mnemos-coder/dist/codebase/SearchEngine.d.ts

CLI-based coding agent with graph-based execution loop and terminal UI

/**
 * New semantic search engine using API embeddings and Vectra
 * Replaces the old TF-IDF based search
 */
import { VectraDatabase } from './VectraDatabase.js';
import { ApiEmbedder } from './ApiEmbedder.js';
export interface SearchOptions {
    limit?: number;
    threshold?: number;
    includeContent?: boolean;
    fileTypes?: string[];
    chunkTypes?: string[];
    hybridWeight?: number;
}
export interface SearchContext {
    filePath?: string;
    language?: string;
    recentFiles?: string[];
    currentFunction?: string;
}
export interface EnhancedSearchResult {
    chunk: any;
    similarity_score: number;
    text_score?: number;
    combined_score: number;
    relevance_type: 'semantic' | 'text' | 'hybrid' | 'contextual';
    file_context?: string[];
    related_chunks?: string[];
}
export declare class SearchEngine {
    private db;
    private embedder;
    private defaultOptions;
    constructor(db: VectraDatabase, embedder: ApiEmbedder);
    /**
     * Hybrid search combining vector similarity and text search
     */
    search(query: string, options?: SearchOptions, context?: SearchContext): Promise<EnhancedSearchResult[]>;
    /**
     * Pure vector similarity search
     */
    vectorSearch(query: string, options: SearchOptions): Promise<EnhancedSearchResult[]>;
    /**
     * Text-based search using FTS5
     */
    textSearch(query: string, options: SearchOptions): Promise<EnhancedSearchResult[]>;
    /**
     * Quick search for exact matches and patterns
     */
    quickSearch(pattern: string, options?: SearchOptions): Promise<EnhancedSearchResult[]>;
    /**
     * Suggest context based on current code location
     */
    suggestContext(filePath: string, lineNumber?: number, options?: SearchOptions): Promise<EnhancedSearchResult[]>;
    /**
     * Combine vector and text search results
     */
    private combineResults;
    /**
     * Apply contextual boosting based on search context
     */
    private applyContextualBoosting;
    /**
     * Get file context for a chunk
     */
    private getFileContext;
    /**
     * Get related chunks for a chunk
     */
    private getRelatedChunks;
    /**
     * Get search statistics
     */
    getStats(): {
        totalChunks: number;
        totalEmbeddings: number;
        embeddingModel: string;
        embeddingDimension: number;
    };
}
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