Update app.py

app.py

@@ -147,7 +147,7 @@ def infer_with_lora(input_image, prompt, selected_index, custom_lora, seed=42, r
         lora_to_use = custom_lora
     elif selected_index is not None and flux_loras and selected_index < len(flux_loras):
         lora_to_use = flux_loras[selected_index]
-    
+    print(f"Loaded {len(flux_loras)} LoRAs from JSON")
     # Load LoRA if needed
     if lora_to_use and lora_to_use != current_lora:
         try:
@@ -160,11 +160,7 @@ def infer_with_lora(input_image, prompt, selected_index, custom_lora, seed=42, r
             if lora_path:
                 pipe.load_lora_weights(lora_path, adapter_name="selected_lora")
                 current_lora = lora_to_use
-                
-                # Add trigger word to prompt if available
-                trigger_word = lora_to_use.get("trigger_word", "")
-                if trigger_word and trigger_word not in prompt:
-                    prompt = f"convert the style of this portrait photo to {trigger_word} while maintaining the identity of the person. {prompt}. make sure to maintain the person's facial identity and features, while still changing the style to {trigger_word}."
+
             
         except Exception as e:
             print(f"Error loading LoRA: {e}")
@@ -172,13 +168,12 @@ def infer_with_lora(input_image, prompt, selected_index, custom_lora, seed=42, r
     
     # Set LoRA scale if LoRA is loaded
     if current_lora and hasattr(pipe, 'set_adapters'):
-        try:
-            pipe.set_adapters("selected_lora", adapter_weights=[lora_scale])
-        except:
-            # Fallback for older diffusers versions
-            pass
+        pipe.set_adapters("selected_lora", adapter_weights=[lora_scale])
     
     input_image = input_image.convert("RGB")
+    # Add trigger word to prompt
+    trigger_word = lora_to_use["trigger_word"]
+    prompt = f"convert the style of this portrait photo to {trigger_word} while maintaining the identity of the person. {prompt}. make sure to maintain the person's facial identity and features, while still changing the style to {trigger_word}."
     
     try:
         image = pipe(