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

import gradio as gr
import torch

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 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
        if not shared.args.cpu:
            gc.collect()
            torch.cuda.empty_cache()
        shared.model, shared.tokenizer = load_model(shared.model_name)

    return selected_model

def load_lora_wrapper(selected_lora):
    shared.lora_name = 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')]

    if not shared.args.cpu:
        gc.collect()
        torch.cuda.empty_cache()
    add_lora_to_model(selected_lora)

    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()