Update app.py

app.py

@@ -14,27 +14,36 @@ MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048
 
 @spaces.GPU()
-def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
+def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, guidance_scale=7.5, progress=gr.Progress(track_tqdm=True)):
+    if width > MAX_IMAGE_SIZE or height > MAX_IMAGE_SIZE:
+        raise ValueError("Image size exceeds the maximum allowed dimensions.")
+    
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
     generator = torch.Generator().manual_seed(seed)
-    image = pipe(
-            prompt = prompt, 
-            width = width,
-            height = height,
-            num_inference_steps = num_inference_steps, 
-            generator = generator,
-            guidance_scale=0.0
-    ).images[0] 
-    return image, seed
+    
+    try:
+        image = pipe(
+                prompt=prompt, 
+                width=width,
+                height=height,
+                num_inference_steps=num_inference_steps, 
+                generator=generator,
+                guidance_scale=guidance_scale
+        ).images[0] 
+    except Exception as e:
+        return None, seed, f"Error: {str(e)}"
+    
+    return image, seed, None
  
 examples = [
     "a tiny astronaut hatching from an egg on the moon",
     "a cat holding a sign that says hello world",
     "an anime illustration of a wiener schnitzel",
+    # Add more diverse examples
 ]
 
-css="""
+css = """
 #col-container {
     margin: 0 auto;
     max-width: 520px;
@@ -50,21 +59,18 @@ with gr.Blocks(css=css) as demo:
         """)
         
         with gr.Row():
-            
-            prompt = gr.Text(
+            prompt = gr.Textbox(
                 label="Prompt",
                 show_label=False,
                 max_lines=1,
                 placeholder="Enter your prompt",
                 container=False,
             )
-            
             run_button = gr.Button("Run", scale=0)
         
         result = gr.Image(label="Result", show_label=False)
         
         with gr.Accordion("Advanced Settings", open=False):
-            
             seed = gr.Slider(
                 label="Seed",
                 minimum=0,
@@ -72,11 +78,9 @@ with gr.Blocks(css=css) as demo:
                 step=1,
                 value=0,
             )
-            
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
             
             with gr.Row():
-                
                 width = gr.Slider(
                     label="Width",
                     minimum=256,
@@ -84,7 +88,6 @@ with gr.Blocks(css=css) as demo:
                     step=32,
                     value=1024,
                 )
-                
                 height = gr.Slider(
                     label="Height",
                     minimum=256,
@@ -94,8 +97,6 @@ with gr.Blocks(css=css) as demo:
                 )
             
             with gr.Row():
-                
-  
                 num_inference_steps = gr.Slider(
                     label="Number of inference steps",
                     minimum=1,
@@ -103,20 +104,31 @@ with gr.Blocks(css=css) as demo:
                     step=1,
                     value=4,
                 )
+                guidance_scale = gr.Slider(
+                    label="Guidance Scale",
+                    minimum=0.0,
+                    maximum=20.0,
+                    step=0.5,
+                    value=7.5,
+                )
         
         gr.Examples(
-            examples = examples,
-            fn = infer,
-            inputs = [prompt],
-            outputs = [result, seed],
+            examples=examples,
+            fn=infer,
+            inputs=[prompt],
+            outputs=[result, seed],
             cache_examples="lazy"
         )
 
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn = infer,
-        inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
-        outputs = [result, seed]
+    run_button.click(
+        fn=infer,
+        inputs=[prompt, seed, randomize_seed, width, height, num_inference_steps, guidance_scale],
+        outputs=[result, seed],
     )
 
+    gr.Markdown("""
+    ## Save Your Image
+    Right-click on the image and select 'Save As' to download the generated image.
+    """)
+    
 demo.launch()