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A newer version of the Gradio SDK is available:
4.42.0
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