Update main.py

main.py

@@ -69,25 +69,29 @@ answer_embeddings = load_or_download_embeddings()
 # --- Load Model + Data ---
 def load_resources():
     try:
+        # Load model
         model = SentenceTransformer(MODEL_PATH)
+        # Load dataset
         df = pd.read_csv(CSV_PATH).dropna(subset=['question', 'answer'])
 
-        emb_path = ensure_embeddings_file()
-        if emb_path and os.path.exists(emb_path):
-            answer_embeddings = torch.load(emb_path)
-            print("✅ Loaded precomputed embeddings")
-        else:
-            print("⚙️ Computing new embeddings...")
+        # Use already loaded embeddings from HF
+        if answer_embeddings is None:
+            print("⚙️ Computing new embeddings from scratch...")
             answers = df['answer'].tolist()
-            answer_embeddings = model.encode(answers, convert_to_tensor=True)
-            torch.save(answer_embeddings, EMBEDDINGS_PATH)
+            embeddings = model.encode(answers, convert_to_tensor=True)
+            torch.save(embeddings, EMBEDDINGS_PATH)
             print("✅ Computed and saved embeddings")
+        else:
+            embeddings = answer_embeddings
+            print("✅ Using embeddings loaded from Hugging Face")
+
+        return model, df, embeddings
 
-        return model, df, answer_embeddings
     except Exception as e:
         print(f"❌ Error loading resources: {e}")
         return None, None, None
 
+
 model, df, answer_embeddings = load_resources()
 
 # --- FastAPI Setup ---