Update app.py

app.py

@@ -67,24 +67,24 @@ def generate(prompt, negative_prompt, width=1024, height=1024, num_inference_ste
 
     clean_lora_id = lora_id.strip() if lora_id else ""
 
-    try:
-        # --- IF LORA ID IS NONE, USE ONE LORA ---
-        if not clean_lora_id:
-            print("No custom LoRA provided. Using ONLY the base LoRA.")
-            # Activate just the default LoRA
-            pipe.set_adapters([DEFAULT_LORA_NAME], adapter_weights=[1.0])
-
-        # --- OTHERWISE, LOAD AND USE TWO LORAS ---
-        else:
-            print(f"Custom LoRA provided. Loading '{clean_lora_id}' and combining with base LoRA.")
-            # Load the custom LoRA fresh for this run
-            pipe.load_lora_weights(clean_lora_id, adapter_name=CUSTOM_LORA_NAME)
-
-            # Activate BOTH LoRAs together
-            pipe.set_adapters(
-                [DEFAULT_LORA_NAME, CUSTOM_LORA_NAME],
-                adapter_weights=[1.0, 1.0]  # Strength for base, strength for custom
-            )
+    # try:
+    # --- IF LORA ID IS NONE, USE ONE LORA ---
+    if not clean_lora_id:
+        print("No custom LoRA provided. Using ONLY the base LoRA.")
+        # Activate just the default LoRA
+        pipe.set_adapters([DEFAULT_LORA_NAME], adapter_weights=[1.0])
+
+    # --- OTHERWISE, LOAD AND USE TWO LORAS ---
+    else:
+        print(f"Custom LoRA provided. Loading '{clean_lora_id}' and combining with base LoRA.")
+        # Load the custom LoRA fresh for this run
+        pipe.load_lora_weights(clean_lora_id, adapter_name=CUSTOM_LORA_NAME)
+
+        # Activate BOTH LoRAs together
+        pipe.set_adapters(
+            [DEFAULT_LORA_NAME, CUSTOM_LORA_NAME],
+            adapter_weights=[1.0, 1.0]  # Strength for base, strength for custom
+        )
 
 
     pipe.to("cuda")