import { RankedItem } from "./rrf.mjs";

//#region ../ai/src/rag/hybrid/bm25.d.ts
/** A document to score lexically. */
type LexicalDoc = {
  id: string;
  text: string;
};
/**
 * Rank `docs` against `query` with BM25 (A4) — the lexical half of hybrid
 * retrieval. Scores keyword overlap with TF saturation (`k1`) and length
 * normalization (`b`) over the candidate set, so an exact-term match
 * surfaces even when dense embeddings miss it. Returns docs sorted by
 * score (highest first); zero-score docs are dropped.
 *
 * Operates over the supplied candidate set (typically the dense retriever's
 * over-fetch), so it needs no global corpus index — ideal for fusing with
 * a vector ranking via {@link reciprocalRankFusion}.
 */
declare function bm25Rank(query: string, docs: ReadonlyArray<LexicalDoc>): RankedItem[];
//#endregion
export { LexicalDoc, bm25Rank };
//# sourceMappingURL=bm25.d.mts.map