import gradio as gr
from PIL import Image

def predict(merge_ratio, guidance, steps, sharpness, prompt1, prompt2, seed):
    result_image = Image.new('RGB', [512,512], (seed))
    print(merge_ratio, guidance, steps, sharpness, prompt1, prompt2, seed)
    return result_image


with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            image = gr.Image(type="pil")
        with gr.Column():
            merge_ratio = gr.Slider(minimum=0, maximum=50, step=1, label="Merge Ratio")
            guidance = gr.Slider(label="Guidance")
            steps = gr.Slider(label="Steps")
            sharpness = gr.Slider(minimum=0, maximum=50, step=1, label="sharpness")
            seed = gr.Slider(randomize=True, minimum=0, maximum=12013012031030)
            prompt1 = gr.Textbox(label="Prompt 1")
            prompt2 = gr.Textbox(label="Prompt 2")
            generate_bt = gr.Button("Generate")
    
    inputs = [merge_ratio, guidance, steps, sharpness, prompt1, prompt2, seed]
    generate_bt.click(predict, inputs=inputs, outputs=image, show_progress=False)
    seed.change(predict, inputs=inputs, outputs=image, show_progress=False)
if __name__ == "__main__":
    demo.launch()