POD 趋势感知 Agent：缓存热点模式 + 三图合成 + 热点去重/风格去重 + review 兜底
- 缓存热点批量流程（有采集缓存不触发 Google） - 简报不足直接从采集缓存生成（轻量补齐） - 三图合成（模特/印花/底图）+ 底图压缩 <2MB - 热点去重→风格去重自动切换 + 不适合类目 review 兜底 - 透明背景（background=transparent）+ 提示词清洗（敏感词/背景描述） - 任务前 basemap 校验 + 模板国家校验 + 模特任务级分配
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"""节点 6.5：产品图生成（product）。
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在 prompt_build 之后、compose 之前运行（prompt_build → product → compose）：
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热点提示词 → SPU/颜色选品 → basemap 底图 → 纯印花设计稿 → 模特试穿合成图。
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产物写入 output/<country>/product/（底图拷贝 / *_design.png / *_model / *_composite.png / products.json）。
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模板选择按 SPU.mark 驱动：
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mark==1 → 新三图合成模板 MODEL_WEAR_PROMPT（图1=模特实拍 / 图2=纯印花设计 / 图3=平铺底图）
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mark!=1 → 旧两图合成模板 composite_prompt（底图 + 印花设计 → 平铺服装图）
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配置（config.yaml product 段）：
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enabled 开关（默认 true）
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db_path SPU/SKU 数据库（默认 db/spu_sku.db，相对路径按运行根解析）
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basemap_dir 底图目录（默认 basemap）
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material_library_dir 模特图库（默认 material_library）
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model_category 模特品类子目录（T-shirt）；为空/无图时取 material_library 第一个有图子目录
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brief_index 用第几个 safe 简报的提示词（0=第一个）
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spu_code / sku_code 指定款号/颜色编码（留空自动选第一个有本地底图的）
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spu_tasks [{"spu": "DG004", "skus": "DG004-BL01,..."}] 多款号批量选品（优先于 spu_code）
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spu_count 款号数量上限（0=不限；取任务清单前 N 个）
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spu_per_color true=每颜色一个 SPU 块；false=单 SPU 下挂所有颜色 SKU 变体
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backend 图像后端：openai(真生图,需 key) / mock(占位) / 留空=跳过生成仅存底图
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缺底图/模特图时跳过对应步骤并提示，不中断流水线；多款号逐个处理，单个失败不影响其它。
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"""
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import json
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import random
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import shutil
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import threading
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import time
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from graph.paths import project_root, runtime_root
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from graph.product import (
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find_basemap,
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find_first_model_folder,
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first_available_sku,
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list_colors,
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list_spus,
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)
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from graph.validate import with_fallback
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_USED_LOCK = threading.Lock() # used_designs.json 并发写锁
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_MODEL_LOCK = threading.Lock() # 同款共用模特缓存并发锁
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_MODEL_CACHE: Dict[str, Any] = {} # 同款共用模特：spu_code → model 路径
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def _next_img_idx(prod_dir: Path, prefix: str) -> int:
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"""货号续号：扫 prod_dir 已有 {prefix}{数字}* 文件，返回下一个起始序号（不覆盖旧产物）。"""
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import re
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max_n = -1
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try:
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if prod_dir.exists():
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for f in prod_dir.iterdir():
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m = re.match(rf"{re.escape(prefix)}(\d+)", f.stem)
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if m:
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max_n = max(max_n, int(m.group(1)))
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except Exception: # noqa: BLE001
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pass
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return max_n + 1
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MODEL_WEAR_PROMPT = (
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"你是一个专业的电商AI视觉合成工具，执行“高保真印花与色彩移植/印花替换”:把图2的印花设计印到图3的衣服底图上，"
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"并让图1的模特穿上这件带有图2印花设计的图3底图衣服。\n"
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"【图片角色,按提交顺序,不要弄反】\n"
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"第一张图(图1)=模特实拍图(基底,要被替换衣服图案和颜色的目标区域,保留原有背景/人物/光影)；\n"
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"第二张图(图2)=纯印花设计稿(要印上去的图案内容,忽略其背景环境与无关元素,保留图案原始线条与色号)；\n"
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"第三张图(图3)=平铺衣服底图(只提取衣服本身的底色与面料材质;忽略平铺图的背景、桌面、环境、场景阴影等一切与衣服无关的元素,只保留衣服面料的颜色、质感和纹理)。\n"
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"最终效果为图1的模特穿着一件“颜色为图3底色、印有图2图案”的衣服。\n"
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"【执行规则】\n"
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"1.底色锁定:从图3平铺衣服中提取衣服底色与面料属性,该底色在最终合成中必须100%保持不变,"
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"严禁偏色、混入图1原衣服颜色或图2背景色。\n"
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"2.印花提取与叠加:从图2中精准提取纯印花图案主体,保留原始线条、色号、比例关系;"
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"将印花叠加到图3底色衣服上,形成“图3底色+图2印花”的合成面料。\n"
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"3.印花尺寸适配:印花的整体尺寸必须与衣服(图3)的面料面积成合理比例——"
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"居中印在胸/背/衣身的主体区域,占衣身面积约30%-45%,四周保留自然留白与衣摆、领口、肩线余量;"
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"严禁印花过大(撑满整件衣服、溢出领口袖口下摆)或过小(占比低于20%)。\n"
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"4.主体识别与遮罩:识别图1模特的服装穿着区域,忽略皮肤、头发、背景、配饰;"
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"将该区域视为“空白画布”,用上述合成面料(图3底色+图2印花)完整覆盖。图1原有衣服颜色与图案全部清除。\n"
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"5.精准贴合:合成面料严格跟随图1衣服的立体结构——有褶皱、身体扭转时印花相应变形;"
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"印花与新底色须“沉入”褶皱中,保留布料原有明暗纹理与物理属性,杜绝“贴纸感”与“平面涂色感”。\n"
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"6.光影融合:提取图1的环境光方向,调整合成面料的亮度/对比度与环境光匹配;"
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"图3底色在阴影区须自然变暗,在高光区须有布料反光;印花色彩受环境光影响产生相应明暗变化,但色号本身不偏移。\n"
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"7.纯净输出:仅输出一张最终合成图;严禁文字/水印/额外装饰;"
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"图1原本的背景、人物、构图及光影结构100%不变,仅替换图1衣服上的印花图案与衣服底色。"
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)
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def _resolve_sku(db_path, basemap_root, spu_code: str, sku_code: str, colors=None) -> Optional[str]:
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"""选定 SKU：显式指定优先；否则第一个有本地底图的；再无则第一个颜色（便于模板导出）。"""
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if sku_code:
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return sku_code
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s = first_available_sku(db_path, basemap_root, spu_code)
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if s:
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return s
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if colors:
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return colors[0]["sku_code"]
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return None
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def _template_out_path(prod_dir: Path, chosen_sku: str) -> Path:
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"""模板输出路径：默认 {sku}_已填写.xlsx；若文件被其它程序占用（如已打开），自动换名加序号，避免导出失败。"""
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base = prod_dir / f"{chosen_sku}_已填写.xlsx"
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try:
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with open(base, "ab"):
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pass
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return base
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except OSError:
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pass
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for i in range(2, 100):
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cand = prod_dir / f"{chosen_sku}_已填写_{i}.xlsx"
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if not cand.exists():
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return cand
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return prod_dir / f"{chosen_sku}_已填写_{int(time.time())}.xlsx"
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def _retry_image(fn, *args, attempts: int = 3, backoff=(5, 20, 40), **kwargs):
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"""图像合成带退避重试（网关超载/超时常见）：成功返回 out_path；全部失败返回 None。"""
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import time as _t
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last = None
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for i in range(attempts):
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try:
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return fn(*args, **kwargs)
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except Exception as e: # noqa: BLE001
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last = e
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if i < attempts - 1:
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_t.sleep(backoff[i])
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print(f"[product] 图像合成重试 {attempts} 次均失败: {last}")
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return None
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def _process_spu(
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db_path, basemap_root, material_root, category, prod_dir, brief, ib,
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spu, sku_code, pcfg, errors, shared_design=None, title_backend=None, country="",
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img_code="", model_img=None,
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) -> Optional[Dict[str, Any]]:
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"""处理单个款号：选色 → 底图 → 设计稿 → (mark==1) 模特 → 合成 → 模板导出。
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shared_design: compose 节点生成的纯印花设计稿路径（图2）；为 None 时回退本节点 generate。
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img_code: 货号（前缀+3位计数）；本产品所有图片文件归入 prod_dir/{img_code}/ 子文件夹
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（按货号命名，包含该货号对应的所有图片）。
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返回 result dict；内部异常已兜底，不中断。
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"""
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# 输出目录 = 货号子文件夹（product/DG000/…），该货号所有图片都放这里
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prod_dir = prod_dir / img_code
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prod_dir.mkdir(parents=True, exist_ok=True)
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colors = list_colors(db_path, spu["code"])
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valid_codes = {c["sku_code"] for c in colors}
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if sku_code:
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sku_codes = [s.strip() for s in sku_code.split(",") if s.strip() and s.strip() in valid_codes]
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if not sku_codes:
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print(f"[product] 颜色 {sku_code!r} 均不在款号 {spu['code']} 下，可选: {[c['sku_code'] for c in colors]}")
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return None
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else:
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first = _resolve_sku(db_path, basemap_root, spu["code"], "", colors)
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if first is None:
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print(f"[product] 款号 {spu['code']} 无颜色数据，可选: {[c['sku_code'] for c in colors]}")
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return None
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sku_codes = [first]
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# 模板模式自动判定（UI 不再选择）：单色=每色一SPU；多色=单SPU多色；CLI --single-spu 显式覆盖
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spu_per_color = pcfg.get("spu_per_color")
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if spu_per_color is None:
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spu_per_color = len(sku_codes) <= 1
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else:
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spu_per_color = bool(spu_per_color)
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chosen_sku = sku_codes[0] # 生图用第一个颜色
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tag = f"[product/{img_code or chosen_sku}]" # 日志前缀用货号（DG000），失败/进度一眼定位
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basemap_img = find_basemap(basemap_root, spu["code"], chosen_sku)
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if basemap_img is None:
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print(f"{tag} 底图缺失（{basemap_root}/{spu['code']}/{chosen_sku}/），将跳过印花/模特，仅导出模板")
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result: Dict[str, Any] = {
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"spu_code": spu["code"],
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"sku_code": chosen_sku,
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"color": next((c["color"] for c in colors if c["sku_code"] == chosen_sku), ""),
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"topic": brief.get("topic", ""),
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"art_style": brief.get("art_style", ""),
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"color_palette": brief.get("color_palette", ""),
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"basemap": str(basemap_img) if basemap_img else "",
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"composite_prompt": brief.get("composite_prompt", ""),
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"markup_percent": pcfg.get("markup_percent", 0), # 加价%（后续定价用）
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}
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# 拷贝底图（图3）：命名 = 货号 + SKU code（如 DG003_DG004-BL01_basemap.jpg），
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# 同一 SKU 多个设计（数量 N）时底图文件也各自独立，不覆盖、不混淆
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if basemap_img is not None:
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base_copy = prod_dir / f"{img_code}_{chosen_sku}_basemap{basemap_img.suffix}"
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shutil.copy2(basemap_img, base_copy)
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result["basemap_copy"] = str(base_copy)
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print(f"{tag} 底图: {base_copy}")
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if ib is None:
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print(f"{tag} 未配置 product.backend（openai/mock），跳过印花/模特生成。")
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elif basemap_img is None:
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print(f"{tag} 无底图，跳过印花/模特生成。")
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else:
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# 5) 纯印花设计稿（图2）：直接用 compose 节点生成的共享设计稿（designs/ 已有，不拷贝）
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if shared_design and Path(shared_design).exists():
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design_path = shared_design
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result["design_path"] = design_path
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result["design_from"] = "compose"
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print(f"{tag} 设计稿（来自 compose 节点，designs/ 已有）: {design_path}")
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else:
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design_path = str(prod_dir / f"{img_code}_design.png")
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try:
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from graph.style_rules import sanitize_image_prompt, ensure_rebrand_hint
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prompt = ensure_rebrand_hint(brief, sanitize_image_prompt(brief.get("image_prompt", "")))
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ib.generate(prompt, design_path,
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brief.get("composite_negative", ""),
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size="1024x1024") # 印花设计统一 1024x1024
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result["design_path"] = design_path
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result["design_from"] = "product"
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print(f"{tag} 纯印花设计稿已生成（product 节点）: {design_path}")
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except Exception as e: # noqa: BLE001
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errors.append({"node": "product", "type": type(e).__name__, "message": f"设计稿生成失败: {e}", "trace": ""})
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print(f"{tag} 设计稿生成失败: {e}")
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# 6) 模板选择按 SPU.mark 决定：
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# mark==1 → 新三图合成模板 MODEL_WEAR_PROMPT（图1模特 + 图2印花设计 + 图3底图）
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# mark!=1 → 旧两图合成模板 composite_prompt（底图 + 印花设计）
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if int(spu.get("mark") or 0) == 1:
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print(f"{tag} SPU {spu['code']} mark=1 → 使用三图合成模板（图1模特+图2印花+图3底图）")
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if model_img is not None:
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# 任务级模特分配（product_node 预分配：一个 SPU 一个模特，SPU 数>模特数循环兜底）
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model_copy = prod_dir / f"{img_code}_model{model_img.suffix}"
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shutil.copy2(model_img, model_copy)
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result["model_path"] = str(model_copy)
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result["model_folder"] = model_img.parent.name
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print(f"{tag} 模特图（任务级分配，{model_img.parent.name}/）: {model_copy}")
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else:
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print(f"{tag} material_library 无模特图，回退两图合成（composite_prompt）")
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else:
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print(f"{tag} SPU {spu['code']} mark={spu.get('mark')} → 使用两图合成模板 composite_prompt（底图+印花）")
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# 7) 合成：
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# 有模特图 → 三图合成（图1=模特 / 图2=印花设计 / 图3=底图）
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# 无模特图 → 两图合成平铺服装图（图3=底图 + 图2=印花设计）
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if "design_path" not in result:
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print(f"{tag} 无设计稿，跳过合成")
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elif model_img is not None:
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composite_path = str(prod_dir / f"{img_code}_composite.png")
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try:
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# 三图合成：优先用简报的 composite_prompt（模板化三图文案），回退内置 MODEL_WEAR_PROMPT
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wear_prompt = (brief.get("composite_prompt") or "").strip() or MODEL_WEAR_PROMPT
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print(f"{tag} 三图合成提交中（3 参考图 img2img，网关处理约 2-6 分钟，请耐心等待）…")
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t0 = time.time()
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ib.print(wear_prompt, str(model_img), composite_path,
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brief.get("composite_negative", ""),
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extra_images=[design_path, str(basemap_img)], # 图2印花, 图3底图
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size="1504x2000") # 三合一统一 1504x2000
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result["composite_path"] = composite_path
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print(f"{tag} 三图模特合成图已生成（耗时 {int(time.time()-t0)}s）: {composite_path}")
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except Exception as e: # noqa: BLE001
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# 合成失败 → 带退避重试（网关超载/超时常见，重试 3 次）
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print(f"{tag} 三图合成失败，退避重试…: {e}")
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retried = _retry_image(ib.print, wear_prompt, str(model_img), composite_path,
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brief.get("composite_negative", ""),
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extra_images=[design_path, str(basemap_img)], size="1504x2000")
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if retried is not None:
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result["composite_path"] = composite_path
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||||
print(f"{tag} 三图合成重试成功（耗时 {int(time.time()-t0)}s）: {composite_path}")
|
||||
else:
|
||||
errors.append({"node": "product", "type": type(e).__name__, "message": f"模特合成失败(重试仍失败): {e}", "trace": ""})
|
||||
print(f"{tag} 三图合成重试仍失败 → 跳过该产品（不生成标题/不写模板）: {e}")
|
||||
return None
|
||||
else:
|
||||
printed_path = str(prod_dir / f"{img_code}_printed.png")
|
||||
try:
|
||||
# 两图合成（无模特）：用平铺印图文案（wearable_prompt），回退旧 composite_prompt
|
||||
flat_prompt = (brief.get("wearable_prompt") or "").strip() or brief.get("composite_prompt", "")
|
||||
ib.print(flat_prompt, str(basemap_img), printed_path,
|
||||
brief.get("composite_negative", ""),
|
||||
extra_images=[design_path], # 图2印花
|
||||
size="1504x2000") # 合成统一 1504x2000
|
||||
result["printed_path"] = printed_path
|
||||
print(f"{tag} 平铺服装图已生成（无模特，底图+印花）: {printed_path}")
|
||||
except Exception as e: # noqa: BLE001
|
||||
print(f"{tag} 平铺服装图失败，退避重试…: {e}")
|
||||
retried = _retry_image(ib.print, flat_prompt, str(basemap_img), printed_path,
|
||||
brief.get("composite_negative", ""),
|
||||
extra_images=[design_path], size="1504x2000")
|
||||
if retried is not None:
|
||||
result["printed_path"] = printed_path
|
||||
print(f"{tag} 平铺服装图重试成功: {printed_path}")
|
||||
else:
|
||||
errors.append({"node": "product", "type": type(e).__name__, "message": f"平铺服装图生成失败(重试仍失败): {e}", "trace": ""})
|
||||
print(f"{tag} 平铺服装图重试仍失败 → 跳过该产品（不生成标题/不写模板）: {e}")
|
||||
return None
|
||||
|
||||
# 7.2) 多色：单 SPU 多色时每个颜色再执行一次三合一（用各自底图），轮播图按颜色路由
|
||||
color_composites: List[Dict[str, Any]] = []
|
||||
if model_img is not None and result.get("composite_path"):
|
||||
# 首色主图始终记录（单色/多色都走模板填充）
|
||||
color_composites.append({"sku_code": chosen_sku, "color": result.get("color", ""),
|
||||
"composite_path": result["composite_path"]})
|
||||
for sc in sku_codes[1:]:
|
||||
bm = find_basemap(basemap_root, spu["code"], sc)
|
||||
if bm is None:
|
||||
print(f"{tag} 颜色 {sc} 无底图，跳过该色三合一")
|
||||
continue
|
||||
cp = str(prod_dir / f"{img_code}_{str(sc).split('-')[-1]}_composite.png")
|
||||
try:
|
||||
ib.print(MODEL_WEAR_PROMPT, str(model_img), cp,
|
||||
brief.get("composite_negative", ""),
|
||||
extra_images=[design_path, str(bm)], # 图2印花, 图3该色底图
|
||||
size="1504x2000") # 三合一统一 1504x2000
|
||||
col = next((c["color"] for c in colors if c["sku_code"] == sc), sc)
|
||||
color_composites.append({"sku_code": sc, "color": col, "composite_path": cp})
|
||||
print(f"{tag} 颜色 {sc}（{col}）三合一已生成: {cp}")
|
||||
except Exception as e: # noqa: BLE001
|
||||
errors.append({"node": "product", "type": type(e).__name__,
|
||||
"message": f"颜色 {sc} 三合一失败: {e}", "trace": ""})
|
||||
result["color_composites"] = color_composites
|
||||
|
||||
# 7.5) 多模态标题生成：合成图/平铺图/设计稿 → 中英双语 SEO 标题（按国家路由模板）
|
||||
if title_backend is not None:
|
||||
title_img = (result.get("composite_path") or result.get("printed_path")
|
||||
or result.get("design_path"))
|
||||
if title_img:
|
||||
t = title_backend.generate_title(title_img, country=country)
|
||||
if t.get("en_title") or t.get("cn_title") or t.get("ja_title"):
|
||||
result["en_title"] = t.get("en_title", "")
|
||||
result["cn_title"] = t.get("cn_title", "")
|
||||
result["ja_title"] = t.get("ja_title", "")
|
||||
print(f"{tag} 标题已生成: EN={t.get('en_title','')[:50]}... "
|
||||
f"CN={t.get('cn_title','')[:30]}... JA={t.get('ja_title','')[:30]}...")
|
||||
|
||||
return result
|
||||
|
||||
|
||||
@with_fallback("product")
|
||||
def product_node(state: Dict[str, Any]) -> Dict[str, Any]:
|
||||
config = state["config"]
|
||||
pcfg = config.get("product") or {}
|
||||
stats = dict(state.get("stats") or {})
|
||||
if not pcfg.get("enabled", True):
|
||||
return {"product": [], "stats": stats}
|
||||
|
||||
country = state["country"]
|
||||
briefs = state.get("briefs") or []
|
||||
output_dir = Path(state["output_dir"]) # 本次任务产物（时间戳文件夹）
|
||||
cache_dir = Path(state.get("cache_dir") or output_dir) # 缓存/去重（根目录）
|
||||
errors = list(state.get("errors") or [])
|
||||
|
||||
# 路径解析：相对路径 → 优先运行根（exe 旁自定义数据），其次数据根（打包=_MEIPASS 内置）
|
||||
def _abs(key: str, default: str) -> Path:
|
||||
p = Path(pcfg.get(key, default))
|
||||
if p.is_absolute():
|
||||
return p
|
||||
for root in (runtime_root(), project_root()):
|
||||
cand = root / p
|
||||
if cand.exists():
|
||||
return cand
|
||||
return project_root() / p
|
||||
|
||||
db_path = _abs("db_path", "db/spu_sku.db")
|
||||
basemap_root = _abs("basemap_dir", "basemap")
|
||||
material_root = _abs("material_library_dir", "material_library")
|
||||
category = pcfg.get("model_category", "T-shirt")
|
||||
brief_index = int(pcfg.get("brief_index", 0))
|
||||
spu_code = (pcfg.get("spu_code") or "").strip()
|
||||
sku_code = (pcfg.get("sku_code") or "").strip()
|
||||
spu_tasks = pcfg.get("spu_tasks") or []
|
||||
spu_count = int(pcfg.get("spu_count") or 0)
|
||||
|
||||
# 1) 选简报（优先 safe）
|
||||
safe = [b for b in briefs if b.get("risk_level") == "safe"] or briefs
|
||||
if not safe:
|
||||
print("[product] 无可用简报，跳过产品图生成")
|
||||
return {"product": [], "stats": stats}
|
||||
brief = safe[brief_index] if brief_index < len(safe) else safe[0]
|
||||
|
||||
# 2) 图像后端
|
||||
backend_name = (pcfg.get("backend") or "").strip()
|
||||
ib = None
|
||||
if backend_name:
|
||||
from graph.backends import get_image_backend
|
||||
ib = get_image_backend(backend_name)
|
||||
if ib is not None:
|
||||
ib.bind_config(config.get("compose") or {}) # 复用 compose.api_key/model/size
|
||||
|
||||
# 3) 构造款号工作清单：spu_tasks（多款号）优先；否则 spu_code / 自动第一个
|
||||
spus = list_spus(db_path)
|
||||
worklist: List[tuple] = [] # (spu, skus, brief) —— 每个款号可绑定自己的热点简报
|
||||
by_topic = {str(b.get("topic", "")).lower(): b for b in briefs}
|
||||
if not spus:
|
||||
print(f"[product] db 无 SPU 数据（{db_path}），跳过")
|
||||
return {"product": [], "stats": stats}
|
||||
if spu_tasks:
|
||||
for ti, t in enumerate(spu_tasks):
|
||||
code = (t.get("spu") or t.get("spu_code") or "").strip()
|
||||
spu = next((s for s in spus if s["code"] == code), None)
|
||||
if spu is None:
|
||||
print(f"[product] 任务款号 {code} 不在 db，跳过（可选: {[s['code'] for s in spus][:12]}）")
|
||||
continue
|
||||
tb = None
|
||||
tp = (t.get("topic") or "").strip()
|
||||
if tp:
|
||||
tb = by_topic.get(tp.lower())
|
||||
if tb is None:
|
||||
print(f"[product] 任务热点「{tp}」不在简报中，回退按序号分配")
|
||||
if tb is None:
|
||||
# 未指定热点（完整流水线）：按任务序号取不同简报，避免多个产品用同一个
|
||||
idx = min(ti, len(safe) - 1) if safe else brief_index
|
||||
tb = safe[idx] if safe else None
|
||||
if tb is None:
|
||||
print(f"[product] 无可用简报，跳过任务 {code}")
|
||||
continue
|
||||
worklist.append((spu, (t.get("skus") or "").strip(), tb))
|
||||
if not worklist:
|
||||
print("[product] 任务清单无有效款号，跳过产品图生成")
|
||||
return {"product": [], "stats": stats}
|
||||
elif spu_code:
|
||||
spu = next((s for s in spus if s["code"] == spu_code), None)
|
||||
if spu is None:
|
||||
print(f"[product] 款号 {spu_code} 不在 db，可选: {[s['code'] for s in spus][:12]}")
|
||||
return {"product": [], "stats": stats}
|
||||
worklist.append((spu, sku_code, brief))
|
||||
else:
|
||||
spu = next((s for s in spus if first_available_sku(db_path, basemap_root, s["code"])), None)
|
||||
if spu is None:
|
||||
print(f"[product] 没有任何款号存在本地底图（{basemap_root}/<款号>/<SKU.code>/）")
|
||||
return {"product": [], "stats": stats}
|
||||
worklist.append((spu, sku_code, brief))
|
||||
|
||||
# 4) 不再按 spu_count 截断：worklist 已是扩展后的完整任务（数量 N = 每款设计数），
|
||||
# 全部任务进入队列处理（并发 5）。
|
||||
|
||||
prod_dir = output_dir / "product"
|
||||
prod_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# 4.1) 任务级模特分配（material_library-<category>）：
|
||||
# 一个 SPU 对应一个模特；SPU（不同款）数 > 模特数 → 从全部模特循环兜底（允许重复）
|
||||
model_assign: Dict[str, Any] = {}
|
||||
_all_models: List[str] = []
|
||||
try:
|
||||
_folder, _all_models = find_first_model_folder(material_root, category)
|
||||
except Exception: # noqa: BLE001
|
||||
_all_models = []
|
||||
if _all_models:
|
||||
seen_spu: Dict[str, str] = {}
|
||||
for _i, (_spu, _skus, _tb) in enumerate(worklist):
|
||||
code = _spu.get("code", "")
|
||||
if code not in seen_spu:
|
||||
seen_spu[code] = _all_models[_i % len(_all_models)] # SPU>模特数 → 循环兜底
|
||||
model_assign[code] = seen_spu[code]
|
||||
print(f"[product] 任务级模特分配：{len(seen_spu)} 个 SPU，模特池 {len(_all_models)} 张"
|
||||
f"{'（SPU>模特，循环兜底）' if len(seen_spu) > len(_all_models) else ''}")
|
||||
|
||||
# 5) compose 节点生成的共享设计稿（图2）：每个任务用自己的热点简报设计（tb.design_path），
|
||||
# 一个货号对应一个设计（多颜色共用该设计），不再所有产品共用第一个
|
||||
designs_dir = output_dir / "designs"
|
||||
designs_dir.mkdir(parents=True, exist_ok=True)
|
||||
designs_map = {str(d.get("topic", "")).strip().lower(): d.get("path", "")
|
||||
for d in (state.get("designs") or []) if isinstance(d, dict)}
|
||||
for _d in (state.get("briefs") or []):
|
||||
if isinstance(_d, dict) and _d.get("design_path"):
|
||||
designs_map.setdefault(str(_d.get("topic", "")).strip().lower(), _d.get("design_path"))
|
||||
|
||||
def _resolve_design(tb) -> Optional[str]:
|
||||
"""任务绑定的简报 → 该热点自己的设计稿路径（按货号命名拷贝到 designs/）。"""
|
||||
topic = str(tb.get("topic", "")).strip().lower()
|
||||
src = designs_map.get(topic) or tb.get("design_path")
|
||||
if not src or not Path(src).exists():
|
||||
return None
|
||||
return src
|
||||
|
||||
# 6) 逐个款号处理（每款号用自己绑定的热点简报）
|
||||
title_backend = None
|
||||
ls_cfg = config.get("llm_screen") or {}
|
||||
if (ls_cfg.get("provider") or "") not in ("", "mock"):
|
||||
try:
|
||||
from graph.llms import get_backend as _glb
|
||||
_tb = _glb(ls_cfg.get("provider"))
|
||||
_tb.bind_config(ls_cfg)
|
||||
if _tb.has_key:
|
||||
title_backend = _tb
|
||||
except Exception as e: # noqa: BLE001
|
||||
print(f"[product] 标题后端初始化失败: {e}")
|
||||
|
||||
results: List[Dict[str, Any]] = []
|
||||
prefix = str(pcfg.get("code_prefix") or "DG").strip()
|
||||
# 并发：默认每个 SPU 一个独立线程（任务数即并发数，提速）；
|
||||
# config.product.concurrency 显式配置可覆盖（如限流时设 3-5）；
|
||||
# 默认并发上限 5：全量并发（任务数）会压垮图像网关（10 并发 → 全部超时），
|
||||
# 超出上限的任务在线程池排队，逐批处理
|
||||
concurrency = int(pcfg.get("concurrency") or 0) or min(len(worklist), 5)
|
||||
print(f"[product] 并发 {concurrency}（每 SPU 一线程，上限 {concurrency}）处理 {len(worklist)} 个产品任务")
|
||||
|
||||
def _run_one(idx: int, spu, skus, tb):
|
||||
"""并发执行单个产品：返回 (result or None, img_code)。失败由 _process_spu 内部兜底。"""
|
||||
img_code = f"{prefix}{idx:03d}" # 货号：图片按此命名（DG000_design.png…）
|
||||
try:
|
||||
# 每个任务用自己的热点设计（designs_map），并拷贝为货号命名（designs/DG000_design.png）
|
||||
design_src = _resolve_design(tb)
|
||||
design_path = None
|
||||
if design_src:
|
||||
design_path = str(designs_dir / f"{img_code}_design.png")
|
||||
try:
|
||||
shutil.copy2(design_src, design_path)
|
||||
except Exception: # noqa: BLE001
|
||||
design_path = design_src
|
||||
tb = dict(tb)
|
||||
tb["design_path"] = design_path
|
||||
r = _process_spu(db_path, basemap_root, material_root, category, prod_dir,
|
||||
tb, ib, spu, skus, pcfg, errors, design_path, title_backend,
|
||||
country, img_code=img_code,
|
||||
model_img=model_assign.get(spu.get("code", "")))
|
||||
if r:
|
||||
r["img_code"] = img_code
|
||||
return r, img_code
|
||||
except Exception as e: # noqa: BLE001 # 单产品任何异常都不拖垮整体
|
||||
print(f"[product/{img_code}] 产品处理异常（跳过该产品）: {e}")
|
||||
return None, img_code
|
||||
|
||||
import concurrent.futures
|
||||
# 货号自动续号：任务一开始全部按序分配（start_idx 起），不覆盖已生成的产物
|
||||
start_idx = _next_img_idx(prod_dir, prefix)
|
||||
with concurrent.futures.ThreadPoolExecutor(max_workers=concurrency) as ex:
|
||||
futures = [ex.submit(_run_one, start_idx + i, spu, skus, tb)
|
||||
for i, (spu, skus, tb) in enumerate(worklist)]
|
||||
for f in concurrent.futures.as_completed(futures):
|
||||
r, img_code = f.result()
|
||||
if r:
|
||||
results.append(r)
|
||||
try:
|
||||
_record_used(cache_dir, r) # (热点-风格) 去重记录 → 缓存根目录
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
|
||||
results.sort(key=lambda x: x.get("img_code", "")) # 按货号排序，模板/清单顺序稳定
|
||||
_write_products(prod_dir, results)
|
||||
stats["product"] = {
|
||||
"spus": [r.get("spu_code") for r in results],
|
||||
"skus": [r.get("sku_code") for r in results],
|
||||
"topic": brief.get("topic", ""),
|
||||
"count": len(results),
|
||||
"composite": sum(1 for r in results if r.get("composite_path")),
|
||||
"printed": sum(1 for r in results if r.get("printed_path")),
|
||||
"templates": sum(1 for r in results if r.get("template_path")),
|
||||
"output_dir": str(prod_dir),
|
||||
}
|
||||
return {"product": results, "stats": stats, "errors": errors}
|
||||
|
||||
|
||||
def _record_used(output_dir: Path, r: Dict[str, Any]):
|
||||
"""记录已用 (热点-风格-配色)，供后续去重：output/<国家>/used_designs.json。"""
|
||||
topic = r.get("topic", "")
|
||||
if not topic:
|
||||
return
|
||||
with _USED_LOCK: # 并发下 used_designs.json 读写互斥
|
||||
p = output_dir / "used_designs.json"
|
||||
used = []
|
||||
if p.exists():
|
||||
try:
|
||||
used = json.loads(p.read_text(encoding="utf-8")).get("used", []) or []
|
||||
except Exception:
|
||||
used = []
|
||||
entry = {
|
||||
"topic": topic,
|
||||
"art_style": r.get("art_style", ""),
|
||||
"color_palette": r.get("color_palette", ""),
|
||||
"spu_code": r.get("spu_code", ""),
|
||||
"sku_code": r.get("sku_code", ""),
|
||||
"date": time.strftime("%Y-%m-%d"),
|
||||
}
|
||||
# 同 (topic, art_style) 已记录则跳过，避免去重记录重复堆积
|
||||
if any(str(u.get("topic", "")).strip().lower() == str(entry["topic"]).strip().lower()
|
||||
and str(u.get("art_style", "")).strip().lower() == str(entry["art_style"]).strip().lower()
|
||||
for u in used):
|
||||
return
|
||||
used.append(entry)
|
||||
p.write_text(json.dumps(
|
||||
{"updated_at": time.strftime("%Y-%m-%dT%H:%M:%S"), "used": used},
|
||||
ensure_ascii=False, indent=2), encoding="utf-8")
|
||||
|
||||
|
||||
def _write_products(prod_dir: Path, products: List[Dict[str, Any]]):
|
||||
(prod_dir / "products.json").write_text(
|
||||
json.dumps({"generated_at": time.strftime("%Y-%m-%dT%H:%M:%S"), "products": products},
|
||||
ensure_ascii=False, indent=2), encoding="utf-8")
|
||||
Reference in New Issue
Block a user