catai

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CatAI

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Run GGUF models on your computer with a chat ui.

Your own AI assistant runs locally on your computer.

Inspired by Node-Llama-Cpp, Llama.cpp

Installation & Use

Make sure you have Node.js (download current) installed.

npm install -g catai

catai install vicuna-7b-16k-q4_k_s
catai up

catai

Features

  • Auto detect programming language 🧑‍💻
  • Click on user icon to show original message 💬
  • Real time text streaming ⏱️
  • Fast model downloads 🚀

CLI

Usage: catai [options] [command]

Options:
-V, --version output the version number
-h, --help display help for command

Commands:
install|i [options] [models...] Install any GGUF model
models|ls [options] List all available models
use [model] Set model to use
serve|up [options] Open the chat website
update Update server to the latest version
active Show active model
remove|rm [options] [models...] Remove a model
uninstall Uninstall server and delete all models
help [command] display help for command

Install command

Usage: cli install|i [options] [models...]

Install any GGUF model

Arguments:
models Model name/url/path

Options:
-t --tag [tag] The name of the model in local directory
-l --latest Install the latest version of a model (may be unstable)
-b --bind [bind] The model binding method
-bk --bind-key [key] key/cookie that the binding requires
-h, --help display help for command

Cross-platform

You can use it on Windows, Linux and Mac.

This package uses node-llama-cpp which supports the following platforms:

  • darwin-x64
  • darwin-arm64
  • linux-x64
  • linux-arm64
  • linux-armv7l
  • linux-ppc64le
  • win32-x64-msvc

Memory usage

Runs on most modern computers. Unless your computer is very very old, it should work.

According to a llama.cpp discussion thread, here are the memory requirements:

  • 7B => ~4 GB
  • 13B => ~8 GB
  • 30B => ~16 GB

Good to know

  • All download data will be downloaded at ~/catai folder by default.
  • The download is multi-threaded, so it may use a lot of bandwidth, but it will download faster!

Web API

There is also a simple API that you can use to ask the model questions.

const response = await fetch('http://127.0.0.1:3000/api/chat/prompt', {
method: 'POST',
body: JSON.stringify({
prompt: 'Write me 100 words story'
}),
headers: {
'Content-Type': 'application/json'
}
});

const data = await response.text();

For more information, please read the API guide

Configuration

You can edit the configuration via the web ui.

More information here

Contributing

Contributions are welcome!

Please read our contributing guide to get started.

License

This project uses Llama.cpp to run models on your computer. So any license applied to Llama.cpp is also applied to this project.


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