v89-v91 模板增强 + 图源映射 + 多模态提示词可配置化

- 图源映射统一：热点采集与 Pinterest 模式均走 config.product.mark_dirs 配置，按任务序号随机抽模特图/平铺图
- 商品产地固定：统一为「中国大陆」+「产地省份=广东省」（不再读站点/字典映射）
- 模板 SKU 字段检测：按建议售价同一套路检测 SKU分类/SKU数量/SKU数量单位，必填时填入单品/1/件
- 多模态分析提示词可配置：prompts/pinterest_analyze_system.md + user.md，支持国家覆盖，不丢文件回退内置
- 自定义图片模式：新增 pinterest_custom_load_node，图片数量硬校验，选品清单 ≤ 有效图片数
- 模板导出优化：写入前按货号末 3 位升序排序，不再产生空白 xlsx
- 修复 v90 project review 10 项（503 致命终止、线程安全、原子写入等）

graph/nodes/pinterest_search_node.py

@@ -33,6 +33,8 @@ def pinterest_search_node(state: Dict[str, Any]) -> Dict[str, Any]:
 
     provider = str(pcfg.get("provider") or "openai").strip().lower()
     search_mode = str(pcfg.get("search_mode") or "direct").strip().lower()
+    _raw_suffix = str(pcfg.get("search_term_suffix") if pcfg.get("search_term_suffix") is not None else " t-shirt design").strip()
+    suffix = _raw_suffix if _raw_suffix else ""   # 配置留空则后缀为空（不追加），不再回退默认
     want = int(pcfg.get("search_terms_per_run", 1))   # 每次搜索词数量
     seed_sample = int(pcfg.get("seed_sample", 40))
     max_used_in_prompt = int(pcfg.get("max_used_terms_in_prompt", 100))
@@ -57,9 +59,9 @@ def pinterest_search_node(state: Dict[str, Any]) -> Dict[str, Any]:
         fresh = [s for s in pool if s.lower() not in used_set]
         if not fresh:
             fresh = pool   # 库内词全部用过 → 允许复用（词库有限）
-        terms = [f"{s} t-shirt design" if "t-shirt design" not in s.lower() else s
+        terms = [f"{s} {suffix}".strip() if suffix and suffix not in s.lower() else s
                  for s in random.sample(fresh, min(want, len(fresh)))]
-        print(f"[pinterest_search] direct 模式：国家种子词库随机抽 {len(terms)} 个 + t-shirt design（{country}）")
+        print(f"[pinterest_search] direct 模式：国家种子词库随机抽 {len(terms)} 个 + 后缀「{suffix}」（{country}）")
     else:
         used_llm = merge_used(used, attempted)
         if max_used_in_prompt > 0:
@@ -79,7 +81,8 @@ def pinterest_search_node(state: Dict[str, Any]) -> Dict[str, Any]:
 
         if llm is not None and hasattr(llm, "generate_pinterest_terms"):
             try:
-                ctx = {"country": country, "seeds": seeds, "used_terms": used_llm, "count": want}
+                ctx = {"country": country, "seeds": seeds, "used_terms": used_llm, "count": want,
+                       "search_term_suffix": suffix}
                 res = llm.generate_pinterest_terms(ctx)
                 terms = [str(t).strip() for t in (res.get("search_terms") or []) if str(t).strip()]
                 print(f"[pinterest_search] LLM 生成搜索词 {len(terms)} 个（{country}，已用词注入 {len(used_llm)}）")
@@ -89,7 +92,7 @@ def pinterest_search_node(state: Dict[str, Any]) -> Dict[str, Any]:
 
         # 3) 兜底：LLM 无结果 → 种子词池随机抽样
         if not terms:
-            terms = [f"{s} t-shirt design" if "t-shirt design" not in s.lower() else s
+            terms = [f"{s} {suffix}".strip() if suffix and suffix not in s.lower() else s
                      for s in random.sample(seeds, min(want, len(seeds)))]
             print(f"[pinterest_search] 兜底：从种子词池取 {len(terms)} 个")