Update app.py

app.py

@@ -483,12 +483,14 @@ def run_lora(prompt, cfg_scale, steps, selected_indices, lora_scale_1, lora_scal
     # Load LoRA weights with respective scales
     lora_names = []
     lora_weights = []
+    lora_scales = [lora_scale_1, lora_scale_2, lora_scale_3, lora_scale_4]  # List of scales
     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)
+            # Use the scale based on the index, ensuring it does not exceed the list length
+            lora_weights.append(lora_scales[idx] if idx < len(lora_scales) else lora_scale_4)  # Default to last scale if out of bounds
             lora_path = lora['repo']
             weight_name = lora.get("weights")
             print(f"Lora Path: {lora_path}")
@@ -499,8 +501,8 @@ def run_lora(prompt, cfg_scale, steps, selected_indices, lora_scale_1, lora_scal
                 low_cpu_mem_usage=True,
                 adapter_name=lora_name
             )
-        print("Loaded LoRAs:", lora_names)
-        print("Adapter weights:", lora_weights)
+    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)
 ##        else: