text-generation-webui/docs/Extensions.md

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This web UI supports extensions. They are simply files under
```
extensions/your_extension_name/script.py
```
which can be invoked with the
```
--extension your_extension_name
```
command-line flag.
## [text-generation-webui-extensions](https://github.com/oobabooga/text-generation-webui-extensions)
The link above contains a directory of user extensions for text-generation-webui.
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If you create an extension, you are welcome to host it in a GitHub repository and submit it to the list above.
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## Built-in extensions
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Most of these have been created by the extremely talented contributors that you can find here: [contributors](https://github.com/oobabooga/text-generation-webui/graphs/contributors?from=2022-12-18&to=&type=a).
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|Extension|Description|
|---------|-----------|
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|[api](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/api)| Creates an API with two endpoints, one for streaming at `/api/v1/stream` port 5005 and another for blocking at `/api/v1/generate` por 5000. This is the main API for this web UI. |
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|[google_translate](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/google_translate)| Automatically translates inputs and outputs using Google Translate.|
|[character_bias](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/character_bias)| Just a very simple example that biases the bot's responses in chat mode.|
|[gallery](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/gallery/)| Creates a gallery with the chat characters and their pictures. |
|[silero_tts](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/silero_tts)| Text-to-speech extension using [Silero](https://github.com/snakers4/silero-models). When used in chat mode, it replaces the responses with an audio widget. |
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|[elevenlabs_tts](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/elevenlabs_tts)| Text-to-speech extension using the [ElevenLabs](https://beta.elevenlabs.io/) API. You need an API key to use it. |
|[send_pictures](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/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](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/whisper_stt)| Allows you to enter your inputs in chat mode using your microphone. |
|[sd_api_pictures](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/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](https://github.com/oobabooga/text-generation-webui/pull/309). |
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|[llava](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/llava) | Adds LLaVA multimodal model support. For detailed description see [README.md](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/llava/README.md) in the extension directory. |
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|[openai](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/openai)| Creates an API that mimics the OpenAI API and can be used as a drop-in replacement. |
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|[superbooga](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/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. |
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## How to write an extension
`script.py` has access to all variables in the UI through the `modules.shared` module, and it may define the following functions:
| Function | Description |
|-------------|-------------|
| `def ui()` | Creates custom gradio elements when the UI is launched. |
| `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 input parameters before it is used by the text generation functions. |
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| `def bot_prefix_modifier(string)` | Applied in chat mode to the prefix for the bot's reply (more on that below). |
| `def custom_generate_reply(...)` | Overrides the main text generation function. |
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| `def custom_generate_chat_prompt(...)` | Overrides the prompt generator in chat mode. |
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| `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 `llava` extension for an example |
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Additionally, the script may define two special global variables:
#### `params` dictionary
```python
params = {
"language string": "ja",
}
```
This dicionary can be used to make the extension parameters customizable by adding entries to a `settings.json` file like this:
```python
"google_translate-language string": "fr",
```
#### `input_hijack` dictionary
```python
input_hijack = {
'state': False,
'value': ["", ""]
}
```
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This is only relevant in chat mode. If your extension sets `input_hijack['state']` to `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 `llava` extension above for an example.
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## 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.
## 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. For `custom_generate_chat_prompt`, only the first declaration encountered will be used and the rest will be ignored.
```
python server.py --extensions enthusiasm translate # First apply enthusiasm, then translate
python server.py --extensions translate enthusiasm # First apply translate, then enthusiasm
```
## `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.
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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.
```python
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
```
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## `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.
```python
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
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# 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]
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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'
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else:
template = state['turn_template'].replace(r'\n', '\n')
replacements = {
'<|user|>': state['name1'].strip(),
'<|bot|>': state['name2'].strip(),
}
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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
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i = len(shared.history['internal']) - 1
while i >= 0 and len(encode(''.join(rows))[0]) < max_length:
if _continue and i == len(shared.history['internal']) - 1:
rows.insert(1, bot_turn_stripped + shared.history['internal'][i][1].strip())
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else:
rows.insert(1, bot_turn.replace('<|bot-message|>', shared.history['internal'][i][1].strip()))
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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)}))
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i -= 1
if impersonate:
min_rows = 2
rows.append(user_turn_stripped.rstrip(' '))
elif not _continue:
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# 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"]))}))
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# Adding the Character prefix
rows.append(apply_extensions("bot_prefix", bot_turn_stripped.rstrip(' ')))
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while len(rows) > min_rows and len(encode(''.join(rows))[0]) >= max_length:
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rows.pop(1)
prompt = ''.join(rows)
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if also_return_rows:
return prompt, rows
else:
return prompt
```