Update app.py

app.py

@@ -409,6 +409,7 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
 
     print("Loaded state dict:", loaded_state_dict)
     print("Last LoRA:", last_lora, "| Current LoRA:", repo_name)
+    print("LoRA scale:", lora_scale, "Type:", type(lora_scale))
 
     # Prepare control images and scales based on face detection
     if face_detected:
@@ -437,14 +438,43 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
     # Improved LoRA loading and caching
     if last_lora != repo_name:
         if last_fused:
-            pipe.unfuse_lora()
-            pipe.unload_lora_weights()
-            pipe.unload_textual_inversion()
+            try:
+                # Unload previous LoRA adapter
+                pipe.delete_adapters(["style_lora"])
+                print("Unloaded previous LoRA adapter")
+            except Exception as e:
+                print(f"Warning: Could not unload previous adapter: {e}")
+                # Try alternative method
+                try:
+                    pipe.unload_lora_weights()
+                    print("Unloaded LoRA weights via alternative method")
+                except:
+                    pass
+            
+            try:
+                pipe.unload_textual_inversion()
+                print("Unloaded textual inversion")
+            except Exception as e:
+                print(f"Warning: Could not unload textual inversion: {e}")
 
         # Load LoRA with better error handling
         try:
-            pipe.load_lora_weights(full_path_lora)
-            pipe.fuse_lora(lora_scale)
+            # For diffusers >= 0.27, load_lora_weights expects different parameters
+            if full_path_lora.endswith('.safetensors') or full_path_lora.endswith('.bin'):
+                # Single file loading
+                import os
+                lora_dir = os.path.dirname(full_path_lora)
+                lora_file = os.path.basename(full_path_lora)
+                print(f"Loading LoRA from: {lora_dir}/{lora_file}")
+                pipe.load_lora_weights(lora_dir, weight_name=lora_file, adapter_name="style_lora")
+            else:
+                # Directory loading
+                print(f"Loading LoRA from directory: {full_path_lora}")
+                pipe.load_lora_weights(full_path_lora, adapter_name="style_lora")
+            
+            # Set adapter scale instead of fusing
+            pipe.set_adapters(["style_lora"], adapter_weights=[float(lora_scale)])
+            print(f"LoRA loaded and adapter set with scale: {lora_scale}")
             last_fused = True
             
             # Handle pivotal tuning embeddings
@@ -466,8 +496,13 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
                     tokenizer=pipe.tokenizer_2
                 )
         except Exception as e:
+            import traceback
+            full_error = traceback.format_exc()
             print(f"Error loading LoRA: {e}")
-            raise gr.Error(f"Failed to load LoRA: {str(e)}")
+            print(f"Full traceback:\n{full_error}")
+            print(f"Full path attempted: {full_path_lora}")
+            print(f"LoRA scale attempted: {lora_scale} (type: {type(lora_scale)})")
+            raise gr.Error(f"Failed to load LoRA: {str(e)}\n\nPath: {full_path_lora}\nScale: {lora_scale}")
 
     print("Processing prompt...")
     conditioning, pooled = compel(prompt)