app.py

import gradio as gr
from diffusers import DiffusionPipeline

# Load the SHAP-E diffusion pipeline
pipe = DiffusionPipeline.from_pretrained("openai/shap-e")

def generate_image(prompt):
    # Generate the image from the prompt
    image = pipe(prompt).images[0]
    return image

# Create a Gradio interface
iface = gr.Interface(
    fn=generate_image,
    inputs=gr.Textbox(label="Enter your prompt", placeholder="e.g. Astronaut in a jungle"),
    outputs=gr.Image(label="Generated Image"),
    title="SHAP-E Image Generator",
    description="Generate images using the SHAP-E diffusion model based on your prompts."
)

if __name__ == "__main__":
    iface.launch()