pulse-ai-utils/supabase/vector-helpers.d.ts

Utility functions and helpers for AI-powered applications

/**
 * Helper functions for working with pgvector data in Supabase
 */
/**
 * Parse a pgvector string representation to a JavaScript array
 * Handles the string format returned by Supabase: "[0.1,0.2,0.3,...]"
 */
export declare function parseVectorString(vectorString: string): number[];
/**
 * Convert a JavaScript array to pgvector format for insertion
 * This handles the proper formatting for Supabase/PostgreSQL
 */
export declare function formatVectorForInsert(vector: number[]): string;
/**
 * Safely get embedding from Supabase response
 * Handles both array and string formats
 */
export declare function getEmbeddingArray(data: any): number[] | null;
/**
 * Calculate cosine similarity between two vectors
 * Useful for client-side similarity calculations
 */
export declare function cosineSimilarity(vec1: number[], vec2: number[]): number;
/**
 * Batch process content with embeddings
 * Ensures proper formatting for bulk operations
 */
export declare function prepareContentForBulkInsert(documents: Array<{
    id: string;
    data: any;
    embedding?: number[];
}>): Array<any>;
/**
 * Transform Supabase response to ensure embeddings are arrays
 * Use this after fetching data with embedding fields
 */
export declare function transformSupabaseResponse<T extends {
    embedding?: any;
}>(data: T[]): T[];