app.py

import gradio as gr
from gradio.inputs import Textbox

from PIL import Image
from io import BytesIO
import torch
from torch.cuda.amp import autocast
from diffusers import DiffusionPipeline
import os

model_id = "stabilityai/stable-diffusion-xl-base-1.0"
device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32, use_safetensors=True, variant="fp16")
pipe = pipe.to(device)

def generate_image(prompt: str, secret: str):
    if secret != os.getenv("SECRET_KEY"):
        return "Not Authorized"

    with autocast(device):
        image = pipe(prompt, guidance_scale=8.5).images[0]

    buffer = BytesIO()
    image.save(buffer, format="PNG") 
    buffer.seek(0)

    return buffer

iface = gr.Interface(fn=generate_image, inputs=[Textbox(label="prompt"), Textbox(label="secret")], outputs=gr.outputs.Bytes())
iface.launch()