3218485270
f493bde8a9
- 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
27 lines
908 B
Python
27 lines
908 B
Python
"""节点 3/6：打分（score）。
|
||
|
||
归一化（按 source/kind 分组 min-max）-> 跨源融合（combine）-> 综合分阈值预筛。
|
||
纯逻辑节点，with_fallback 兜底。
|
||
"""
|
||
from typing import Any, Dict, List
|
||
|
||
from graph.scoring import combine, normalize
|
||
from graph.validate import with_fallback
|
||
|
||
|
||
@with_fallback("score")
|
||
def score_node(state: Dict[str, Any]) -> Dict[str, Any]:
|
||
rows: List[Dict[str, Any]] = state.get("filtered_rows") or []
|
||
config = state["config"]
|
||
weights = config.get("weights") or {}
|
||
llm_cfg = config.get("llm_screen") or {}
|
||
min_score = float(llm_cfg.get("min_score", 0.0))
|
||
|
||
normalize(rows)
|
||
combined = combine(rows, weights)
|
||
combined = [c for c in combined if float(c.get("score", 0)) >= min_score]
|
||
|
||
stats = dict(state.get("stats") or {})
|
||
stats["score"] = {"combined": len(combined)}
|
||
return {"scored_rows": combined, "stats": stats}
|