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

graph/classify.py

@@ -0,0 +1,47 @@
+"""热点类型分类（规则版）+ Prompt 灵感生成。
+
+后续可把 classify() 换成一次 LLM 调用，产出更准的 Event/Meme/Style/Niche 标签。
+"""
+from typing import Dict, List
+
+EVENT_WORDS: List[str] = [
+    "eclipse", "olympic", "olympics", "christmas", "halloween", "election",
+    "thanksgiving", "valentine", "new year", "festival", "concert", "super bowl",
+    "world cup", "graduation", "wedding", "birthday", "2024", "2025", "2026",
+]
+MEME_WORDS: List[str] = [
+    "meme", "funny", "lol", "joke", "relatable", "viral", "sarcasm",
+    "hilarious", "pun", "cat", "dog",
+]
+STYLE_WORDS: List[str] = [
+    "vintage", "retro", "kawaii", "minimalist", "anime", "grunge", "boho",
+    "aesthetic", "streetwear", "gothic", "pastel", "vaporwave", "90s", "80s",
+    "cottagecore", "y2k", "punk", "minimal",
+]
+
+
+def classify(topic: str) -> str:
+    t = (topic or "").lower()
+    if any(w in t for w in EVENT_WORDS):
+        return "Event"
+    if any(w in t for w in MEME_WORDS):
+        return "Meme"
+    if any(w in t for w in STYLE_WORDS):
+        return "Style"
+    return "Niche"
+
+
+PROMPT_TEMPLATES: Dict[str, str] = {
+    "Event": "A vintage poster style design of {topic}, distressed texture, bold typography, vector style, isolated on white background.",
+    "Meme": "A funny cartoon illustration of {topic}, bold comic style, high contrast, humorous pure print design, isolated on white background.",
+    "Style": "A {topic} aesthetic illustration, trendy color palette, clean vector graphics, pure print design, isolated on white background.",
+    "Niche": "A cute illustration of {topic}, kawaii style, flat design, pastel colors, high contrast, pure print design, isolated on white background.",
+}
+
+# 通用负向约束：避免侵权与真实人物
+NEGATIVE = "no copyrighted characters, no real people, no brand logos, no trademarks, no politics, no religion, no hate, no violence, no sexual content, no readable text unless it is a short original English slogan, no gibberish text"
+
+
+def prompt_suggestion(topic: str, type_: str) -> str:
+    tpl = PROMPT_TEMPLATES.get(type_, PROMPT_TEMPLATES["Niche"])
+    return tpl.format(topic=topic) + " --no " + NEGATIVE