Update app.py

app.py

@@ -35,6 +35,21 @@ pipe = AuraFlowPipeline.from_pretrained(
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
+@spaces.GPU()
+def infer_example(prompt, negative_prompt="", seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=5.0, num_inference_steps=28, model_version="0.2", comparison_mode=False, progress=gr.Progress(track_tqdm=True)):
+    seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator().manual_seed(seed)
+    image = pipe(
+            prompt = prompt, 
+            negative_prompt = negative_prompt,
+            width=width,
+            height=height,
+            guidance_scale = guidance_scale, 
+            num_inference_steps = num_inference_steps, 
+            generator = generator
+    ).images[0] 
+    return image, seed
+    
 @spaces.GPU(duration=95)
 def infer(prompt, negative_prompt="", seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=5.0, num_inference_steps=28, model_version="0.2", comparison_mode=False, progress=gr.Progress(track_tqdm=True)):
     
@@ -184,7 +199,7 @@ with gr.Blocks(css=css) as demo:
         
         gr.Examples(
             examples = examples,
-            fn = infer,
+            fn = infer_example,
             inputs = [prompt],
             outputs = [result, result_compare, seed],
             cache_examples="lazy"