freedak
641e33b834
- 语义检索(FAISS + embedding)+ 精确查找(法规名+条号) - RAG 问答(SSE 流式,支持 thinking 折叠显示) - 法规浏览(原文阅读) - 历史记录(检索+对话持久化到 SQLite) - 设置页(系统提示词/模板/LLM 参数可配置) - 检索质量评估脚本 Generated with [Devin](https://devin.ai) Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
90 lines
2.9 KiB
Python
90 lines
2.9 KiB
Python
"""检索 API — /api/search"""
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from fastapi import APIRouter, Request, HTTPException, Query
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from typing import Optional
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from app.services.retriever import Retriever
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from app.services.embedding import embed_text
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from app.services.history import add_search_history
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from app.config import MAX_QUERY_LENGTH
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router = APIRouter()
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@router.get("/search")
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async def search(
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request: Request,
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query: str = Query(..., min_length=1, max_length=MAX_QUERY_LENGTH, description="查询文本"),
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mode: str = Query("semantic", description="检索模式:semantic(语义) / keyword(关键词精确)"),
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category: Optional[str] = Query(None, description="法规类别过滤"),
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province: Optional[str] = Query(None, description="省份过滤"),
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city: Optional[str] = Query(None, description="市级过滤"),
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top_k: int = Query(20, ge=1, le=100, description="返回数量"),
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page: int = Query(1, ge=1, description="页码"),
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page_size: int = Query(20, ge=1, le=100, description="每页数量"),
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):
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"""检索法规条文(语义检索或关键词精确搜索)
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- mode=semantic: 向量化查询 → FAISS 检索 → metadata 过滤(默认)
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- mode=keyword: 按法规名+条号精确匹配,支持"郑州市劳动用工条例 第三十二条"
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"""
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trace_id = getattr(request.state, "trace_id", "")
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retriever = Retriever.get_instance()
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if not retriever.is_ready():
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raise HTTPException(status_code=503, detail="索引未加载,请等待或检查索引文件")
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if mode == "keyword":
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# 关键词精确搜索
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results = retriever.keyword_search(
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query=query,
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top_k=top_k * 3 if (category or province or city) else top_k,
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category=category,
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province=province,
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city=city,
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)
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else:
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# 语义检索
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try:
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query_vec = await embed_text(query)
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except Exception as e:
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raise HTTPException(
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status_code=503,
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detail=f"embedding 服务不可用: {str(e)}",
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)
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fetch_k = top_k * 3 if (category or province or city) else top_k
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results = retriever.search(
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query_vec=query_vec,
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top_k=fetch_k,
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category=category,
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province=province,
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city=city,
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)
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# 分页
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total = len(results)
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start = (page - 1) * page_size
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end = start + page_size
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page_results = results[start:end]
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# 记录检索历史
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add_search_history(
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query=query,
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category=category,
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province=province,
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city=city,
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result_count=total,
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top_k=top_k,
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)
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return {
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"code": 0,
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"message": "ok",
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"data": {
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"results": page_results,
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"total": total,
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"page": page,
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"page_size": page_size,
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},
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"trace_id": trace_id,
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}
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