/**
 * Hybrid Retriever for Memory System
 *
 * Combines vector and keyword search with RRF (Reciprocal Rank Fusion).
 */
import { EmbeddedDatabase } from '../embedded';
import { AllowedSet, RetrievalConfig, RetrievalResponse } from './types';
/**
 * Hybrid Retriever with RRF fusion
 */
export declare class HybridRetriever {
    private db;
    private namespace;
    private collection;
    private config;
    private prefix;
    private bm25;
    private indexed;
    constructor(db: EmbeddedDatabase, namespace: string, collection: string, config?: RetrievalConfig);
    /**
     * Create retriever from database
     */
    static fromDatabase(db: EmbeddedDatabase, namespace: string, collection: string, config?: RetrievalConfig): HybridRetriever;
    /**
     * Index documents for retrieval
     */
    indexDocuments(documents: Array<{
        id: string;
        content: string;
        embedding: number[];
        metadata?: Record<string, any>;
    }>): Promise<void>;
    /**
     * Retrieve documents with hybrid search
     */
    retrieve(queryText: string, queryVector: number[], allowed: AllowedSet, k?: number): Promise<RetrievalResponse>;
    /**
     * Explain ranking for a specific document
     */
    explain(queryText: string, queryVector: number[], docId: string): Promise<{
        vectorRank?: number;
        keywordRank?: number;
        expectedRrfScore?: number;
    }>;
}
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