import torch 
import gradio as gr
from diffusers import StableDiffusionPipeline 

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):
    image = apply(
        prompt, num_inference_steps=CFG.image_gen_steps,
        generator=CFG.generator , 
        guidance_scale=CFG.image_gen_guidance_scale
    ).image[0] 
    image = image.resize(CFG.image_gen_size)
    return image
    


title = "تصوَّر"
description = "أدخل نص نحولها لك صوره"

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