Update app.py

app.py

@@ -196,14 +196,14 @@ def randomize_loras(selected_indices, loras_state):
         lora_scale_1 = 1.15
         lora_scale_2 = 1.15
         lora_scale_3 = 1.15
-        lora_image_1 = lora1['image']
-        lora_image_2 = lora2['image']
-        lora_image_3 = lora3['image']
+        lora_image_1 = lora1.get('image', 'path/to/default/image.png')
+        lora_image_2 = lora2.get('image', 'path/to/default/image.png')
+        lora_image_3 = lora3.get('image', 'path/to/default/image.png')
         random_prompt = random.choice(prompt_values)
         return selected_info_1, selected_info_2, selected_info_3, selected_indices, lora_scale_1, lora_scale_2, lora_scale_3, lora_image_1, lora_image_2, lora_image_3, random_prompt
     except Exception as e:
         print(f"Error in randomize_loras: {str(e)}")
-        return "Error", "Error", "Error", [], 1.15, 1.15, 1.15, None, None, None, ""
+        return "Error", "Error", "Error", [], 1.15, 1.15, 1.15, 'path/to/default/image.png', 'path/to/default/image.png', 'path/to/default/image.png', ""
 
 def add_custom_lora(custom_lora, selected_indices, current_loras):
     if custom_lora:
@@ -366,7 +366,7 @@ def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps
 
 def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2, lora_scale_3, randomize_seed, seed, width, height, loras_state, progress=gr.Progress(track_tqdm=True)):
     try:
-        # 한글 감지 및 번역
+        # 한글 감지 및 번역 (이 부분은 그대로 유지)
         if any('\u3131' <= char <= '\u318E' or '\uAC00' <= char <= '\uD7A3' for char in prompt):
             translated = translator(prompt, max_length=512)[0]['translation_text']
             print(f"Original prompt: {prompt}")
@@ -378,7 +378,7 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
 
         selected_loras = [loras_state[idx] for idx in selected_indices]
 
-        # Build the prompt with trigger words
+        # Build the prompt with trigger words (이 부분은 그대로 유지)
         prepends = []
         appends = []
         for lora in selected_loras:
@@ -396,41 +396,52 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
             pipe.unload_lora_weights()
             pipe_i2i.unload_lora_weights()
             
-        print(pipe.get_active_adapters())
+        print(f"Active adapters before loading: {pipe.get_active_adapters()}")
+        
         # Load LoRA weights with respective scales
         lora_names = []
         lora_weights = []
         with calculateDuration("Loading LoRA weights"):
             for idx, lora in enumerate(selected_loras):
-                lora_name = f"lora_{idx}"
-                lora_names.append(lora_name)
-                lora_weights.append(lora_scale_1 if idx == 0 else lora_scale_2 if idx == 1 else lora_scale_3)
-                lora_path = lora['repo']
-                weight_name = lora.get("weights")
-                print(f"Lora Path: {lora_path}")
-                if image_input is not None:
-                    if weight_name:
-                        pipe_i2i.load_lora_weights(lora_path, weight_name=weight_name, low_cpu_mem_usage=True, adapter_name=lora_name)
+                try:
+                    lora_name = f"lora_{idx}"
+                    lora_path = lora['repo']
+                    weight_name = lora.get("weights")
+                    print(f"Loading LoRA {lora_name} from {lora_path}")
+                    if image_input is not None:
+                        if weight_name:
+                            pipe_i2i.load_lora_weights(lora_path, weight_name=weight_name, adapter_name=lora_name)
+                        else:
+                            pipe_i2i.load_lora_weights(lora_path, adapter_name=lora_name)
                     else:
-                        pipe_i2i.load_lora_weights(lora_path, low_cpu_mem_usage=True, adapter_name=lora_name)
-                else:
-                    if weight_name:
-                        pipe.load_lora_weights(lora_path, weight_name=weight_name, low_cpu_mem_usage=True, adapter_name=lora_name)
-                    else:
-                        pipe.load_lora_weights(lora_path, low_cpu_mem_usage=True, adapter_name=lora_name)
+                        if weight_name:
+                            pipe.load_lora_weights(lora_path, weight_name=weight_name, adapter_name=lora_name)
+                        else:
+                            pipe.load_lora_weights(lora_path, adapter_name=lora_name)
+                    lora_names.append(lora_name)
+                    lora_weights.append(lora_scale_1 if idx == 0 else lora_scale_2 if idx == 1 else lora_scale_3)
+                except Exception as e:
+                    print(f"Failed to load LoRA {lora_name}: {str(e)}")
+
             print("Loaded LoRAs:", lora_names)
             print("Adapter weights:", lora_weights)
-            if image_input is not None:
-                pipe_i2i.set_adapters(lora_names, adapter_weights=lora_weights)
+            
+            if lora_names:
+                if image_input is not None:
+                    pipe_i2i.set_adapters(lora_names, adapter_weights=lora_weights)
+                else:
+                    pipe.set_adapters(lora_names, adapter_weights=lora_weights)
             else:
-                pipe.set_adapters(lora_names, adapter_weights=lora_weights)
-        print(pipe.get_active_adapters())
-        # Set random seed for reproducibility
+                print("No LoRAs were successfully loaded.")
+                return None, seed, gr.update(visible=False)
+
+        print(f"Active adapters after loading: {pipe.get_active_adapters()}")
+
+        # 여기서부터 이미지 생성 로직 (이 부분은 그대로 유지)
         with calculateDuration("Randomizing seed"):
             if randomize_seed:
                 seed = random.randint(0, MAX_SEED)
 
-        # Generate image
         if image_input is not None:
             final_image = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, seed)
         else:
@@ -442,15 +453,12 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
                 final_image = image
                 progress_bar = f'<div class="progress-container"><div class="progress-bar" style="--current: {step_counter}; --total: {steps};"></div></div>'
                 yield image, seed, gr.update(value=progress_bar, visible=True)
-            
-
 
         if final_image is None:
             raise Exception("Failed to generate image")
         
         return final_image, seed, gr.update(visible=False)
 
-
     except Exception as e:
         print(f"Error in run_lora: {str(e)}")
         return None, seed, gr.update(visible=False)