Add AI embeddings and suggestions for categories, a few validation step tweaks/fixes

inventory-server/src/services/ai/embeddings/similarity.js

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+/**
+ * Vector similarity utilities
+ */
+
+/**
+ * Compute cosine similarity between two vectors
+ * @param {number[]} a
+ * @param {number[]} b
+ * @returns {number} Similarity score between -1 and 1
+ */
+function cosineSimilarity(a, b) {
+  if (!a || !b || a.length !== b.length) {
+    return 0;
+  }
+
+  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];
+  }
+
+  const denominator = Math.sqrt(normA) * Math.sqrt(normB);
+  if (denominator === 0) return 0;
+
+  return dotProduct / denominator;
+}
+
+/**
+ * Find top K most similar items from a collection
+ * @param {number[]} queryEmbedding - The embedding to search for
+ * @param {Array<{id: any, embedding: number[]}>} items - Items with embeddings
+ * @param {number} topK - Number of results to return
+ * @returns {Array<{id: any, similarity: number}>}
+ */
+function findTopMatches(queryEmbedding, items, topK = 10) {
+  if (!queryEmbedding || !items || items.length === 0) {
+    return [];
+  }
+
+  const scored = items.map(item => ({
+    id: item.id,
+    similarity: cosineSimilarity(queryEmbedding, item.embedding)
+  }));
+
+  scored.sort((a, b) => b.similarity - a.similarity);
+
+  return scored.slice(0, topK);
+}
+
+/**
+ * Find matches above a similarity threshold
+ * @param {number[]} queryEmbedding
+ * @param {Array<{id: any, embedding: number[]}>} items
+ * @param {number} threshold - Minimum similarity (0-1)
+ * @returns {Array<{id: any, similarity: number}>}
+ */
+function findMatchesAboveThreshold(queryEmbedding, items, threshold = 0.5) {
+  if (!queryEmbedding || !items || items.length === 0) {
+    return [];
+  }
+
+  const scored = items
+    .map(item => ({
+      id: item.id,
+      similarity: cosineSimilarity(queryEmbedding, item.embedding)
+    }))
+    .filter(item => item.similarity >= threshold);
+
+  scored.sort((a, b) => b.similarity - a.similarity);
+
+  return scored;
+}
+
+module.exports = {
+  cosineSimilarity,
+  findTopMatches,
+  findMatchesAboveThreshold
+};