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- FastAPI + Qdrant + Redis + Ollama 技术栈 - L1→L2→L3→chunk 四层分层检索（dense + sparse RRF 融合） - 文档三级总结与 2.5 级回退 - query 解析路由与分类 - /admin 管理页面
25 lines
1.0 KiB
Python
25 lines
1.0 KiB
Python
"""检索结果重排：RRF 融合与最终截断"""
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from qdrant_client import models
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def rrf_fuse(result_lists: list[list[models.ScoredPoint]], k: int = 60) -> list[models.ScoredPoint]:
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"""标准 RRF（Reciprocal Rank Fusion）融合
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融合分 = Σ 1/(k + rank)（rank 从 1 开始），按 point id 去重合并，
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返回按融合分降序的列表，score 字段写回融合分。空输入返回 []。
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"""
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scores: dict[str | int, float] = {}
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points: dict[str | int, models.ScoredPoint] = {}
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for results in result_lists:
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for rank, point in enumerate(results, start=1):
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scores[point.id] = scores.get(point.id, 0.0) + 1.0 / (k + rank)
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points.setdefault(point.id, point)
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ordered = sorted(points, key=lambda pid: scores[pid], reverse=True)
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return [points[pid].model_copy(update={"score": scores[pid]}) for pid in ordered]
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def finalize(points: list[models.ScoredPoint], final_k: int) -> list[models.ScoredPoint]:
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"""截断为最终返回的 top final_k"""
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return points[:final_k]
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