Update app.py

app.py

@@ -563,7 +563,7 @@ def infer_upscale(
     progress=gr.Progress(track_tqdm=True),
 ):
     if input_image is None:
-        return None, seed
+        return None, seed, gr.update(), gr.update(), gr.update(), gr.update(), gr.update(visible=True, value="Please upload an image for upscaling.")
 
     try:
 
@@ -609,15 +609,15 @@ def infer_upscale(
         # resize to target desired size
         image = image.resize((w_original * upscale_factor, h_original * upscale_factor))
         
-        return image, seed
 
+
+        return image, seed, num_inference_steps, upscale_factor, controlnet_conditioning_scale, gr.update(), gr.update(visible=False)
     except Exception as e:
         print(f"Error in infer_upscale: {str(e)}")
         import traceback
         traceback.print_exc()
-        return None, seed
+        return None, seed, gr.update(), gr.update(), gr.update(), gr.update(), gr.update(visible=True, value=f"Error: {str(e)}")
         
-
 def check_upscale_input(input_image, *args):
     if input_image is None:
         return gr.update(interactive=False), *args, gr.update(visible=True, value="Please upload an image for upscaling.")
@@ -785,8 +785,9 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css, delete_cache=(60, 3600)) as a
         inputs=[upscale_input],
         outputs=[upscale_button]
     )
-
     
+    upscale_error = gr.Markdown(visible=False, value="")
+
     upscale_button.click(
         infer_upscale,
         inputs=[
@@ -797,17 +798,15 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css, delete_cache=(60, 3600)) as a
             upscale_factor,
             controlnet_conditioning_scale,
         ],
-
-
         outputs=[
-            upscale_input,
-            upscale_seed,
-            upscale_randomize_seed,
+            upscale_result,
+            upscale_seed_output,
             upscale_steps,
             upscale_factor,
             controlnet_conditioning_scale,
+            upscale_randomize_seed,
             upscale_error
-        ]
+        ],
     ).then(
         infer_upscale,
         inputs=[