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from txt2img import StableDiffusionMGX, get_args
import gradio as gr


def main():
    args = get_args()
    # Note: This will load the models, which can take several minutes
    sd = StableDiffusionMGX(args.onnx_model_path, args.compiled_model_path,
                            args.fp16, args.batch, args.force_compile,
                            args.exhaustive_tune)
    sd.warmup(5)

    def gr_wrapper(prompt, negative_prompt, steps, seed, scale):
        result = sd.run(str(prompt), str(negative_prompt), int(steps),
                        int(seed), float(scale))
        return StableDiffusionMGX.convert_to_rgb_image(result)

    demo = gr.Interface(
        gr_wrapper,
        [
            gr.Textbox(value=args.prompt, label="Prompt"),
            gr.Textbox(value=args.negative_prompt,
                       label="Negative prompt (Optional)"),
            gr.Slider(
                1, 100, step=1, value=args.steps, label="Number of steps"),
            gr.Textbox(value=args.seed, label="Random seed"),
            gr.Slider(
                1, 20, step=0.1, value=args.scale, label="Guidance scale"),
        ],
        gr.Gallery(),
    )
    demo.launch()


if __name__ == "__main__":
    main()