67 lines
1.6 KiB
Python
67 lines
1.6 KiB
Python
# app/api/search.py
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"""
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BM25 keyword search across the document library.
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MIT — no tier gate. No Ollama required.
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"""
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from __future__ import annotations
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import logging
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import os
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from typing import Annotated
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from fastapi import APIRouter, Depends
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from pydantic import BaseModel, Field
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from app.services.bm25_index import BM25Index
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/search", tags=["search"])
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class SearchRequest(BaseModel):
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query: str
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top_k: int = Field(default=10, ge=1, le=50)
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doc_ids: list[str] | None = None
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class SearchResult(BaseModel):
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chunk_id: str
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doc_id: str
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page_number: int
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text_snippet: str # first 300 chars of the page text
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bm25_score: float
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def _get_bm25() -> BM25Index:
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import app.main as _main
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bm25 = getattr(_main, "_bm25", None)
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if bm25 is None:
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raise RuntimeError("BM25 index not initialised — app.main not loaded")
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return bm25
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def _get_db_path() -> str:
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"""Read lazily so test fixtures (monkeypatch.setattr) take effect."""
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import pathlib
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data_dir = pathlib.Path(os.environ.get("PAGEPIPER_DATA_DIR", "data"))
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return str(data_dir / "pagepiper.db")
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@router.post("")
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def search(
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req: SearchRequest,
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bm25: Annotated[BM25Index, Depends(_get_bm25)],
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) -> list[SearchResult]:
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bm25.ensure_fresh(_get_db_path())
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hits = bm25.query(req.query, top_k=req.top_k, doc_ids=req.doc_ids)
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return [
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SearchResult(
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chunk_id=h.chunk_id,
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doc_id=h.doc_id,
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page_number=h.page_number,
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text_snippet=(h.text or "")[:300],
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bm25_score=h.score,
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)
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for h in hits
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]
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