import streamlit as st
from diffusers import AutoPipelineForText2Image
import torch
from PIL import Image
import io
import os

# Force CPU usage
os.environ["CUDA_VISIBLE_DEVICES"] = ""

@st.cache_resource
def load_model():
    pipe = AutoPipelineForText2Image.from_pretrained(
        "stabilityai/sd-turbo", 
        torch_dtype=torch.float32  # CPU-compatible
    )
    pipe.to("cpu")
    return pipe

st.title("⚡ Fast AI Image Generator (under 1 minute)")

prompt = st.text_input("Enter your prompt:", 
                       "A glowing alien city with floating islands and neon rivers, concept art, 8K")

guidance = st.slider("Guidance scale (higher = more faithful to prompt)", 1.0, 10.0, 3.0)

if st.button("Generate Image"):
    with st.spinner("Generating image (approx. 20–40 seconds on CPU)..."):
        pipe = load_model()
        result = pipe(prompt, guidance_scale=guidance, num_inference_steps=20)
        image = result.images[0]

        st.image(image, caption="Generated Image", use_column_width=True)

        buf = io.BytesIO()
        image.save(buf, format="PNG")
        st.download_button("Download Image", buf.getvalue(), "generated.png", "image/png")