app.py

import streamlit as st
from diffusers import DiffusionPipeline
import torch
from PIL import Image
from io import BytesIO

# Load the diffusion pipeline
@st.cache_resource
def load_pipeline():
    return DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0").to("cuda" if torch.cuda.is_available() else "cpu")

pipeline = load_pipeline()

def generate_image(prompt):
    # Generate image
    with torch.no_grad():
        result = pipeline(prompt).images[0]
    return result

def main():
    st.title("Stable Diffusion Image Generator")

    # Get user input
    prompt = st.text_input("Enter a prompt for image generation:")
    
    if st.button("Generate Image"):
        if prompt:
            # Generate and display the image
            image = generate_image(prompt)
            st.image(image, caption="Generated Image")
        else:
            st.warning("Please enter a prompt.")

if __name__ == "__main__":
    main()