UNPKG

@qianjue/mcp-memory-server

Version:

A Model Context Protocol (MCP) server for intelligent memory management with vector search capabilities

94 lines 2.69 kB
/** * 向量计算工具类 */ export declare class VectorUtils { /** * 计算两个向量的余弦相似度 */ static cosineSimilarity(vectorA: number[], vectorB: number[]): number; /** * 计算欧几里得距离 */ static euclideanDistance(vectorA: number[], vectorB: number[]): number; /** * 计算曼哈顿距离 */ static manhattanDistance(vectorA: number[], vectorB: number[]): number; /** * 向量归一化(L2范数) */ static normalize(vector: number[]): number[]; /** * 计算向量的L2范数(欧几里得范数) */ static l2Norm(vector: number[]): number; /** * 计算向量的L1范数(曼哈顿范数) */ static l1Norm(vector: number[]): number; /** * 向量加法 */ static add(vectorA: number[], vectorB: number[]): number[]; /** * 向量减法 */ static subtract(vectorA: number[], vectorB: number[]): number[]; /** * 向量标量乘法 */ static multiply(vector: number[], scalar: number): number[]; /** * 向量点积 */ static dotProduct(vectorA: number[], vectorB: number[]): number; /** * 批量计算相似度 */ static batchCosineSimilarity(queryVector: number[], vectors: number[][]): number[]; /** * 找到最相似的向量索引 */ static findMostSimilar(queryVector: number[], vectors: number[][], threshold?: number): { index: number; similarity: number; } | null; /** * 找到前N个最相似的向量 */ static findTopSimilar(queryVector: number[], vectors: number[][], topK?: number, threshold?: number): Array<{ index: number; similarity: number; }>; /** * 验证向量格式 */ static validateVector(vector: any): vector is number[]; /** * 检查向量维度是否匹配 */ static checkDimensions(vectors: number[][]): boolean; /** * 计算向量集合的统计信息 */ static computeStats(vectors: number[][]): { count: number; dimensions: number; avgMagnitude: number; minMagnitude: number; maxMagnitude: number; }; /** * 向量量化(减少精度以节省存储空间) */ static quantize(vector: number[], precision?: number): number[]; /** * 检查向量是否为零向量 */ static isZeroVector(vector: number[], tolerance?: number): boolean; /** * 生成随机向量(用于测试) */ static generateRandomVector(dimensions: number, normalize?: boolean): number[]; } //# sourceMappingURL=VectorUtils.d.ts.map