Update app.py

app.py

@@ -34,7 +34,7 @@ def run(prompt, negative_prompt="", guidance_scale=7.0, pag_scale=3.0, randomize
     
     generator = torch.Generator(device="cuda").manual_seed(seed)
     image_normal = pipe(prompt, guidance_scale=guidance_scale, generator=generator, num_inference_steps=25).images[0]
-    return image_pag, image_normal, seed
+    return (image_pag, image_normal), seed
 
 css = '''
 .gradio-container{
@@ -51,13 +51,13 @@ with gr.Blocks(css=css, theme=theme) as demo:
       with gr.Row():
         prompt = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt", info="Leave blank to test unconditional generation")
         button = gr.Button("Generate", min_width=120)
-      output = ImageSlider(label="Your result image", interactive=False)
+      output = ImageSlider(label="Left: PAG+CFG, Right: CFG", interactive=False)
       with gr.Accordion("Advanced Settings", open=False):
         guidance_scale = gr.Number(label="Guidance Scale", value=7.0)
         pag_scale = gr.Number(label="Pag Scale", value=3.0)
         randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
         seed = gr.Slider(minimum=1, maximum=18446744073709551615, step=1, randomize=True)
-    gr.Examples(fn=run, examples=["", "an insect robot preparing a delicious meal, anime style", "a photo of a group of friends at an amusement park"], inputs=prompt, outputs=output, cache_examples=True)
+    gr.Examples(fn=run, examples=["", "an insect robot preparing a delicious meal, anime style", "a photo of a group of friends at an amusement park"], inputs=prompt, outputs=[output, seed], cache_examples=True)
     gr.on(
         triggers=[
             button.click,