UNPKG

@langchain/community

Version:
30 lines (29 loc) 1.09 kB
import { Document } from "@langchain/core/documents"; import { BaseRetriever, BaseRetrieverInput } from "@langchain/core/retrievers"; //#region src/retrievers/bm25.d.ts type BM25RetrieverOptions = { docs: Document[]; k: number; includeScore?: boolean; } & BaseRetrieverInput; /** * A retriever that uses the BM25 algorithm to rank documents based on their * similarity to a query. It uses the "okapibm25" package for BM25 scoring. * The k parameter determines the number of documents to return for each query. */ declare class BM25Retriever extends BaseRetriever { includeScore: boolean; static lc_name(): string; lc_namespace: string[]; static fromDocuments(documents: Document[], options: Omit<BM25RetrieverOptions, "docs">): BM25Retriever; docs: Document[]; k: number; constructor(options: BM25RetrieverOptions); private preprocessFunc; _getRelevantDocuments(query: string): Promise<(Document<Record<string, any>> | Document<{ bm25Score: number; }>)[]>; } //#endregion export { BM25Retriever, BM25RetrieverOptions }; //# sourceMappingURL=bm25.d.cts.map