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
2026-08-22 14:14:01 +08:00
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+"""Mock LLM 后端：启发式兜底（无 key 也能端到端跑通）。
+
+逻辑：黑名单硬拦 -> 常识风险词标 review -> 动态风格/配色推导 -> 分类。
+这是生产环境 LLM 不可用时的安全降级路径，保证流水线永远能产出可用结果。
+"""
+from typing import Any, Dict, List
+
+from ..classify import classify, prompt_suggestion
+from ..style_rules import derive_style_palette, derive_composition
+
+
+def _dedup_limit(items: List[str], limit: int) -> List[str]:
+    """去重（大小写不敏感）并限量，保留首次出现顺序。"""
+    seen = set()
+    out: List[str] = []
+    for it in items:
+        it = (it or "").strip()
+        if not it:
+            continue
+        low = it.lower()
+        if low in seen:
+            continue
+        seen.add(low)
+        out.append(it)
+        if len(out) >= limit:
+            break
+    return out
+
+
+# 常识风险词（兜底用；真实判定交给 LLM）。同时被 seed_node 复用为「种子护栏」，
+# 避免真人/IP/平台词作为 Google Trends 相关查询种子浪费抓取。
+COMMON_RISK_WORDS = [
+    "disney", "marvel", "nike", "adidas", "apple", "iphone", "mcdonalds",
+    "mcdonald", "starbucks", "coca", "pepsi", "pokemon", "mario", "hello kitty",
+    "sanrio", "sonic", "minions", "barbie", "harry potter", "batman", "spiderman",
+    "star wars", "fortnite", "roblox", "minecraft", "tiktok", "netflix", "pearl jam",
+    "nirvana", "taylor swift", "trump", "biden", "kardashian", "lebron", "kanye",
+    "kick", "gta", "ufc", "westmeath", "lottery", "prison break", "margot robbie",
+    "dana white", "euro", "spotify", "youtube", "instagram", "xbox", "playstation",
+    "noah kahan", "gina carano", "camry", "hurricanes", "eras tour",
+    "springsteen", "reiner", "eliza lopes", "camilla", "h&m", "truck accident attorney",
+]
+
+# 原创短标语池（mock 模式的 slogan；纯原创、无版权无品牌）
+# 原创短标语池（mock 模式的 slogan；纯原创、无版权无品牌）
+# 英语通用 + 各国语言（JP=日语短标语），按国家动态注入
+_STABLE_SLOGANS_EN = [
+    "good vibes", "stay cozy", "happy place", "be kind", "dream big",
+    "keep smiling", "sunshine", "peace love", "stay wild", "pet the cat",
+    "coffee first", "tiny paws", "warm hugs", "soft life", "grow slowly",
+    "lucky charm", "sweet dreams", "go outside", "mindful", "lazy days",
+]
+_STABLE_SLOGANS_JP = [
+    "ゆめいっぱい", "やさしい気持ち", "ずっと元気", "おだやかな日", "きょうもハッピー",
+    "ねこが好き", "いっしょにね", "ぽかぽか", "はるの風", "なつのおもいで",
+    "きらきら", "わくわく", "のんびり", "しあわせ", "えがお",
+]
+
+
+def _stable_slogan(topic: str, country: str = "") -> str:
+    """按主题哈希稳定选一条原创标语（同一主题缓存一致；mock 兜底用）。
+    country=JP → 日语短标语；其他国家 → 英语。"""
+    import hashlib
+    pool = _STABLE_SLOGANS_JP if str(country).upper() == "JP" else _STABLE_SLOGANS_EN
+    h = int(hashlib.md5((topic or "").encode("utf-8")).hexdigest(), 16)
+    return pool[h % len(pool)]
+
+
+class MockBackend:
+    name = "mock"
+
+    def screen(
+        self,
+        topics: List[str],
+        country: str,
+        aesthetic_hint: str,
+        system_prompt: str,
+        blacklist: List[str],
+        batch_size: int = 12,
+    ) -> List[Dict[str, Any]]:
+        bl = [b.lower() for b in (blacklist or [])]
+        out: List[Dict[str, Any]] = []
+        for t in topics:
+            tl = t.lower()
+            hits = [b for b in bl if b and b in tl]
+            blocked = bool(hits)
+            soft_hits = [w for w in COMMON_RISK_WORDS if w in tl]
+            if blocked:
+                risk_level = "blocked"
+            elif soft_hits:
+                risk_level = "review"
+            else:
+                risk_level = "safe"
+            cat = classify(t)
+            art_style, palette = derive_style_palette(t, country, category=cat)
+            # motif：从分类模板取核心描述，去掉配色/白底尾巴，保持干净可复用
+            motif = prompt_suggestion(t, cat).split(" --no ")[0].split(",")[0].strip()
+            composition = derive_composition(t, cat)
+            negative = ("no real people, no likeness of any person, no copyrighted characters, "
+                        "no brand logos, no trademarks, no celebrity, no readable text unless safe")
+            slogan = _stable_slogan(t, country)   # 按国家语言（JP→日语短标语，其余英语）
+            out.append({
+                "topic": t,
+                "safe_for_print": not blocked,
+                "risk_level": risk_level,
+                "risk_reasons": [f"命中黑名单: {hits}"] if hits
+                else (["疑似受保护实体，需人工复核"] if soft_hits else []),
+                "suitable_for_print": not blocked,
+                "design_category": cat,
+                "concept": f"（启发式兜底）围绕「{t}」做原创{art_style}风格印花",
+                "motif": motif,
+                "art_style": art_style,
+                "color_palette": palette,
+                "composition": composition,
+                "slogan": slogan,
+                "negative_prompt": negative,
+                "confidence": 0.55 if risk_level == "safe" else 0.4,
+            })
+        return out
+
+    def generate_seeds(self, context: Dict[str, Any]) -> Dict[str, Any]:
+        """规则生成种子词（零 API 成本）：借用月份主题、临近节日、trending 派生、历史热点。"""
+        month_themes = context.get("month_themes", []) or []
+        upcoming = context.get("upcoming_holidays", []) or []
+        trending = context.get("trending_seeds", []) or []
+        history = context.get("history_hotspots", []) or []
+
+        style: List[str] = []
+        related: List[str] = []
+        # 月份主题 + 临近节日 → 风格种子（带美学倾向）
+        style += list(month_themes)
+        style += [f"{h.lower()} aesthetic" for h in upcoming]
+        style += trending[:4]
+        # related：历史 safe 热点 + 剩余 trending（行业交叉验证）
+        related += history[:6]
+        related += trending[4:8]
+
+        max_style = int(context.get("max_style_seeds", 10) or 10)
+        max_related = int(context.get("max_related_seeds", 10) or 10)
+        return {
+            "style_seeds": _dedup_limit(style, max_style),
+            "related_seeds": _dedup_limit(related, max_related),
+        }