import gradio as gr

def predict(*args):
    print(args)
    return {"inputs": list[args]}

with gr.Blocks() as demo:    
    s = gr.CheckboxGroup(choices=['Text-to-Image', 'Image-to-Image'], interactive=True) #value='Text-to-Image',

    @gr.render(inputs=s, triggers=[s.input])
    def render(value):
        #texts = []
        for Mode in value:
            with gr.Tab(label=Mode):
              if value=='Text-to-Image':
                #gr.Markdown(value=Mode)
                demo_t2i = gr.load('stabilityai/stable-diffusion-xl-base-1.0', src='models')
                #gr.load('minimaxir/sdxl-wrong-lora', src='models') #.launch(debug=True, quiet=True) #minimaxir/sdxl-wrong-lora stabilityai/sdxl-turbo ByteDance/SDXL-Lightning
              else:
                #gr.Markdown(value=Mode)
                demo_t2i = gr.load('stabilityai/stable-diffusion-xl-refiner-1.0', src='models') #.launch(height=1000, quiet=True)

demo.launch(debug=True, quiet=True)