Update app.py

app.py

@@ -6,9 +6,7 @@ from diffusers import DiffusionPipeline
 # Device setup
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model_repo_id_turbo = "stabilityai/sdxl-turbo"  # Stability AI Model
-pipe_turbo = DiffusionPipeline.from_pretrained(
-    model_repo_id_turbo, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
-).to(device)
+pipe_turbo = DiffusionPipeline.from_pretrained(model_repo_id_turbo, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32).to(device)
 
 # Placeholder for ZB-Tech model
 def load_zb_model():
@@ -18,17 +16,16 @@ def load_zb_model():
 def custom_infer(
     model_choice, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps
 ):
+    # Load the selected model
     if model_choice == "Faster image generation (suitable for CPUs)":
-        # Call ZB-Tech model for faster generation
         model = load_zb_model()
         return model(prompt)
     else:
-        # Use Stability AI's model with customizable options
         default_negative_prompt = "no watermark, hezzy, blurry"
         combined_negative_prompt = f"{default_negative_prompt}, {negative_prompt}" if negative_prompt else default_negative_prompt
         
         if randomize_seed:
-            seed = random.randint(0, 2147483647)
+            seed = random.randint(0, np.iinfo(np.int32).max)
         
         generator = torch.Generator().manual_seed(seed)
         image = pipe_turbo(
@@ -42,19 +39,22 @@ def custom_infer(
         ).images[0]
         return image, seed
 
-# CSS for aligning the UI
+# CSS for centering UI
 css = """
 #col-container {
-    margin: 0 auto;
-    max-width: 640px;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    justify-content: center;
     text-align: center;
+    margin: 0 auto;
 }
 """
 
 # Gradio app
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        # App title and description
+        # App name and description
         gr.Markdown(
             """
             # AI-Powered Text-to-Image Generator  
@@ -72,11 +72,9 @@ with gr.Blocks(css=css) as demo:
             value="Faster image generation (suitable for CPUs)",
         )
 
-        # Input for the text prompt
+        # Input section
         prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
-
-        # Advanced options (conditionally displayed)
-        with gr.Row(visible=False) as advanced_settings:
+        with gr.Accordion("Advanced Settings", open=False):
             negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt here...")
             seed = gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1, value=0)
             randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
@@ -86,21 +84,8 @@ with gr.Blocks(css=css) as demo:
             num_inference_steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=25)
 
         # Output section
-        result = gr.Image(label="Generated Image", type="pil", elem_id="col-container")
-        generate_button = gr.Button("Generate")
-
-        # Event to toggle advanced options based on model selection
-        def toggle_advanced_options(model_choice):
-            return model_choice != "Faster image generation (suitable for CPUs)"
-
-        model_choice.change(
-            toggle_advanced_options,
-            inputs=[model_choice],
-            outputs=[advanced_settings]
-        )
-
-        # Generate button action
-        generate_button.click(
+        result = gr.Image(label="Generated Image", type="pil")
+        gr.Button("Generate").click(
             custom_infer,
             inputs=[model_choice, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
             outputs=result