Rename appCODE.py to app.py

appCODE.py → app.py

@@ -28,10 +28,16 @@ if os.path.exists(lora_path):
     lora_state_dict = torch.load(lora_path, map_location=device)
     
     try:
+        # Assuming `pipeline` has a method `load_lora_weights` to load LoRA weights directly
+        # If the pipeline does not support this method, we might need to apply the LoRA weights manually
         pipeline.load_lora_weights(lora_state_dict)  # Load LoRA weights into the pipeline
         print("✅ LoRA weights loaded successfully!")
-    except ValueError as e:
-        print(f"❌ Error loading LoRA: {e}")
+    except AttributeError:
+        print("❌ pipeline does not support load_lora_weights method. Attempting manual application.")
+        # Manual application of weights if load_lora_weights method does not exist
+        # This is just a placeholder; you'll need to update this part based on how your LoRA weights should be applied
+        # Example:
+        # pipeline.model.load_state_dict(lora_state_dict, strict=False)
 else:
     print("⚠️ LoRA file not found! Running base model.")