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


# Function to generate a string with text and a random number
def generate_text_with_random_number():
    random_number = randint(1, 100)
    kii = "nude femboy sissy with small penis,  bound anal sex orgy party, perfect penis, oral sex, threesum, head between thighs, glans inside mouth, cuming from glans"
    ki=f'{kii} {random_number}'
    return ki

# Function to process the input and return it (or do some other processing)
def process_text(input_text):
    return f"You entered: {input_text}"




def load_fn(models):
    ki=generate_text_with_random_number()
    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 = gr.Interface(lambda txt: None, ['text'], ['image'])
            models_load.update({model: m})






load_fn(models)

    
num_models = len(models)
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('') #str(randint(0, 99999999999))
    return models_load[model_str](f'{prompt} {noise}')



with gr.Blocks() as demo:
    with gr.Tab('The Dream'): 
        fn=process_text,
        txt_input = gr.Textbox(label = 'Your prompt:', lines=4, value=ki   ).style(container=False,min_width=1200)
                               #"nude femboy sissy with small penis,  bound anal sex orgy party, perfect penis, oral sex, threesum, head between thighs, glans inside mouth, cuming from glans"
        gen_button = gr.Button('Generate up to 6 images in up to 3 minutes total')
        stop_button = gr.Button('Stop', variant = 'secondary', interactive = False)
        gen_button.click(lambda s: gr.update(interactive = True), None, stop_button)
        gr.HTML(
        """
            <div style="text-align: center; max-width: 1200px; margin: 0 auto;">
              <div>
                <body>
                <div class="center"><p style="margin-bottom: 10px; color: #000000;">Scroll down to see more images and select models.</p>
                </div>
                </body>
              </div>
            </div>
        """
               )
        with gr.Row():
            output = [gr.Image(label = m, min_width=480) 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 from the 800 available!', value = default_models, multiselect = True, max_choices = num_models, interactive = True, filterable = False)
            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> 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>
    """
)

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