # that the same seed reproduces the same mesh. Never faked locally. + payload["model_seed"] = int(seed) + payload["texture_seed"] = int(seed) + payload.update(provider_kwargs) + return payload + + # ── inference ───────────────────────────────────────────────────────────── + + def infer( + self, + image: Any = None, + seed: int = 42, + decimation_target: Optional[int] = None, + texture_size: Optional[int] = None, + *, + prompt: Optional[str] = None, + negative_prompt: Optional[str] = None, + image_url: Optional[str] = None, + verbose: Optional[bool] = None, + **provider_kwargs: Any, + ) -> bytes: + """ + Generate one 3D asset and return the model file bytes. + + [C6] Submits the task, polls until it finishes, downloads the artifact — + all inside this call. Typical wall time is 20 s to 4 min. + + Args: + image: Reference image as `PIL.Image.Image`, `np.ndarray` or PNG + `bytes`. Not a path (R3.2). Give `image`, `image_url` or + `prompt`; image wins when several are present. + seed: [C5] Forwarded as `model_seed` / `texture_seed`. Reproducibility + is not guaranteed server-side. + decimation_target: Target face count, forwarded as `face_limit`. + None leaves it to the service. + texture_size: Accepted for signature parity with `Trellis2Model` and + **ignored** — Tripo exposes `texture_quality`, not a + resolution. Pass `texture_quality=` to the constructor. + prompt: Text prompt for text-to-3D. [A4 decision] The operator slot is + image-to-3D today; accepting `prompt` here keeps text-to-3D + available without a second wrapper. + negative_prompt: Text-to-3D only. + image_url: Publicly reachable image URL, used instead of uploading. + verbose: Override the constructor's verbosity for this call. + **provider_kwargs: Merged into the request body verbatim, so a new + API parameter needs no change here. + + Returns: + The model file as `bytes` — GLB unless `output_format`/`convert_path` + say otherwise. + + Raises: + CloudAPIAuthError: no or invalid `TRIPO_API_KEY`. + CloudAPIQuotaError: out of credits (terminal, never retried). + CloudTaskTimeout: not finished within `timeout`; carries `task_id`. + CloudTaskFailed: the service rejected or failed the task. + """ + verbose = self.verbose if verbose is None else verbose + if image is None and image_url is None and not prompt: + raise ValueError( + "TripoModel.infer needs an image (`image=` / `image_url=`) or a " + "text `prompt=`; got neither.") + if texture_size is not None: + # [CONTRACT-DEVIATION C2-style] accepted for parity, ignored. + logger.debug("[tripo] texture_size=%s ignored; use texture_quality", + texture_size) + if self.output_format != "glb" and not self.convert_path: + raise NotImplementedError( + f"TripoModel produces GLB; output_format={self.output_format!r} needs " + f"Tripo's conversion endpoint, whose path is not pinned in the public " + f"v3 docs. Either set convert_path=... on the constructor, use " + f"MeshyModel(output_format='fbx') which returns FBX natively, or " + f"convert the GLB with engine_adapters/blender/." + ) + + png = cloud_api.image_to_png_bytes(image) if image is not None else None + use_image = png is not None or bool(image_url) + payload = self._build_payload( + # The image endpoint has no prompt field — sending one is a terminal + # 400. An image plus a prompt means "use the image". + prompt=None if use_image else prompt, + negative_prompt=None if use_image else negative_prompt, + seed=seed, + decimation_target=decimation_target, provider_kwargs=provider_kwargs, + ) + + # [C8] Cache key covers everything that changes the output. The image is + # represented by its hash, never its bytes, and the key never sees the API key. + cache_key = cloud_api.request_hash({ + "provider": self.PROVIDER, + "payload": payload, + "image_sha256": cloud_api.bytes_hash(png) if png else None, + "image_url": image_url, + "output_format": self.output_format, + }) + cached = self._cache.get(cache_key, ext=self.output_format) + if cached is not None: + self.last_call_info = { + "provider": self.PROVIDER, "cached": True, "cache_key": cache_key, + "bytes": len(cached), **glb_summary(cached), + } + return cached + + t0 = time.time() + if png is not None: + # `input` takes a file_token, a public URL or a previous task id. + payload["input"] = self._upload_image(png) + endpoint = "/generation/image-to-model" + elif image_url: + payload["input"] = image_url + endpoint = "/generation/image-to-model" + else: + endpoint = "/generation/text-to-model" + + created = self._unwrap(self.client.request("POST", endpoint, json_body=payload)) + task_id = str(created.get("task_id") or created.get("id") or "") + if not task_id: + raise cloud_api.CloudAPIError( + f"{endpoint} accepted the request but returned no task_id: {created}") + if verbose: + print(f"[tripo] task {task_id} submitted ({endpoint})") + + # Some responses already carry a finished task; only poll when they do not. + state = str(created.get("status", "")).lower() + if state in DONE_STATES: + task = created + else: + task = cloud_api.poll_task( + lambda: self._fetch_task(task_id), + task_id=task_id, + timeout=self.timeout, + poll_interval=self.poll_interval, + done_states=DONE_STATES, + failed_states=FAILED_STATES, + verbose=verbose, + ) + + data = self.client.download(self._extract_model_url(task)) + elapsed = time.time() - t0 + + info = glb_summary(data) if self.output_format == "glb" else {"bytes": len(data)} + self.last_call_info = { + "provider": self.PROVIDER, + "model": self.model_path, + "task_id": task_id, + "elapsed_sec": round(elapsed, 2), + "credits": task.get("credits_consumed", task.get("credits")), + "cached": False, + "cache_key": cache_key, + # The provider's own render — see the note in meshy_model.py. + "preview_url": (task.get("output") or {}).get("rendered_image_url"), + **info, + } + # R9.8 — one line per billed call: what it cost and what it produced. + logger.info( + "[tripo] task=%s model=%s %.1fs credits=%s triangles=%s bytes=%s", + task_id, self.model_path, elapsed, self.last_call_info.get("credits"), + info.get("triangles"), len(data), + ) + if verbose: + print(f"[tripo] {self.last_call_info}") + + self._cache.put(cache_key, data, { + "provider": self.PROVIDER, "payload": payload, + **{k: v for k, v in self.last_call_info.items() if k != "cache_key"}, + }, ext=self.output_format) + return data + + def infer_and_save( + self, + image: Any = None, + output_path: Optional[str] = None, + seed: int = 42, + decimation_target: Optional[int] = None, + texture_size: Optional[int] = None, + *, + prompt: Optional[str] = None, + negative_prompt: Optional[str] = None, + image_url: Optional[str] = None, + verbose: Optional[bool] = None, + **provider_kwargs: Any, + ) -> str: + """ + [C7] The documented R1.2 exception: run `infer()` and write the result. + + The path comes **in** from the caller and is never derived here — the + operator owns artifact placement. + + Args: + output_path: Destination file. Parent directories are created. + (everything else: see `infer`) + + Returns: + `str(output_path)`. + """ + if not output_path: + raise ValueError("output_path is required (model_require.md R1.2)") + data = self.infer( + image, seed, decimation_target, texture_size, + prompt=prompt, negative_prompt=negative_prompt, image_url=image_url, + verbose=verbose, **provider_kwargs, + ) + out = Path(output_path) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_bytes(data) + return str(out) + + # ── account ─────────────────────────────────────────────────────────────── + + def balance(self) -> dict: + """ + Remaining credits: ``{"balance": float, "frozen": float}``. + + Cheap and unbilled — call it before a batch to check the budget (C4 note: + this is the only method that talks to the API without generating). + """ + return self._unwrap(self.client.request("GET", "/account/balance")) diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/operators/gen_3d_object/operator.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/operators/gen_3d_object/operator.py new file mode 100644 index 0000000000000000000000000000000000000000..c5b3d362ea28a51bac750f7a3efcd9a6459786db --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/operators/gen_3d_object/operator.py @@ -0,0 +1,596 @@ +""" +operators/gen_3d_object/operator.py + +Gen3DObjectOperator — accepts a loaded model and processes an input dict into a +3D output (GLB file on disk). + +The operator is intentionally model-agnostic: you inject any object that +implements the same interface as Trellis2Model. New model wrappers can be +swapped in without touching this file. + +Output layout — two modes, chosen by whether `output_dir` is given: + + * **per-game (default, `output_dir=None`)** — resolved by + `pipeline.common.paths`, so artifacts are grouped by generated game project:: + + test_data/outputs///assets/3d_object// + ├── model.glb + └── meta.json + + * **flat (legacy, `output_dir="..."`)** — writes `/.glb`, + byte-for-byte the historical behaviour. Existing callers are unaffected. + +Usage: + from models.gen_3d_object.trellis_2_model import Trellis2Model + from operators.gen_3d_object.operator import Gen3DObjectOperator + + model = Trellis2Model(model_path="...") + + # per-game layout + op = Gen3DObjectOperator(model=model, run_id="20260731_1032") + + # legacy flat layout (unchanged) + op = Gen3DObjectOperator(model=model, output_dir="outputs/3d_object") + + result = op.run({ + "game_id": "gameA_cyberpunk_shooter", # optional, inferred when omitted + "task_id": "sword_001", + "image_path": "path/to/image.png", # or "image": PIL.Image + "seed": 42, + }) + print(result["glb_path"]) + +Two optional extras, both additive and off unless asked for: + + * naming an ``asset_id`` in the task hands the finished mesh to the + three.js adapter — staged, oriented, manifest rewritten; + * ``run_art_plan(game_id, image_model)`` generates a whole game's + recorded art plan (``funcs/art_plan.py``) that way in one call. + +``funcs/asset_pack.py`` covers the other case: three CC0 models, +downloaded and imported in seconds, for when generating is overkill. + +A third route skips inference entirely. Passing ``spec`` instead of an +image builds the mesh from a declarative part list +(``funcs/code_asset.py``), which suits anything exactly describable — a +crate, a sign, a wheel, a rifle. It needs no model and no GPU, states its +own facing and size instead of leaving them to be guessed, and keeps its +parts as named glTF nodes so gameplay can still move them:: + + op = Gen3DObjectOperator(model=None, run_id="20260826_1400") + op.run({ + "game_id": "gameA_cyberpunk_shooter", + "task_id": "crate_001", + "spec": { + "subject": "wooden supply crate", + "units": "metres", "forward": "+z", + "asset_type": "prop", "height_metres": 0.6, + "parts": [{"id": "body", "kind": "box", + "size": [0.6, 0.6, 0.6], "at": [0, 0.3, 0]}], + }, + }) + +The two can be mixed, which is usually the best available answer for a +detailed hard-surface asset. A ``mesh`` part reads a GLB off disk — one +component generated by a cloud model — and is placed, measured and gated +exactly like a primitive. What each side contributes is not +interchangeable: the generator supplies shapes no formula states (a +moulded grip's finger swells), and the spec supplies the dimensions and +placement a prompt cannot specify (a rail's 30 mm slot pitch). Spending +generation on something a lathe states exactly buys an approximation at a +hundred times the triangles, and the approximation is the part that can no +longer be adjusted by editing a number — so the ``provenance`` gate +reports what was delegated and at what cost:: + + op.run({ + "game_id": "gameA_cyberpunk_shooter", + "task_id": "rifle_001", + "spec": { + "subject": "assault rifle", + "units": "metres", "forward": "+z", + "asset_type": "weapon", "height_metres": 0.24, + "parts": [ + # exact dimensions: stated + {"id": "receiver", "kind": "box", + "size": [0.04, 0.048, 0.30], "at": [0, 0.139, -0.03]}, + # moulded surface: fetched, with a uniform `size` so the + # mesh keeps the proportions it was generated with + {"id": "grip", "kind": "mesh", + "source": "parts/grip.glb", + "size": [0.116, 0.116, 0.116], "at": [0, 0.045, -0.104]}, + ], + }, + }) +""" +from __future__ import annotations + +import time +from pathlib import Path +from typing import Any, Optional + +from PIL import Image + +#: Registered task kind for this operator (see pipeline/common/paths.py). +TASK_KIND = "3d_object" + +#: Artifact filename used by the per-game layout. +GLB_FILENAME = "model.glb" + + +class Gen3DObjectOperator: + """ + Operator for 3D object generation. + + Args: + model: A loaded model with an `infer_and_save(image, output_path, ...)` method. + Currently supports Trellis2Model; any model with the same interface works. + output_dir (str, optional): **Legacy flat mode.** When given, every GLB is + written as `/.glb`, exactly as before. When + omitted (default), the per-game layout under + `test_data/outputs///assets/3d_object//` + is used instead. + run_id (str): Groups all artifacts of one generation run. Per-game mode only. + default_game_id (str, optional): Fallback game project for tasks that carry + no `game_id` and whose input paths reveal none. Per-game mode only. + """ + + def __init__( + self, + model: Any, + output_dir: Optional[str] = None, + run_id: str = "default", + default_game_id: Optional[str] = None, + ): + self.model = model + self.run_id = run_id + self.default_game_id = default_game_id + # Legacy flat mode is active only when an explicit output_dir is supplied. + self.output_dir = Path(output_dir) if output_dir else None + if self.output_dir is not None: + self.output_dir.mkdir(parents=True, exist_ok=True) + + # -------------------------------------------------------------------------- + + def _load_image(self, inp: dict) -> Image.Image: + """Return a PIL image from an input dict that has 'image_path' or 'image'.""" + if "image" in inp and isinstance(inp["image"], Image.Image): + return inp["image"] + if "image_path" in inp: + p = Path(inp["image_path"]) + if not p.is_absolute() and not p.exists(): + # resolve relative to repo root (codes_official/) + repo_root = Path(__file__).resolve().parents[2] + p = repo_root / inp["image_path"] + return Image.open(str(p)).convert("RGBA") + raise ValueError("Input must contain 'image_path' (str) or 'image' (PIL.Image).") + + # -------------------------------------------------------------------------- + + def _artifact_suffix(self) -> str: + """ + File extension for the artifact — GLB unless the injected model says + otherwise (the cloud backends can emit FBX / OBJ / USDZ). + + The result dict keeps the ``glb_path`` key whatever the extension is: + renaming a returned key breaks `eval.py` and `test/`. + """ + fmt = getattr(self.model, "output_format", None) + return str(fmt).lower().lstrip(".") if fmt else "glb" + + def _resolve_out_path(self, inp: dict, task_id: str) -> tuple[str, Path, Path]: + """ + Return ``(game_id, task_dir, glb_path)`` for either output mode. + + Legacy flat mode keeps the historical `/.glb`. + """ + suffix = self._artifact_suffix() + if self.output_dir is not None: + game_id = str(inp.get("game_id") or inp.get("game") or "") + return game_id, self.output_dir, self.output_dir / f"{task_id}.{suffix}" + + from pipeline.common import paths + game_id = paths.infer_game_id(inp, fallback=self.default_game_id) + task_dir = paths.task_output_dir(game_id, TASK_KIND, task_id, run_id=self.run_id) + filename = GLB_FILENAME if suffix == "glb" else f"model.{suffix}" + return game_id, task_dir, task_dir / filename + + # -------------------------------------------------------------------------- + + def run(self, inp: dict) -> dict: + """ + Generate a 3D object from an image prompt, or build one from a spec. + + Args: + inp (dict): + - image_path (str): path to the reference / concept image + OR image (PIL.Image): pre-loaded image + OR spec (dict): a part spec, which builds the mesh instead + of inferring it (see `funcs/code_asset.py`) + - compose (dict): combine_avatar arguments, including caller-defined + socket_definitions, grip_templates and optional slot_definitions + - game_id (str, optional): game project this task belongs to; + inferred from `image_path` when omitted + - task_id (str, optional): used to name the output file / directory + - seed (int, optional): random seed (default 42) + - decimation_target (int, optional) + - texture_size (int, optional) + + Returns: + dict: + - task_id (str) + - glb_path (str): absolute path to the saved GLB file + - elapsed_sec (float) + - game_id (str), task_kind (str), output_dir (str) ← additive + """ + if inp.get("compose") is not None: + if inp.get("spec") is not None: + raise ValueError("provide compose or spec, not both") + return self._run_compose(inp) + if inp.get("spec") is not None: + return self._run_spec(inp) + + task_id = inp.get("task_id", f"task_{int(time.time())}") + seed = inp.get("seed", 42) + decimation_target = inp.get("decimation_target", 1_000_000) + texture_size = inp.get("texture_size", 4096) + + game_id, task_dir, out_path = self._resolve_out_path(inp, task_id) + + text_mode = inp.get("input_mode") == "text_to_3d" + if text_mode and not str(inp.get("prompt") or "").strip(): + raise ValueError("text_to_3d requires a non-empty prompt") + image = None if text_mode else self._load_image(inp) + inference_kwargs = {"prompt": inp["prompt"]} if text_mode else {} + + t0 = time.time() + glb_path = self.model.infer_and_save( + image, + output_path=str(out_path), + seed=seed, + decimation_target=decimation_target, + texture_size=texture_size, + **inference_kwargs, + ) + elapsed = time.time() - t0 + + result = { + "task_id": task_id, + "glb_path": glb_path, + "elapsed_sec": round(elapsed, 2), + "game_id": game_id, + "task_kind": TASK_KIND, + "output_dir": str(task_dir), + } + + # Image-to-3D infers a floor under a subject that stands on the edge + # of its own crop, and it is never wanted: measured at a fifth of the + # triangle budget, and a grey pancake under the character in the + # scene. Removing it here means every consumer of this task output + # gets a clean mesh, rather than each game discovering the slab. + if inp.get("strip_ground_plate", True): + from .funcs.mesh_cleanup import strip_ground_plate + + cleanup = strip_ground_plate(glb_path) + result["ground_plate"] = cleanup + if cleanup.get("applied"): + result.setdefault("warnings", []).append( + f"removed an inferred floor: {cleanup['plate_count']} " + f"sheets and {cleanup['debris_count']} loose lumps, " + f"{cleanup['removed_fraction']:.0%} of the mesh" + ) + elif cleanup.get("reason") and "nothing" not in cleanup["reason"]: + result.setdefault("warnings", []).append( + f"left the mesh alone: {cleanup['reason']}" + ) + + # meta.json only in per-game mode, so legacy output dirs stay untouched. + if self.output_dir is None: + from pipeline.common import paths + meta = { + **result, + "run_id": self.run_id, + "prompt": inp.get("prompt"), + "source_image": inp.get("image_path"), + "seed": seed, + "decimation_target": decimation_target, + "texture_size": texture_size, + "model": type(self.model).__name__, + } + for key in ("asset_id", "asset_type", "forward_axis", + "scale_hint_metres", "notes"): + if inp.get(key) is not None: + meta[key] = inp[key] + # Cloud backends expose what the call cost and produced — task id, + # credits, triangle count (api_model_require.md R9.8). Recording it + # here is what makes a billed run reproducible after the fact. + call_info = getattr(self.model, "last_call_info", None) + if call_info: + meta["model_call"] = dict(call_info) + paths.write_task_meta(task_dir, meta) + + # Optional handover to the engine adapter, active only when the task + # names an asset. A generated mesh is not part of a game until the + # adapter has staged it and recorded which way it faces. + if inp.get("asset_id") and self.output_dir is None: + from .funcs.asset_import import import_asset + result.update( + import_asset( + game_id, + task_id, + asset_id=str(inp["asset_id"]), + asset_type=str(inp.get("asset_type") or "prop"), + run_id=self.run_id, + forward_axis=str(inp.get("forward_axis") or ""), + scale_hint_metres=inp.get("scale_hint_metres"), + verified_by=str(inp.get("verified_by") or "heuristic"), + notes=str(inp.get("notes") or ""), + project_hint=str(inp.get("project_hint") or ""), + preview=bool(inp.get("preview", True)), + ) + ) + + return result + + # -------------------------------------------------------------------------- + + def _run_compose(self, inp: dict) -> dict: + """Resolve caller-configured attachments, then build through the spec route.""" + import json + from .funcs.code_asset_templates.human_template.combine import ( + combine_avatar, write_report, + ) + + task_id = inp.get("task_id", f"task_{int(time.time())}") + _, _, out_path = self._resolve_out_path(inp, task_id) + directory = out_path.parent / f"{out_path.stem}_compose" + config = dict(inp["compose"]) + config.setdefault("parts_dir", directory / "parts") + started = time.time() + combined = combine_avatar(**config) + result = self._run_spec({**inp, "task_id": task_id, "spec": combined["spec"]}) + report_path = write_report(combined["report"], directory / "report.json") + sockets_path = directory / "sockets.json" + sockets_path.write_text(json.dumps(combined["report"]["sockets"], indent=2), + encoding="utf-8") + result["compose"] = {**combined["report"], "report_path": report_path, + "sockets_path": str(sockets_path)} + result["elapsed_sec"] = round(time.time() - started, 2) + return result + + def _run_spec(self, inp: dict) -> dict: + """Build the asset from a declarative spec rather than an image. + + Taken when the task carries a ``spec``. No model is loaded and no + image is read, so this path works with ``model=None`` — a crate + does not need a GPU, and requiring one to build a box is what makes + primitives feel like a defeat rather than a choice. + + Three things come out of the spec that the generated path can only + guess at, which is the reason to prefer it wherever it applies: + + * ``forward_axis`` is *stated*, so the import is recorded as + ``verified_by="spec"`` rather than ``"heuristic"``. Facing is + the one property `orientation_review` exists to establish, and + here there is nothing to establish. + * ``scale_hint_metres`` is stated, so the mesh has a real size + instead of a unit box someone has to scale by eye. + * parts keep their ids as glTF node names, so a wheel can be spun + after import. A reconstructed mesh is one fused body. + + ``strip_ground_plate`` is deliberately not run: it removes a floor + that image-to-3D *invented*, and a spec cannot invent one. Running + it here would risk deleting a plinth that was asked for. + + A spec may also carry ``mesh`` parts, which read a GLB off disk — + typically one component from a cloud model, composed in where no + formula states the shape. Those change one thing here and nothing + else: ``verified_by`` drops to ``"spec+generated"``, because a + generated part's facing was *asserted* by whoever placed it and not + established by anything. Claiming ``"spec"`` for a composition that + is largely fetched geometry would put an unverified facing behind the + one label that is supposed to mean it was not guessed. + """ + from .funcs.code_asset import MESH_KIND, build_code_asset + + task_id = inp.get("task_id", f"task_{int(time.time())}") + game_id, task_dir, out_path = self._resolve_out_path(inp, task_id) + # A spec always yields glTF, whatever output_format an injected + # model happens to advertise. + out_path = out_path.with_suffix(".glb") + task_dir.mkdir(parents=True, exist_ok=True) + + t0 = time.time() + report = build_code_asset( + inp["spec"], + str(out_path), + revise=inp.get("revise"), + strict=bool(inp.get("strict", True)), + ) + elapsed = time.time() - t0 + + # Which parts were fetched rather than derived. Carried on the result + # because after export the two are indistinguishable, and only one of + # them can still be changed by editing a number: a reviewer who wants + # the grip 4 mm thicker needs to know that means regenerating it. + # `long_axis` travels too, since a regenerated part is a new set of + # axes and the rotation that placed the old one will not place it. + generated_parts = [ + { + "id": part["id"], + "source": part["source"], + "long_axis": part.get("long_axis"), + } + for part in report["spec"]["parts"] + if part.get("kind") == MESH_KIND + ] + + result: dict[str, Any] = { + "task_id": task_id, + "glb_path": report["glb_path"], + "elapsed_sec": round(elapsed, 2), + "game_id": game_id, + "task_kind": TASK_KIND, + "output_dir": str(task_dir), + "source": "code_asset+generated" if generated_parts else "code_asset", + "spec_ok": report["ok"], + "gates": report["gates"], + "triangles": report["triangles"], + "bounds": report["bounds"], + "part_ids": report["part_ids"], + "generated_parts": generated_parts, + "stop_reason": report["stop_reason"], + "attempts": report["attempts"], + } + if report["warnings"]: + result.setdefault("warnings", []).extend(report["warnings"]) + if report["failures"]: + # Surfaced as warnings on the result *and* kept in `gates`: a + # gate failure that only appears in a nested dict is the silent + # early return this whole module is shaped against. + result.setdefault("warnings", []).extend( + f"gate: {message}" for message in report["failures"] + ) + + if self.output_dir is None: + from pipeline.common import paths + + meta = { + **result, + "run_id": self.run_id, + "spec": report["spec"], + "forward_axis": report["forward_axis"], + "scale_hint_metres": report["scale_hint_metres"], + "model": "code_asset", + } + for key in ("asset_id", "asset_type", "notes"): + if inp.get(key) is not None: + meta[key] = inp[key] + paths.write_task_meta(task_dir, meta) + + # A failed spec is not handed to the engine. An asset that exists + # gets used, so a gate failure has to stop it becoming an asset. + if inp.get("asset_id") and self.output_dir is None and report["ok"]: + from .funcs.asset_import import import_asset + + result.update( + import_asset( + game_id, + task_id, + asset_id=str(inp["asset_id"]), + asset_type=str( + inp.get("asset_type") + or report["spec"].get("asset_type") + or "prop" + ), + run_id=self.run_id, + # Stated by the spec, not inferred from a view. + forward_axis=report["forward_axis"], + scale_hint_metres=report["scale_hint_metres"], + # "spec" means the facing was stated rather than guessed. + # With generated parts in the composition that is only + # half true: the *placement* is stated, but the mesh + # inside it came from a generator with no facing of its + # own, and whoever wrote the rotation asserted one. Said + # distinctly so a reviewer knows an orientation check is + # still worth a look, instead of trusting a label that + # was earned by a different route. + verified_by="spec+generated" if generated_parts else "spec", + notes=str(inp.get("notes") or "") + or ( + f"Built from a spec: {report['subject']}." + + ( + f" {len(generated_parts)} generated part(s): " + f"{', '.join(part['id'] for part in generated_parts)}." + if generated_parts else "" + ) + ), + project_hint=str(inp.get("project_hint") or ""), + preview=bool(inp.get("preview", True)), + ) + ) + return result + + # -------------------------------------------------------------------------- + + def run_art_plan( + self, + game_id: str, + image_model: Any = None, + plan: Optional[list[dict]] = None, + assets: tuple[str, ...] = (), + ) -> list[dict]: + """ + Generate a game's recorded art plan and import each asset. + + The plan lives in `funcs/art_plan.py`; it names a subject, an asset + type and a **height in metres**, because a mesh normalised into a + unit box has no size of its own. Concept images come from + `image_model` unless an entry points at one. + + Facing is recorded as `heuristic`, never as verified: single-image + reconstruction puts the input view on a predictable axis, but a + guess labelled as checked stops anyone checking. Each import leaves + a review sheet for `agent_skills/asset_qa/`. + """ + from .funcs.art_plan import concept_image, plan_for_game + + entries = plan if plan is not None else plan_for_game(game_id) + if not entries: + raise ValueError( + f"No art plan for {game_id!r}; add one to " + "operators/gen_3d_object/funcs/art_plan.py" + ) + + results: list[dict] = [] + for entry in entries: + if assets and entry["asset_id"] not in assets: + continue + image, provenance, framing = concept_image(entry, image_model) + task_dir = Path( + self._resolve_out_path( + {"game_id": game_id}, entry["task_id"] + )[1] + ) + task_dir.mkdir(parents=True, exist_ok=True) + # Keep the concept image beside the mesh it produced: a bad + # asset is almost always a bad concept image, and that is not + # diagnosable after the fact if the input was thrown away. + image.save(task_dir / "concept.png") + result = self.run( + { + "game_id": game_id, + "task_id": entry["task_id"], + "image": image, + "prompt": entry["full_prompt"], + "seed": entry.get("seed", 42), + "decimation_target": entry["triangles"], + "texture_size": entry["texture"], + "asset_id": entry["asset_id"], + "asset_type": entry["type"], + "forward_axis": entry["faces"], + "scale_hint_metres": entry["height"], + "verified_by": "heuristic", + "notes": entry["notes"] + or f"Generated from: {provenance}. Facing assumed " + "from the input view.", + } + ) + result["asset_id"] = entry["asset_id"] + result["concept_source"] = provenance + result["framing"] = framing + if framing.get("touched_border"): + # The subject ran off the edge of the generated image, so + # part of it was never drawn. Cropping cannot invent it. + result.setdefault("warnings", []).append( + "the concept image was cropped at the border, so the " + "mesh is probably truncated: regenerate with another " + "seed" + ) + results.append(result) + return results + + # -------------------------------------------------------------------------- + + def run_batch(self, inputs: list[dict]) -> list[dict]: + """Run a list of input dicts sequentially and return results.""" + return [self.run(inp) for inp in inputs] diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/paths.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/paths.py new file mode 100644 index 0000000000000000000000000000000000000000..94e8ec7b966e0c84658fd5322dc30f0c769f0f2f --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/paths.py @@ -0,0 +1,444 @@ +""" +pipeline/common/paths.py + +Single source of truth for every input / output path in 3AGameFactory. + +The benchmark is authored **per game project**, so outputs are organized the same +way. An artifact is uniquely addressed by ``(game_id, run_id, task_kind, task_id)``:: + + test_data/test_samples///... # inputs (read-only) + test_data/outputs////// # outputs + +Full output tree:: + + test_data/outputs/ # OUTPUT_ROOT ($AAAGF_OUTPUT_ROOT) + └── gameA_cyberpunk_shooter/ # one dir per generated game project + ├── latest -> 20260731_1032/ # symlink to the most recent run + └── / # "default", or a timestamp + ├── run_meta.json # ckpts · seeds · git sha · argv + ├── assets/ + │ ├── 3d_object// # model.glb + meta.json + │ ├── tpose// # tpose_fg.png + meta.json + │ ├── 3d_scene// + │ ├── motion// + │ ├── cg_video// + │ └── audio// # dialogue / sound-effect audio + meta.json + ├── mechanic// # engine project + demo_outputs/ + launch.sh + ├── ui// + ├── pipeline// # end-to-end game-slice artifacts + └── eval/ + ├── // # metrics.json · build.log · judge_log.json + └── summary.json # aggregate over the whole run + +The root stays next to the test set so any evaluator finds inputs and outputs side +by side. Generated artifacts get large — point ``$AAAGF_OUTPUT_ROOT`` at a scratch +disk to relocate the whole tree without touching code. + +This module has **no third-party dependencies** and imports no models, so it is +safe to import from anywhere (including CPU-only tooling and tests). +""" +from __future__ import annotations + +import json +import os +import subprocess +import sys +from datetime import datetime +from pathlib import Path +from typing import Any, Optional + +# ── Roots ───────────────────────────────────────────────────────────────────── + +REPO_ROOT = Path(__file__).resolve().parents[2] + +TEST_DATA_ROOT = REPO_ROOT / "test_data" +TEST_SAMPLES_ROOT = TEST_DATA_ROOT / "test_samples" + +#: Output root. Override with ``export AAAGF_OUTPUT_ROOT=/scratch/aaagf_outputs``. +OUTPUT_ROOT = Path( + os.environ.get("AAAGF_OUTPUT_ROOT", TEST_DATA_ROOT / "outputs") +).expanduser() + +#: Used when a task carries no game association (ad-hoc single-image demos). +UNASSIGNED_GAME = "_scratch" + +#: Run id used when the caller does not ask for a fresh timestamped one. +DEFAULT_RUN_ID = "default" + +LATEST_LINK = "latest" + + +# ── Task kinds ──────────────────────────────────────────────────────────────── + +#: task_kind -> layer directory. Layer A = assets, B = mechanic, C = ui. +TASK_LAYER: dict[str, str] = { + # Layer A — asset generation + "3d_object": "assets", + "tpose": "assets", + "3d_scene": "assets", + "motion": "assets", + "cg_video": "assets", + "audio": "assets", + # Game design (story / chapters / asset & screen plan) — A-layer diagnostic only + "design": "design", + # Layer B / C — code generation + "mechanic": "mechanic", + "ui": "ui", + # End-to-end vertical slice + "pipeline": "pipeline", + # Whitebox-stage game evaluation (stage-1 LLM/Agent whitebox rubric) — + # an eval-only kind: results land under ``eval/whitebox//`` + "whitebox": "whitebox", +} + +#: task_kind -> directory name inside ``test_samples//``. +TASK_INPUT_DIR: dict[str, str] = { + "3d_object": "3D_object", + "tpose": "tpose", + "3d_scene": "3D_scene", + "motion": "motion", + "cg_video": "cg_video", + "audio": "audio", + "design": "design", + "mechanic": "mechanic", + "ui": "ui", + "pipeline": "pipeline", + # whitebox case inputs (game_spec/rubric/references) live under + # ``test_bench_example//``; this dir keeps the registration + # complete for the shared task-input helpers. + "whitebox": "whitebox", +} + +#: task_kind -> per-game task list filename inside ``TASK_INPUT_DIR``. +TASK_JSONL: dict[str, str] = { + "3d_object": "object_tasks.jsonl", + "tpose": "tpose_tasks.jsonl", + "3d_scene": "scene_tasks.jsonl", + "motion": "motion_tasks.jsonl", + "cg_video": "cg_tasks.jsonl", + "audio": "audio_tasks.jsonl", + "design": "design_tasks.jsonl", + "mechanic": "mechanic_tasks.jsonl", + "ui": "ui_tasks.jsonl", + "pipeline": "pipeline_task.jsonl", + "whitebox": "whitebox_tasks.jsonl", +} + +#: task_kind -> cross-game aggregate jsonl under ``test_samples/``. +TASK_COLLECT_JSONL: dict[str, str] = { + "3d_object": "3D_object_gen_collect.jsonl", + "tpose": "tpose_gen_collect.jsonl", + "3d_scene": "3D_scene_gen_collect.jsonl", + "motion": "motion_gen_collect.jsonl", + "cg_video": "cg_video_collect.jsonl", + "audio": "audio_gen_collect.jsonl", + "design": "design_collect.jsonl", + "mechanic": "mechanic_collect.jsonl", + "ui": "ui_collect.jsonl", + "pipeline": "pipeline_collect.jsonl", + "whitebox": "whitebox_collect.jsonl", +} + +#: Layer-A kinds only — what ``pipeline/assets_gen/`` covers. +ASSET_TASK_KINDS = tuple(k for k, v in TASK_LAYER.items() if v == "assets") + + +def check_kind(task_kind: str) -> str: + """Raise a helpful error for an unregistered task kind.""" + if task_kind not in TASK_LAYER: + raise ValueError( + f"Unknown task_kind {task_kind!r}. Register it in " + f"pipeline/common/paths.py first. Known: {sorted(TASK_LAYER)}" + ) + return task_kind + + +# ── Input paths ─────────────────────────────────────────────────────────────── + +def game_input_dir(game_id: str) -> Path: + """``test_data/test_samples//``""" + return TEST_SAMPLES_ROOT / game_id + + +def task_input_dir(game_id: str, task_kind: str) -> Path: + """``test_data/test_samples///``""" + return game_input_dir(game_id) / TASK_INPUT_DIR[check_kind(task_kind)] + + +def task_jsonl(game_id: str, task_kind: str) -> Path: + """``test_data/test_samples///_tasks.jsonl``""" + return task_input_dir(game_id, task_kind) / TASK_JSONL[check_kind(task_kind)] + + +def collect_jsonl(task_kind: str) -> Path: + """``test_data/test_samples/_collect.jsonl`` — cross-game task list.""" + return TEST_SAMPLES_ROOT / TASK_COLLECT_JSONL[check_kind(task_kind)] + + +def resolve_tasks_path(task_kind: str, tasks: str | None = None, + game_id: str | None = None) -> Path: + """ + Standard task-list resolution shared by every ``run.py`` / ``eval.py``: + + explicit ``--tasks`` → the game's own ``*_tasks.jsonl`` (if non-empty) + → the cross-game ``*_collect.jsonl``. + """ + if tasks: + return resolve_input_path(tasks) + if game_id: + per_game = task_jsonl(game_id, task_kind) + if per_game.exists() and per_game.stat().st_size > 0: + return per_game + return collect_jsonl(task_kind) + + +def list_games() -> list[str]: + """Every game project directory present in the test set.""" + if not TEST_SAMPLES_ROOT.is_dir(): + return [] + return sorted( + p.name + for p in TEST_SAMPLES_ROOT.iterdir() + if p.is_dir() and not p.name.startswith((".", "_")) + ) + + +def infer_game_id(task: dict, fallback: Optional[str] = None) -> str: + """ + Resolve which game project a task belongs to. + + Priority: explicit ``game_id`` / ``game`` field → any path-like field that + sits under ``test_samples//`` → ``fallback`` → ``UNASSIGNED_GAME``. + """ + for key in ("game_id", "game"): + if task.get(key): + return str(task[key]) + + for value in task.values(): + if not isinstance(value, str) or "test_samples" not in value: + continue + parts = Path(value).parts + if "test_samples" in parts: + idx = parts.index("test_samples") + if idx + 1 < len(parts): + return parts[idx + 1] + + return fallback or UNASSIGNED_GAME + + +def iter_tasks(tasks_path: str | Path, game_filter: str | None = None): + """ + Yield ``(task_dict, game_id)`` from a jsonl, skipping blanks and comments. + + Every runner should iterate through this so `game_id` resolution and the + `--game` filter behave identically across tasks. + """ + with open(tasks_path) as f: + for lineno, line in enumerate(f, 1): + line = line.strip() + if not line or line.startswith("//"): + continue + try: + task = json.loads(line) + except json.JSONDecodeError as e: + raise ValueError(f"{tasks_path}:{lineno} is not valid JSON: {e}") from e + game_id = infer_game_id(task) + if game_filter and game_id != game_filter: + continue + yield task, game_id + + +# ── Output paths ────────────────────────────────────────────────────────────── + +def new_run_id(prefix: str = "") -> str: + """Timestamped run id, e.g. ``20260731_103200`` or ``qwen3b_20260731_103200``.""" + stamp = datetime.now().strftime("%Y%m%d_%H%M%S") + return f"{prefix}_{stamp}" if prefix else stamp + + +def game_output_dir(game_id: str) -> Path: + """``test_data/outputs//``""" + return OUTPUT_ROOT / game_id + + +def run_dir(game_id: str, run_id: str = DEFAULT_RUN_ID) -> Path: + """``test_data/outputs///`` — root of one generation run.""" + return game_output_dir(game_id) / run_id + + +def task_output_dir( + game_id: str, + task_kind: str, + task_id: str, + run_id: str = DEFAULT_RUN_ID, + create: bool = True, +) -> Path: + """ + ``test_data/outputs////[/]/`` + + One directory per task, so an artifact ships alongside its preview, + intermediates and ``meta.json`` without filename mangling. + """ + check_kind(task_kind) + layer = TASK_LAYER[task_kind] + base = run_dir(game_id, run_id) / layer + # assets/ is further split by kind; mechanic/ ui/ pipeline/ *are* the kind. + if layer == "assets": + base = base / task_kind + path = base / task_id + if create: + path.mkdir(parents=True, exist_ok=True) + return path + + +def eval_output_dir( + game_id: str, + task_kind: str, + task_id: str, + run_id: str = DEFAULT_RUN_ID, + create: bool = True, +) -> Path: + """``test_data/outputs///eval///``""" + check_kind(task_kind) + path = run_dir(game_id, run_id) / "eval" / task_kind / task_id + if create: + path.mkdir(parents=True, exist_ok=True) + return path + + +def eval_summary_path(game_id: str, run_id: str = DEFAULT_RUN_ID) -> Path: + """``test_data/outputs///eval/summary.json``""" + return run_dir(game_id, run_id) / "eval" / "summary.json" + + +def results_summary_path(game_id: str, task_kind: str, + run_id: str = DEFAULT_RUN_ID) -> Path: + """``test_data/outputs///_results_summary.json``""" + check_kind(task_kind) + return run_dir(game_id, run_id) / f"{task_kind}_results_summary.json" + + +def run_meta_path(game_id: str, run_id: str = DEFAULT_RUN_ID) -> Path: + """``test_data/outputs///run_meta.json``""" + return run_dir(game_id, run_id) / "run_meta.json" + + +# ── Run bookkeeping ─────────────────────────────────────────────────────────── + +def _git_sha() -> Optional[str]: + try: + out = subprocess.run( + ["git", "-C", str(REPO_ROOT), "rev-parse", "--short", "HEAD"], + capture_output=True, text=True, timeout=5, + ) + return out.stdout.strip() or None + except Exception: + return None + + +def update_latest_link(game_id: str, run_id: str) -> None: + """Repoint ``/latest`` at ``run_id`` (best effort, never fatal).""" + if run_id == LATEST_LINK: + return + link = game_output_dir(game_id) / LATEST_LINK + try: + link.parent.mkdir(parents=True, exist_ok=True) + if link.is_symlink() or link.exists(): + link.unlink() + link.symlink_to(run_id, target_is_directory=True) + except OSError: + pass # filesystem without symlink support — not fatal + + +def write_run_meta( + game_id: str, + run_id: str = DEFAULT_RUN_ID, + *, + task_kind: Optional[str] = None, + extra: Optional[dict[str, Any]] = None, +) -> Path: + """Record how a run was produced, so results stay reproducible.""" + path = run_meta_path(game_id, run_id) + path.parent.mkdir(parents=True, exist_ok=True) + + meta: dict[str, Any] = { + "game_id": game_id, + "run_id": run_id, + "task_kind": task_kind, + "created_at": datetime.now().isoformat(timespec="seconds"), + "git_sha": _git_sha(), + "argv": sys.argv, + } + if extra: + meta.update(extra) + + if path.exists(): # merge with an earlier task_kind in the same run + try: + prev = json.loads(path.read_text(encoding="utf-8")) + history = prev.pop("history", []) + history.append(prev) + meta["history"] = history + except (json.JSONDecodeError, OSError): + pass + + path.write_text(json.dumps(meta, indent=2, ensure_ascii=False), encoding="utf-8") + return path + + +def write_task_meta(task_dir: str | Path, meta: dict[str, Any]) -> Path: + """Write ``/meta.json`` next to the artifacts.""" + d = Path(task_dir) + d.mkdir(parents=True, exist_ok=True) + path = d / "meta.json" + from .record_paths import portable_value + path.write_text(json.dumps(portable_value(meta, d), indent=2, ensure_ascii=False, default=str), + encoding="utf-8") + return path + + +def write_results_summary(results: list[dict], task_kind: str, + run_id: str = DEFAULT_RUN_ID) -> list[Path]: + """ + Group ``run()`` results by ``game_id`` and write one summary per game, + refresh ``run_meta.json`` and the ``latest`` symlink. + + Returns the summary paths written. + """ + check_kind(task_kind) + grouped: dict[str, list[dict]] = {} + for r in results: + grouped.setdefault(r.get("game_id") or UNASSIGNED_GAME, []).append(r) + + written = [] + for game_id, items in grouped.items(): + path = results_summary_path(game_id, task_kind, run_id) + path.parent.mkdir(parents=True, exist_ok=True) + path.write_text(json.dumps(items, indent=2, ensure_ascii=False, default=str), + encoding="utf-8") + write_run_meta(game_id, run_id, task_kind=task_kind, + extra={"num_tasks": len(items)}) + update_latest_link(game_id, run_id) + written.append(path) + return written + + +# ── Misc ────────────────────────────────────────────────────────────────────── + +def resolve_input_path(path_like: str | Path) -> Path: + """Resolve a possibly repo-relative input path (jsonl paths are repo-relative).""" + if str(path_like).replace("\\", "/").startswith("bench/"): + from .record_paths import resolve_path + return resolve_path(path_like) + p = Path(path_like) + if p.is_absolute() or p.exists(): + return p + return REPO_ROOT / p + + +def rel_to_repo(path: str | Path) -> str: + """Repo-relative string if possible, else the absolute path — for logs / meta.""" + p = Path(path).resolve() + try: + return str(p.relative_to(REPO_ROOT)) + except ValueError: + return str(p) diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/record_paths.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/record_paths.py new file mode 100644 index 0000000000000000000000000000000000000000..21084bcfe232636debebeb9d1b9df5da1e2909da --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/GameFactory-3A/pipeline/common/record_paths.py @@ -0,0 +1,77 @@ +"""Portable workspace paths for persisted records; resolve only when doing I/O.""" +from __future__ import annotations + +from pathlib import Path +import re + +BENCH = Path(__file__).resolve().parents[3] +_PREFIXES = ("test_data/", "GameFactory-3A/", "scripts/", "prompts/", "config/", "reports/") +_ROOT = BENCH.as_posix() +_INLINE_ROOT = re.compile(re.escape(_ROOT).replace("/", r"[\\/]"), re.IGNORECASE) + + +def resolve_path(value: str | Path) -> Path: + text = str(value).replace("\\", "/") + if text == "bench" or text.startswith("bench/"): + path = (BENCH.parent / text).resolve() + path.relative_to(BENCH.resolve()) + return path + path = Path(value) + return path if path.is_absolute() else BENCH / path + + +def portable_path(value: str | Path, base: Path | None = None) -> str: + original = str(value) + text = original.replace("\\", "/") + if re.match(r"^[A-Za-z][A-Za-z0-9+.-]*:", text) and not re.match(r"^[A-Za-z]:/", text): + return original # URLs, API URIs and dependency descriptors retain their meaning. + if text.casefold() == _ROOT.casefold() or text.casefold().startswith(_ROOT.casefold() + "/"): + return "bench" + text[len(_ROOT):] + if text == "bench" or text.startswith("bench/"): + path = resolve_path(text) + suffix = path.relative_to(BENCH.resolve()).as_posix() + return "bench" if suffix == "." else "bench/" + suffix + if text.startswith(_PREFIXES): + path = (BENCH / text).resolve() + path.relative_to(BENCH.resolve()) + return "bench/" + path.relative_to(BENCH.resolve()).as_posix() + if base is not None and "/" in text and "\n" not in text and not text.startswith("/"): + candidate = base / text + try: + if candidate.exists(): + return "bench/" + candidate.resolve().relative_to(BENCH.resolve()).as_posix() + except (OSError, ValueError): + pass + return original + + +def portable_text(value: str) -> str: + """Convert workspace paths embedded in log/error text, leaving URLs intact.""" + pattern = re.compile(r"(?:https?://[^\s<>]+)|(" + _INLINE_ROOT.pattern + r"(?:[\\/][^\r\n\"'<>|;,)]*)?)", re.IGNORECASE) + return pattern.sub(lambda match: portable_path(match.group(1)) if match.group(1) else match.group(0), value) + + +def portable_value(value, base: Path | None = None): + if isinstance(value, dict): + return {portable_path(key) if isinstance(key, str) else key: portable_value(item, base) + for key, item in value.items()} + if isinstance(value, (list, tuple)): + return [portable_value(item, base) for item in value] + if isinstance(value, Path): + return portable_path(value, base) + if isinstance(value, str): + result = portable_path(value, base) + return portable_text(result) + return value + + +def runtime_value(value): + """Hydrate a verified frozen plan for runtime use; never use before hashing.""" + if isinstance(value, dict): + return {str(resolve_path(key)) if isinstance(key, str) and (key == "bench" or key.startswith("bench/")) else key: + runtime_value(item) for key, item in value.items()} + if isinstance(value, list): + return [runtime_value(item) for item in value] + if isinstance(value, str) and (value == "bench" or value.startswith("bench/")): + return str(resolve_path(value)) + return value diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/prompts/stage2_assets.md b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/prompts/stage2_assets.md new file mode 100644 index 0000000000000000000000000000000000000000..bd5f2cb297be9a913eaf0cb8aae96779b20cbcd9 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/prompts/stage2_assets.md @@ -0,0 +1,95 @@ +# GameFactory-3A Stage 2 — asset generation + +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。** + +## 测例输入 + +- 游戏测例：`{GAME_ID}` +- 测例目录：`{CASE_ROOT}` +- GameFactory-3A 根目录：`{FRAMEWORK_ROOT}` +- 总入口文档：`{SETTING_OVERVIEW}` +- 目标引擎：`{ENGINE}` +- 完整游戏需求：`{GENERAL_REQUIREMENT}` +- 当前 run 根目录：`{RUN_ROOT}` +- runner 控制面（冻结索引、prompt/packet/log）：`{GENERATION_CONTROL_ROOT}` +- 第一阶段白模 run：`{WHITEBOX_RUN_ROOT}` +- 第一阶段白模 workspace：`{WHITEBOX_WORKSPACE}` +- 第一阶段资产接口：`{ASSET_SLOTS}` +- 第一阶段计划/TODO：`{GENERATION_PLAN}` +- 外部冻结的资产任务索引：`{ASSET_TASK_INDEX}` +- 资产输出根目录：`{ASSET_OUTPUT_ROOT}` +- 当前阶段 pipeline task 目录：`{STAGE_WORKSPACE}` +- 资产 QA 证据根：`{RUN_ROOT}/eval///` + +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。 + +## 本阶段任务 + +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； +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； +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； +4. 保持第一阶段定义的 asset ID 和游戏/UI/mechanic contract 不变； +5. 记录资产来源、配置、参考图、QA 和后续导入要求； +6. 生成完整的资产 manifest，供第三阶段导入使用。 + +## 限制 + +- 不修改第一阶段核心游戏机制和需求； +- 不擅自删除、合并或跳过资产任务； +- 资产失败必须记录为失败，不能伪造成功； +- 不将资产生成 QA 当成游戏已经完成； +- 本阶段默认不执行 Agent repair。 + +## 输出位置和 Layer 规则 + +资产必须按框架标准布局写入： + +- `{ASSET_OUTPUT_ROOT}/tpose//`； +- `{ASSET_OUTPUT_ROOT}/3d_object//`； +- `{ASSET_OUTPUT_ROOT}/3d_scene//`； +- `{ASSET_OUTPUT_ROOT}/motion//`； +- `{ASSET_OUTPUT_ROOT}/audio//`； +- `{ASSET_OUTPUT_ROOT}/cg_video//`。 + +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 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///`。至少生成： + +- `asset_manifest.json`； +- `asset_generation_report.json`； +- `asset_task_index.json`（由外部入口生成，不得删改任务）； +- 失败任务及其失败原因。 + +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///` 放置，不能把所有文件平铺在 pipeline task 目录。 + +## 已确认的优先 3D Object 双服务对比 + +当用户明确选择优先 200 条对象任务的 Meshy / Tripo API 对比时，使用 +`scripts/asset/generate_3d_comparison.py` 与 `config/asset_3d_comparison.json`， +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； +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。 + +- 输入以 `test_data/priority_gen/3d_object_priority_lowpoly_collect.jsonl` 的全部 200 条为准， + 保留原 task ID、prompt、seed、参考图及最高 8000 三角面的既定政策。 +- 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， + 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。 +- 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 + 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。 +- 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 + 仅保留后续接入口，本轮不启用、不消耗第三家额度。 +- 固定具体模型版本，不使用 `latest`；Meshy 本轮使用 standard + remesh， + 不依赖将于 2026-10-30 退役的 `model_type=lowpoly`。 +- 原始 API mesh 写为 `model.glb`，统一后处理的导入 mesh 写为 `import/model.glb`。 + 两家使用同一固定工具、参数与贴图上限；分别记录原始和后处理 QA、耗时及缺陷。 + 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。 +- 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； + 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。 +- 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： + `test_data/outputs//assets/3d_object///`， + `` 为 `meshy` / `tripo`，不使用 `asset_comparison` 输出目录。 + 原始 `model.glb`、`import/model.glb`、`meta.json`、服务端预览均放在厂商目录内； + QA 写入 `test_data/outputs//eval/3d_object///`。 + manifest/阶段报告按游戏、批次、厂商放在 + `test_data/outputs//pipeline/_pipeline///`， + 冻结输入、计费回执与跨游戏预览保存在 `test_data/outputs/_asset_batches//`。 + 不覆盖不同批次已有的厂商资产，也不覆盖白模工程。 + 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。 + 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。 diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/cloud_journal.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/cloud_journal.py new file mode 100644 index 0000000000000000000000000000000000000000..d2d6fbd911b70a3dec2b7e42bcde3d3703347ec9 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/cloud_journal.py @@ -0,0 +1,178 @@ +"""Durable submit receipts for the comparison runner; no automatic POST retry. + +Uses the framework's HTTP plumbing. A lost create response is ambiguous: retain +the credit reservation and require reconciliation instead of buying a new task. +The runner holds one batch lock while using this client. +""" +from __future__ import annotations + +import json +import math +import os +from pathlib import Path +from typing import Any + +from models.common import cloud_api +from pipeline.common.record_paths import portable_value, portable_text + + +def read_json(path: Path, default=None): + return json.loads(path.read_text(encoding="utf-8")) if path.is_file() else default + + +def write_json(path: Path, value: Any, *, portable: bool = True) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + temporary = path.with_name(path.name + ".tmp") + with temporary.open("w", encoding="utf-8", newline="\n") as stream: + json.dump(portable_value(value, path.parent) if portable else value, + stream, ensure_ascii=False, indent=2) + stream.write("\n") + stream.flush() + os.fsync(stream.fileno()) + os.replace(temporary, path) + + +def safe_error(exc: Exception) -> str: + value = str(exc) + for name in ("MESHY_API_KEY", "TRIPO_API_KEY"): + secret = os.environ.get(name) + if secret: + value = value.replace(secret, "[REDACTED]") + return portable_text(value)[:1600] + + +class BudgetExceeded(RuntimeError): + pass + + +class AmbiguousSubmission(RuntimeError): + pass + + +def reserved_credits(directory: Path) -> int: + return sum( + int(item["reserved_credits"]) + for path in directory.glob("*.json") + for item in read_json(path, {}).get("submissions", {}).values() + if item["status"] != "rejected" + ) + + +class JournalClient: + """Replay successful create receipts and query the same remote task on resume.""" + + def __init__(self, base: str, key: str, journal: Path, cap: int, + prices: dict[str, int], provider: str, transport=None, resume_refused=False): + self.journal = journal + self.cap = cap + self.prices = prices + self.provider = provider + self.resume_refused = resume_refused + # GET is safe to retry. A billed POST gets exactly one transport attempt. + self.reader = transport or cloud_api.CloudAPIClient(base, key, max_retries=3) + self.writer = transport or cloud_api.CloudAPIClient(base, key, max_retries=0) + self.public = None + + def _cost(self, endpoint: str, body: dict) -> int: + if endpoint == "/files": + return 0 + if self.provider == "meshy": + if endpoint == "/openapi/v2/text-to-3d": + return self.prices["text_refine" if body.get("mode") == "refine" else "text_preview"] + if endpoint == "/openapi/v1/image-to-3d": + return self.prices["image"] + elif endpoint in ("/generation/text-to-model", "/generation/image-to-model"): + return self.prices["text" if "text-to" in endpoint else "image"] + raise ValueError(f"Unpriced POST endpoint: {endpoint}") + + def request(self, method: str, endpoint: str, **kwargs): + state = read_json(self.journal, {"submissions": {}, "results": {}}) + if method != "POST": + result = self.reader.request(method, endpoint, **kwargs) + if method == "GET" and isinstance(result, dict): + state["results"][endpoint] = result + payload = result.get("data", result) + if isinstance(payload, dict): + remote_id = payload.get("task_id") or payload.get("id") + reported = payload.get("credits_consumed", payload.get("credits")) + for record in state["submissions"].values(): + if remote_id and record.get("remote_id") == remote_id and isinstance(reported, (int, float)): + record["reported_credits"] = reported + record["reserved_credits"] = max(record["reserved_credits"], math.ceil(reported)) + write_json(self.journal, state) + return result + + # Hash binary inputs; never persist image bytes or credentials in receipts. + descriptor = {"endpoint": endpoint, "body": kwargs.get("json_body"), + "files": {name: cloud_api.bytes_hash(value[1]) + for name, value in (kwargs.get("files") or {}).items()}} + fingerprint = cloud_api.request_hash(descriptor) + previous = state["submissions"].get(fingerprint) + if previous: + if previous["status"] == "created": + return previous["response"] + if previous["status"] == "rejected" and not (self.resume_refused and previous.get("resource_refusal")): + raise cloud_api.CloudAPIRequestError(previous["error"]) + if previous["status"] != "rejected": + raise AmbiguousSubmission( + f"Unconfirmed submission {fingerprint} in {self.journal}. " + "Reconcile its remote task ID; no automatic resubmission.") + + cost = self._cost(endpoint, kwargs.get("json_body") or {}) + used = reserved_credits(self.journal.parent) + if used + cost > self.cap: + raise BudgetExceeded(f"{self.provider}: {used} reserved + {cost} exceeds cap {self.cap}") + record = {"endpoint": endpoint, "reserved_credits": cost, "status": "submitting"} + if previous: + record["rejection_history"] = [*previous.get("rejection_history", []), + {k: v for k, v in previous.items() if k != "rejection_history"}] + state["submissions"][fingerprint] = record + write_json(self.journal, state) # commit before the request can incur a charge + try: + response = self.writer.request(method, endpoint, **kwargs) + except cloud_api.CloudAPIError as exc: + # These are explicit refusals. 5xx/timeouts may have created a task. + if exc.status in (400, 401, 402, 403, 404, 405, 413, 415, 422, 429): + record.update(status="rejected", error=safe_error(exc), resource_refusal=isinstance( + exc, (cloud_api.CloudAPIAuthError, cloud_api.CloudAPIQuotaError, cloud_api.CloudAPIRateLimitError))) + else: + record.update(status="uncertain", error=safe_error(exc)) + write_json(self.journal, state) + if record["status"] == "uncertain": + raise AmbiguousSubmission(f"Unconfirmed POST {fingerprint}; {safe_error(exc)}") from exc + raise + + rejected = isinstance(response, dict) and response.get("code") not in (None, 0) + envelope = response.get("data", response) if isinstance(response, dict) else {} + remote_id = (envelope.get("task_id") or envelope.get("id") or envelope.get("result") + or envelope.get("file_token") or envelope.get("token")) if isinstance(envelope, dict) else None + if rejected: + rejection = cloud_api.classify_http_error(400, response) + record.update(status="rejected", error=safe_error(rejection), resource_refusal=isinstance( + rejection, (cloud_api.CloudAPIAuthError, cloud_api.CloudAPIQuotaError))) + elif not remote_id: + record.update(status="uncertain", error="Response contained no remote task/file ID") + else: + record.update(status="created", remote_id=remote_id, response=response) + write_json(self.journal, state) + if rejected: + raise rejection + if record["status"] == "uncertain": + raise AmbiguousSubmission(f"Unconfirmed POST {fingerprint}: missing task/file ID") + return response + + def download(self, url: str, **kwargs) -> bytes: + # Signed CDN downloads must not receive the provider's Authorization key. + if not url.startswith("https://"): + raise ValueError("Artifact download must use HTTPS") + if self.public is None: + self.public = cloud_api.CloudAPIClient("", "", max_retries=3) + self.public.session.headers.pop("Authorization", None) + return self.public.download(url, **kwargs) + + def close(self): + self.reader.close() + if self.writer is not self.reader: + self.writer.close() + if self.public is not None: + self.public.close() diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/generate_3d_comparison.py b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/generate_3d_comparison.py new file mode 100644 index 0000000000000000000000000000000000000000..37fd64a94489f8fea40f24af84e5237413a00fc1 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/generate_3d_comparison.py @@ -0,0 +1,603 @@ +#!/usr/bin/env python3 +"""Prepare, run and resume the frozen Meshy/Tripo 200-object comparison. + +Prepare/status are offline. Run requires explicit spending caps and API keys. +Native generation outputs remain unmodified. A shared postprocessor produces +separate import meshes; visual acceptance is a separate review. +""" +from __future__ import annotations + +import argparse +from collections import Counter, defaultdict +from contextlib import contextmanager +from datetime import datetime, timezone +import hashlib +import io +import json +import math +import os +from pathlib import Path +import re +import shutil +import struct +import subprocess +import sys + +BENCH = Path(__file__).resolve().parents[2] +FRAMEWORK = BENCH / "GameFactory-3A" +sys.path.insert(0, str(FRAMEWORK)) +from pipeline.common import paths +from pipeline.common.record_paths import portable_value, resolve_path, runtime_value +from models.common import cloud_api +from models.common.glb_utils import glb_json_chunk, glb_summary +from cloud_journal import (AmbiguousSubmission, BudgetExceeded, JournalClient, + read_json, reserved_credits, safe_error, write_json) + +DEFAULT_CONFIG = BENCH / "config/asset_3d_comparison.json" +IDENTIFIER = re.compile(r"^[A-Za-z0-9][A-Za-z0-9_-]{0,160}$") +RUNTIME_FILES = [Path(__file__), Path(__file__).with_name("cloud_journal.py"), + FRAMEWORK / "pipeline/common/record_paths.py", + FRAMEWORK / "pipeline/common/paths.py", + BENCH / "prompts/stage2_assets.md", + FRAMEWORK / "operators/gen_3d_object/operator.py", + FRAMEWORK / "models/gen_3d_object/meshy_model.py", + FRAMEWORK / "models/gen_3d_object/tripo_model.py", + FRAMEWORK / "models/common/cloud_api.py", + FRAMEWORK / "models/common/glb_utils.py", + Path(__file__).with_name("mesh_tools") / "process_mesh.mjs", + Path(__file__).with_name("mesh_tools") / "package-lock.json"] +MESH_TOOL = Path(__file__).with_name("mesh_tools") / "process_mesh.mjs" + + +def now(): + return datetime.now(timezone.utc).isoformat(timespec="seconds") + + +def digest(path: Path): + return hashlib.sha256(path.read_bytes()).hexdigest() + + +def checked_id(value: str): + if not IDENTIFIER.fullmatch(value): + raise ValueError(f"Invalid path identifier: {value!r}") + return value + + +def bench_path(value: str): + result = resolve_path(value).resolve() + result.relative_to(BENCH.resolve()) + return result + + +def batch_directory(config: dict, batch_id: str): + return bench_path(config["output_root"]) / "_asset_batches" / checked_id(batch_id) + + +@contextmanager +def exclusive_batch(directory: Path): + """OS lock releases on process exit, including an interrupted run.""" + directory.mkdir(parents=True, exist_ok=True) + with (directory / "batch.lock").open("a+b") as stream: + stream.seek(0, 2) + if stream.tell() == 0: + stream.write(b"0") + stream.flush() + stream.seek(0) + if os.name == "nt": + import msvcrt + msvcrt.locking(stream.fileno(), msvcrt.LK_NBLCK, 1) + else: + import fcntl + fcntl.flock(stream, fcntl.LOCK_EX | fcntl.LOCK_NB) + try: + yield + finally: + stream.seek(0) + if os.name == "nt": + msvcrt.locking(stream.fileno(), msvcrt.LK_UNLCK, 1) + else: + fcntl.flock(stream, fcntl.LOCK_UN) + + +def game_directory(plan: dict, game: str): + return Path(plan["output_root"]) / checked_id(game) + + +def pipeline_directory(plan: dict, provider: str, game: str): + return (game_directory(plan, game) / "pipeline" / (game + "_pipeline") + / checked_id(plan["batch_id"]) / checked_id(provider)) + + +def generation_index(plan: dict, provider: str, game: str): + return (game_directory(plan, game) / ".generation/3d_object" / checked_id(provider) + / checked_id(plan["batch_id"]) / "asset_task_index.json") + + +def short_context(text: str, limit: int): + """Declared deterministic excerpts, not a claim that the model read the brief.""" + title = re.search(r"^title:\s*(.+)$", text, re.M) + lines = [line.strip() for line in text.splitlines() if line.strip()] + title_text = title.group(1) if title else next((s.lstrip("# ") for s in lines if s.startswith("#")), "") + world = next((line for line in lines if re.match(r"-\s*W01\b", line)), "") + 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:"))), "") + if not loop: + loop = next((line for line in lines if re.match(r"-\s*S01\b", line)), "") + if not loop: + heading = re.search(r"^##[^\n]*(?:核心循环|一句话定位)[^\n]*\n([^#]+)", text, re.M) + loop = heading.group(1) if heading else "" + pieces = [re.sub(r"\s+", " ", value).strip()[:size] + for value, size in ((title_text, 70), (world, 110), (loop, 110)) if value] + value = " | ".join(pieces) + if not value: + raise ValueError("Cannot extract game context; provide a reviewed short context") + return value[:limit] + + +def frozen_copy(source: Path, destination: Path): + if destination.exists() and digest(destination) != digest(source): + raise ValueError(f"Frozen input changed; use a new batch ID: {destination}") + destination.parent.mkdir(parents=True, exist_ok=True) + if not destination.exists(): + shutil.copyfile(source, destination) + return {"path": str(destination.resolve()), "sha256": digest(destination), + "source": str(source.resolve())} + + +def node_process(arguments: list[str], timeout: int): + node = shutil.which("node") + if not node: + raise ValueError("Node.js is required for the fixed mesh pipeline") + environment = os.environ.copy() + for key in ("MESHY_API_KEY", "TRIPO_API_KEY"): + environment.pop(key, None) + if os.name == "nt": + # Conda's DLLs can shadow sharp's libvips dependencies in child processes. + environment["PATH"] = str(Path(node).parent) + os.pathsep + str(Path(os.environ["SystemRoot"]) / "System32") + return subprocess.run([node, str(MESH_TOOL), *arguments], capture_output=True, + text=True, encoding="utf-8", timeout=timeout, env=environment) + + +def mesh_runtime(): + result = node_process(["--check"], timeout=60) + if result.returncode: + raise ValueError("Mesh postprocessor unavailable; run npm ci in scripts/asset/mesh_tools. " + result.stderr[-500:]) + return json.loads(result.stdout) + + +def subject_group(task: dict): + role = task.get("role", "") + return "character" if task.get("rig", "none") != "none" or role in ( + "character", "player", "event_figure", "npc", "creature", "unit_special") or role.startswith("enemy") else "rigid" + + +def prepare(config: dict, batch_id: str): + if config["input_policy"] != "shared_short_context_and_reference_only" or not config["input_policy_confirmed"]: + raise ValueError("The input protocol must be confirmed before preparing this comparison") + directory = batch_directory(config, batch_id) + plan_file = directory / "plan.json" + if plan_file.exists(): + raise ValueError(f"Batch is already frozen: {plan_file}. Use status/run or a new batch ID.") + source = bench_path(config["tasks"]) + tasks = [json.loads(line) for line in source.read_text(encoding="utf-8-sig").splitlines() if line.strip()] + if len(tasks) != config["expected_tasks"]: + raise ValueError(f"Expected {config['expected_tasks']} tasks; got {len(tasks)}") + for task in tasks: + for provider in config["providers"]: + output = (bench_path(config["output_root"]) / checked_id(task["game_id"]) + / "assets/3d_object" / checked_id(task["task_id"]) / checked_id(provider)) + if output.is_dir() and any(p.name != ".gitkeep" for p in output.iterdir()): + raise ValueError(f"Provider directory already contains assets; resume its batch: {output}") + seen = set() + frozen_tasks = [] + documents = {} + tool_runtime = mesh_runtime() + for task in tasks: + game = checked_id(task["game_id"]) + task_id = checked_id(task["task_id"]) + identity = (game, task_id) + if identity in seen: + raise ValueError(f"Duplicate task: {identity}") + seen.add(identity) + case = BENCH / "test_data/test_samples" / game + if game not in documents: + requirement = case / "general_requirement.txt" + full_text = requirement.read_text(encoding="utf-8") + doc_root = directory / "inputs" / game + documents[game] = { + "general_requirement": frozen_copy(requirement, doc_root / "general_requirement.txt"), + "object_requirement": frozen_copy(case / "3D_object/requirement.txt", doc_root / "object_requirement.txt"), + "context_excerpt": short_context(full_text, config["context_excerpt_max_chars"]), + "context_method": "deterministic title/world/core-loop excerpts; full brief retained locally", + } + mode = task["input_mode"] + prompt = None + reference = None + if mode == "text_to_3d": + # Never shorten the asset prompt. Both providers receive this exact string. + prompt = f"Game context (excerpt): {documents[game]['context_excerpt']}\nAsset: {task['prompt']}" + if len(prompt) > config["shared_prompt_max_chars"]: + raise ValueError(f"Shared prompt exceeds limit: {task_id} ({len(prompt)} chars)") + elif mode == "image_to_3d": + source_image = bench_path(task["image_path"]) + reference = frozen_copy(source_image, directory / "references" / (digest(source_image) + source_image.suffix.lower())) + else: + raise ValueError(f"Unsupported input mode: {mode}") + if not 500 <= task["decimation_target"] <= 8000: + raise ValueError(f"Unexpected triangle target: {task_id}") + frozen_tasks.append({"task": task, "shared_prompt": prompt, "reference": reference, + "subject_group": subject_group(task), + "context_condition": "shared_short_context" if prompt else "reference_only"}) + output_root = bench_path(config["output_root"]) + plan = {"schema_version": "asset_3d_comparison_plan_v1", "batch_id": batch_id, + "created_at": now(), "scope": "3d_object_only_not_complete_stage2", + "config": config, "output_root": str(output_root), "directory": str(directory), + "source": frozen_copy(source, directory / "inputs/source_tasks.jsonl"), + "method_reference": frozen_copy(bench_path(config["method_reference"]), directory / "inputs/method_selection.md"), + "documents": documents, "tasks": frozen_tasks, + "runtime_sources": {str(p.resolve()): digest(p) for p in RUNTIME_FILES}, + "estimated_credits": {}, "recommended_credit_caps": {}, + "qa_policy": "basic structural checks + pending visual review; no automatic acceptance", + "texture_policy": "preserve native output; same deterministic downsize for both import meshes", + "postprocess": config["postprocess"], "mesh_runtime": tool_runtime, + "deferred_providers": {"hunyuan3d_pro": {"status": "not_enabled", "adapter_contract": + "infer_and_save(image, output_path, seed, decimation_target, texture_size, *, prompt); requires pinned cloud version and input capability check"}}} + for provider, settings in config["providers"].items(): + prices = settings["credits"] + estimate = sum((prices["text_preview"] + prices["text_refine"] if provider == "meshy" else prices["text"]) + if item["shared_prompt"] else prices["image"] for item in frozen_tasks) + plan["estimated_credits"][provider] = estimate + plan["recommended_credit_caps"][provider] = (estimate * 11 + 9) // 10 + plan["plan_sha256"] = cloud_api.request_hash(portable_value(plan)) + write_json(plan_file, plan) + write_json(directory / "asset_task_index.json", {"plan_sha256": plan["plan_sha256"], + "task_count": len(frozen_tasks), "tasks": frozen_tasks}) + for provider in config["providers"]: + for game in documents: + write_json(generation_index(plan, provider, game), { + "plan_sha256": plan["plan_sha256"], "game_id": game, "provider": provider, + "scope": plan["scope"], "tasks": [item for item in frozen_tasks if item["task"]["game_id"] == game]}) + refresh_reports(plan) + return plan + + +def load_plan(config: dict, batch_id: str): + plan = read_json(batch_directory(config, batch_id) / "plan.json") + if not plan: + raise ValueError("Prepare this batch first") + claimed = plan["plan_sha256"] + if cloud_api.request_hash({k: v for k, v in plan.items() if k != "plan_sha256"}) != claimed: + raise ValueError("Frozen plan was modified") + return runtime_value(plan) + + +def validate_inputs(plan: dict): + if mesh_runtime() != plan["mesh_runtime"]: + raise ValueError("Mesh runtime differs from the frozen version") + for filename, expected in plan["runtime_sources"].items(): + if digest(Path(filename)) != expected: + raise ValueError(f"Runtime changed after freeze: {filename}; prepare a new batch") + files = [plan["source"], plan["method_reference"]] + files.extend(doc[field] for doc in plan["documents"].values() + for field in ("general_requirement", "object_requirement")) + files.extend(item["reference"] for item in plan["tasks"] if item["reference"]) + for entry in files: + if digest(Path(entry["path"])) != entry["sha256"]: + raise ValueError(f"Frozen input changed: {entry['path']}") + + +def basic_qa(filename: Path, task: dict): + data = filename.read_bytes() + summary = glb_summary(data) + checks = {"parseable_glb": "error" not in summary} + if checks["parseable_glb"]: + doc = glb_json_chunk(data) + checks["glb_v2_exact_length"] = struct.unpack_from(" 0 + checks["textures_present"] = summary["textures"] > 0 and summary["images"] > 0 + primitives = [p for m in doc.get("meshes", []) for p in m.get("primitives", [])] + checks["uv_present"] = bool(primitives) and all("TEXCOORD_0" in p.get("attributes", {}) for p in primitives) + checks["self_contained"] = all("uri" not in b or b["uri"].startswith("data:") for b in doc.get("buffers", [])) and all( + "bufferView" in image or str(image.get("uri", "")).startswith("data:") for image in doc.get("images", [])) + return {"status": "PASS" if all(checks.values()) else "FAIL", "checks": checks, + "summary": summary, "triangle_target": task["decimation_target"], + "requested_texture_size": task.get("texture_size"), + "texture_budget_verified": False, "visual_status": "PENDING", + "limitations": ["No visual, orientation, scale, rigging or engine acceptance yet", + "Native texture resolution retained; task texture_size is not enforced", + "Basic checks do not validate every accessor, topology defect or PBR channel"]} + + +def process_import_mesh(source: Path, task: dict): + destination = source.parent / "import/model.glb" + result = node_process([str(source), str(destination), str(task["decimation_target"]), + str(task["texture_size"])], timeout=300) + if result.returncode: + raise RuntimeError("Postprocessing failed: " + result.stderr[-1200:]) + report = json.loads(result.stdout) + return destination, report + + +def task_directories(plan: dict, provider: str, task: dict): + root = game_directory(plan, task["game_id"]) + task_id, provider = checked_id(task["task_id"]), checked_id(provider) + output = root / "assets/3d_object" / task_id / provider + evaluation = root / "eval/3d_object" / task_id / provider + return output, evaluation + + +def refresh_reports(plan: dict): + summary = {"batch_id": plan["batch_id"], "plan_sha256": plan["plan_sha256"], + "updated_at": now(), "expected_assets": len(plan["tasks"]) * len(plan["config"]["providers"]), + "estimated_credits": plan["estimated_credits"], "providers": {}} + for provider in plan["config"]["providers"]: + by_game = defaultdict(list) + for item in plan["tasks"]: + task = item["task"] + output, evaluation = task_directories(plan, provider, task) + meta = read_json(output / "meta.json", {}) + by_game[task["game_id"]].append({"task_id": task["task_id"], "asset_name": task["asset_name"], + "task_kind": "3d_object", "status": meta.get("status", "prepared"), + "artifact": str(output / "import/model.glb"), "native_artifact": str(output / "model.glb"), + "meta": str(output / "meta.json"), "native_structural_qa": meta.get("native_structural_qa"), + "import_structural_qa": meta.get("import_structural_qa"), + "native_delivered": meta.get("native_delivered", False), + "import_delivered": meta.get("import_delivered", False), + "qa": str(evaluation / "qa.json"), "visual_status": "PENDING", + "context_condition": item["context_condition"], "subject_group": item["subject_group"], + "input_mode": task["input_mode"], "error": meta.get("error")}) + all_entries = [entry for entries in by_game.values() for entry in entries] + summary["providers"][provider] = {"task_count": len(all_entries), + "status_counts": dict(Counter(entry["status"] for entry in all_entries)), + "reserved_credits": reserved_credits(Path(plan["directory"]) / "submissions" / provider), + "visual_accepted": 0, "method_group": plan["config"]["method_group"], + "benchmark_metrics": {name: {"status": "UNKNOWN", "value": None} + for name in ("C", "Q1", "Q2", "Q3")}, + "subgroups": {key: dict(Counter(e[key] for e in all_entries)) + for key in ("subject_group", "input_mode", "context_condition")}, + "game_macro_delivery": sum(sum(e["status"] == "delivered" for e in entries) / len(entries) + for entries in by_game.values()) / len(by_game), + "game_macro_native_delivery": sum(sum(e["native_delivered"] for e in entries) / len(entries) + for entries in by_game.values()) / len(by_game), + "native_structural_pass": sum(e["native_structural_qa"] == "PASS" for e in all_entries), + "import_structural_pass": sum(e["import_structural_qa"] == "PASS" for e in all_entries), + "delivery_metric_status": "NOT_RUN" if all(e["status"] == "prepared" for e in all_entries) else "PARTIAL"} + for game, entries in by_game.items(): + pipeline = pipeline_directory(plan, provider, game) + manifest = {"game_id": game, "provider": provider, "batch_id": plan["batch_id"], + "plan_sha256": plan["plan_sha256"], "scope": plan["scope"], "assets": entries, + "full_context": plan["documents"][game], "status": "pending_visual_review"} + write_json(pipeline / "asset_manifest.json", manifest) + write_json(pipeline / "asset_generation_report.json", { + "task_count": len(entries), "status_counts": dict(Counter(e["status"] for e in entries)), + "failures": [e for e in entries if e["error"]], "visual_accepted": 0}) + paths.write_task_meta(pipeline, {"game_id": game, "task_id": game + "_pipeline", + "task_kind": "pipeline", "run_id": plan["batch_id"], "status": "comparison_only", + "provider": provider, "scope": plan["scope"]}) + write_json(Path(plan["directory"]) / "asset_generation_report.json", summary) + return summary + + +def make_model(plan: dict, provider: str, task: dict, cap: int): + from models.gen_3d_object.meshy_model import MeshyModel + from models.gen_3d_object.tripo_model import TripoModel + settings = plan["config"]["providers"][provider] + cls = MeshyModel if provider == "meshy" else TripoModel + control = Path(plan["directory"]) + model = cls(model_path=settings["model"], device="cpu", api_base=settings["api_base"], + cache_dir=str(control / "cache" / task["game_id"] / task["task_id"]), + timeout=1800, poll_interval=5, **settings["options"]) + key = cloud_api.require_api_key(None, provider.upper() + "_API_KEY", "See the comparison README") + journal = control / "submissions" / provider / (task["game_id"] + "__" + task["task_id"] + ".json") + model._client = JournalClient(settings["api_base"], key, journal, cap, settings["credits"], provider, + resume_refused=True) + return model + + +def download_preview(model, output: Path): + from PIL import Image + url = model.last_call_info.get("preview_url") + if not url: + return {"status": "unavailable"} + try: + data = model.client.download(url) + with Image.open(io.BytesIO(data)) as preview: + preview.verify() + extension = {"PNG": ".png", "JPEG": ".jpg", "WEBP": ".webp"}.get(preview.format) + if not extension: + return {"status": "unsupported_image_format"} + path = output / ("preview" + extension) + path.write_bytes(data) + return {"status": "downloaded", "path": str(path), "visual_review": "PENDING"} + except Exception as exc: + return {"status": "failed", "error": safe_error(exc)} + + +def run(plan: dict, args): + from operators.gen_3d_object.operator import Gen3DObjectOperator + + class SharedStoreOperator(Gen3DObjectOperator): + def _resolve_out_path(self, inp, task_id): + output, _ = task_directories(plan, provider, inp) + output.mkdir(parents=True, exist_ok=True) + return inp["game_id"], output, output / "model.glb" + + if not args.allow_paid: + raise ValueError("Paid generation requires --allow-paid and explicit provider credit caps") + validate_inputs(plan) + selected = list(dict.fromkeys(args.provider or list(plan["config"]["providers"]))) + caps = {p: getattr(args, p + "_credit_cap") for p in selected} + for provider in selected: + if not caps[provider] or caps[provider] < reserved_credits(Path(plan["directory"]) / "submissions" / provider): + raise ValueError(f"Supply a positive --{provider}-credit-cap covering existing reservations") + cloud_api.require_api_key(None, provider.upper() + "_API_KEY", "See scripts/asset/README_3d_comparison.md") + selection = set(args.task_id or []) + known = {item["task"]["task_id"] for item in plan["tasks"]} + if selection - known: + raise ValueError(f"Unknown task IDs: {sorted(selection - known)}") + jobs = [item for item in plan["tasks"] if not selection or item["task"]["task_id"] in selection] + if args.limit is not None: + if args.limit < 1: + raise ValueError("--limit must be positive") + jobs = jobs[:args.limit] + write_json(Path(plan["directory"]) / "spending_authorization.json", { + "plan_sha256": plan["plan_sha256"], "credit_caps": caps, "recorded_at": now(), + "selected_task_ids": [item["task"]["task_id"] for item in jobs], + "note": "Caps reserve estimated credits; account-side limits remain authoritative"}) + interrupted = False + for provider in selected: + failures = 0 + for item in jobs: + task = item["task"] + output, evaluation = task_directories(plan, provider, task) + previous = read_json(output / "meta.json", {}) + if previous and previous.get("plan_sha256") != plan["plan_sha256"]: + raise ValueError(f"Another batch owns this provider directory; do not overwrite: {output}") + if not previous and output.is_dir() and any(p.name != ".gitkeep" for p in output.iterdir()): + raise ValueError(f"Untracked provider artifacts must not be overwritten: {output}") + if previous.get("status") == "delivered" and (output / "model.glb").is_file(): + imported = output / "import/model.glb" + if previous.get("artifact_sha256") == digest(output / "model.glb") and imported.is_file() and previous.get("import_sha256") == digest(imported): + continue + if previous.get("status") == "failed": + continue # one generation attempt, no cherry-picking on rerun + output.mkdir(parents=True, exist_ok=True) + meta = {"game_id": task["game_id"], "task_id": task["task_id"], "asset_name": task["asset_name"], + "task_kind": "3d_object", "run_id": plan["batch_id"], "provider": provider, + "plan_sha256": plan["plan_sha256"], "context_condition": item["context_condition"], + "full_context": plan["documents"][task["game_id"]], "source_task": task, + "shared_prompt": item["shared_prompt"], "reference": item["reference"], + "status": "running", "updated_at": now(), "visual_status": "PENDING"} + write_json(output / "meta.json", meta) + model = None + stop = False + try: + model = make_model(plan, provider, task, caps[provider]) + # Preserve native output for a fair comparison. No automatic mesh cleanup/import. + inp = {**task, "strip_ground_plate": False} + inp.pop("asset_id", None) + if item["reference"]: + inp["image_path"] = item["reference"]["path"] + else: + inp["prompt"] = item["shared_prompt"] + result = SharedStoreOperator(model, run_id=plan["batch_id"]).run(inp) + raw_qa = basic_qa(Path(result["glb_path"]), task) + meta.update(native_delivered=raw_qa["checks"]["parseable_glb"], result=result, + native_structural_qa=raw_qa["status"], model_call=model.last_call_info, + artifact_sha256=digest(output / "model.glb")) + write_json(evaluation / "qa.json", {"native": raw_qa, "import": {"status": "PENDING"}, + "visual_status": "PENDING"}) + imported, postprocess = process_import_mesh(Path(result["glb_path"]), task) + import_qa = basic_qa(imported, task) + import_qa["texture_budget_verified"] = all(max(t["after"]) <= task["texture_size"] for t in postprocess["textures"]) + import_qa["checks"]["texture_budget"] = import_qa["texture_budget_verified"] + import_qa["status"] = "PASS" if all(import_qa["checks"].values()) else "FAIL" + write_json(evaluation / "qa.json", {"native": raw_qa, "import": import_qa, + "postprocess": postprocess, "visual_status": "PENDING"}) + meta.update(status="delivered", result=result, model_call=model.last_call_info, + import_delivered=import_qa["checks"]["parseable_glb"], + artifact_sha256=digest(output / "model.glb"), import_sha256=digest(imported), + native_structural_qa=raw_qa["status"], import_structural_qa=import_qa["status"], + postprocess=postprocess, + preview=download_preview(model, output)) + failures = 0 + except Exception as exc: + status = "failed" + if isinstance(exc, cloud_api.CloudTaskTimeout): + status = "remote_pending" + elif isinstance(exc, AmbiguousSubmission): + status, stop = "submission_uncertain", True + elif isinstance(exc, (BudgetExceeded, cloud_api.CloudAPIAuthError, cloud_api.CloudAPIQuotaError)): + status, stop = "blocked", True + elif isinstance(exc, cloud_api.CloudAPIServerError): + status = "resume_required" # known receipts survive poll/download failures + elif not isinstance(exc, (cloud_api.CloudTaskFailed, cloud_api.CloudAPIRequestError, ValueError)): + status = "resume_required" # retain a downloaded asset after local/tool failures + meta.update(status=status, error=safe_error(exc), error_type=type(exc).__name__) + failures += 1 + stop = stop or failures >= 3 + finally: + if model is not None: + model.unload() + meta["updated_at"] = now() + journal = read_json(Path(plan["directory"]) / "submissions" / provider / + (task["game_id"] + "__" + task["task_id"] + ".json"), {}) + meta["generation_cost"] = [{"endpoint": record["endpoint"], "remote_id": record.get("remote_id"), + "reservation": record["reserved_credits"], "reported_credits": record.get("reported_credits"), + "status": record["status"]} for record in journal.get("submissions", {}).values()] + write_json(output / "meta.json", meta) + refresh_reports(plan) + print(json.dumps({"provider": provider, "task_id": task["task_id"], "status": meta["status"], + "error": meta.get("error")}, ensure_ascii=False), flush=True) + if stop: + interrupted = True + break + if interrupted: + break + incomplete = any(read_json(task_directories(plan, p, item["task"])[0] / "meta.json", {}).get("status") != "delivered" + for p in selected for item in jobs) + return 2 if interrupted or incomplete else 0 + + +def recover(plan: dict, args): + """Attach an inspected remote ID to an ambiguous receipt; never submit here.""" + checked_id(args.remote_task_id) + matches = [item["task"] for item in plan["tasks"] if item["task"]["task_id"] == args.task_id] + if len(matches) != 1: + raise ValueError("Recover requires exactly one known task") + task = matches[0] + journal = Path(plan["directory"]) / "submissions" / args.provider / (task["game_id"] + "__" + task["task_id"] + ".json") + state = read_json(journal, {}) + record = state.get("submissions", {}).get(args.request_hash) + if not record or record["status"] not in ("submitting", "uncertain") or record["endpoint"] == "/files": + raise ValueError("Receipt is not an ambiguous generation submission") + record.update(status="created", remote_id=args.remote_task_id, reconciled_at=now(), + response={"result": args.remote_task_id} if args.provider == "meshy" else + {"code": 0, "data": {"task_id": args.remote_task_id}}) + write_json(journal, state) + return {"recovered_task_id": args.remote_task_id, "network_requests": 0} + + +def main(argv=None): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--config", type=Path, default=DEFAULT_CONFIG) + sub = parser.add_subparsers(dest="command", required=True) + for name in ("prepare", "status", "run", "recover"): + command = sub.add_parser(name) + command.add_argument("--batch-id", required=True) + if name == "run": + command.add_argument("--allow-paid", action="store_true") + command.add_argument("--meshy-credit-cap", type=int) + command.add_argument("--tripo-credit-cap", type=int) + command.add_argument("--provider", action="append", choices=("meshy", "tripo")) + command.add_argument("--task-id", action="append") + command.add_argument("--limit", type=int, help="Limit tasks per selected provider; full inventory is retained") + elif name == "recover": + command.add_argument("--provider", required=True, choices=("meshy", "tripo")) + command.add_argument("--task-id", required=True) + command.add_argument("--request-hash", required=True) + command.add_argument("--remote-task-id", required=True) + args = parser.parse_args(argv) + config = read_json(args.config) + with exclusive_batch(batch_directory(config, args.batch_id)): + if args.command == "prepare": + plan = prepare(config, args.batch_id) + print(json.dumps(portable_value({"plan": str(Path(plan["directory"]) / "plan.json"), + "tasks_per_provider": len(plan["tasks"]), "estimated_credits": plan["estimated_credits"], + "recommended_credit_caps": plan["recommended_credit_caps"]}), indent=2)) + else: + plan = load_plan(config, args.batch_id) + if args.command == "run": + return run(plan, args) + value = recover(plan, args) if args.command == "recover" else refresh_reports(plan) + print(json.dumps(portable_value(value), indent=2, ensure_ascii=False)) + return 0 + + +if __name__ == "__main__": + try: + raise SystemExit(main()) + except (ValueError, OSError, cloud_api.CloudAPIError) as exc: + print(safe_error(exc), file=sys.stderr) + raise SystemExit(2) diff --git a/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/package-lock.json b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/package-lock.json new file mode 100644 index 0000000000000000000000000000000000000000..070ddb648ed455c400b216bf2bc6e6ac1df75912 --- 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b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/process_mesh.mjs new file mode 100644 index 0000000000000000000000000000000000000000..557990005845f673eb56da1e4dbf7f4309f7f7df --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/obj200_meshy_tripo_20261015_v2/delivery/runtime/bench/scripts/asset/mesh_tools/process_mesh.mjs @@ -0,0 +1,77 @@ +// One fixed pipeline for both services; keep the original GLB separately. +import {readFileSync, mkdirSync} from 'node:fs'; +import {dirname} from 'node:path'; +import {performance} from 'node:perf_hooks'; +import {NodeIO, Logger} from '@gltf-transform/core'; +import {ALL_EXTENSIONS} from '@gltf-transform/extensions'; +import {simplify, weld} from '@gltf-transform/functions'; +import {MeshoptDecoder, MeshoptSimplifier} from 'meshoptimizer'; +import draco from 'draco3dgltf'; +import sharp from 'sharp'; + +const settings = JSON.parse(readFileSync(new URL('./package.json', import.meta.url))); +await Promise.all([MeshoptDecoder.ready, MeshoptSimplifier.ready]); +const runtime = {node: process.versions.node, dependencies: settings.dependencies}; +if (process.argv[2] === '--check') { + console.log(JSON.stringify({status: 'ready', ...runtime})); +} else { + const [source, destination, triangleArg, textureArg] = process.argv.slice(2); + const triangleTarget = Number(triangleArg), textureTarget = Number(textureArg); + if (!source || !destination || !Number.isInteger(triangleTarget) || triangleTarget <= 0 + || !Number.isInteger(textureTarget) || textureTarget <= 0) { + throw new Error('Expected: source.glb destination.glb triangle_target texture_size'); + } + const started = performance.now(); + const io = new NodeIO().registerExtensions(ALL_EXTENSIONS).registerDependencies({ + 'draco3d.decoder': await draco.createDecoderModule(), + 'meshopt.decoder': MeshoptDecoder, + }); + const document = await io.read(source); + document.setLogger(new Logger(Logger.Verbosity.SILENT)); + // The decoded import GLB is not dependent on the provider's mesh codec. + for (const extension of document.getRoot().listExtensionsUsed()) { + if (['KHR_draco_mesh_compression', 'EXT_meshopt_compression'].includes(extension.extensionName)) { + extension.dispose(); + } + } + function triangleCount() { + let count = 0; + for (const mesh of document.getRoot().listMeshes()) { + for (const primitive of mesh.listPrimitives()) { + if (primitive.getMode() !== 4) throw new Error('Only triangle primitives are supported'); + const n = (primitive.getIndices() || primitive.getAttribute('POSITION')).getCount(); + count += n / 3; + } + } + return count; + } + const before = triangleCount(); + if (before > triangleTarget) { + await document.transform(weld(), simplify({simplifier: MeshoptSimplifier, + ratio: triangleTarget / before, error: 0.01, lockBorder: false})); + } + const textures = []; + for (const texture of document.getRoot().listTextures()) { + const image = texture.getImage(); + if (!image) throw new Error('Texture has no decoded image'); + const input = Buffer.from(image); + const info = await sharp(input).metadata(); + let sizeAfter = [info.width, info.height]; + if (Math.max(...sizeAfter) > textureTarget) { + const {data, info: resized} = await sharp(input).resize({width: textureTarget, height: textureTarget, + fit: 'inside', withoutEnlargement: true, kernel: 'lanczos3'}).png({compressionLevel: 9}).toBuffer({resolveWithObject: true}); + texture.setImage(new Uint8Array(data)).setMimeType('image/png').setURI(''); + sizeAfter = [resized.width, resized.height]; + } + textures.push({name: texture.getName(), before: [info.width, info.height], after: sizeAfter}); + } + const after = triangleCount(); + mkdirSync(dirname(destination), {recursive: true}); + await io.write(destination, document); + console.log(JSON.stringify({status: after <= triangleTarget ? 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b/outputs/G056_garden_minigolf/.generation/3d_object/tripo/obj200_meshy_tripo_20261015_v2/asset_task_index.json new file mode 100644 index 0000000000000000000000000000000000000000..289abe8e9b16723b9202be377493f08febed9eb0 --- /dev/null +++ b/outputs/G056_garden_minigolf/.generation/3d_object/tripo/obj200_meshy_tripo_20261015_v2/asset_task_index.json @@ -0,0 +1,52 @@ +{ + "plan_sha256": "5c287b8399f00fbb0dddf94c9e3f5ffcbcc2e679ff76882bc8fc369d6eae840d", + "game_id": "G056_garden_minigolf", + "provider": "tripo", + "scope": "3d_object_only_not_complete_stage2", + "tasks": [ + { + "task": { + "game_id": "G056_garden_minigolf", + "task_id": "G056_garden_minigolf_obj_002", + "asset_name": "golf_ball", + "name_zh": "高尔夫球", + "role": "prop", + "input_mode": "text_to_3d", + "prompt": "Single dimpled golf ball with a soft pearl sheen, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "seed": 1562, + "decimation_target": 3000, + "texture_size": 1024, + "rig": "none", + "animation_strategy": "procedural", + "spec_ref": "L01", + "poly_policy": "low_poly_priority" + }, + "shared_prompt": "Game context (excerpt): 漂浮花园的迷你高尔夫 | - W01 世界与时代背景：架空云海时代的「浮屿花园」——园艺师们在漂浮于云海的花屿上经营三洞试炼球场，庆祝春分的推杆大会今夜开杆。 | - S01 类型：3D 俯视迷你高尔夫（单人杆数制）。本测例包含的能力：三洞冻结球场、蓄力击球物理、坡面反弹摩擦、瞄准线与轨迹残影反馈、界外复位与罚杆、双镜头模式、开场/结算视频。\nAsset: Single dimpled golf ball with a soft pearl sheen, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "reference": null, + "subject_group": "rigid", + "context_condition": "shared_short_context" + }, + { + "task": { + "game_id": "G056_garden_minigolf", + "task_id": "G056_garden_minigolf_obj_003", + "asset_name": "hole_flag", + "name_zh": "球洞与旗杆", + "role": "prop", + "input_mode": "text_to_3d", + "prompt": "Miniature golf hole cup with a slender striped pennant flag and a subtle glow rim, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "seed": 1563, + "decimation_target": 6000, + "texture_size": 2048, + "rig": "none", + "animation_strategy": "procedural", + "spec_ref": "L01", + "poly_policy": "low_poly_priority" + }, + "shared_prompt": "Game context (excerpt): 漂浮花园的迷你高尔夫 | - W01 世界与时代背景：架空云海时代的「浮屿花园」——园艺师们在漂浮于云海的花屿上经营三洞试炼球场，庆祝春分的推杆大会今夜开杆。 | - S01 类型：3D 俯视迷你高尔夫（单人杆数制）。本测例包含的能力：三洞冻结球场、蓄力击球物理、坡面反弹摩擦、瞄准线与轨迹残影反馈、界外复位与罚杆、双镜头模式、开场/结算视频。\nAsset: Miniature golf hole cup with a slender striped pennant flag and a subtle glow rim, clean stylized, game-ready, PBR textures, low-poly style, minimal triangle count, flat faceted surfaces, clean silhouette, no fine surface detail", + "reference": null, + "subject_group": "rigid", + "context_condition": "shared_short_context" + } + ] +} diff --git a/outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_002/meshy/import/model.glb b/outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_002/meshy/import/model.glb new file mode 100644 index 0000000000000000000000000000000000000000..f08363b9a0bbd691adb6ba5d5065f880462d2326 --- /dev/null +++ b/outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_002/meshy/import/model.glb @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b372e23d31a7a03c5786287763a588246082ce9a61d1b0d917ee1f108a25dba0 +size 1097568 diff --git a/outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_002/meshy/meta.json b/outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_002/meshy/meta.json new file mode 100644 index 0000000000000000000000000000000000000000..95c4bbe0906e2042260fa3d6886a42a8af134ac5 --- /dev/null +++ b/outputs/G056_garden_minigolf/assets/3d_object/G056_garden_minigolf_obj_002/meshy/meta.json @@ 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