Smart Connections MCP Server

/** * Embedding utilities for vector similarity calculations */ /** * Calculate cosine similarity between two vectors */ export function cosineSimilarity(vecA, vecB) { if (vecA.length !== vecB.length) { throw new Error('Vectors must have the same length'); } let dotProduct = 0; let normA = 0; let normB = 0; for (let i = 0; i < vecA.length; i++) { dotProduct += vecA[i] * vecB[i]; normA += vecA[i] * vecA[i]; normB += vecB[i] * vecB[i]; } const magnitude = Math.sqrt(normA) * Math.sqrt(normB); if (magnitude === 0) { return 0; } return dotProduct / magnitude; } /** * Find k nearest neighbors using cosine similarity */ export function findNearestNeighbors(queryVec, vectors, k, threshold = 0.0) { const similarities = vectors.map(item => ({ id: item.id, similarity: cosineSimilarity(queryVec, item.vec), metadata: item.metadata })); // Filter by threshold and sort by similarity (descending) return similarities .filter(item => item.similarity >= threshold) .sort((a, b) => b.similarity - a.similarity) .slice(0, k); } /** * Normalize a vector to unit length */ export function normalizeVector(vec) { const norm = Math.sqrt(vec.reduce((sum, val) => sum + val * val, 0)); if (norm === 0) return vec; return vec.map(val => val / norm); } //# sourceMappingURL=embedding-utils.js.map