Update app.py

app.py

@@ -18,13 +18,13 @@ css = """
     max-width: 512px;
 }
 """
-
+'''
 if torch.cuda.is_available():
     power_device = "GPU"
     device = "cuda"
-else:
-    power_device = "CPU"
-    device = "cpu"
+else:'''
+power_device = "CPU"
+device = "cpu"
 
 
 huggingface_token = os.getenv("HUGGINFACE_TOKEN")
@@ -48,7 +48,7 @@ pipe = FluxControlNetPipeline.from_pretrained(
 pipe.to(device)
 
 MAX_SEED = 1000000
-MAX_PIXEL_BUDGET = 1024 * 1024
+MAX_PIXEL_BUDGET = 512 * 512
 
 
 def process_input(input_image, upscale_factor, **kwargs):
@@ -150,9 +150,9 @@ with gr.Blocks(css=css) as demo:
             num_inference_steps = gr.Slider(
                 label="Number of Inference Steps",
                 minimum=8,
-                maximum=50,
+                maximum=25,
                 step=1,
-                value=28,
+                value=10,
             )
             upscale_factor = gr.Slider(
                 label="Upscale Factor",
@@ -225,8 +225,7 @@ with gr.Blocks(css=css) as demo:
 
     gr.Markdown("**Disclaimer:**")
     gr.Markdown(
-        "This demo is only for research purpose. Jasper cannot be held responsible for the generation of NSFW (Not Safe For Work) content through the use of this demo. Users are solely responsible for any content they create, and it is their obligation to ensure that it adheres to appropriate and ethical standards. Jasper provides the tools, but the responsibility for their use lies with the individual user."
-    )
+
     gr.on(
         [run_button.click],
         fn=infer,
@@ -239,8 +238,8 @@ with gr.Blocks(css=css) as demo:
             controlnet_conditioning_scale,
         ],
         outputs=result,
-        show_api=False,
-        # show_progress="minimal",
+        show_api=True,
+        show_progress="minimal",
     )
 
-demo.queue().launch(share=False, show_api=False)
+demo.queue().launch(share=False, show_api=True)