Create app.py

app.py

@@ -0,0 +1,933 @@
+import os
+import requests
+import warnings
+
+os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
+os.environ['BITSANDBYTES_NOWELCOME'] = '1'
+warnings.filterwarnings('ignore', category=UserWarning, message='TypedStorage is deprecated')
+
+# This is a hack to prevent Gradio from phoning home when it gets imported
+def my_get(url, **kwargs):
+    print('Gradio HTTP request redirected to localhost :)')
+    kwargs.setdefault('allow_redirects', True)
+    return requests.api.request('get', 'http://127.0.0.1/', **kwargs)
+
+original_get = requests.get
+requests.get = my_get
+import gradio as gr
+requests.get = original_get
+
+# This fixes LaTeX rendering on some systems
+import matplotlib
+matplotlib.use('Agg')
+
+import importlib
+import io
+import json
+import math
+import os
+import re
+import sys
+import time
+import traceback
+import zipfile
+from datetime import datetime
+from functools import partial
+from pathlib import Path
+
+import psutil
+import torch
+import yaml
+from PIL import Image
+
+import modules.extensions as extensions_module
+from modules import chat, shared, training, ui
+from modules.html_generator import chat_html_wrapper
+from modules.LoRA import add_lora_to_model
+from modules.models import load_model, load_soft_prompt, unload_model
+from modules.text_generation import (encode, generate_reply,
+                                     stop_everything_event)
+
+
+def get_available_models():
+    if shared.args.flexgen:
+        return sorted([re.sub('-np$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if item.name.endswith('-np')], key=str.lower)
+    else:
+        return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json', '.yaml'))], key=str.lower)
+
+
+def get_available_presets():
+    return sorted(set((k.stem for k in Path('presets').glob('*.txt'))), key=str.lower)
+
+
+def get_available_prompts():
+    prompts = []
+    prompts += sorted(set((k.stem for k in Path('prompts').glob('[0-9]*.txt'))), key=str.lower, reverse=True)
+    prompts += sorted(set((k.stem for k in Path('prompts').glob('*.txt'))), key=str.lower)
+    prompts += ['None']
+    return prompts
+
+
+def get_available_characters():
+    paths = (x for x in Path('characters').iterdir() if x.suffix in ('.json', '.yaml', '.yml'))
+    return ['None'] + sorted(set((k.stem for k in paths if k.stem != "instruction-following")), key=str.lower)
+
+
+def get_available_instruction_templates():
+    path = "characters/instruction-following"
+    paths = []
+    if os.path.exists(path):
+        paths = (x for x in Path(path).iterdir() if x.suffix in ('.json', '.yaml', '.yml'))
+    return ['None'] + sorted(set((k.stem for k in paths)), 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((k.stem for k in Path('softprompts').glob('*.zip'))), key=str.lower)
+
+
+def get_available_loras():
+    return sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
+
+
+def load_model_wrapper(selected_model):
+    try:
+        yield f"Loading {selected_model}..."
+        shared.model_name = selected_model
+        unload_model()
+        if selected_model != '':
+            shared.model, shared.tokenizer = load_model(shared.model_name)
+
+        yield f"Successfully loaded {selected_model}"
+    except:
+        yield traceback.format_exc()
+
+
+def load_lora_wrapper(selected_loras):
+    yield ("Applying the following LoRAs to {}:\n\n{}".format(shared.model_name, '\n'.join(selected_loras)))
+    add_lora_to_model(selected_loras)
+    yield ("Successfuly applied the LoRAs")
+
+
+def load_preset_values(preset_menu, state, 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:
+        state.update(generate_params)
+        return state, *[generate_params[k] for k in ['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']]
+
+
+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 save_prompt(text):
+    fname = f"{datetime.now().strftime('%Y-%m-%d-%H%M%S')}.txt"
+    with open(Path(f'prompts/{fname}'), 'w', encoding='utf-8') as f:
+        f.write(text)
+    return f"Saved to prompts/{fname}"
+
+
+def load_prompt(fname):
+    if fname in ['None', '']:
+        return ''
+    else:
+        with open(Path(f'prompts/{fname}.txt'), 'r', encoding='utf-8') as f:
+            text = f.read()
+            if text[-1] == '\n':
+                text = text[:-1]
+            return text
+
+
+def count_tokens(text):
+    tokens = len(encode(text)[0])
+    return f'{tokens} tokens in the input.'
+
+
+def download_model_wrapper(repo_id):
+    try:
+        downloader = importlib.import_module("download-model")
+
+        model = repo_id
+        branch = "main"
+        check = False
+
+        yield ("Cleaning up the model/branch names")
+        model, branch = downloader.sanitize_model_and_branch_names(model, branch)
+
+        yield ("Getting the download links from Hugging Face")
+        links, sha256, is_lora = downloader.get_download_links_from_huggingface(model, branch, text_only=False)
+
+        yield ("Getting the output folder")
+        output_folder = downloader.get_output_folder(model, branch, is_lora)
+
+        if check:
+            yield ("Checking previously downloaded files")
+            downloader.check_model_files(model, branch, links, sha256, output_folder)
+        else:
+            yield (f"Downloading files to {output_folder}")
+            downloader.download_model_files(model, branch, links, sha256, output_folder, threads=1)
+            yield ("Done!")
+    except:
+        yield traceback.format_exc()
+
+
+# Update the command-line arguments based on the interface values
+def update_model_parameters(state, initial=False):
+    elements = ui.list_model_elements()  # the names of the parameters
+    gpu_memories = []
+
+    for i, element in enumerate(elements):
+        if element not in state:
+            continue
+
+        value = state[element]
+        if element.startswith('gpu_memory'):
+            gpu_memories.append(value)
+            continue
+
+        if initial and vars(shared.args)[element] != vars(shared.args_defaults)[element]:
+            continue
+
+        # Setting null defaults
+        if element in ['wbits', 'groupsize', 'model_type'] and value == 'None':
+            value = vars(shared.args_defaults)[element]
+        elif element in ['cpu_memory'] and value == 0:
+            value = vars(shared.args_defaults)[element]
+
+        # Making some simple conversions
+        if element in ['wbits', 'groupsize', 'pre_layer']:
+            value = int(value)
+        elif element == 'cpu_memory' and value is not None:
+            value = f"{value}MiB"
+
+        setattr(shared.args, element, value)
+
+    found_positive = False
+    for i in gpu_memories:
+        if i > 0:
+            found_positive = True
+            break
+
+    if not (initial and vars(shared.args)['gpu_memory'] != vars(shared.args_defaults)['gpu_memory']):
+        if found_positive:
+            shared.args.gpu_memory = [f"{i}MiB" for i in gpu_memories]
+        else:
+            shared.args.gpu_memory = None
+
+
+def get_model_specific_settings(model):
+    settings = shared.model_config
+    model_settings = {}
+
+    for pat in settings:
+        if re.match(pat.lower(), model.lower()):
+            for k in settings[pat]:
+                model_settings[k] = settings[pat][k]
+
+    return model_settings
+
+
+def load_model_specific_settings(model, state, return_dict=False):
+    model_settings = get_model_specific_settings(model)
+    for k in model_settings:
+        if k in state:
+            state[k] = model_settings[k]
+
+    return state
+
+
+def save_model_settings(model, state):
+    if model == 'None':
+        yield ("Not saving the settings because no model is loaded.")
+        return
+
+    with Path(f'{shared.args.model_dir}/config-user.yaml') as p:
+        if p.exists():
+            user_config = yaml.safe_load(open(p, 'r').read())
+        else:
+            user_config = {}
+
+        if model not in user_config:
+            user_config[model] = {}
+
+        for k in ui.list_model_elements():
+            user_config[model][k] = state[k]
+
+        with open(p, 'w') as f:
+            f.write(yaml.dump(user_config))
+
+        yield (f"Settings for {model} saved to {p}")
+
+
+def create_model_menus():
+    # Finding the default values for the GPU and CPU memories
+    total_mem = []
+    for i in range(torch.cuda.device_count()):
+        total_mem.append(math.floor(torch.cuda.get_device_properties(i).total_memory / (1024 * 1024)))
+
+    default_gpu_mem = []
+    if shared.args.gpu_memory is not None and len(shared.args.gpu_memory) > 0:
+        for i in shared.args.gpu_memory:
+            if 'mib' in i.lower():
+                default_gpu_mem.append(int(re.sub('[a-zA-Z ]', '', i)))
+            else:
+                default_gpu_mem.append(int(re.sub('[a-zA-Z ]', '', i)) * 1000)
+    while len(default_gpu_mem) < len(total_mem):
+        default_gpu_mem.append(0)
+
+    total_cpu_mem = math.floor(psutil.virtual_memory().total / (1024 * 1024))
+    if shared.args.cpu_memory is not None:
+        default_cpu_mem = re.sub('[a-zA-Z ]', '', shared.args.cpu_memory)
+    else:
+        default_cpu_mem = 0
+
+    with gr.Row():
+        with gr.Column():
+            with gr.Row():
+                with gr.Column():
+                    with gr.Row():
+                        shared.gradio['model_menu'] = gr.Dropdown(choices=get_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['lora_menu'] = gr.Dropdown(multiselect=True, choices=get_available_loras(), value=shared.lora_names, label='LoRA(s)')
+                        ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': get_available_loras(), 'value': shared.lora_names}, 'refresh-button')
+
+        with gr.Column():
+            with gr.Row():
+                shared.gradio['lora_menu_apply'] = gr.Button(value='Apply the selected LoRAs')
+            with gr.Row():
+                unload = gr.Button("Unload the model")
+                reload = gr.Button("Reload the model")
+                save_settings = gr.Button("Save settings for this model")
+
+    with gr.Row():
+        with gr.Column():
+            with gr.Box():
+                gr.Markdown('Transformers parameters')
+                with gr.Row():
+                    with gr.Column():
+                        for i in range(len(total_mem)):
+                            shared.gradio[f'gpu_memory_{i}'] = gr.Slider(label=f"gpu-memory in MiB for device :{i}", maximum=total_mem[i], value=default_gpu_mem[i])
+                        shared.gradio['cpu_memory'] = gr.Slider(label="cpu-memory in MiB", maximum=total_cpu_mem, value=default_cpu_mem)
+
+                    with gr.Column():
+                        shared.gradio['auto_devices'] = gr.Checkbox(label="auto-devices", value=shared.args.auto_devices)
+                        shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk)
+                        shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu)
+                        shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16)
+                        shared.gradio['load_in_8bit'] = gr.Checkbox(label="load-in-8bit", value=shared.args.load_in_8bit)
+
+        with gr.Column():
+            with gr.Box():
+                gr.Markdown('GPTQ parameters')
+                with gr.Row():
+                    with gr.Column():
+                        shared.gradio['wbits'] = gr.Dropdown(label="wbits", choices=["None", 1, 2, 3, 4, 8], value=shared.args.wbits if shared.args.wbits > 0 else "None")
+                        shared.gradio['groupsize'] = gr.Dropdown(label="groupsize", choices=["None", 32, 64, 128], value=shared.args.groupsize if shared.args.groupsize > 0 else "None")
+
+                    with gr.Column():
+                        shared.gradio['model_type'] = gr.Dropdown(label="model_type", choices=["None", "llama", "opt", "gptj"], value=shared.args.model_type or "None")
+                        shared.gradio['pre_layer'] = gr.Slider(label="pre_layer", minimum=0, maximum=100, value=shared.args.pre_layer)
+
+    with gr.Row():
+        with gr.Column():
+            shared.gradio['custom_model_menu'] = gr.Textbox(label="Download custom model or LoRA", info="Enter Hugging Face username/model path, e.g: facebook/galactica-125m")
+            shared.gradio['download_model_button'] = gr.Button("Download")
+
+        with gr.Column():
+            shared.gradio['model_status'] = gr.Markdown('No model is loaded' if shared.model_name == 'None' else 'Ready')
+
+    # In this event handler, the interface state is read and updated
+    # with the model defaults (if any), and then the model is loaded
+    shared.gradio['model_menu'].change(
+        ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+        load_model_specific_settings, [shared.gradio[k] for k in ['model_menu', 'interface_state']], shared.gradio['interface_state']).then(
+        ui.apply_interface_values, shared.gradio['interface_state'], [shared.gradio[k] for k in ui.list_interface_input_elements(chat=shared.is_chat())], show_progress=False).then(
+        update_model_parameters, shared.gradio['interface_state'], None).then(
+        load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=True)
+
+    unload.click(
+        unload_model, None, None).then(
+        lambda: "Model unloaded", None, shared.gradio['model_status'])
+
+    reload.click(
+        unload_model, None, None).then(
+        ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+        update_model_parameters, shared.gradio['interface_state'], None).then(
+        load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=False)
+
+    save_settings.click(
+        ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+        save_model_settings, [shared.gradio[k] for k in ['model_menu', 'interface_state']], shared.gradio['model_status'], show_progress=False)
+
+    shared.gradio['lora_menu_apply'].click(load_lora_wrapper, shared.gradio['lora_menu'], shared.gradio['model_status'], show_progress=False)
+    shared.gradio['download_model_button'].click(download_model_wrapper, shared.gradio['custom_model_menu'], shared.gradio['model_status'], show_progress=False)
+
+
+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.Row():
+                shared.gradio['preset_menu'] = gr.Dropdown(choices=get_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')
+        with gr.Column():
+            shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)')
+
+    with gr.Row():
+        with gr.Column():
+            with gr.Box():
+                gr.Markdown('Custom generation parameters ([click here to view technical documentation](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', info='Primary factor to control randomness of outputs. 0 = deterministic (only the most likely token is used). Higher value = more randomness.')
+                        shared.gradio['top_p'] = gr.Slider(0.0, 1.0, value=generate_params['top_p'], step=0.01, label='top_p', info='If not set to 1, select tokens with probabilities adding up to less than this number. Higher value = higher range of possible random results.')
+                        shared.gradio['top_k'] = gr.Slider(0, 200, value=generate_params['top_k'], step=1, label='top_k', info='Similar to top_p, but select instead only the top_k most likely tokens. Higher value = higher range of possible random results.')
+                        shared.gradio['typical_p'] = gr.Slider(0.0, 1.0, value=generate_params['typical_p'], step=0.01, label='typical_p', info='If not set to 1, select only tokens that are at least this much more likely to appear than random tokens, given the prior text.')
+                    with gr.Column():
+                        shared.gradio['repetition_penalty'] = gr.Slider(1.0, 1.5, value=generate_params['repetition_penalty'], step=0.01, label='repetition_penalty', info='Exponential penalty factor for repeating prior tokens. 1 means no penalty, higher value = less repetition, lower value = more repetition.')
+                        shared.gradio['encoder_repetition_penalty'] = gr.Slider(0.8, 1.5, value=generate_params['encoder_repetition_penalty'], step=0.01, label='encoder_repetition_penalty', info='Also known as the "Hallucinations filter". Used to penalize tokens that are *not* in the prior text. Higher value = more likely to stay in context, lower value = more likely to diverge.')
+                        shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=generate_params['no_repeat_ngram_size'], label='no_repeat_ngram_size', info='If not set to 0, specifies the length of token sets that are completely blocked from repeating at all. Higher values = blocks larger phrases, lower values = blocks words or letters from repeating. Only 0 or high values are a good idea in most cases.')
+                        shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'], label='min_length', info='Minimum generation length in tokens.')
+                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')
+
+                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')
+                        shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty')
+                    with gr.Column():
+                        shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping')
+
+            with gr.Box():
+                with gr.Row():
+                    with gr.Column():
+                        shared.gradio['truncation_length'] = gr.Slider(value=shared.settings['truncation_length'], minimum=shared.settings['truncation_length_min'], maximum=shared.settings['truncation_length_max'], step=1, label='Truncate the prompt up to this length', info='The leftmost tokens are removed if the prompt exceeds this length. Most models require this to be at most 2048.')
+                        shared.gradio['custom_stopping_strings'] = gr.Textbox(lines=1, value=shared.settings["custom_stopping_strings"] or None, label='Custom stopping strings', info='In addition to the defaults. Written between "" and separated by commas. For instance: "\\nYour Assistant:", "\\nThe assistant:"')
+                    with gr.Column():
+                        shared.gradio['add_bos_token'] = gr.Checkbox(value=shared.settings['add_bos_token'], label='Add the bos_token to the beginning of prompts', info='Disabling this can make the replies more creative.')
+                        shared.gradio['ban_eos_token'] = gr.Checkbox(value=shared.settings['ban_eos_token'], label='Ban the eos_token', info='Forces the model to never end the generation prematurely.')
+
+                        shared.gradio['skip_special_tokens'] = gr.Checkbox(value=shared.settings['skip_special_tokens'], label='Skip special tokens', info='Some specific models need this unset.')
+
+    with gr.Accordion('Soft prompt', open=False):
+        with gr.Row():
+            shared.gradio['softprompts_menu'] = gr.Dropdown(choices=get_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['preset_menu'].change(load_preset_values, [shared.gradio[k] for k in ['preset_menu', 'interface_state']], [shared.gradio[k] for k in ['interface_state', '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['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, bool_active):
+    modes = ["default", "notebook", "chat", "cai_chat"]
+    cmd_list = vars(shared.args)
+    bool_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:]:
+        setattr(shared.args, k, False)
+    if interface_mode != "default":
+        setattr(shared.args, interface_mode, True)
+
+    for k in bool_list:
+        setattr(shared.args, k, False)
+    for k in bool_active:
+        setattr(shared.args, k, True)
+
+    shared.need_restart = True
+
+
+def create_interface():
+
+    # Defining some variables
+    gen_events = []
+    default_preset = shared.settings['presets'][next((k for k in shared.settings['presets'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
+    if len(shared.lora_names) == 1:
+        default_text = load_prompt(shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_names[0].lower())), 'default')])
+    else:
+        default_text = load_prompt(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'
+
+    # Authentication variables
+    auth = None
+    if shared.args.gradio_auth_path is not None:
+        gradio_auth_creds = []
+        with open(shared.args.gradio_auth_path, 'r', encoding="utf8") as file:
+            for line in file.readlines():
+                gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()]
+        auth = [tuple(cred.split(':')) for cred in gradio_auth_creds]
+
+    # Importing the extension files and executing their setup() functions
+    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 shared.is_chat() else ui.css + ui.chat_css, analytics_enabled=False, title=title, theme=ui.theme) as shared.gradio['interface']:
+
+        # Create chat mode interface
+        if shared.is_chat():
+            shared.input_elements = ui.list_interface_input_elements(chat=True)
+            shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
+            shared.gradio['Chat input'] = gr.State()
+
+            with gr.Tab('Text generation', elem_id='main'):
+                shared.gradio['display'] = gr.HTML(value=chat_html_wrapper(shared.history['visible'], shared.settings['name1'], shared.settings['name2'], 'cai-chat'))
+                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', elem_id='Generate', variant='primary')
+                    shared.gradio['Continue'] = gr.Button('Continue')
+
+                with gr.Row():
+                    shared.gradio['Copy last reply'] = gr.Button('Copy last reply')
+                    shared.gradio['Regenerate'] = gr.Button('Regenerate')
+                    shared.gradio['Replace last reply'] = gr.Button('Replace last reply')
+
+                with gr.Row():
+                    shared.gradio['Impersonate'] = gr.Button('Impersonate')
+                    shared.gradio['Send dummy message'] = gr.Button('Send dummy message')
+                    shared.gradio['Send dummy reply'] = gr.Button('Send dummy reply')
+
+                with gr.Row():
+                    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)
+
+                shared.gradio['mode'] = gr.Radio(choices=['cai-chat', 'chat', 'instruct'], value=shared.settings['mode'], label='Mode')
+                shared.gradio['instruction_template'] = gr.Dropdown(choices=get_available_instruction_templates(), label='Instruction template', value='None', visible=shared.settings['mode'] == 'instruct', info='Change this according to the model/LoRA that you are using.')
+
+            with gr.Tab('Character', elem_id='chat-settings'):
+                with gr.Row():
+                    with gr.Column(scale=8):
+                        shared.gradio['name1'] = gr.Textbox(value=shared.settings['name1'], lines=1, label='Your name')
+                        shared.gradio['name2'] = gr.Textbox(value=shared.settings['name2'], lines=1, label='Character\'s name')
+                        shared.gradio['greeting'] = gr.Textbox(value=shared.settings['greeting'], lines=4, label='Greeting')
+                        shared.gradio['context'] = gr.Textbox(value=shared.settings['context'], lines=4, label='Context')
+                        shared.gradio['turn_template'] = gr.Textbox(value=shared.settings['turn_template'], lines=1, label='Turn template', info='Used to precisely define the placement of spaces and new line characters in instruction prompts.')
+
+                    with gr.Column(scale=1):
+                        shared.gradio['character_picture'] = gr.Image(label='Character picture', type='pil')
+                        shared.gradio['your_picture'] = gr.Image(label='Your picture', type='pil', value=Image.open(Path('cache/pfp_me.png')) if Path('cache/pfp_me.png').exists() else None)
+
+                with gr.Row():
+                    shared.gradio['character_menu'] = gr.Dropdown(choices=get_available_characters(), 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'):
+                        gr.Markdown('# JSON format')
+                        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')
+                        gr.Markdown('# TavernAI PNG format')
+                        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'] = 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['stop_at_newline'] = gr.Checkbox(value=shared.settings['stop_at_newline'], label='Stop generating at new line character')
+
+                create_settings_menus(default_preset)
+
+        # Create notebook mode interface
+        elif shared.args.notebook:
+            shared.input_elements = ui.list_interface_input_elements(chat=False)
+            shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
+            shared.gradio['last_input'] = gr.State('')
+            with gr.Tab("Text generation", elem_id="main"):
+                with gr.Row():
+                    with gr.Column(scale=4):
+                        with gr.Tab('Raw'):
+                            shared.gradio['textbox'] = gr.Textbox(value=default_text, elem_classes="textbox", lines=27)
+
+                        with gr.Tab('Markdown'):
+                            shared.gradio['markdown'] = gr.Markdown()
+
+                        with gr.Tab('HTML'):
+                            shared.gradio['html'] = gr.HTML()
+
+                        with gr.Row():
+                            shared.gradio['Generate'] = gr.Button('Generate', variant='primary', elem_classes="small-button")
+                            shared.gradio['Stop'] = gr.Button('Stop', elem_classes="small-button")
+                            shared.gradio['Undo'] = gr.Button('Undo', elem_classes="small-button")
+                            shared.gradio['Regenerate'] = gr.Button('Regenerate', elem_classes="small-button")
+
+                    with gr.Column(scale=1):
+                        gr.HTML('<div style="padding-bottom: 13px"></div>')
+                        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'])
+                        with gr.Row():
+                            shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt')
+                            ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button')
+
+                        shared.gradio['save_prompt'] = gr.Button('Save prompt')
+                        shared.gradio['count_tokens'] = gr.Button('Count tokens')
+                        shared.gradio['status'] = gr.Markdown('')
+
+            with gr.Tab("Parameters", elem_id="parameters"):
+                create_settings_menus(default_preset)
+
+        # Create default mode interface
+        else:
+            shared.input_elements = ui.list_interface_input_elements(chat=False)
+            shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
+            shared.gradio['last_input'] = gr.State('')
+            with gr.Tab("Text generation", elem_id="main"):
+                with gr.Row():
+                    with gr.Column():
+                        shared.gradio['textbox'] = gr.Textbox(value=default_text, elem_classes="textbox_default", lines=27, 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'])
+                        with gr.Row():
+                            shared.gradio['Generate'] = gr.Button('Generate', variant='primary', elem_classes="small-button")
+                            shared.gradio['Stop'] = gr.Button('Stop', elem_classes="small-button")
+                            shared.gradio['Continue'] = gr.Button('Continue', elem_classes="small-button")
+                            shared.gradio['save_prompt'] = gr.Button('Save prompt', elem_classes="small-button")
+                            shared.gradio['count_tokens'] = gr.Button('Count tokens', elem_classes="small-button")
+
+                        with gr.Row():
+                            with gr.Column():
+                                with gr.Row():
+                                    shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt')
+                                    ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button')
+
+                            with gr.Column():
+                                shared.gradio['status'] = gr.Markdown('')
+
+                    with gr.Column():
+                        with gr.Tab('Raw'):
+                            shared.gradio['output_textbox'] = gr.Textbox(elem_classes="textbox_default_output", lines=27, 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)
+
+        # Model tab
+        with gr.Tab("Model", elem_id="model-tab"):
+            create_model_menus()
+
+        # Training tab
+        with gr.Tab("Training", elem_id="training-tab"):
+            training.create_train_interface()
+
+        # Interface mode tab
+        with gr.Tab("Interface mode", elem_id="interface-mode"):
+            modes = ["default", "notebook", "chat", "cai_chat"]
+            current_mode = "default"
+            for mode in modes[1:]:
+                if getattr(shared.args, mode):
+                    current_mode = mode
+                    break
+            cmd_list = vars(shared.args)
+            bool_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes + ui.list_model_elements()]
+            bool_active = [k for k in bool_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['bool_menu'] = gr.CheckboxGroup(choices=bool_list, value=bool_active, label="Boolean command-line flags")
+            shared.gradio['reset_interface'] = gr.Button("Apply and restart the interface")
+
+            # Reset interface event
+            shared.gradio['reset_interface'].click(
+                set_interface_arguments, [shared.gradio[k] for k in ['interface_modes_menu', 'extensions_menu', 'bool_menu']], None).then(
+                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); return []}')
+
+        # chat mode event handlers
+        if shared.is_chat():
+            shared.input_params = [shared.gradio[k] for k in ['Chat input', 'interface_state']]
+            clear_arr = [shared.gradio[k] for k in ['Clear history-confirm', 'Clear history', 'Clear history-cancel']]
+            reload_inputs = [shared.gradio[k] for k in ['name1', 'name2', 'mode']]
+
+            gen_events.append(shared.gradio['Generate'].click(
+                ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                lambda x: (x, ''), shared.gradio['textbox'], [shared.gradio['Chat input'], shared.gradio['textbox']], show_progress=False).then(
+                chat.cai_chatbot_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+            )
+
+            gen_events.append(shared.gradio['textbox'].submit(
+                ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                lambda x: (x, ''), shared.gradio['textbox'], [shared.gradio['Chat input'], shared.gradio['textbox']], show_progress=False).then(
+                chat.cai_chatbot_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+            )
+
+            gen_events.append(shared.gradio['Regenerate'].click(
+                ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+            )
+
+            gen_events.append(shared.gradio['Continue'].click(
+                ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                chat.continue_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+            )
+
+            gen_events.append(shared.gradio['Impersonate'].click(
+                ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=shared.args.no_stream)
+            )
+
+            shared.gradio['Replace last reply'].click(
+                chat.replace_last_reply, [shared.gradio[k] for k in ['textbox', 'name1', 'name2', 'mode']], shared.gradio['display'], show_progress=shared.args.no_stream).then(
+                lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+
+            shared.gradio['Send dummy message'].click(
+                chat.send_dummy_message, [shared.gradio[k] for k in ['textbox', 'name1', 'name2', 'mode']], shared.gradio['display'], show_progress=shared.args.no_stream).then(
+                lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+
+            shared.gradio['Send dummy reply'].click(
+                chat.send_dummy_reply, [shared.gradio[k] for k in ['textbox', 'name1', 'name2', 'mode']], shared.gradio['display'], show_progress=shared.args.no_stream).then(
+                lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+
+            shared.gradio['Clear history-confirm'].click(
+                lambda: [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr).then(
+                chat.clear_chat_log, [shared.gradio[k] for k in ['name1', 'name2', 'greeting', 'mode']], shared.gradio['display']).then(
+                chat.save_history, shared.gradio['mode'], None, show_progress=False)
+
+            shared.gradio['Stop'].click(
+                stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None).then(
+                chat.redraw_html, reload_inputs, shared.gradio['display'])
+
+            shared.gradio['mode'].change(
+                lambda x: gr.update(visible=x == 'instruct'), shared.gradio['mode'], shared.gradio['instruction_template']).then(
+                lambda x: gr.update(interactive=x != 'instruct'), shared.gradio['mode'], shared.gradio['character_menu']).then(
+                chat.redraw_html, reload_inputs, shared.gradio['display'])
+
+            shared.gradio['instruction_template'].change(
+                chat.load_character, [shared.gradio[k] for k in ['instruction_template', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'turn_template', 'display']]).then(
+                chat.redraw_html, reload_inputs, shared.gradio['display'])
+
+            shared.gradio['upload_chat_history'].upload(
+                chat.load_history, [shared.gradio[k] for k in ['upload_chat_history', 'name1', 'name2']], None).then(
+                chat.redraw_html, reload_inputs, shared.gradio['display'])
+
+            shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, None, shared.gradio['textbox'], show_progress=shared.args.no_stream)
+            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-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[k] for k in ['name1', 'name2', 'mode']], [shared.gradio['display'], shared.gradio['textbox']], show_progress=False)
+            shared.gradio['download_button'].click(lambda x: chat.save_history(x, timestamp=True), shared.gradio['mode'], shared.gradio['download'])
+            shared.gradio['Upload character'].click(chat.upload_character, [shared.gradio['upload_json'], shared.gradio['upload_img_bot']], [shared.gradio['character_menu']])
+            shared.gradio['character_menu'].change(chat.load_character, [shared.gradio[k] for k in ['character_menu', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'turn_template', 'display']])
+            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['your_picture'].change(chat.upload_your_profile_picture, [shared.gradio[k] for k in ['your_picture', 'name1', 'name2', 'mode']], shared.gradio['display'])
+            shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js+ui.chat_js}}}")
+
+        # notebook/default modes event handlers
+        else:
+            shared.input_params = [shared.gradio[k] for k in ['textbox', 'interface_state']]
+            if shared.args.notebook:
+                output_params = [shared.gradio[k] for k in ['textbox', 'markdown', 'html']]
+            else:
+                output_params = [shared.gradio[k] for k in ['output_textbox', 'markdown', 'html']]
+
+            gen_events.append(shared.gradio['Generate'].click(
+                lambda x: x, shared.gradio['textbox'], shared.gradio['last_input']).then(
+                ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream)  # .then(
+                # None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
+            )
+
+            gen_events.append(shared.gradio['textbox'].submit(
+                lambda x: x, shared.gradio['textbox'], shared.gradio['last_input']).then(
+                ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream)  # .then(
+                # None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
+            )
+
+            if shared.args.notebook:
+                shared.gradio['Undo'].click(lambda x: x, shared.gradio['last_input'], shared.gradio['textbox'], show_progress=False)
+                gen_events.append(shared.gradio['Regenerate'].click(
+                    lambda x: x, shared.gradio['last_input'], shared.gradio['textbox'], show_progress=False).then(
+                    ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                    generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream)  # .then(
+                    # None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
+                )
+            else:
+                gen_events.append(shared.gradio['Continue'].click(
+                    ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
+                    generate_reply, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=shared.args.no_stream)  # .then(
+                    # None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[1]; element.scrollTop = element.scrollHeight}")
+                )
+
+            shared.gradio['Stop'].click(stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None)
+            shared.gradio['prompt_menu'].change(load_prompt, shared.gradio['prompt_menu'], shared.gradio['textbox'], show_progress=False)
+            shared.gradio['save_prompt'].click(save_prompt, shared.gradio['textbox'], shared.gradio['status'], show_progress=False)
+            shared.gradio['count_tokens'].click(count_tokens, shared.gradio['textbox'], shared.gradio['status'], show_progress=False)
+            shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")
+
+        shared.gradio['interface'].load(partial(ui.apply_interface_values, {}, use_persistent=True), None, [shared.gradio[k] for k in ui.list_interface_input_elements(chat=shared.is_chat())], show_progress=False)
+        # Extensions block
+        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=shared.args.listen_host or '0.0.0.0', server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch, auth=auth)
+    else:
+        shared.gradio['interface'].launch(prevent_thread_lock=True, share=shared.args.share, server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch, auth=auth)
+
+
+if __name__ == "__main__":
+    # 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]
+
+    # Default extensions
+    extensions_module.available_extensions = get_available_extensions()
+    if shared.is_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)
+
+    available_models = get_available_models()
+
+    # Model defined through --model
+    if shared.args.model is not None:
+        shared.model_name = shared.args.model
+
+    # Only one model is available
+    elif len(available_models) == 1:
+        shared.model_name = available_models[0]
+
+    # Select the model from a command-line menu
+    elif shared.args.model_menu:
+        if len(available_models) == 0:
+            print('No models are available! Please download at least one.')
+            sys.exit(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]
+
+    # If any model has been selected, load it
+    if shared.model_name != 'None':
+        model_settings = get_model_specific_settings(shared.model_name)
+        shared.settings.update(model_settings)  # hijacking the interface defaults
+        update_model_parameters(model_settings, initial=True)  # hijacking the command-line arguments
+
+        # Load the model
+        shared.model, shared.tokenizer = load_model(shared.model_name)
+        if shared.args.lora:
+            add_lora_to_model(shared.args.lora)
+
+    # Force a character to be loaded
+    if shared.is_chat():
+        shared.persistent_interface_state.update({
+            'mode': shared.settings['mode'],
+            'character_menu': shared.args.character or shared.settings['character'],
+            'instruction_template': shared.settings['instruction_template']
+        })
+
+    # Launch the web UI
+    create_interface()
+    while True:
+        time.sleep(0.5)
+        if shared.need_restart:
+            shared.need_restart = False
+            shared.gradio['interface'].close()
+            create_interface()