antarys/dist/src/worker.d.ts

High-performance Node.js client for Antarys vector database with HTTP/2, connection pooling, and intelligent caching

interface WorkerMessage {
    task: string;
    data: any;
    taskId: string;
}
interface WorkerResponse {
    taskId: string;
    result?: any;
    error?: string;
}
/**
 * Optimize vector for JSON serialization and network transmission
 * Round to reasonable precision to reduce payload size
 */
declare function optimizeVector(vector: number[]): number[];
/**
 * Preprocess vectors for optimal serialization
 */
declare function preprocessVectors(vectors: any[]): any[];
/**
 * Process query vectors for optimal performance
 */
declare function processQueryVectors(vectors: number[][]): number[][];
/**
 * Process batch data with additional optimizations
 */
declare function processBatch(batch: any[]): any[];
/**
 * Calculate vector similarity using cosine similarity
 */
declare function calculateCosineSimilarity(vectorA: number[], vectorB: number[]): number;
/**
 * Batch similarity calculation for local filtering/ranking
 */
declare function batchSimilarityCalculation(queryVector: number[], targetVectors: number[][]): number[];
/**
 * Normalize vectors to unit length for cosine similarity optimization
 */
declare function normalizeVectors(vectors: number[][]): number[][];
/**
 * Validate vector dimensions against expected dimensions
 */
declare function validateVectorDimensions(vectors: any[], expectedDimensions: number): {
    valid: boolean;
    errors: string[];
};
/**
 * Convert vectors to Float32Array for better memory efficiency and performance
 */
declare function convertToFloat32Arrays(vectors: number[][]): Float32Array[];
/**
 * Compress vectors using simple quantization (for storage optimization)
 */
declare function quantizeVectors(vectors: number[][], precision?: number): number[][];
/**
 * Main worker message handler
 */
declare function handleWorkerMessage(message: WorkerMessage): WorkerResponse;
export { optimizeVector, preprocessVectors, processQueryVectors, processBatch, calculateCosineSimilarity, batchSimilarityCalculation, normalizeVectors, validateVectorDimensions, convertToFloat32Arrays, quantizeVectors, handleWorkerMessage };
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