text-generation-webui/docs/Extensions.md

Extensions are defined by files named script.py inside subfolders of text-generation-webui/extensions. They are loaded at startup if specified with the --extensions flag.

For instance, extensions/silero_tts/script.py gets loaded with python server.py --extensions silero_tts.

text-generation-webui-extensions

The link above contains a directory of user extensions for text-generation-webui.

If you create an extension, you are welcome to host it in a GitHub repository and submit it to the list above.

Built-in extensions

Most of these have been created by the extremely talented contributors that you can find here: contributors.

Extension	Description
api	Creates an API with two endpoints, one for streaming at /api/v1/stream port 5005 and another for blocking at /api/v1/generate port 5000. This is the main API for this web UI.
google_translate	Automatically translates inputs and outputs using Google Translate.
character_bias	Just a very simple example that biases the bot's responses in chat mode.
gallery	Creates a gallery with the chat characters and their pictures.
silero_tts	Text-to-speech extension using Silero. When used in chat mode, it replaces the responses with an audio widget.
elevenlabs_tts	Text-to-speech extension using the ElevenLabs API. You need an API key to use it.
send_pictures	Creates an image upload field that can be used to send images to the bot in chat mode. Captions are automatically generated using BLIP.
whisper_stt	Allows you to enter your inputs in chat mode using your microphone.
sd_api_pictures	Allows you to request pictures from the bot in chat mode, which will be generated using the AUTOMATIC1111 Stable Diffusion API. See examples here.
multimodal	Adds multimodality support (text+images). For a detailed description see README.md in the extension directory.
openai	Creates an API that mimics the OpenAI API and can be used as a drop-in replacement.
superbooga	An extension that uses ChromaDB to create an arbitrarily large pseudocontext, taking as input text files, URLs, or pasted text. Based on https://github.com/kaiokendev/superbig.

How to write an extension

script.py may define the special functions and variables below.

Predefined functions

Function	Description
def ui()	Creates custom gradio elements when the UI is launched.
def custom_css()	Returns custom CSS as a string. It is applied whenever the web UI is loaded.
def custom_js()	Same as above but for javascript.
def input_modifier(string)	Modifies the input string before it enters the model. In chat mode, it is applied to the user message. Otherwise, it is applied to the entire prompt.
def output_modifier(string)	Modifies the output string before it is presented in the UI. In chat mode, it is applied to the bot's reply. Otherwise, it is applied to the entire output.
def state_modifier(state)	Modifies the dictionary containing the UI input parameters before it is used by the text generation functions.
def bot_prefix_modifier(string)	Applied in chat mode to the prefix for the bot's reply.
def custom_generate_reply(...)	Overrides the main text generation function.
def custom_generate_chat_prompt(...)	Overrides the prompt generator in chat mode.
def tokenizer_modifier(state, prompt, input_ids, input_embeds)	Modifies the input_ids/input_embeds fed to the model. Should return prompt, input_ids, input_embeds. See the multimodal extension for an example.
def custom_tokenized_length(prompt)	Used in conjunction with tokenizer_modifier, returns the length in tokens of prompt. See the multimodal extension for an example.

params dictionary

In this dictionary, display_name is used to define the displayed name of the extension in the UI, and is_tab is used to define whether the extension should appear in a new tab. By default, extensions appear at the bottom of the "Text generation" tab.

Example:

params = {
    "display_name": "Google Translate",
    "is_tab": True,
}

Additionally, params may contain variables that you want to be customizable through a settings.json file. For instance, assuming the extension is in extensions/google_translate, the variable language string in

params = {
    "display_name": "Google Translate",
    "is_tab": True,
    "language string": "jp"
}

can be customized by adding a key called google_translate-language string to settings.json:

"google_translate-language string": "fr",

That is, the syntax is extension_name-variable_name.

input_hijack dictionary

input_hijack = {
    'state': False,
    'value': ["", ""]
}

This is only used in chat mode. If your extension sets input_hijack['state'] = True at any moment, the next call to modules.chat.chatbot_wrapper will use the values inside input_hijack['value'] as the user input for text generation. See the send_pictures extension above for an example.

Additionally, your extension can set the value to be a callback in the form of def cb(text: str, visible_text: str) -> [str, str]. See the multimodal extension above for an example.

Using multiple extensions at the same time

In order to use your extension, you must start the web UI with the --extensions flag followed by the name of your extension (the folder under text-generation-webui/extension where script.py resides).

You can activate more than one extension at a time by providing their names separated by spaces. The input, output, and bot prefix modifiers will be applied in the specified order.

python server.py --extensions enthusiasm translate # First apply enthusiasm, then translate
python server.py --extensions translate enthusiasm # First apply translate, then enthusiasm

Do note, that for:

• custom_generate_chat_prompt
• custom_generate_reply
• tokenizer_modifier
• custom_tokenized_length

only the first declaration encountered will be used and the rest will be ignored.

The bot_prefix_modifier

In chat mode, this function modifies the prefix for a new bot message. For instance, if your bot is named Marie Antoinette, the default prefix for a new message will be

Marie Antoinette:

Using bot_prefix_modifier, you can change it to:

Marie Antoinette: *I am very enthusiastic*

Marie Antoinette will become very enthusiastic in all her messages.

custom_generate_reply example

Once defined in a script.py, this function is executed in place of the main generation functions. You can use it to connect the web UI to an external API, or to load a custom model that is not supported yet.

Note that in chat mode, this function must only return the new text, whereas in other modes it must return the original prompt + the new text.

import datetime

def custom_generate_reply(question, original_question, seed, state, eos_token, stopping_strings):
    cumulative = ''
    for i in range(10):
        cumulative += f"Counting: {i}...\n"
        yield cumulative

    cumulative += f"Done! {str(datetime.datetime.now())}"
    yield cumulative

custom_generate_chat_prompt example

Below is an extension that just reproduces the default prompt generator in modules/chat.py. You can modify it freely to come up with your own prompts in chat mode.

def custom_generate_chat_prompt(user_input, state, **kwargs):
    impersonate = kwargs['impersonate'] if 'impersonate' in kwargs else False
    _continue = kwargs['_continue'] if '_continue' in kwargs else False
    also_return_rows = kwargs['also_return_rows'] if 'also_return_rows' in kwargs else False
    is_instruct = state['mode'] == 'instruct'
    rows = [state['context'] if is_instruct else f"{state['context'].strip()}\n"]
    min_rows = 3

    # Finding the maximum prompt size
    chat_prompt_size = state['chat_prompt_size']
    if shared.soft_prompt:
        chat_prompt_size -= shared.soft_prompt_tensor.shape[1]

    max_length = min(get_max_prompt_length(state), chat_prompt_size)

    # Building the turn templates
    if 'turn_template' not in state or state['turn_template'] == '':
        if is_instruct:
            template = '<|user|>\n<|user-message|>\n<|bot|>\n<|bot-message|>\n'
        else:
            template = '<|user|>: <|user-message|>\n<|bot|>: <|bot-message|>\n'
    else:
        template = state['turn_template'].replace(r'\n', '\n')

    replacements = {
        '<|user|>': state['name1'].strip(),
        '<|bot|>': state['name2'].strip(),
    }

    user_turn = replace_all(template.split('<|bot|>')[0], replacements)
    bot_turn = replace_all('<|bot|>' + template.split('<|bot|>')[1], replacements)
    user_turn_stripped = replace_all(user_turn.split('<|user-message|>')[0], replacements)
    bot_turn_stripped = replace_all(bot_turn.split('<|bot-message|>')[0], replacements)

    # Building the prompt
    i = len(shared.history['internal']) - 1
    while i >= 0 and get_encoded_length(''.join(rows)) < max_length:
        if _continue and i == len(shared.history['internal']) - 1:
            rows.insert(1, bot_turn_stripped + shared.history['internal'][i][1].strip())
        else:
            rows.insert(1, bot_turn.replace('<|bot-message|>', shared.history['internal'][i][1].strip()))

        string = shared.history['internal'][i][0]
        if string not in ['', '<|BEGIN-VISIBLE-CHAT|>']:
            rows.insert(1, replace_all(user_turn, {'<|user-message|>': string.strip(), '<|round|>': str(i)}))

        i -= 1

    if impersonate:
        min_rows = 2
        rows.append(user_turn_stripped.rstrip(' '))
    elif not _continue:
        # Adding the user message
        if len(user_input) > 0:
            rows.append(replace_all(user_turn, {'<|user-message|>': user_input.strip(), '<|round|>': str(len(shared.history["internal"]))}))

        # Adding the Character prefix
        rows.append(apply_extensions("bot_prefix", bot_turn_stripped.rstrip(' ')))

    while len(rows) > min_rows and get_encoded_length(''.join(rows)) >= max_length:
        rows.pop(1)

    prompt = ''.join(rows)
    if also_return_rows:
        return prompt, rows
    else:
        return prompt