import gradio as gr

import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
from datasets import load_dataset
from PIL import Image  
import re

model_id = "CompVis/stable-diffusion-v1-4"
device = "cuda"

pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
pipe = pipe.to(device)

def infer(prompt):
    with autocast("cuda"):
        images_list = pipe(
            [prompt])['sample']
    return images_list
prompt = 'a perfect photo of a sunset on a Greek beach' 

intf = gr.Interface(fn = infer, inputs = prompt, outputs = gr.outputs.Image())

intf.launch()