@promptbook/utils/esm/typings/src/book-2.0/commitments/KNOWLEDGE/RAGService.d.ts

Promptbook: Run AI apps in plain human language across multiple models and platforms

import type { string_url } from '../../../types/typeAliases';
import type { RAGConfig } from './types';
import type { RetrievalResult } from './types';
/**
 * RAG (Retrieval-Augmented Generation) Service
 * Handles knowledge source processing and retrieval
 *
 * @private
 */
export declare class RAGService {
    private knowledgeBase;
    private config;
    constructor(config?: Partial<RAGConfig>);
    /**
     * Add a knowledge source from URL
     */
    addKnowledgeSource(url: string_url): Promise<void>;
    /**
     * Retrieve relevant chunks for a query
     */
    retrieveRelevantChunks(query: string): RetrievalResult[];
    /**
     * Get formatted context for the agent
     */
    getContextForQuery(query: string): string;
    /**
     * Get knowledge base statistics
     */
    getStats(): {
        sources: number;
        chunks: number;
        lastUpdated: Date;
    };
    /**
     * Clear all knowledge sources
     */
    clearKnowledgeBase(): void;
    /**
     * Tokenize query into words for relevance scoring
     */
    private tokenizeQuery;
    /**
     * Calculate relevance score between content and query words
     * Simple keyword matching - in production, use embeddings
     */
    private calculateRelevanceScore;
    /**
     * Generate content hash for caching
     */
    private generateContentHash;
}
/**
 * TODO: !!!! use the already existing RAG instead of this
 */