Update app.py

app.py

@@ -30,7 +30,6 @@ def infer(
     height=1024,
     guidance_scale=3,
     num_inference_steps=20,
-    num_images=1,
     progress=gr.Progress(track_tqdm=True),
 ):
     if randomize_seed:
@@ -38,7 +37,7 @@ def infer(
 
     generator = torch.Generator().manual_seed(seed)
 
-    images = pipe(
+    image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
         guidance_scale=guidance_scale,
@@ -46,10 +45,10 @@ def infer(
         width=width,
         height=height,
         generator=generator,
-        num_images_per_prompt=num_images,
-    ).images
+    ).images[0]
+
+    return image, seed
 
-    return images, seed
 
 examples = [
         "A capybara wearing a suit holding a sign that reads Hello World",
@@ -64,7 +63,7 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # [Stable Diffusion 3.5 Medium Turbo]")
+        gr.Markdown(" # [Stable Diffusion 3.5 Medium Turbo")
         with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
@@ -76,7 +75,7 @@ with gr.Blocks(css=css) as demo:
 
             run_button = gr.Button("Run", scale=0, variant="primary")
 
-        result = gr.Gallery(label="Results").style(grid=[4], preview=True)
+        result = gr.Image(label="Result", show_label=False)
 
         with gr.Accordion("Advanced Settings", open=False):
             negative_prompt = gr.Text(
@@ -130,14 +129,6 @@ with gr.Blocks(css=css) as demo:
                     value=20,
                 )
 
-            num_images = gr.Slider(
-                label="Number of Images",
-                minimum=1,
-                maximum=4,
-                step=1,
-                value=1,
-            )
-
         gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=True, cache_mode="lazy")
     gr.on(
         triggers=[run_button.click, prompt.submit],
@@ -151,10 +142,9 @@ with gr.Blocks(css=css) as demo:
             height,
             guidance_scale,
             num_inference_steps,
-            num_images,
         ],
         outputs=[result, seed],
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()