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@@ -1,7 +1,10 @@
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-"""创作 query 筛选器：调用 acquisition/query_filter.txt（LLM 只做 keep/排除），批量判一组 query。
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+"""创作 query 筛选器：调用 acquisition/query_filter.txt，批量判一组 query。
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-命中 A–E 任一即排除：A 语义不通 / B 题材本身 / C 制作工具 / D 应试学术公务政企 / E 作品素材。
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-返回与输入等长的 [{keep: bool, reason: str}]。供 build_creation_demo、filter_multiaxis 等共用。
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+模型对每条 query 打两项：语义合法性 valid(0-10) + 创作相关性 relevant(bool)。
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+最终保留 keep = valid ≥ VALID_MIN 且 relevant —— 阈值放代码里(好调，不改提示词)。
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+ · valid：词组合本身说不说得通(机械正交易产生的废话短语在此淘汰)。
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+ · relevant：搜回来是否和创作知识相关(三把尺=设计决策vs工艺/可迁移/业务阶段；再排 制作/题材本身/应试政企/作品)。
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+返回与输入等长的 [{keep, valid, relevant, reason}]。供 build_creation_demo、filter_multiaxis 等共用。
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"""
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from __future__ import annotations
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@@ -13,6 +16,7 @@ import httpx
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from core.config import Settings
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PROMPT = Path(__file__).resolve().parent / "query_filter.txt"
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+VALID_MIN = 6 # 语义合法性阈值：valid ≥ 此值才算说得通；调这里即可松紧
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def filter_queries(queries: list[str], settings: Settings, *, batch: int = 40) -> list[dict]:
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@@ -40,7 +44,17 @@ def _filter_batch(queries: list[str], settings: Settings) -> list[dict]:
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data = json.loads(txt)
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arr = data if isinstance(data, list) else next((v for v in data.values() if isinstance(v, list)), [])
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by = {d.get("idx"): d for d in arr if isinstance(d, dict)}
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- return [{"keep": bool(by.get(i, {}).get("keep", True)),
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- "reason": str(by.get(i, {}).get("reason", ""))[:50]} for i in range(len(queries))]
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+ out = []
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+ for i in range(len(queries)):
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+ d = by.get(i, {})
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+ try:
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+ valid = int(d.get("valid", 10))
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+ except (TypeError, ValueError):
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+ valid = 10
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+ relevant = bool(d.get("relevant", True))
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+ out.append({"keep": valid >= VALID_MIN and relevant, # 阈值在代码里判
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+ "valid": valid, "relevant": relevant,
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+ "reason": str(d.get("reason", ""))[:50]})
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+ return out
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except Exception as exc:
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- return [{"keep": True, "reason": f"筛选失败:{str(exc)[:30]}"} for _ in queries]
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+ return [{"keep": True, "valid": 10, "relevant": True, "reason": f"筛选失败:{str(exc)[:30]}"} for _ in queries]
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SamLee