CatAI

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

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

npm install -g catai

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

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

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

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

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

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

• 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!

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

You can edit the configuration via the web ui.

More information here

Contributions are welcome!

Please read our contributing guide to get started.

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

If you like this repo, star it ✨