@juspay/neurolink/dist/lib/rag/retrieval/hybridSearch.d.ts

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/**
 * Hybrid Search Implementation
 *
 * Combines vector (dense) search with BM25 (sparse) search for improved retrieval.
 * Supports multiple fusion methods: Reciprocal Rank Fusion (RRF) and Linear Combination.
 */
import type { BM25Result, HybridSearchConfig, HybridSearchResult, BM25Index, HybridSearchOptions } from "../../types/index.js";
/**
 * In-memory BM25 implementation for testing and development
 */
export declare class InMemoryBM25Index implements BM25Index {
    private documents;
    private avgDocLength;
    private k1;
    private b;
    search(query: string, topK?: number): Promise<BM25Result[]>;
    addDocuments(documents: Array<{
        id: string;
        text: string;
        metadata?: Record<string, unknown>;
    }>): Promise<void>;
    private tokenize;
    private countTermFrequency;
    private countDocumentsWithTerm;
}
/**
 * Reciprocal Rank Fusion
 * Combines rankings from multiple retrieval methods
 *
 * @param rankings - Array of ranking lists, each with id and rank
 * @param k - RRF constant (default: 60)
 * @returns Map of document IDs to fused scores
 */
export declare function reciprocalRankFusion(rankings: Array<Array<{
    id: string;
    rank: number;
}>>, k?: number): Map<string, number>;
/**
 * Linear Combination of normalized scores
 *
 * @param vectorScores - Vector search scores
 * @param bm25Scores - BM25 search scores
 * @param alpha - Weight for vector scores (0-1), bm25 gets 1-alpha
 * @returns Map of document IDs to combined scores
 */
export declare function linearCombination(vectorScores: Map<string, number>, bm25Scores: Map<string, number>, alpha?: number): Map<string, number>;
/**
 * Create a hybrid search function
 *
 * @param options - Search options
 * @returns Hybrid search function
 */
export declare function createHybridSearch(options: HybridSearchOptions): (query: string, config?: HybridSearchConfig) => Promise<HybridSearchResult[]>;