import io
import json
import re
import sys
import time
import zipfile
from pathlib import Path

import gradio as gr

import modules.chat as chat
import modules.extensions as extensions_module
import modules.shared as shared
import modules.ui as ui
from modules.html_generator import generate_chat_html
from modules.LoRA import add_lora_to_model
from modules.models import load_model, load_soft_prompt
from modules.text_generation import clear_torch_cache, generate_reply

# Loading custom settings
settings_file = None
if shared.args.settings is not None and Path(shared.args.settings).exists():
    settings_file = Path(shared.args.settings)
elif Path('settings.json').exists():
    settings_file = Path('settings.json')
if settings_file is not None:
    print(f"Loading settings from {settings_file}...")
    new_settings = json.loads(open(settings_file, 'r').read())
    for item in new_settings:
        shared.settings[item] = new_settings[item]

def get_available_models():
    if shared.args.flexgen:
        return sorted([re.sub('-np$', '', item.name) for item in list(Path('models/').glob('*')) if item.name.endswith('-np')], key=str.lower)
    else:
        return sorted([re.sub('.pth$', '', item.name) for item in list(Path('models/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)

def get_available_presets():
    return sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('presets').glob('*.txt'))), key=str.lower)

def get_available_characters():
    return ['None'] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('characters').glob('*.json'))), key=str.lower)

def get_available_extensions():
    return sorted(set(map(lambda x : x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower)

def get_available_softprompts():
    return ['None'] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('softprompts').glob('*.zip'))), key=str.lower)

def get_available_loras():
    return ['None'] + sorted([item.name for item in list(Path('loras/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)

def load_model_wrapper(selected_model):
    if selected_model != shared.model_name:
        shared.model_name = selected_model
        shared.model = shared.tokenizer = None
        clear_torch_cache()
        shared.model, shared.tokenizer = load_model(shared.model_name)

    return selected_model

def load_lora_wrapper(selected_lora):
    shared.lora_name = selected_lora
    add_lora_to_model(selected_lora)
    default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')]

    return selected_lora, default_text

def load_preset_values(preset_menu, return_dict=False):
    generate_params = {
        'do_sample': True,
        'temperature': 1,
        'top_p': 1,
        'typical_p': 1,
        'repetition_penalty': 1,
        'encoder_repetition_penalty': 1,
        'top_k': 50,
        'num_beams': 1,
        'penalty_alpha': 0,
        'min_length': 0,
        'length_penalty': 1,
        'no_repeat_ngram_size': 0,
        'early_stopping': False,
    }
    with open(Path(f'presets/{preset_menu}.txt'), 'r') as infile:
        preset = infile.read()
    for i in preset.splitlines():
        i = i.rstrip(',').strip().split('=')
        if len(i) == 2 and i[0].strip() != 'tokens':
            generate_params[i[0].strip()] = eval(i[1].strip())

    generate_params['temperature'] = min(1.99, generate_params['temperature'])

    if return_dict:
        return generate_params
    else:
        return preset_menu, generate_params['do_sample'], generate_params['temperature'], generate_params['top_p'], generate_params['typical_p'], generate_params['repetition_penalty'], generate_params['encoder_repetition_penalty'], generate_params['top_k'], generate_params['min_length'], generate_params['no_repeat_ngram_size'], generate_params['num_beams'], generate_params['penalty_alpha'], generate_params['length_penalty'], generate_params['early_stopping']

def upload_soft_prompt(file):
    with zipfile.ZipFile(io.BytesIO(file)) as zf:
        zf.extract('meta.json')
        j = json.loads(open('meta.json', 'r').read())
        name = j['name']
        Path('meta.json').unlink()

    with open(Path(f'softprompts/{name}.zip'), 'wb') as f:
        f.write(file)

    return name

def create_model_and_preset_menus():
    with gr.Row():
        with gr.Column():
            with gr.Row():
                shared.gradio['model_menu'] = gr.Dropdown(choices=available_models, value=shared.model_name, label='Model')
                ui.create_refresh_button(shared.gradio['model_menu'], lambda : None, lambda : {'choices': get_available_models()}, 'refresh-button')
        with gr.Column():
            with gr.Row():
                shared.gradio['preset_menu'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
                ui.create_refresh_button(shared.gradio['preset_menu'], lambda : None, lambda : {'choices': get_available_presets()}, 'refresh-button')

def create_settings_menus(default_preset):
    generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', return_dict=True)

    with gr.Row():
        with gr.Column():
            with gr.Box():
                gr.Markdown('Custom generation parameters ([reference](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.GenerationConfig))')
                with gr.Row():
                    with gr.Column():
                        shared.gradio['temperature'] = gr.Slider(0.01, 1.99, value=generate_params['temperature'], step=0.01, label='temperature')
                        shared.gradio['top_p'] = gr.Slider(0.0,1.0,value=generate_params['top_p'],step=0.01,label='top_p')
                        shared.gradio['top_k'] = gr.Slider(0,200,value=generate_params['top_k'],step=1,label='top_k')
                        shared.gradio['typical_p'] = gr.Slider(0.0,1.0,value=generate_params['typical_p'],step=0.01,label='typical_p')
                    with gr.Column():
                        shared.gradio['repetition_penalty'] = gr.Slider(1.0, 1.5, value=generate_params['repetition_penalty'],step=0.01,label='repetition_penalty')
                        shared.gradio['encoder_repetition_penalty'] = gr.Slider(0.8, 1.5, value=generate_params['encoder_repetition_penalty'],step=0.01,label='encoder_repetition_penalty')
                        shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=generate_params['no_repeat_ngram_size'], label='no_repeat_ngram_size')
                        shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'] if shared.args.no_stream else 0, label='min_length', interactive=shared.args.no_stream)
                shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
        with gr.Column():
            with gr.Box():
                gr.Markdown('Contrastive search')
                shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha')

            with gr.Box():
                gr.Markdown('Beam search (uses a lot of VRAM)')
                with gr.Row():
                    with gr.Column():
                        shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams')
                    with gr.Column():
                        shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty')
                shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping')

            shared.gradio['seed'] = gr.Number(value=-1, label='Seed (-1 for random)')

    with gr.Row():
        shared.gradio['preset_menu_mirror'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
        ui.create_refresh_button(shared.gradio['preset_menu_mirror'], lambda : None, lambda : {'choices': get_available_presets()}, 'refresh-button')

    with gr.Row():
        shared.gradio['lora_menu'] = gr.Dropdown(choices=available_loras, value=shared.lora_name, label='LoRA')
        ui.create_refresh_button(shared.gradio['lora_menu'], lambda : None, lambda : {'choices': get_available_loras()}, 'refresh-button')

    with gr.Accordion('Soft prompt', open=False):
        with gr.Row():
            shared.gradio['softprompts_menu'] = gr.Dropdown(choices=available_softprompts, value='None', label='Soft prompt')
            ui.create_refresh_button(shared.gradio['softprompts_menu'], lambda : None, lambda : {'choices': get_available_softprompts()}, 'refresh-button')

        gr.Markdown('Upload a soft prompt (.zip format):')
        with gr.Row():
            shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip'])

    shared.gradio['model_menu'].change(load_model_wrapper, [shared.gradio['model_menu']], [shared.gradio['model_menu']], show_progress=True)
    shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio[k] for k in ['preset_menu_mirror', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
    shared.gradio['preset_menu_mirror'].change(load_preset_values, [shared.gradio['preset_menu_mirror']], [shared.gradio[k] for k in ['preset_menu', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
    shared.gradio['lora_menu'].change(load_lora_wrapper, [shared.gradio['lora_menu']], [shared.gradio['lora_menu'], shared.gradio['textbox']], show_progress=True)
    shared.gradio['softprompts_menu'].change(load_soft_prompt, [shared.gradio['softprompts_menu']], [shared.gradio['softprompts_menu']], show_progress=True)
    shared.gradio['upload_softprompt'].upload(upload_soft_prompt, [shared.gradio['upload_softprompt']], [shared.gradio['softprompts_menu']])

def set_interface_arguments(interface_mode, extensions, cmd_active):
    modes = ["default", "notebook", "chat", "cai_chat"]
    cmd_list = vars(shared.args)
    cmd_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes]

    shared.args.extensions = extensions
    for k in modes[1:]:
        exec(f"shared.args.{k} = False")
    if interface_mode != "default":
        exec(f"shared.args.{interface_mode} = True")

    for k in cmd_list:
        exec(f"shared.args.{k} = False")
    for k in cmd_active:
        exec(f"shared.args.{k} = True")

    shared.need_restart = True

available_models = get_available_models()
available_presets = get_available_presets()
available_characters = get_available_characters()
available_softprompts = get_available_softprompts()
available_loras = get_available_loras()

# Default extensions
extensions_module.available_extensions = get_available_extensions()
if shared.args.chat or shared.args.cai_chat:
    for extension in shared.settings['chat_default_extensions']:
        shared.args.extensions = shared.args.extensions or []
        if extension not in shared.args.extensions:
            shared.args.extensions.append(extension)
else:
    for extension in shared.settings['default_extensions']:
        shared.args.extensions = shared.args.extensions or []
        if extension not in shared.args.extensions:
            shared.args.extensions.append(extension)

# Default model
if shared.args.model is not None:
    shared.model_name = shared.args.model
else:
    if len(available_models) == 0:
        print('No models are available! Please download at least one.')
        sys.exit(0)
    elif len(available_models) == 1:
        i = 0
    else:
        print('The following models are available:\n')
        for i, model in enumerate(available_models):
            print(f'{i+1}. {model}')
        print(f'\nWhich one do you want to load? 1-{len(available_models)}\n')
        i = int(input())-1
        print()
    shared.model_name = available_models[i]
shared.model, shared.tokenizer = load_model(shared.model_name)
if shared.args.lora:
    print(shared.args.lora)
    shared.lora_name = shared.args.lora
    add_lora_to_model(shared.lora_name)

# Default UI settings
default_preset = shared.settings['presets'][next((k for k in shared.settings['presets'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')]
if default_text == '':
    default_text = shared.settings['prompts'][next((k for k in shared.settings['prompts'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
title ='Text generation web UI'
description = '\n\n# Text generation lab\nGenerate text using Large Language Models.\n'
suffix = '_pygmalion' if 'pygmalion' in shared.model_name.lower() else ''

def create_interface():

    gen_events = []
    if shared.args.extensions is not None and len(shared.args.extensions) > 0:
        extensions_module.load_extensions()

    with gr.Blocks(css=ui.css if not any((shared.args.chat, shared.args.cai_chat)) else ui.css+ui.chat_css, analytics_enabled=False, title=title) as shared.gradio['interface']:
        if shared.args.chat or shared.args.cai_chat:
            with gr.Tab("Text generation", elem_id="main"):
                if shared.args.cai_chat:
                    shared.gradio['display'] = gr.HTML(value=generate_chat_html(shared.history['visible'], shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}'], shared.character))
                else:
                    shared.gradio['display'] = gr.Chatbot(value=shared.history['visible']).style(color_map=("#326efd", "#212528"))
                shared.gradio['textbox'] = gr.Textbox(label='Input')
                with gr.Row():
                    shared.gradio['Stop'] = gr.Button('Stop', elem_id="stop")
                    shared.gradio['Generate'] = gr.Button('Generate')
                with gr.Row():
                    shared.gradio['Impersonate'] = gr.Button('Impersonate')
                    shared.gradio['Regenerate'] = gr.Button('Regenerate')
                with gr.Row():
                    shared.gradio['Copy last reply'] = gr.Button('Copy last reply')
                    shared.gradio['Replace last reply'] = gr.Button('Replace last reply')
                    shared.gradio['Remove last'] = gr.Button('Remove last')

                    shared.gradio['Clear history'] = gr.Button('Clear history')
                    shared.gradio['Clear history-confirm'] = gr.Button('Confirm', variant="stop", visible=False)
                    shared.gradio['Clear history-cancel'] = gr.Button('Cancel', visible=False)

                create_model_and_preset_menus()

            with gr.Tab("Character", elem_id="chat-settings"):
                shared.gradio['name1'] = gr.Textbox(value=shared.settings[f'name1{suffix}'], lines=1, label='Your name')
                shared.gradio['name2'] = gr.Textbox(value=shared.settings[f'name2{suffix}'], lines=1, label='Bot\'s name')
                shared.gradio['context'] = gr.Textbox(value=shared.settings[f'context{suffix}'], lines=5, label='Context')
                with gr.Row():
                    shared.gradio['character_menu'] = gr.Dropdown(choices=available_characters, value='None', label='Character', elem_id='character-menu')
                    ui.create_refresh_button(shared.gradio['character_menu'], lambda : None, lambda : {'choices': get_available_characters()}, 'refresh-button')

                with gr.Row():
                    with gr.Tab('Chat history'):
                        with gr.Row():
                            with gr.Column():
                                gr.Markdown('Upload')
                                shared.gradio['upload_chat_history'] = gr.File(type='binary', file_types=['.json', '.txt'])
                            with gr.Column():
                                gr.Markdown('Download')
                                shared.gradio['download'] = gr.File()
                                shared.gradio['download_button'] = gr.Button(value='Click me')
                    with gr.Tab('Upload character'):
                        with gr.Row():
                            with gr.Column():
                                gr.Markdown('1. Select the JSON file')
                                shared.gradio['upload_json'] = gr.File(type='binary', file_types=['.json'])
                            with gr.Column():
                                gr.Markdown('2. Select your character\'s profile picture (optional)')
                                shared.gradio['upload_img_bot'] = gr.File(type='binary', file_types=['image'])
                        shared.gradio['Upload character'] = gr.Button(value='Submit')
                    with gr.Tab('Upload your profile picture'):
                        shared.gradio['upload_img_me'] = gr.File(type='binary', file_types=['image'])
                    with gr.Tab('Upload TavernAI Character Card'):
                        shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image'])

            with gr.Tab("Parameters", elem_id="parameters"):
                with gr.Box():
                    gr.Markdown("Chat parameters")
                    with gr.Row():
                        with gr.Column():
                            shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
                            shared.gradio['chat_prompt_size_slider'] = gr.Slider(minimum=shared.settings['chat_prompt_size_min'], maximum=shared.settings['chat_prompt_size_max'], step=1, label='Maximum prompt size in tokens', value=shared.settings['chat_prompt_size'])
                        with gr.Column():
                            shared.gradio['chat_generation_attempts'] = gr.Slider(minimum=shared.settings['chat_generation_attempts_min'], maximum=shared.settings['chat_generation_attempts_max'], value=shared.settings['chat_generation_attempts'], step=1, label='Generation attempts (for longer replies)')
                            shared.gradio['check'] = gr.Checkbox(value=shared.settings[f'stop_at_newline{suffix}'], label='Stop generating at new line character?')

                create_settings_menus(default_preset)

            function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
            shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'seed', 'name1', 'name2', 'context', 'check', 'chat_prompt_size_slider', 'chat_generation_attempts']]

            gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
            gen_events.append(shared.gradio['textbox'].submit(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
            gen_events.append(shared.gradio['Regenerate'].click(chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
            gen_events.append(shared.gradio['Impersonate'].click(chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=shared.args.no_stream))
            shared.gradio['Stop'].click(chat.stop_everything_event, [], [], cancels=gen_events)

            shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, [], shared.gradio['textbox'], show_progress=shared.args.no_stream)
            shared.gradio['Replace last reply'].click(chat.replace_last_reply, [shared.gradio['textbox'], shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'], show_progress=shared.args.no_stream)

            # Clear history with confirmation
            clear_arr = [shared.gradio[k] for k in ['Clear history-confirm', 'Clear history', 'Clear history-cancel']]
            shared.gradio['Clear history'].click(lambda :[gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, clear_arr)
            shared.gradio['Clear history-confirm'].click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr)
            shared.gradio['Clear history-confirm'].click(chat.clear_chat_log, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
            shared.gradio['Clear history-cancel'].click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr)

            shared.gradio['Remove last'].click(chat.remove_last_message, [shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['display'], shared.gradio['textbox']], show_progress=False)
            shared.gradio['download_button'].click(chat.save_history, inputs=[], outputs=[shared.gradio['download']])
            shared.gradio['Upload character'].click(chat.upload_character, [shared.gradio['upload_json'], shared.gradio['upload_img_bot']], [shared.gradio['character_menu']])

            # Clearing stuff and saving the history
            for i in ['Generate', 'Regenerate', 'Replace last reply']:
                shared.gradio[i].click(lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False)
                shared.gradio[i].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
            shared.gradio['Clear history-confirm'].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
            shared.gradio['textbox'].submit(lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False)
            shared.gradio['textbox'].submit(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)

            shared.gradio['character_menu'].change(chat.load_character, [shared.gradio['character_menu'], shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['name2'], shared.gradio['context'], shared.gradio['display']])
            shared.gradio['upload_chat_history'].upload(chat.load_history, [shared.gradio['upload_chat_history'], shared.gradio['name1'], shared.gradio['name2']], [])
            shared.gradio['upload_img_tavern'].upload(chat.upload_tavern_character, [shared.gradio['upload_img_tavern'], shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['character_menu']])
            shared.gradio['upload_img_me'].upload(chat.upload_your_profile_picture, [shared.gradio['upload_img_me']], [])

            reload_func = chat.redraw_html if shared.args.cai_chat else lambda : shared.history['visible']
            reload_inputs = [shared.gradio['name1'], shared.gradio['name2']] if shared.args.cai_chat else []
            shared.gradio['upload_chat_history'].upload(reload_func, reload_inputs, [shared.gradio['display']])
            shared.gradio['upload_img_me'].upload(reload_func, reload_inputs, [shared.gradio['display']])
            shared.gradio['Stop'].click(reload_func, reload_inputs, [shared.gradio['display']])

            shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js+ui.chat_js}}}")
            shared.gradio['interface'].load(lambda : chat.load_default_history(shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}']), None, None)
            shared.gradio['interface'].load(reload_func, reload_inputs, [shared.gradio['display']], show_progress=True)

        elif shared.args.notebook:
            with gr.Tab("Text generation", elem_id="main"):
                with gr.Tab('Raw'):
                    shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=25)
                with gr.Tab('Markdown'):
                    shared.gradio['markdown'] = gr.Markdown()
                with gr.Tab('HTML'):
                    shared.gradio['html'] = gr.HTML()

                with gr.Row():
                    shared.gradio['Stop'] = gr.Button('Stop')
                    shared.gradio['Generate'] = gr.Button('Generate')
                shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])

                create_model_and_preset_menus()
            with gr.Tab("Parameters", elem_id="parameters"):
                create_settings_menus(default_preset)

            shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'seed']]
            output_params = [shared.gradio[k] for k in ['textbox', 'markdown', 'html']]
            gen_events.append(shared.gradio['Generate'].click(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream, api_name='textgen'))
            gen_events.append(shared.gradio['textbox'].submit(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream))
            shared.gradio['Stop'].click(None, None, None, cancels=gen_events)
            shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")

        else:
            with gr.Tab("Text generation", elem_id="main"):
                with gr.Row():
                    with gr.Column():
                        shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=15, label='Input')
                        shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
                        shared.gradio['Generate'] = gr.Button('Generate')
                        with gr.Row():
                            with gr.Column():
                                shared.gradio['Continue'] = gr.Button('Continue')
                            with gr.Column():
                                shared.gradio['Stop'] = gr.Button('Stop')

                        create_model_and_preset_menus()

                    with gr.Column():
                        with gr.Tab('Raw'):
                            shared.gradio['output_textbox'] = gr.Textbox(lines=25, label='Output')
                        with gr.Tab('Markdown'):
                            shared.gradio['markdown'] = gr.Markdown()
                        with gr.Tab('HTML'):
                            shared.gradio['html'] = gr.HTML()
            with gr.Tab("Parameters", elem_id="parameters"):
                create_settings_menus(default_preset)

            shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'seed']]
            output_params = [shared.gradio[k] for k in ['output_textbox', 'markdown', 'html']]
            gen_events.append(shared.gradio['Generate'].click(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream, api_name='textgen'))
            gen_events.append(shared.gradio['textbox'].submit(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream))
            gen_events.append(shared.gradio['Continue'].click(generate_reply, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=shared.args.no_stream))
            shared.gradio['Stop'].click(None, None, None, cancels=gen_events)
            shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")

        with gr.Tab("Interface mode", elem_id="interface-mode"):
            modes = ["default", "notebook", "chat", "cai_chat"]
            current_mode = "default"
            for mode in modes[1:]:
                if eval(f"shared.args.{mode}"):
                    current_mode = mode
                    break
            cmd_list = vars(shared.args)
            cmd_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes]
            active_cmd_list = [k for k in cmd_list if vars(shared.args)[k]]

            gr.Markdown("*Experimental*")
            shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode")
            shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=get_available_extensions(), value=shared.args.extensions, label="Available extensions")
            shared.gradio['cmd_arguments_menu'] = gr.CheckboxGroup(choices=cmd_list, value=active_cmd_list, label="Boolean command-line flags")
            shared.gradio['reset_interface'] = gr.Button("Apply and restart the interface", type="primary")

            shared.gradio['reset_interface'].click(set_interface_arguments, [shared.gradio[k] for k in ['interface_modes_menu', 'extensions_menu', 'cmd_arguments_menu']], None)
            shared.gradio['reset_interface'].click(lambda : None, None, None, _js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500)}')

        if shared.args.extensions is not None:
            extensions_module.create_extensions_block()

    # Launch the interface
    shared.gradio['interface'].queue()
    if shared.args.listen:
        shared.gradio['interface'].launch(prevent_thread_lock=True, share=shared.args.share, server_name='0.0.0.0', server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch)
    else:
        shared.gradio['interface'].launch(prevent_thread_lock=True, share=shared.args.share, server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch)

create_interface()

while True:
    time.sleep(0.5)
    if shared.need_restart:
        shared.need_restart = False
        shared.gradio['interface'].close()
        create_interface()