app.py

import gradio as gr
from diffusers import StableDiffusionPipeline
import torch
import os

# Retrieve Hugging Face API key from environment variables (Hugging Face Secrets)
hf_token = os.getenv("HF_TOKEN")

# Load the Stable Diffusion model in CPU mode
pipe = StableDiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-2",
    torch_dtype=torch.float32,  # Ensure compatibility with CPU
    use_auth_token=hf_token
)

# Force model to run on CPU
pipe.to("cpu")

# Optimize performance for CPU execution
pipe.enable_attention_slicing()

# Define image generation function
def generate_image(prompt):
    try:
        image = pipe(prompt).images[0]
        return image
    except Exception as e:
        return f"Error: {str(e)}"

# Gradio Interface
iface = gr.Interface(
    fn=generate_image,
    inputs=gr.Textbox(label="Enter your prompt"),
    outputs=gr.Image(label="Generated Image"),
    title="Stable Diffusion (CPU Optimized)",
    description="Generate AI-generated images using Stable Diffusion on CPU. No GPU required!"
)

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