Update app.py

app.py

@@ -231,7 +231,7 @@ def remove_lora_2(selected_indices, loras_state):
 
 def remove_lora_3(selected_indices, loras_state):
     if len(selected_indices) >= 3:
-        selected_indices.pop(1)
+        selected_indices.pop(2)
     selected_info_1 = "Select a Celebrity as LoRA 1"
     selected_info_2 = "Select a LoRA 2"
     selected_info_3 = "Select a LoRA 3"
@@ -267,7 +267,7 @@ def remove_lora_3(selected_indices, loras_state):
 
 def remove_lora_4(selected_indices, loras_state):
     if len(selected_indices) >= 4:
-        selected_indices.pop(1)
+        selected_indices.pop(3)
     selected_info_1 = "Select a Celebrity as LoRA 1"
     selected_info_2 = "Select a LoRA 2"
     selected_info_3 = "Select a LoRA 3"
@@ -451,12 +451,27 @@ def generate_image(prompt, steps, seed, cfg_scale, width, height, progress):
             yield img, seed, f"Generated image {img} with seed {seed}"
     return img
 
-@spaces.GPU(duration=75)
+@spaces.GPU(duration=85)
 def run_lora(prompt, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2, lora_scale_3, lora_scale_4, randomize_seed, seed, width, height, loras_state, progress=gr.Progress(track_tqdm=True)):
     if not selected_indices:
         raise gr.Error("You must select at least one LoRA before proceeding.")
 
     selected_loras = [loras_state[idx] for idx in selected_indices]
+    
+    # Debugging snippet: Inspect LoRAs before loading
+    for idx, lora in enumerate(selected_loras):
+        print(f"Inspecting LoRA {idx + 1}: {lora['title']}")
+        try:
+            lora_weights = torch.load(lora['repo'])  # Load the LoRA weights
+            print(f"LoRA Parameter Keys for {lora['title']}: {list(lora_weights.keys())}")
+        except Exception as e:
+            print(f"Error loading LoRA weights for {lora['title']} from {lora['repo']}: {e}")
+            raise gr.Error(f"Failed to load LoRA weights for {lora['title']}.")
+
+    # Print the selected LoRAs
+    print("Running with the following LoRAs:")
+    for lora in selected_loras:
+        print(f"- {lora['title']} from {lora['repo']} with scale {lora_scale_1 if selected_loras.index(lora) == 0 else lora_scale_2}")
 
     # Build the prompt with trigger words
     prepends = []
@@ -470,7 +485,7 @@ def run_lora(prompt, cfg_scale, steps, selected_indices, lora_scale_1, lora_scal
                 appends.append(trigger_word)
     prompt_mash = " ".join(prepends + [prompt] + appends)
     print("Prompt Mash: ", prompt_mash)
-    print("--Seed--:", seed)
+    print(":--Seed--:", seed)
 
     # Unload previous LoRA weights
     with calculateDuration("Unloading LoRA"):
@@ -484,20 +499,24 @@ def run_lora(prompt, cfg_scale, steps, selected_indices, lora_scale_1, lora_scal
     with calculateDuration("Loading LoRA weights"):
         for idx, lora in enumerate(selected_loras):
             lora_name = f"lora_{idx}"
-            lora_names.append(lora_name)
-            print(f"Lora Name: {lora_name}")
-            lora_weights.append(lora_scale_1 if idx == 0 else lora_scale_2)
+            lora_weights_path = lora.get("weights")
+            print(f"Loading LoRA: {lora['title']} from {lora['repo']} with adapter name: {lora_name}")
+        
             pipe.load_lora_weights(
                 lora['repo'],
-                weight_name=lora.get("weights"),
+                weight_name=lora_weights_path,
                 low_cpu_mem_usage=True,
                 adapter_name=lora_name,
-            )
-        print("Base Model:", base_model)
-        print("Loaded LoRAs:", selected_indices)
-        print("Adapter weights:", lora_weights)
+                merge_and_unload=True,  # Explicitly merge weights to avoid runtime conflicts
+        )
         
+        print("Adapter weights:", lora_weights)
+    try:
         pipe.set_adapters(lora_names, adapter_weights=lora_weights)
+    except Exception as e:
+        print(f"Error while setting adapters: {e}")
+        raise
+#pipe.set_adapters(lora_names, adapter_weights=lora_weights)
 
     # Set random seed if required
     if randomize_seed:
@@ -512,7 +531,7 @@ def run_lora(prompt, cfg_scale, steps, selected_indices, lora_scale_1, lora_scal
         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)
 
-run_lora.zerogpu = True
+run_lora.zerogpu = False
 
 def get_huggingface_safetensors(link):
     split_link = link.split("/")
@@ -703,7 +722,8 @@ with gr.Blocks(theme=gr.themes.Soft(font=font), css=css, delete_cache=(128, 256)
     gallery.select(
         update_selection,
         inputs=[selected_indices, loras_state, width, height],
-        outputs=[prompt, selected_info_1, selected_info_2, selected_info_3, selected_info_4, selected_indices, lora_scale_1, lora_scale_2, lora_scale_3, lora_scale_4, width, height, lora_image_1, lora_image_2, lora_image_3, lora_image_4])
+        outputs=[prompt, selected_info_1, selected_info_2, selected_info_3, selected_info_4, selected_indices, lora_scale_1, lora_scale_2, lora_scale_3, lora_scale_4, width, height, lora_image_1, lora_image_2, lora_image_3, lora_image_4]
+    )
     remove_button_1.click(
         remove_lora_1,
         inputs=[selected_indices, loras_state],