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
import os

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

pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=os.environ["auth_token"], revision="fp16", torch_dtype=torch.float16)
pipe = pipe.to(device)

def infer(prompt):
    generator = torch.Generator(device=device)
    with autocast("cuda"):
        images_list = pipe(
            [prompt],
        generator=generator)
    return images_list

text = gr.Textbox(
    label="Enter your prompt",         
    show_label=False,
    max_lines=1,
    placeholder="Enter your prompt") 
    
gallery = gr.Gallery(
    label="Generated images", 
    show_label=False)

intf = gr.Interface(fn = infer, inputs = text, outputs = gallery)

intf.launch()