app.py

### App
### This code for app.py
from __future__ import annotations
import os
import random
import uuid
import gradio as gr
import spaces
import numpy as np
import uuid
import gradio as gr
import diffusers 
from diffusers import StableDiffusionPipeline
import torch

class CFG:
    device = "cpu"
    seed = 42
    generator = torch.Generator(device).manual_seed(seed)
    image_gen_steps = 35
    image_gen_model_id = "stabilityai/stable-diffusion-2"
    image_gen_size = (400, 400)
    image_gen_guidance_scale = 9

image_gen_model = StableDiffusionPipeline.from_pretrained(
    CFG.image_gen_model_id, torch_dtype=torch.float32,
    revision="fp16", use_auth_token='hf_pxvzpoafqjfkELFKMLTESNpvmyvkTVuD01', guidance_scale=9
)
apply = image_gen_model.to(CFG.device)

def generate_image(prompt):
  ## add translation model here before apply
    image = apply(
        prompt, num_inference_steps=CFG.image_gen_steps,
        generator=CFG.generator,
        guidance_scale=CFG.image_gen_guidance_scale
    ).images[0]
    image = image.resize(CFG.image_gen_size)
    return image


title = "نموذج توليد الصور"
description = " اكتب وصف للصورة التي تود من النظام التوليدي انشاءها"

iface = gr.Interface(fn=generate_image, inputs="text", outputs="image", title=title, description=description)
iface.launch()