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
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"""节点 0/6：动态种子词（seed）。
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在 fetch 之前运行：收集「trending 派生 + 历史 safe 热点 + 月份/节日」上下文，
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按 seed_provider 策略（static / mock / LLM）生成/合并种子词，注入 country_config 的
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style.seeds / related.seed_keywords，供后续 fetch 的 related_queries 展开使用。
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关键机制：动态种子词按 (国家, provider, 日期) 缓存（.cache/seeds/）。
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同一天内多次运行使用同一套种子词 → related_queries 的 24h 缓存稳定命中，
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避免「history 每次跑完都变 → 种子词震荡 → Google 反复全量重抓 → 429 限流」。
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带 with_fallback：任何异常都降级为"仅用 yaml 静态种子"，不阻塞整图。
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"""
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import datetime
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import hashlib
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import json
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import os
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from pathlib import Path
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from typing import Any, Dict
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from graph.llms import get_backend
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from graph.llms.mock_backend import COMMON_RISK_WORDS
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from graph.paths import runtime_root
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from graph.scoring import filter_person_names, filter_query_noise
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from graph.seeds import get_seed_strategy
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from graph.seeds.holidays import build_holiday_context
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from graph.sources.google_trends_source import fetch_trending
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from graph.validate import with_fallback
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_CACHE_DIR = runtime_root() / ".cache" / "seeds"
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def _cache_key(country: str, provider: str, cfg: Dict[str, Any]) -> str:
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"""缓存键含「配置指纹」：改了种子相关参数（数量/上下文上限）即换新键重新生成，
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避免命中旧参数生成的种子；旧文件保留（不删缓存，取最新）。"""
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fp = hashlib.md5(
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json.dumps(
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{k: cfg.get(k) for k in ("max_style_seeds", "max_related_seeds",
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"trending_context_limit", "history_limit")},
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sort_keys=True, ensure_ascii=False,
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).encode("utf-8")
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).hexdigest()[:8]
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return f"{country}-{provider}-{fp}-{datetime.date.today().isoformat()}"
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def _cache_get(key: str):
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try:
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p = _CACHE_DIR / f"{key}.json"
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if p.exists():
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return json.loads(p.read_text(encoding="utf-8"))
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except Exception:
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pass
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return None
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def _cache_set(key: str, val: Dict[str, Any]):
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try:
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_CACHE_DIR.mkdir(parents=True, exist_ok=True)
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(_CACHE_DIR / f"{key}.json").write_text(
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json.dumps(val, ensure_ascii=False), encoding="utf-8")
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except Exception:
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pass
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@with_fallback("seed")
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def seed_node(state: Dict[str, Any]) -> Dict[str, Any]:
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country = state["country"]
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config = state["config"]
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cc = dict(state.get("country_config") or {})
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errors = list(state.get("errors") or [])
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provider = (config.get("seed_provider") or "mock").strip().lower()
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cfg = config.get("seed_provider_cfg") or {}
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trending_limit = int(cfg.get("trending_context_limit", 15))
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history_limit = int(cfg.get("history_limit", 20))
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max_style = int(cfg.get("max_style_seeds", 12))
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max_related = int(cfg.get("max_related_seeds", 12))
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guard = COMMON_RISK_WORDS + [b.lower() for b in (config.get("blacklist") or [])]
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ckey = _cache_key(country, provider, cfg)
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cached = _cache_get(ckey) if provider != "static" else None
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from_cache = cached is not None
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if cached is not None:
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res = cached
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context: Dict[str, Any] = {
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"country": country,
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"max_style_seeds": max_style,
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"max_related_seeds": max_related,
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}
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else:
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# 1) 收集上下文
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context: Dict[str, Any] = {
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"country": country,
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"max_style_seeds": max_style,
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"max_related_seeds": max_related,
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}
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try:
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tl = int((cc.get("trending") or {}).get("limit", 40))
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rows = fetch_trending(geo=country, limit=min(tl, 40))
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# 保留 rows 自带的 source=gt_trending，filter_person_names 的人名模式仅对该源生效
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kept, _ = filter_query_noise(rows, enabled=True)
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kept, _ = filter_person_names(kept)
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kept = [r for r in kept if not any(w and w in r["topic"].lower() for w in guard)]
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context["trending_seeds"] = [r["topic"] for r in kept][:trending_limit]
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except Exception as e: # noqa: BLE001
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print(f"[seed] trending 上下文收集失败(跳过): {e}")
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context["trending_seeds"] = []
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try:
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p = os.path.join(state.get("output_dir", ""), "design_briefs.json")
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if os.path.exists(p):
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data = json.load(open(p, encoding="utf-8")).get("design_briefs", [])
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safe = [d for d in data if d.get("risk_level") == "safe"]
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safe.sort(key=lambda d: -(d.get("score") or 0))
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hrows = [{"topic": d["topic"], "source": "history"} for d in safe]
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hrows, _ = filter_person_names(hrows, pattern_sources={"history"})
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hrows = [r for r in hrows if not any(w and w in r["topic"].lower() for w in guard)]
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context["history_hotspots"] = [r["topic"] for r in hrows][:history_limit]
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else:
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context["history_hotspots"] = []
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except Exception as e: # noqa: BLE001
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print(f"[seed] 历史热点读取失败(跳过): {e}")
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context["history_hotspots"] = []
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# 月份/节日（按国家：各国节日表不同）
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hol = build_holiday_context(country)
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context["season"] = hol["season"]
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context["year"] = hol["year"]
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context["month"] = hol["month"]
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context["date"] = hol["date"]
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context["month_themes"] = hol["month_themes"]
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context["upcoming_holidays"] = hol["upcoming_holidays"]
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# 2) 选策略 + LLM 后端
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strategy = get_seed_strategy(provider)
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llm_backend = None
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if provider != "static":
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llm_backend = get_backend(provider)
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# 注入 llm_screen 配置（api_key/base_url/model），否则 has_key 永远 False 降级 mock
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try:
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llm_backend.bind_config(config.get("llm_screen") or {})
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except Exception as e: # noqa: BLE001
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print(f"[seed] LLM 配置绑定失败: {e}")
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if provider not in ("mock",) and not getattr(llm_backend, "has_key", False):
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print(f"[seed] {provider} 未配置 API key，降级 mock 规则生成种子词")
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llm_backend = get_backend("mock")
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# 3) 生成/合并种子词
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try:
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res = strategy.resolve(country, cc, context, llm_backend)
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except Exception as e: # noqa: BLE001
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print(f"[seed] 策略解析失败，回退静态种子: {e}")
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res = {
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"style_seeds": list((cc.get("style", {}) or {}).get("seeds", []) or []),
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"related_seeds": list((cc.get("related", {}) or {}).get("seed_keywords", []) or []),
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"dynamic": False,
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}
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if provider != "static":
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_cache_set(ckey, res)
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# 4) 注入 cc
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style_block = dict(cc.get("style") or {})
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related_block = dict(cc.get("related") or {})
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style_block["seeds"] = res["style_seeds"]
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related_block["seed_keywords"] = res["related_seeds"]
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cc["style"] = style_block
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cc["related"] = related_block
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stats = dict(state.get("stats") or {})
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stats["seed"] = {
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"provider": provider,
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"dynamic": res.get("dynamic", False),
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"from_cache": from_cache,
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"style_count": len(res["style_seeds"]),
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"related_count": len(res["related_seeds"]),
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"trending_ctx": len(context.get("trending_seeds", [])),
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"history_ctx": len(context.get("history_hotspots", [])),
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"holidays": context.get("upcoming_holidays", []),
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}
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print(
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f"[seed] provider={provider}{'（当日缓存命中）' if from_cache else ''} "
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f"种子词 style={len(res['style_seeds'])} related={len(res['related_seeds'])}"
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)
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return {
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"country_config": cc,
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"seed_words": res,
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"stats": stats,
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"errors": errors,
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}
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