Update app.py

app.py

@@ -16,19 +16,23 @@ import faiss
 # Initialize OpenAI client
 client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
 
-def initialize_embeddings_from_faiss(faiss_path: str):
-    """Load product embeddings directly from FAISS index"""
+def initialize_embeddings_from_pkl(pkl_path: str, faiss_path: str):
+    """從 PKL 檔案載入嵌入，並加載 FAISS 索引"""
+    if not os.path.exists(pkl_path):
+        raise FileNotFoundError(f"Embedding file not found at {pkl_path}")
+    
     if not os.path.exists(faiss_path):
         raise FileNotFoundError(f"FAISS index file not found at {faiss_path}")
     
+    print(f"Loading embeddings from {pkl_path}...")
+    with open(pkl_path, "rb") as f:
+        embeddings = pickle.load(f)
+    
     print(f"Loading FAISS index from {faiss_path}...")
     index = faiss.read_index(faiss_path)
     
-    # Extract embeddings from FAISS index
-    product_embeddings_array = faiss.vector_to_array(index.xb).reshape(index.ntotal, index.d)
     print(f"FAISS index loaded with {index.ntotal} embeddings.")
-    
-    return index, product_embeddings_array
+    return index, embeddings
 
 # Load CSV data
 #df = pd.read_csv("item_new.csv", encoding='utf-8')
@@ -37,7 +41,11 @@ def initialize_embeddings_from_faiss(faiss_path: str):
 # Load embeddings from FAISS
 print("Initializing embeddings...")
 faiss_path = "product_index.faiss"  # Path to FAISS index file
-faiss_index, product_embeddings_array = initialize_embeddings_from_faiss(faiss_path)
+pkl_path = "product_embeddings.pkl"  # Path to embeddings file
+
+# 初始化嵌入
+faiss_index, product_embeddings_array = initialize_embeddings_from_pkl(pkl_path, faiss_path)
+print(f"Loaded embeddings with shape: {len(product_embeddings_array)} x {len(product_embeddings_array[0])}")
 print("Embeddings initialized")