Update app.py

app.py

@@ -512,7 +512,53 @@ def run_lora(prompt, cfg_scale, steps, selected_info_1, selected_info_2, selecte
             lora_path = lora['repo']
             weight_name = lora.get("weights")
             print(f"Lora Path: {lora_path}")
-            pipe_to_use = pipe_i2i if 
+            pipe_to_use = pipe_i2i if image_input is not None else pipe
+            pipe_to_use.load_lora_weights(
+                lora_path, 
+                weight_name=weight_name if weight_name else None,
+                low_cpu_mem_usage=True,
+                adapter_name=lora_name
+            )
+    print("Loaded LoRAs:", lora_names)
+    print("Adapter weights:", lora_weights)
+    
+    # Set random seed for reproducibility
+    with calculateDuration("Randomizing seed"):
+        print("Image Seed:", seed)
+
+    # Generate image
+    try:
+        if image_input is not None:
+            final_image = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, seed)
+            print("Debug: generate_image_to_image output type:", type(final_image))  # Debugging
+            print("Debug: generate_image_to_image output value:", final_image)  # Debugging
+            yield final_image, seed, gr.update(visible=False)
+        else:
+            image_generator = generate_image(prompt_mash, steps, seed, cfg_scale, width, height, progress)
+            # Consume the generator to get the final image
+            final_image = None
+            step_counter = 0
+            for image in image_generator:
+                print("Debug: generate_image yielded type:", type(image))  # Debugging
+                print("Debug: generate_image yielded value:", image)  # Debugging
+                step_counter += 1
+                final_image = image
+                print(f"Yielding image {step_counter}/{steps}")  # Debugging statement
+                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:
+                print("No final image generated.")  # Debugging statement
+            else:
+                print("Debug: final_image type:", type(final_image))  # Debugging
+                print("Debug: final_image value:", final_image)  # Debugging
+                
+            yield final_image, seed, gr.update(value=progress_bar, visible=False)
+
+    except Exception as e:
+        print(f"Error during image generation: {e}")  # Error handling
+        raise gr.Error("An error occurred during image generation.")
+
+run_lora.zerogpu = True
 
 def get_huggingface_safetensors(link):
     split_link = link.split("/")