zrald/dist/core/vector-store.d.ts

Advanced Graph RAG MCP Server with sophisticated graph structures, operators, and agentic capabilities for AI agents

import { Node, Chunk } from '../types/graph.js';
export interface VectorSearchResult {
    id: string;
    score: number;
    node?: Node;
    chunk?: Chunk;
}
export declare class VectorStore {
    private dimension;
    private maxElements;
    private nodeMap;
    private chunkMap;
    private embeddings;
    private currentIndex;
    constructor(dimension?: number, maxElements?: number);
    initialize(): Promise<void>;
    addNode(node: Node): Promise<void>;
    addChunk(chunk: Chunk): Promise<void>;
    searchNodes(queryEmbedding: number[], topK?: number, threshold?: number): Promise<VectorSearchResult[]>;
    searchByNodeTypes(queryEmbedding: number[], nodeTypes: string[], topK?: number, threshold?: number): Promise<VectorSearchResult[]>;
    searchChunks(queryEmbedding: number[], topK?: number, threshold?: number): Promise<VectorSearchResult[]>;
    getNodeById(id: string): Promise<Node | undefined>;
    getChunkById(id: string): Promise<Chunk | undefined>;
    updateNode(node: Node): Promise<void>;
    removeNode(id: string): Promise<void>;
    batchAddNodes(nodes: Node[]): Promise<void>;
    batchAddChunks(chunks: Chunk[]): Promise<void>;
    getStats(): {
        totalNodes: number;
        totalChunks: number;
        dimension: number;
        maxElements: number;
    };
    saveIndex(filePath: string): Promise<void>;
    loadIndex(filePath: string): Promise<void>;
    clear(): Promise<void>;
    static cosineSimilarity(a: number[], b: number[]): number;
    static euclideanDistance(a: number[], b: number[]): number;
}
//# sourceMappingURL=vector-store.d.ts.map