import type { CachedDocument, OfflineVectorExport } from './types.js';
interface LocalRAGResult {
    answer: string;
    sources: Array<{
        title: string;
        snippet: string;
        score: number;
    }>;
    topScore: number;
}
/**
 * Local RAG engine using TF-IDF similarity
 *
 * Provides offline fallback when backend is unavailable.
 * Uses simple TF-IDF for document matching (no vector embeddings).
 */
export interface ExportStatus {
    loaded: boolean;
    loadedFromExport: boolean;
    documentCount: number;
    chunkCount: number;
    exportVersion?: string;
    exportedAt?: string;
}
export declare class CyberneticLocalRAG {
    private documents;
    private idf;
    private indexed;
    private loadedFromExport;
    private exportVersion?;
    private exportedAt?;
    private vocabulary;
    /**
     * Check if documents are indexed
     */
    isIndexed(): boolean;
    /**
     * Index documents for local search
     */
    index(documents: CachedDocument[]): Promise<void>;
    /**
     * Process query and generate response
     */
    ask(query: string): Promise<LocalRAGResult>;
    /**
     * Reset the index
     */
    reset(): void;
    /**
     * Load pre-computed vectors from an export file
     * This skips client-side TF-IDF computation by using pre-computed values
     *
     * @param exportData - The offline vector export data
     */
    loadFromExport(exportData: OfflineVectorExport): Promise<void>;
    /**
     * Get export status information
     */
    getExportStatus(): ExportStatus;
    /**
     * Tokenize text into words
     */
    private tokenize;
    /**
     * Compute term frequency
     */
    private computeTermFrequency;
    /**
     * Compute cosine similarity between two TF-IDF vectors
     */
    private cosineSimilarity;
    /**
     * Extract most relevant snippet from content
     */
    private extractRelevantSnippet;
    /**
     * Check if word is a stop word
     */
    private isStopWord;
}
export {};
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