@andrejs1979/document/dist/operations/hybrid-search.d.ts

MongoDB-compatible document database for NoSQL

/**
 * NoSQL - Hybrid Document+Vector Search
 * Advanced search combining text, metadata, and vector similarity
 */
import { QueryFilter, HybridSearchQuery, HybridSearchResult, VectorDocumentResult, DocumentDatabaseConfig } from '../types';
import { DistanceMetric } from '../../vector/types';
import { DocumentStorage } from '../storage/document-storage';
import { MongoQueryEngine } from './query-engine';
/**
 * Hybrid search engine combining document queries with vector similarity
 */
export declare class HybridSearchEngine {
    private documentStorage;
    private queryEngine;
    private config;
    private searchCache;
    constructor(documentStorage: DocumentStorage, queryEngine: MongoQueryEngine, config: DocumentDatabaseConfig);
    /**
     * Perform hybrid search combining text, vector, and metadata filters
     */
    hybridSearch(database: string, collection: string, query: HybridSearchQuery): Promise<HybridSearchResult>;
    /**
     * Search documents by text content with optional vector boost
     */
    textSearch(database: string, collection: string, searchText: string, options?: {
        vectorBoost?: boolean;
        filters?: QueryFilter;
        limit?: number;
        threshold?: number;
    }): Promise<VectorDocumentResult[]>;
    /**
     * Search documents by vector similarity with optional text boost
     */
    vectorSearch(database: string, collection: string, queryVector: Float32Array | number[], options?: {
        textBoost?: boolean;
        filters?: QueryFilter;
        limit?: number;
        threshold?: number;
        metric?: DistanceMetric;
    }): Promise<VectorDocumentResult[]>;
    /**
     * Semantic search combining text embedding and vector similarity
     */
    semanticSearch(database: string, collection: string, searchText: string, options?: {
        embeddingModel?: string;
        filters?: QueryFilter;
        limit?: number;
        threshold?: number;
        textWeight?: number;
        vectorWeight?: number;
    }): Promise<VectorDocumentResult[]>;
    /**
     * Multi-modal search across different content types
     */
    multiModalSearch(database: string, collection: string, queries: {
        text?: string;
        image?: Uint8Array;
        audio?: Uint8Array;
        video?: Uint8Array;
    }, options?: {
        weights?: Record<string, number>;
        filters?: QueryFilter;
        limit?: number;
        threshold?: number;
    }): Promise<VectorDocumentResult[]>;
    /**
     * Similar document finder using document as query
     */
    findSimilarDocuments(database: string, collection: string, documentId: string, options?: {
        useText?: boolean;
        useVector?: boolean;
        useMetadata?: boolean;
        filters?: QueryFilter;
        limit?: number;
        threshold?: number;
    }): Promise<VectorDocumentResult[]>;
    /**
     * Recommendation engine based on user interaction history
     */
    getRecommendations(database: string, collection: string, userHistory: {
        viewedDocuments?: string[];
        likedDocuments?: string[];
        searchQueries?: string[];
    }, options?: {
        limit?: number;
        diversityFactor?: number;
        filters?: QueryFilter;
    }): Promise<VectorDocumentResult[]>;
    private determineSearchType;
    private performTextSearch;
    private performVectorSearch;
    private performHybridSearch;
    private mergeSearchResults;
    private calculateTextScore;
    private calculateVectorSimilarity;
    private extractSearchableText;
    private extractMetadataFilters;
    private generateEmbedding;
    private generateImageEmbedding;
    private combineEmbeddings;
    private convertToVectorDocumentResults;
    private applyDiversityFilter;
    private calculateDocumentSimilarity;
    private getSearchCacheKey;
    /**
     * Clear search cache
     */
    clearSearchCache(): void;
    /**
     * Get search cache statistics
     */
    getSearchCacheStats(): {
        size: number;
        memoryUsage: number;
    };
}
//# sourceMappingURL=hybrid-search.d.ts.map