MCPMem

import { OpenAIEmbeddingProvider } from './openai-provider.js'; import type { EmbeddingConfig, EmbeddingProvider } from './provider.js'; export class EmbeddingService { private provider: EmbeddingProvider; constructor(config: EmbeddingConfig) { this.provider = this.createProvider(config); } private createProvider(config: EmbeddingConfig): EmbeddingProvider { switch (config.provider) { case 'openai': if (!config.apiKey) { throw new Error('OpenAI API key is required for OpenAI provider'); } return new OpenAIEmbeddingProvider(config.apiKey, config.model, config.baseURL); case 'local': throw new Error('Local embedding provider not yet implemented'); default: throw new Error(`Unknown embedding provider: ${config.provider}`); } } async generateEmbedding(text: string): Promise<number[]> { if (!text.trim()) { throw new Error('Text cannot be empty'); } return this.provider.generateEmbedding(text); } getDimensions(): number { return this.provider.getDimensions(); } getModelName(): string { return this.provider.getModelName(); } static cosineSimilarity(a: number[], b: number[]): number { if (a.length !== b.length) { throw new Error('Embeddings must have the same length'); } let dotProduct = 0; let normA = 0; let normB = 0; for (let i = 0; i < a.length; i++) { dotProduct += a[i] * b[i]; normA += a[i] * a[i]; normB += b[i] * b[i]; } normA = Math.sqrt(normA); normB = Math.sqrt(normB); if (normA === 0 || normB === 0) { return 0; } return dotProduct / (normA * normB); } static preprocessText(text: string): string { return text .trim() .replace(/\s+/g, ' ') .replace(/[\r\n]+/g, ' ') .substring(0, 8000); } }