import os
import gradio as gr
from gradio_client import Client, handle_file
from gradio_imageslider import ImageSlider

stable_diffusion_xl_refiner_10 = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-refiner-1.0"
refiner_client = None

def refine_image(image, prompt, negative_prompt, num_inference_steps, guidance_scale, seed):
    global refiner_client
    if refiner_client is None:
        refiner_client = Client(stable_diffusion_xl_refiner_10)
    job = refiner_client.submit(
        inputs=image,
        parameters={
            "prompt":prompt,
            "negative_prompt": negative_prompt,
            "num_inference_steps": num_inference_steps,
            "guidance_scale": guidance_scale,
            "seed": seed,
        }
    )
    return job.result()

with gr.Blocks() as demo:
    image = gr.Image()
    prompt = gr.Textbox(lines=3, label="Prompt")
    negative_prompt = gr.Textbox(lines=3, label="Negative Prompt")
    num_inference_steps = gr.Number(default=25, label="Number of Inference Steps")
    guidance_scale = gr.Slider(minimum=3, maximum=30, default=12, label="Guidance Scale")
    seed = gr.Number(default=-1, label="Seed")
    refine_btn = gr.Button(text="Refine")
    output = gr.Image()

refine_btn.click(refine_image, inputs=[image, prompt, negative_prompt, num_inference_steps, guidance_scale, seed], outpus=output)

demo.launch()