Update app.py

app.py

@@ -71,39 +71,103 @@ def infer(
         return f"Error: {e}", seed # Return error to Gradio interface
 
 # ... (rest of your Gradio code - examples, CSS, etc. - same as before)
-
-# 4. Image generation function (now decorated)
-@GPU(duration=65)  # Only if in HF Space
-def generate_image(prompt):
-    global pipeline
-    if pipeline is None:
-        print("Error: Pipeline is None (model not loaded)")  # Log this specifically
-        return "Error: Model not loaded!"
-
-    try:
-        print("Starting image generation...")  # Log before the image generation
-        image = pipeline(prompt).images[0]
-        print("Image generated successfully!")
-        return image
-    except Exception as e:
-        error_message = f"Error during image generation: {type(e).__name__}: {e}"  # Include exception type
-        print(f"Full Error Details:\n{error_message}")  # Print full details
-        return error_message  # Return error message to Gradio
-    except RuntimeError as re:
-        error_message = f"Runtime Error during image generation: {type(re).__name__}: {re}"  # Include exception type
-        print(f"Full Runtime Error Details:\n{error_message}")  # Print full details
-        return error_message  # Return error message to Gradio
-
-# 5. Gradio interface
-with gr.Blocks() as demo:
-    prompt_input = gr.Textbox(label="Prompt")
-    image_output = gr.Image(label="Generated Image")
-    generate_button = gr.Button("Generate")
-
-    generate_button.click(
-        fn=generate_image,
-        inputs=prompt_input,
-        outputs=image_output,
+examples = [
+        "A capybara wearing a suit holding a sign that reads Hello World",
+]
+
+css = """
+#col-container {
+    margin: 0 auto;
+    max-width: 640px;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(" # [Stable Diffusion 3.5 Large (8B)](https://huggingface.co/stabilityai/stable-diffusion-3.5-large)")
+        gr.Markdown("[Learn more](https://stability.ai/news/introducing-stable-diffusion-3-5) about the Stable Diffusion 3.5 series. Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), or [download model](https://huggingface.co/stabilityai/stable-diffusion-3.5-large) to run locally with ComfyUI or diffusers.")
+        with gr.Row():
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt",
+                container=False,
+            )
+
+            run_button = gr.Button("Run", scale=0, variant="primary")
+
+        result = gr.Image(label="Result", show_label=False)
+
+        with gr.Accordion("Advanced Settings", open=False):
+            negative_prompt = gr.Text(
+                label="Negative prompt",
+                max_lines=1,
+                placeholder="Enter a negative prompt",
+                visible=False,
+            )
+
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+
+            with gr.Row():
+                width = gr.Slider(
+                    label="Width",
+                    minimum=512,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024, 
+                )
+
+                height = gr.Slider(
+                    label="Height",
+                    minimum=512,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+
+            with gr.Row():
+                guidance_scale = gr.Slider(
+                    label="Guidance scale",
+                    minimum=0.0,
+                    maximum=7.5,
+                    step=0.1,
+                    value=4.5,
+                )
+
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=50,
+                    step=1,
+                    value=40, 
+                )
+
+        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],
+        fn=infer,
+        inputs=[
+            prompt,
+            negative_prompt,
+            seed,
+            randomize_seed,
+            width,
+            height,
+            guidance_scale,
+            num_inference_steps,
+        ],
+        outputs=[result, seed],
     )
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()
+