TavernAI - Extras

What is this

A set of APIs for various SillyTavern extensions.

You need to run the lastest version of my TavernAI fork. Grab it here: Direct link to ZIP, Git repository

All modules require at least 6 Gb of VRAM to run. With Stable Diffusion disabled, it will probably fit in 4 Gb. Alternatively, everything could also be run on the CPU.

Try on Colab (runs KoboldAI backend and TavernAI Extras server alongside):

Colab link: https://colab.research.google.com/github/Cohee1207/SillyTavern/blob/main/colab/GPU.ipynb

How to run

❗ IMPORTANT!

Default requirements.txt contains only basic packages for text processing

If you want to use the most advanced features (like Stable Diffusion, TTS), change that to requirements-complete.txt in commands below. See Modules section for more details.

You must specify a list of module names to be run in the --enable-modules command (caption provided as an example). See Modules section.

☁️ Colab

Open colab link
Select desired "extra" options and start the cell
Wait for it to finish
Get an API URL link from colab output under the ### TavernAI Extensions LINK ### title
Start TavernAI with extensions support: set enableExtensions to true in config.conf
Navigate to TavernAI settings and put in an API URL and tap "Connect" to load the extensions

💻 Locally

Option 1 - Conda (recommended) 🐍

PREREQUISITES

Install Miniconda: https://docs.conda.io/en/latest/miniconda.html
(Important!) Read how to use Conda: https://conda.io/projects/conda/en/latest/user-guide/getting-started.html
Install git: https://git-scm.com/downloads

EXECUTE THESE COMMANDS ONE BY ONE IN THE CONDA COMMAND PROMPT.

TYPE/PASTE EACH COMMAND INTO THE PROMPT, HIT ENTER AND WAIT FOR IT TO FINISH!

Before the first run, create an environment (let's call it extras):

conda create -n extras

Now activate the newly created env

conda activate extras

Install the required system packages

conda install pytorch torchvision torchaudio pytorch-cuda=11.7 git -c pytorch -c nvidia

Clone this repository

git clone https://github.com/Cohee1207/TavernAI-extras

Navigated to the freshly cloned repository

cd TavernAI-extras

Install the project requirements

pip install -r requirements.txt

Run the Extensions API server

python server.py --enable-modules=caption,summarize,classify

Copy the Extra's server API URL listed in the console window after it finishes loading up. On local installs, this defaults to http://localhost:5100.
Open your SillyTavern config.conf file (located in the base install folder), and look for a line "const enableExtensions". Make sure that line has "= true", and not "= false".
Start your SillyTavern server
Open the Extensions panel (via the 'Stacked Blocks' icon at the top of the page), paste the API URL into the input box, and click "Connect" to connect to the Extras extension server.
To run again, simply activate the environment and run these commands. Be sure to the additional options for server.py (see below) that your setup requires.

conda activate extras
python server.py

Option 2 - Vanilla 🍦

Install Python 3.10: https://www.python.org/downloads/release/python-31010/
Install git: https://git-scm.com/downloads
Clone the repo:

git clone https://github.com/Cohee1207/TavernAI-extras
cd TavernAI-extras

Run python -m pip install -r requirements.txt
Run python server.py --enable-modules=caption,summarize,classify
Get the API URL. Defaults to http://localhost:5100 if you run locally.
Start SillyTavern with extensions support: set enableExtensions to true in config.conf
Navigate to SillyTavern extensions menu and put in an API URL and tap "Connect" to load the extensions

Modules

Name	Description	Included in default requirements.txt
`caption`	Image captioning	✔️ Yes
`summarize`	Text summarization	✔️ Yes
`classify`	Text sentiment classification	✔️ Yes
`keywords`	Text key phrases extraction	✔️ Yes
`prompt`	SD prompt generation from text	✔️ Yes
`sd`	Stable Diffusion image generation	❌ No (✔️ remote)

Additional options

Flag	Description
`--enable-modules`	Required option. Provide a list of enabled modules. Expects a comma-separated list of module names. See Modules Example: `--enable-modules=caption,sd`
`--port`	Specify the port on which the application is hosted. Default: 5100
`--listen`	Host the app on the local network
`--share`	Share the app on CloudFlare tunnel
`--cpu`	Run the models on the CPU instead of CUDA
`--summarization-model`	Load a custom summarization model. Expects a HuggingFace model ID. Default: Qiliang/bart-large-cnn-samsum-ChatGPT_v3
`--classification-model`	Load a custom sentiment classification model. Expects a HuggingFace model ID. Default (6 emotions): bhadresh-savani/distilbert-base-uncased-emotion Other solid option is (28 emotions): joeddav/distilbert-base-uncased-go-emotions-student
`--captioning-model`	Load a custom captioning model. Expects a HuggingFace model ID. Default: Salesforce/blip-image-captioning-large
`--keyphrase-model`	Load a custom key phrase extraction model. Expects a HuggingFace model ID. Default: ml6team/keyphrase-extraction-distilbert-inspec
`--prompt-model`	Load a custom prompt generation model. Expects a HuggingFace model ID. Default: FredZhang7/anime-anything-promptgen-v2
`--sd-model`	Load a custom Stable Diffusion image generation model. Expects a HuggingFace model ID. Default: ckpt/anything-v4.5-vae-swapped Must have VAE pre-baked in PyTorch format or the output will look drab!
`--sd-cpu`	Force the Stable Diffusion generation pipeline to run on the CPU. SLOW!
`--sd-remote`	Use a remote SD backend. Supported APIs: sd-webui
`--sd-remote-host`	Specify the host of the remote SD backend Default: 127.0.0.1
`--sd-remote-port`	Specify the port of the remote SD backend Default: 7860
`--sd-remote-ssl`	Use SSL for the remote SD backend Default: False
`--sd-remote-auth`	Specify the `username:password` for the remote SD backend (if required)

API Endpoints

Get active list

GET /api/modules

Input

None

Output

{"modules":["caption", "classify", "summarize"]}

Image captioning

POST /api/caption

Input

{ "image": "base64 encoded image" }

Output

{ "caption": "caption of the posted image" }

Text summarization

POST /api/summarize

Input

{ "text": "text to be summarize", "params": {} }

Output

{ "summary": "summarized text" }

Optional: `params` object for control over summarization:

Name	Default value
`temperature`	1.0
`repetition_penalty`	1.0
`max_length`	500
`min_length`	200
`length_penalty`	1.5
`bad_words`	["\n", '"', "*", "[", "]", "{", "}", ":", "(", ")", "<", ">"]

Text sentiment classification

POST /api/classify

Input

{ "text": "text to classify sentiment of" }

Output

{
    "classification": [
        {
            "label": "joy",
            "score": 1.0
        },
        {
            "label": "anger",
            "score": 0.7
        },
        {
            "label": "love",
            "score": 0.6
        },
        {
            "label": "sadness",
            "score": 0.5
        },
        {
            "label": "fear",
            "score": 0.4
        },
        {
            "label": "surprise",
            "score": 0.3
        }
    ]
}

NOTES

Sorted by descending score order

List of categories defined by the summarization model

Value range from 0.0 to 1.0

Key phrase extraction

POST /api/keywords

Input

{ "text": "text to be scanned for key phrases" }

Output

{
    "keywords": [
        "array of",
        "extracted",
        "keywords",
    ]
}

Stable Diffusion prompt generation

POST /api/prompt

Input

{ "name": "character name (optional)", "text": "textual summary of a character" }

Output

{ "prompts": [ "array of generated prompts" ] }

Stable Diffusion image generation

POST /api/image

Input

{ "prompt": "prompt to be generated", "sampler": "DDIM", "steps": 20, "scale": 6, "model": "model_name" }

Output

{ "image": "base64 encoded image" }

NOTES

Only the "prompt" parameter is required

Both "sampler" and "model" parameters only work when using a remote SD backend

Get available Stable Diffusion models

GET /api/image/models

Output

{ "models": [list of all availabe model names] }

Get available Stable Diffusion samplers

GET /api/image/samplers

Output

{ "samplers": [list of all availabe sampler names] }

Get currently loaded Stable Diffusion model

GET /api/image/model

Output

{ "model": "name of the current loaded model" }

Load a Stable Diffusion model (remote)

POST /api/image/model

Input

{ "model": "name of the model to load" }

Output

{ "previous_model": "name of the previous model", "current_model": "name of the newly loaded model" }

Cohee1207/TavernAI-extras

TavernAI - Extras

What is this

How to run

❗ IMPORTANT!

☁️ Colab

💻 Locally

Option 1 - Conda (recommended) 🐍

Option 2 - Vanilla 🍦

Modules

Additional options

API Endpoints

Get active list

Input

Output

Image captioning

Input

Output

Text summarization

Input

Output

Optional: params object for control over summarization:

Text sentiment classification

Input

Output

Key phrase extraction

Input

Output

Stable Diffusion prompt generation

Input

Output

Stable Diffusion image generation

Input

Output

Get available Stable Diffusion models

Output

Get available Stable Diffusion samplers

Output

Get currently loaded Stable Diffusion model

Output

Load a Stable Diffusion model (remote)

Input

Output

Optional: `params` object for control over summarization: