app.py

import gradio as gr
from diffusers import DiffusionPipeline

def generate_image():
    pipeline = DiffusionPipeline.from_pretrained("nroggendorff/cats")
    pipe = pipeline.to("cuda")
    image = pipe(sample_size=512).images[0]
    return image

with gr.Blocks() as demo:
    btn = gr.Button("Generate Image")
    output_image = gr.Image(label="Generated Image")
    
    btn.click(fn=generate_image, inputs=None, outputs=output_image)

demo.launch()