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

scripts/test_jp_flow.py

@@ -0,0 +1,76 @@
+# -*- coding: utf-8 -*-
+"""JP 流程测试：JPTM001 黑色 × 2 个产品（缓存热点模式）。
+
+步骤：
+1) 用 mock 种子（6 style + 6 related）生成 JP 主题简报（JP-market 模板装配）→ 写入 output/JP/design_briefs.json 作为缓存
+2) run_product_batch：tasks=[JPTM001-BL01 × 2]，count=2 → 2 个产品各绑一个热点
+3) 验证：选色/热点分配/used 去重/JP 标题模板路由/模板导出
+"""
+import json
+import sys
+import time
+from pathlib import Path
+
+BASE = Path(__file__).resolve().parent.parent
+sys.path.insert(0, str(BASE))
+
+import yaml
+from graph.templates import assemble_prompts
+
+config = yaml.safe_load(open(BASE / "config.yaml", encoding="utf-8"))
+# 种子词 6 个
+config["seed_provider"] = "mock"
+cfg = config.setdefault("seed_provider_cfg", {})
+cfg["max_style_seeds"] = 6
+cfg["max_related_seeds"] = 6
+# 图像后端 mock、不上传图床
+config["compose"]["backend"] = "mock"
+config["product"]["backend"] = "mock"
+config["oss"]["enabled"] = False
+config["seed_shot"]["count"] = 1
+
+jp_topics = [
+    ("kawaii cat cafe", "Style", "original kawaii cat with latte art", "kawaii style, soft rounded shapes", "pink, cream, caramel", "centered mascot"),
+    ("tokyo neon night", "Style", "original neon street lamps silhouette", "retro cyberpunk flat vector", "magenta, cyan, black", "symmetrical emblem"),
+    ("shiba inu summer", "Style", "original shiba inu with watermelon slice", "cute japanese mascot illustration", "orange, red, white", "centered"),
+    ("sakura spring", "Style", "original cherry blossom branch with petals", "soft minimal japanese print", "sakura pink, white, mint", "corner flourish"),
+    ("osaka takoyaki food", "Style", "original takoyaki balls with bonito flakes", "playful food illustration", "golden brown, red, green", "centered badge"),
+    ("mt fuji sunrise", "Style", "original mt fuji with rising sun rays", "ukiyo-e inspired flat design", "indigo, red, cream", "symmetrical"),
+]
+tpls = config.get("prompt_templates") or {}
+briefs = []
+for topic, cat, motif, style, palette, comp in jp_topics:
+    prompts = assemble_prompts(motif, style, palette, comp, tpls, "JP")
+    briefs.append({
+        "country": "JP", "topic": topic, "design_category": cat, "risk_level": "safe",
+        "score": 80 - len(briefs) * 3, "motif": motif, "art_style": style,
+        "color_palette": palette, "composition": comp,
+        "image_prompt": prompts["image_prompt"],
+        "composite_prompt": prompts["composite_prompt"],
+        "composite_negative": prompts["composite_negative"],
+    })
+
+out_dir = BASE / "output" / "JP"
+out_dir.mkdir(parents=True, exist_ok=True)
+(out_dir / "design_briefs.json").write_text(
+    json.dumps({"generated_at": time.strftime("%Y-%m-%dT%H:%M:%S"), "total": len(briefs),
+                "design_briefs": briefs}, ensure_ascii=False, indent=2), encoding="utf-8")
+print(f"[setup] JP 缓存热点已写入: {len(briefs)} 条（mock 种子 6/6）")
+p0 = briefs[0]["image_prompt"]
+print("[setup] 模板校验: JP-market 风格段 =", "JP-market" in p0, "| 尺寸上限 26x32 =", "26x32" in p0)
+
+from graph.product_batch import run_product_batch
+
+tasks = [{"spu": "JPTM001", "skus": "JPTM001-BL01"},   # 黑色
+         {"spu": "JPTM001", "skus": "JPTM001-BL01"}]   # 数量 2：同一款号生成 2 个产品
+out = run_product_batch("JP", config, BASE, BASE, tasks, 2, log_q=None)
+print("\n=== 测试结果 ===")
+prods = out.get("product") or []
+print("产品数:", len(prods))
+for r in prods:
+    print(f"  {r.get('spu_code')} | {r.get('sku_code')} | 色={r.get('color')} | topic={r.get('topic')} | "
+          f"template={bool(r.get('template_path'))} | design={bool(r.get('design_path'))}")
+print("errors:", [e.get("message", "")[:80] for e in out.get("errors") or []])
+
+used = json.loads((out_dir / "used_designs.json").read_text(encoding="utf-8")).get("used", []) if (out_dir / "used_designs.json").exists() else []
+print("used_designs 记录:", len(used), "条 →", [u.get("topic") for u in used])