kplam
51dc8dc4f6
- 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
31 lines
1.2 KiB
Python
31 lines
1.2 KiB
Python
"""检索请求与响应的数据模型"""
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from pydantic import BaseModel, Field
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class SearchRequest(BaseModel):
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"""检索请求"""
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query: str = Field(description="查询文本")
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top_k: int | None = Field(default=None, description="返回结果数，为空时使用 settings.retrieval_final_k")
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class SearchHit(BaseModel):
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"""单条检索命中结果"""
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text: str = Field(description="原文 chunk 内容")
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doc_id: str = Field(description="所属文档 ID")
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title: str = Field(default="", description="文档标题")
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section_path: str = Field(default="", description="chunk 所在的章节路径")
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score: float = Field(description="相关性得分")
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doc_summary: str = Field(default="", description="L1 文档总结，仅用于上下文标注")
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class SearchResponse(BaseModel):
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"""检索响应"""
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query: str = Field(description="原始查询文本")
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hits: list[SearchHit] = Field(default_factory=list, description="命中结果列表")
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routed_categories: list[str] = Field(default_factory=list, description="query 路由命中的类目")
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fallback: bool = Field(default=False, description="是否走了全库兜底路径")
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