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import os
import gradio as gr
from random import randint
from all_models import (models , models_test)
from datetime import datetime

now2 = 0
nb_models=16

def split_models(models,nb_models):
    models_temp=[]
    models_lis_temp=[]
    i=0
    for m in models:
        models_temp.append(m)
        i=i+1
        if i%nb_models==0:
            models_lis_temp.append(models_temp)
            models_temp=[]
    return models_lis_temp

models_test=split_models(models,nb_models)

def get_current_time():
    now = datetime.now()
    now2 = now
    current_time = now2.strftime("%Y-%m-%d %H:%M:%S")
    ki = f'{kii} {current_time}'
    return ki
    
def load_fn(models):
    global models_load
    global num_models
    global default_models
    models_load = {}
    num_models = len(models)
    if num_models!=0:
        default_models = models[:num_models]
    else:
        default_models = {}
    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})


"""models = models_test[1]"""
load_fn(models)
"""models = {}
load_fn(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 choice_group_a(group_model_choice):
    for m in models_test:
        if group_model_choice==m[1]:
            choice=m
    return choice

def choice_group_b(group_model_choice):
    choice=choice_group_a(group_model_choice)
    return [gr.Image(label=m, min_width=170, height=170) for m in choice]

def choice_group_c(group_model_choice):
    choice=choice_group_a(group_model_choice)
    return [gr.Textbox(m, visible=False) for m in choice]   

def choice_group_d(var_Test):
    (gen_button,stop_button,output,current_models)=var_Test
    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])
    return gen_event

def test_pass(test):   
    print(test)
    if test==p:
        return gr.Dropdown(label="test Model", show_label=False, choices=list(models_test) , allow_custom_value=True)

def gen_fn(model_str, prompt):
    if model_str == 'NA':
        return None
    noise = str(randint(0, 9999))
    return models_load[model_str](f'{prompt} {noise}')

def make_me():
   # with gr.Tab('The Dream'): 
        with gr.Row():
            #txt_input = gr.Textbox(lines=3, width=300, max_height=100)
            txt_input = gr.Textbox(label='Your prompt:', lines=3, width=300, max_height=100)
        
            gen_button = gr.Button('Generate images', width=150, height=30)
            stop_button = gr.Button('Stop', variant='secondary', interactive=False, width=150, height=30)
            gen_button.click(lambda s: gr.update(interactive=True), None, stop_button)
            gr.HTML("""
            <div style="text-align: center; max-width: 100%; margin: 0 auto;">
                <body>
                </body>
            </div>
            """)
        with gr.Row():
            """output = [gr.Image(label=m, min_width=170, height=170) for m in default_models]
            current_models = [gr.Textbox(m, visible=False) for m in default_models]"""
            choices=[models_test[0][0]]
            output = [gr.Image(label=m, min_width=170, height=170) for m in choices]
            current_models = [gr.Textbox(m, visible=False) for m in choices]
            
            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' {num_models} different models selected', value=default_models, multiselect=True, max_choices=num_models, interactive=True, filterable=False)
            model_choice.change(update_imgbox, (gen_button,stop_button,group_model_choice), output)
            model_choice.change(extend_choices, model_choice, current_models)
        """     
        """with gr.Accordion('Group Model selection'):
            group_model_choice = gr.CheckboxGroup(models_test, label=f' {len(models_test)} different group models', value=1, multiselect=False, max_choices=1, interactive=True, filterable=False)
        """
        with gr.Accordion("test", open=True):
            group_model_choice = gr.Dropdown(label="test Model", show_label=False, choices=list([]) , allow_custom_value=True)
            group_model_choice.change(choice_group_b,group_model_choice,output)
            group_model_choice.change(choice_group_c,group_model_choice,current_models)
            """group_model_choice.change(choice_group_d,(gen_button,stop_button,output,current_models),gen_event)"""
        with gr.Row():
            txt_input_p = gr.Textbox(label='test', lines=1, width=300, max_height=100)
        
            test_button = gr.Button('test', width=30, height=10)
            test_button.click(test_pass,txt_input_p,group_model_choice)
            print(os.getenv('p')
        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>
            """)


js_code = """

    
    console.log('ghgh');

"""


with gr.Blocks(css="div.float.svelte-1mwvhlq {    position: absolute;    top: var(--block-label-margin);    left: var(--block-label-margin);    background: none;    border: none;}") as demo: 
    gr.Markdown("<script>" + js_code + "</script>")
    make_me()



demo.queue(concurrency_count=999)
demo.launch()