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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2026-08-22 14:14:01 +08:00
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"""节点 1/6:抓取(fetch)。
按 config.sources 启用各可插拔数据源,汇总统一格式行。
单源失败不影响其它源(内部逐个 try),整体再套 with_fallback 兜底。
"""
from typing import Any, Dict, List
from graph.sources import get_source
from graph.validate import validate_rows, with_fallback
@with_fallback("fetch")
def fetch_node(state: Dict[str, Any]) -> Dict[str, Any]:
country = state["country"]
config = state["config"]
cc = state["country_config"]
enabled = config.get("sources") or ["google_trends"]
rows: List[Dict[str, Any]] = []
errors = list(state.get("errors") or [])
# 采集缓存优先:采集(fetch_keywords)成功后写入 output/<国>/collected_keywords.json
# 这里直接用(跳过 Google 重抓),避免重复撞限流;无缓存才走数据源抓取
use_collected = (config.get("fetch") or {}).get("use_collected", True)
if use_collected:
try:
import json as _json
from pathlib import Path as _Path
p = _Path(state.get("cache_dir") or state.get("output_dir", "")) / "collected_keywords.json"
if p.exists():
data = _json.loads(p.read_text(encoding="utf-8"))
cached_rows = data.get("keywords") or []
if cached_rows:
rows = [dict(r) for r in cached_rows] # 已过滤去重的关键词
print(f"[fetch] 使用采集缓存 {len(rows)} 条({country},跳过 Google 抓取)")
stats = dict(state.get("stats") or {})
stats["fetch"] = {"raw_rows": len(rows), "sources": ["collected_cache"], "errors": 0}
return {"raw_rows": rows, "errors": errors, "stats": stats}
except Exception as e: # noqa: BLE001
print(f"[fetch] 读取采集缓存失败(回退数据源): {e}")
for name in enabled:
try:
src = get_source(name)
rows.extend(src.fetch(country, cc, config))
except Exception as e: # noqa: BLE001
errors.append({
"node": "fetch", "type": type(e).__name__,
"message": f"source[{name}]: {e}", "trace": "",
})
print(f"[fetch] 数据源 {name} 失败(跳过): {e}")
rows = validate_rows(rows, "fetch")
stats = dict(state.get("stats") or {})
stats["fetch"] = {"raw_rows": len(rows), "sources": enabled, "errors": len(errors)}
return {"raw_rows": rows, "errors": errors, "stats": stats}