rubber-ducky 1.1.0

AI Companion for Pair Programming

rubber ducky

tl;dr

• pip install rubber-ducky
• Install ollama
• ollama run codellama (first time and then you can just have application in background)
• There are probably other dependencies which I forgot to put in setup.py sorry in advance.
• Run with ducky -f <file path>

Why did I make this

I wrote ducky because I annoy engineers too much and I needed to talk someone through my code quickly and validate my approach. Maybe this is why I'm not a senior engineer.

Since I can't dump all my code to GPT and make it tell me I know how to code, I decided to build something for quick iteration. All. Local. I also didn't want to get fired by leaking all our data. Not again.

Dependencies

Bless the folks at Ollama cause they have been carrying my recent projects.

This project is currently only supported on Mac and Linux cause Ollama is a dependency. You will need Ollama installed on your machine. The model I use for this project is codellama.

For the first installation you can run ollama run codellama and it should pull the necessary binaries for you. Ollama is also great because it'll spin up a server which can run in the background and can even do automatic model switching as long as you have it installed.

Usage

Install through pypi:

pip install rubber-ducky .

Simple run

ducky

To use additional options:

ducky --file <path> --prompt <prompt> --directory <directory> --chain --model <model>

Where:

• --prompt or -p: Custom prompt to be used
• --file or -f: The file to be processed
• --directory or -d: The directory to be processed
• --chain or -c: Chain the output of the previous command to the next command
• --model or -m: The model to be used (default is "codellama")

Example output