interface VectorDBConfig {
    dim: number;
    maxElements: number;
    autoCompaction?: boolean;
    compactionInterval?: number;
}
interface VectorEntry {
    id: string;
    vector: number[];
    metadata?: Record<string, any>;
}
interface SearchResult {
    id: string;
    similarity: number;
    metadata: Record<string, any>;
}
interface HybridSearchResult extends SearchResult {
    vectorScore: number;
    textScore: number;
    combinedScore: number;
}
interface HybridSearchOptions {
    vectorWeight?: number;
    textWeight?: number;
    k?: number;
    metadataFilter?: Record<string, any>;
    rerank?: boolean;
}
export declare class VectorDB {
    private readonly dim;
    private readonly maxElements;
    private readonly namespaces;
    private compactionIntervalId;
    private readonly bm25Params;
    constructor(config: VectorDBConfig);
    /**
     * Clean up resources and stop background tasks
     * Call this before your process exits
     */
    destroy(): void;
    private initializeNamespace;
    private validateVector;
    private tokenizeText;
    /**
     * Calculate document length (number of tokens) for BM25
     */
    private calculateDocLength;
    /**
     * Update BM25 statistics when documents are added/removed
     */
    private updateBM25Stats;
    private indexMetadata;
    private withReadLock;
    private withWriteLock;
    setFullTextIndexedFields(namespace: string, fields: string[]): Promise<void>;
    /**
     * Set BM25 parameters for tuning text search
     * @param k1 - Term frequency saturation parameter (default: 1.5, range: 1.2-2.0)
     * @param b - Length normalization parameter (default: 0.75, range: 0-1)
     */
    setBM25Params(k1?: number, b?: number): void;
    insert(namespace: string, id: string, vector: number[], metadata?: Record<string, any>): Promise<void>;
    batchInsert(namespace: string, entries: VectorEntry[]): Promise<void>;
    update(namespace: string, id: string, newVector: number[], newMetadata?: Record<string, any>): Promise<void>;
    delete(namespace: string, id: string): Promise<void>;
    search(namespace: string, queryVector: number[], k?: number, metadataFilter?: Record<string, any>): Promise<SearchResult[]>;
    /**
     * Calculate BM25 score for a document
     * @param termFreq - Map of term to its frequency in the document
     * @param docLength - Length of the document
     * @param nsData - Namespace data containing BM25 statistics
     * @returns BM25 score
     */
    private calculateBM25Score;
    /**
     * Full-text search using BM25 scoring
     */
    fullTextSearch(namespace: string, query: string, k?: number, metadataFilter?: Record<string, any>): Promise<SearchResult[]>;
    /**
     * Perform hybrid search combining vector similarity and BM25 text search
     */
    hybridSearch(namespace: string, queryVector: number[], queryText: string, options?: HybridSearchOptions): Promise<HybridSearchResult[]>;
    /**
     * Reciprocal Rank Fusion (RRF) hybrid search
     */
    hybridSearchRRF(namespace: string, queryVector: number[], queryText: string, k?: number, rrf_k?: number, metadataFilter?: Record<string, any>): Promise<HybridSearchResult[]>;
    private performVectorSearch;
    private performTextSearch;
    private combineSearchResults;
    private rerankResults;
    private cosineSimilarity;
    save(namespace: string, filePath: string): Promise<void>;
    load(namespace: string, filePath: string): Promise<void>;
    private scheduleCompaction;
    private compactNamespace;
}
export {};