Update build_index.py

build_index.py

@@ -19,14 +19,19 @@ print(f"📦 Loaded {len(products)} products from products.json")
 print("🧠 Loading CLIP model...")
 model = SentenceTransformer("sentence-transformers/clip-ViT-B-32", cache_folder="./cache")
 
-# Encode product names
+# Encode product names (normalize for cosine sim)
 print("🔎 Encoding product features...")
 product_names = [p["name"] for p in products]
-embeddings = model.encode(product_names, convert_to_numpy=True, show_progress_bar=True)
-
-# Build FAISS index
+embeddings = model.encode(
+    product_names,
+    convert_to_numpy=True,
+    show_progress_bar=True,
+    normalize_embeddings=True,   # important for cosine similarity
+)
+
+# Build FAISS index with cosine similarity (inner product on normalized vectors)
 dimension = embeddings.shape[1]
-index = faiss.IndexFlatL2(dimension)
+index = faiss.IndexFlatIP(dimension)
 index.add(embeddings)
 
 # Save index