3218485270
b7f429db89
1) 模板导出：识别「基码表-胸围」填 sku.bust（多个胸围列都填）；申报价格模糊匹配多列统一按加价后价格填写；详情图文不再拼接 img_url_2；SPU 款式来源统一填「现货款」；商品产地国家简称映射（沙特→沙特阿拉伯） 2) 模特性别分组：model_features 按男女分组，按模板类目含男/女固定取对应性别模特（含 Pinterest 模式 pipeline） 3) 三合一提示词：去掉 DESIGN CONTENT 四要素描述（设计已由设计稿提供） 4) 生图尺寸：全部改为读 config 不再硬编码（设计图 compose.design_size / 合成图 compose.size / 种草图 seed_shot.size）
237 lines
9.9 KiB
Python
237 lines
9.9 KiB
Python
"""构建并编译 LangGraph，提供 run_country() 入口。
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图结构（线性流水线，节点全部带兜底）：
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START -> seed -> fetch -> filter -> score -> screen -> prompt_build
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-> compose（生成纯印花设计稿 + 导出简报）-> product（底图/模特/三图合成/模板）
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-> oss_upload（压缩 3:4 / ≥1340×1785 / <2MB + 上传阿里云 OSS）-> END
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"""
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import time
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from pathlib import Path
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from typing import Any, Dict, Optional
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from langgraph.graph import END, StateGraph
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from graph.loader import build_country_config
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from graph.nodes import (
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compose_node,
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fetch_node,
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filter_node,
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oss_upload_node,
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product_node,
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prompt_node,
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score_node,
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screen_node,
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seed_node,
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seed_shot_node,
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template_export_node,
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)
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from graph.state import AgentState
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def build_graph():
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"""构建 StateGraph 并编译。"""
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builder = StateGraph(AgentState)
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builder.add_node("seed", seed_node)
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builder.add_node("fetch", fetch_node)
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builder.add_node("filter", filter_node)
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builder.add_node("score", score_node)
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builder.add_node("screen", screen_node)
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builder.add_node("prompt_build", prompt_node)
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builder.add_node("product", product_node)
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builder.add_node("compose", compose_node)
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builder.add_node("oss_upload", oss_upload_node)
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builder.add_node("seed_shot", seed_shot_node)
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builder.add_node("template_export", template_export_node)
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builder.add_edge("__start__", "seed")
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builder.add_edge("seed", "fetch")
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builder.add_edge("fetch", "filter")
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builder.add_edge("filter", "score")
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builder.add_edge("score", "screen")
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builder.add_edge("screen", "prompt_build")
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builder.add_edge("prompt_build", "compose") # compose：生成纯印花设计稿（放前面）
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builder.add_edge("compose", "product") # product：底图/模特/三图合成/模板
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builder.add_edge("product", "oss_upload") # oss_upload：压缩 + 上传图床
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builder.add_edge("oss_upload", "seed_shot") # seed_shot：种草图生成（模板+模特特征 yaml）→ 上传
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builder.add_edge("seed_shot", "template_export") # template_export：最终结果导入商品上传模板
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builder.add_edge("template_export", END)
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return builder.compile()
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def _pinterest_route(state: Dict[str, Any]) -> str:
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"""图池路由：简报达标 → done；图池还有未消费图片 → analyze（继续分析，不搜索）；
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图池不足 → search（新一轮搜索）；轮次耗尽 → done。"""
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target = int(state.get("pinterest_target") or 0)
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if target <= 0:
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target = 1
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briefs = state.get("briefs") or []
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rounds = int(state.get("pinterest_rounds") or 0)
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terms = state.get("pinterest_search_terms") or []
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pcfg = (state.get("config") or {}).get("pinterest") or {}
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max_rounds = int(pcfg.get("max_search_rounds") or 0)
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if max_rounds <= 0:
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max_rounds = max(target * 2, 5)
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if len(briefs) >= target:
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print(f"[pinterest_route] 简报已达目标 {len(briefs)}/{target}，结束")
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return "done"
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# 图池还有未消费图片 → 继续分析（不搜索）
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try:
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from graph.pinterest import load_image_pool, load_used_images, pool_unused_images
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pool = load_image_pool(str(state.get("output_dir") or ""), state.get("country") or "")
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used = load_used_images(str(state.get("output_dir") or ""), state.get("country") or "")
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unused = pool_unused_images(pool, used)
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except Exception: # noqa: BLE001
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unused = []
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if unused:
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print(f"[pinterest_route] 图池还有 {len(unused)} 张未消费图片，继续分析（简报 {len(briefs)}/{target}）")
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return "analyze"
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# 图池不足 → 搜索
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if rounds >= max_rounds:
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print(f"[pinterest_route] 已达最大轮次 {max_rounds}，简报 {len(briefs)}/{target}，按现有结果继续")
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return "done"
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if not terms and rounds > 0:
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print(f"[pinterest_route] 无可用搜索词，停止搜索（简报 {len(briefs)}/{target}）")
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return "done"
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print(f"[pinterest_route] 图池不足，新一轮搜索（第 {rounds} 轮，简报 {len(briefs)}/{target}）")
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return "search"
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def build_pinterest_graph():
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"""Pinterest 参考模式图（按需搜索循环 + 简报池并发生成）：
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pinterest_init（建简报池）→ pinterest_search → pinterest_scrape → pinterest_analyze
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→ [pinterest_route] 简报不足 → 回到 pinterest_search；达标 → pinterest_finalize
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（排空简报池、后台并发生成 设计→三合一→OSS→种草图）→ template_export
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"""
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from graph.nodes import (
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pinterest_analyze_node,
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pinterest_scrape_node,
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pinterest_search_node,
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)
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from graph.nodes.pinterest_finalize_node import pinterest_finalize_node
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from graph.nodes.pinterest_init_node import pinterest_init_node
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builder = StateGraph(AgentState)
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builder.add_node("pinterest_init", pinterest_init_node)
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builder.add_node("pinterest_search", pinterest_search_node)
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builder.add_node("pinterest_scrape", pinterest_scrape_node)
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builder.add_node("pinterest_analyze", pinterest_analyze_node)
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builder.add_node("pinterest_finalize", pinterest_finalize_node)
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builder.add_node("template_export", template_export_node)
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builder.add_edge("__start__", "pinterest_init")
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builder.add_edge("pinterest_init", "pinterest_search")
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builder.add_edge("pinterest_search", "pinterest_scrape")
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builder.add_edge("pinterest_scrape", "pinterest_analyze")
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builder.add_conditional_edges("pinterest_analyze", _pinterest_route, {
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"analyze": "pinterest_analyze", # 图池还有未消费图片 → 继续分析（不搜索）
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"search": "pinterest_search", # 图池不足 → 新一轮搜索
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"done": "pinterest_finalize", # 简报达标/轮次耗尽 → 收尾（排空简报池）
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})
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builder.add_edge("pinterest_finalize", "template_export")
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builder.add_edge("template_export", END)
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return builder.compile()
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def run_country(
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country: str,
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global_config: Dict[str, Any],
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project_root: Path,
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output_root: Optional[Path] = None,
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base_image: Optional[str] = None,
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task_timestamp: Optional[str] = None,
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) -> Dict[str, Any]:
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"""运行单个国家的完整流水线，返回最终 state（含 errors / stats / briefs）。
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project_root：数据文件根（configs / prompts，打包后为 _MEIPASS 只读目录）。
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output_root ：产物输出根（默认=project_root；打包后传 exe 旁运行目录，
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避免把 output/ 写进临时解压目录导致重启丢失）。
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task_timestamp：任务时间戳（每次点击运行 = 一个任务）；None 时自动生成。
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"""
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compiled = build_graph()
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cc = build_country_config(global_config, country, project_root)
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prompts_dir = project_root / "prompts" / country
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cache_dir = (output_root or project_root) / "output" / country # 缓存/去重（根目录）
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ts = task_timestamp or time.strftime("%Y%m%d_%H%M%S")
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_base = ts
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_i = 1
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while (cache_dir / ts).exists(): # 时间戳文件夹唯一（同秒多任务防冲突/覆盖）
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ts = f"{_base}_{_i}"
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_i += 1
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output_dir = cache_dir / ts # 本次任务产物（时间戳文件夹）
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state: Dict[str, Any] = {
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"country": country,
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"config": global_config,
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"country_config": cc,
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"prompts_dir": str(prompts_dir),
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"cache_dir": str(cache_dir),
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"output_dir": str(output_dir),
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"raw_rows": [],
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"filtered_rows": [],
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"scored_rows": [],
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"screened": [],
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"briefs": [],
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"composite": [],
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"designs": [],
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"errors": [],
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"stats": {},
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"task_timestamp": ts, # 任务开始时间戳（OSS 路径段 / 产物文件夹名）
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"oss_seq": 0, # 货号计数（000 起，最多 999）
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}
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if base_image:
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state["base_image"] = base_image
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result = compiled.invoke(state)
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return result
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def run_pinterest_ref(
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country: str,
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global_config: Dict[str, Any],
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project_root: Path,
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output_root: Optional[Path] = None,
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task_timestamp: Optional[str] = None,
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) -> Dict[str, Any]:
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"""Pinterest 参考模式入口：独立于 Google Trends 的完整流程。
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种子词 → LLM 搜索词（json_schema + 动态注入防重复）→ 爬图 → LLM 分析图片
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→ 设计简报 → 设计稿 → 产品图 → 上传 → 种草图 → 模板导出。
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参数语义与 run_country 一致（project_root=数据根，output_root=产物根）。
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"""
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compiled = build_pinterest_graph()
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cc = build_country_config(global_config, country, project_root)
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prompts_dir = project_root / "prompts" / country
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cache_dir = (output_root or project_root) / "output" / country
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ts = task_timestamp or time.strftime("%Y%m%d_%H%M%S")
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_base = ts
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_i = 1
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while (cache_dir / ts).exists(): # 时间戳文件夹唯一（同秒多任务防冲突/覆盖）
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ts = f"{_base}_{_i}"
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_i += 1
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output_dir = cache_dir / ts
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state: Dict[str, Any] = {
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"country": country,
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"config": global_config,
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"country_config": cc,
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"prompts_dir": str(prompts_dir),
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"cache_dir": str(cache_dir),
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"output_dir": str(output_dir),
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"briefs": [],
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"composite": [],
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"designs": [],
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"errors": [],
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"stats": {},
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"task_timestamp": ts,
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"oss_seq": 0,
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# 按需搜索目标：简报数 = spu_tasks 数量（每款一个设计）；无任务时回退 spu_count/1
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"pinterest_target": len((global_config.get("product") or {}).get("spu_tasks") or [])
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or int((global_config.get("product") or {}).get("spu_count") or 0) or 1,
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"pinterest_rounds": 0,
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"pinterest_attempted": [],
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}
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return compiled.invoke(state)
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