returns tuple of cat_idx and score

app.py

@@ -214,7 +214,7 @@ def get_sorted_cosine_similarity(embeddings_metadata):
         cat = categories[index]
         cat_embed = category_embeddings[cat]
         # Calc cosine sim
-        cat_scores.append((cat, np.dot(input_embedding,cat_embed)))
+        cat_scores.append((index, np.dot(input_embedding,cat_embed)))
         # Store doc_id and score as a tuple