app.py

import gradio as gr
import spaces
from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float32)

@spaces.GPU(duration=120)
def generate_image(prompt):
    # Run the diffusion model to generate an image
    image = pipe(prompt, num_inference_steps=50, guidance_scale=7.5)
    return image

gr_interface = gr.Interface(
    fn=generate_image,
    inputs="text",
    outputs="image",
    title="Real-time Image Generation with Diffusion",
    description="Enter a prompt to generate an image",
    theme="soft"
)

# Launch the Gradio app
gr_interface.launch()