import gradio as gr
from random import randint
from all_models import models
from gradio import Interface

# Define Bootstrap CSS styles
bootstrap_css = """
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.6.1/dist/css/bootstrap.min.css" integrity="sha384-zCbKRCUGaJDkqO4aIfeHaHNVy2QWhv2P+nvf4jCF0S42kqR8YcOrHndjw6qplMFZrk" crossorigin="anonymous">
"""

gr.Config.css = [bootstrap_css]

def load_fn(models):
    global models_load
    models_load = {}
    
    for model in models:
        if model not in models_load.keys():
            try:
                m = gr.load(f'models/{model}')
            except Exception as error:
                m = Interface(lambda txt: None, ['text'], ['image'])
            models_Multiplier = {model: m}

    load_fn(models)

    num_models = 150
    default_models = models[:num_models]

    def extend_choices(choices):
        return choices + (num_models - len(choices)) * ['NA']

    def update_imgbox(choices):
        choices_plus = extend_choices(choices)
        return [gr.Image(None, label=m, visible=(m != 'NA')) for m in choices_plus]

    def gen_fn(model_str, prompt):
        if model_str == 'NA':
            return None
        noise = str(randint(0, 99999999999))
        return models_load[model_str](f'{prompt} {noise}')

    with gr.Blocks() as demo:
        with gr.Tab('The Dream'):
            txt_input = gr.Textbox(label='Your prompt:', lines=4).style(
                'text-align: left;',
                'width: 100%;',
                'margin-bottom: 20px;',
                'font-size: 16px;'
            )

            gen_button = gr.Button(
                'Generate up to 150 images in up to 3 minutes total',
                style='margin-bottom: 20px;'
            )

            stop_button = gr.Button(
                'Stop',
                variant='danger',
                interactive=False,
                style='margin-bottom: 20px;'
            )

            gen_button.click(lambda s: gr.update(interactive=True), None, stop_button)

            gr.HTML(
                """
                <div style="text-align: left; max-width: 800px; margin: 0 auto;">
                  <p style="margin-bottom: 10px; color: #333333;">Enter your prompt in the text box and click "Generate" to start generating images.</p>
                </div>
                """
            )

            with gr.Row():
                output = [gr.Image(label=m, min_width=250) for m in default_models]
                current_models = [gr.Textbox(m, visible=False) for m in default_models]

                for m, o in zip(current_models, output):
                    gen_event = gen_button.click(gen_fn, [m, txt_input], o)
                    stop_button.click(lambda s: gr.update(interactive=False), None, stop_button, cancels=[gen_event])

            with gr.Accordion('Model selection'):
                model_choice = gr.CheckboxGroup(
                    models,
                    label=f'Choose up to {num_models} different models out of {len(models)} available!',
                    value=default_models,
                    multiselect=True,
                    max_choices=num_models,
                    interactive=True,
                    filterable=True,
                    style='width: 100%;'
                )

                model_choice.change(update_imgbox, model_choice, output)
                model_choice.change(extend_choices, model_choice, current_models)

            with gr.Row():
                gr.HTML(
                    """
                    <div class="footer">
                        <p style="font-size: 14px; color: #666666;">
                            Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn,
                            the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77 and Omnibus's Maximum Multiplier!
                        </p>
                    </div>
                    """
                )

        demo.queue(concurrency_count=200)
        demo.launch()