🐋 pykoi: Active learning in one unified interface 🌊!

🌱 Installation

To get started to pykoi, we recommend you test on an EC2 instance instance with the following config:

EC2 g5.2x (if you want to run a pretrained model with 7B parameters)
Deep Learning AMI GPU PyTorch 2.0.1 (Ubuntu 20.04) 20230627
EBS: at least 100G

Once you are on your EC2 terminal, create a conda environment using:

conda create -n pykoi python=3.10 -y && source activate pykoi

Then install pykoi and the correlated torch version.

pip3 install pykoi && pip3 install torch --index-url https://download.pytorch.org/whl/cu118

❓ How do I use `pykoi`?

pykoi is a python interface to unify your ML model development and production. You can easily get real-time user feedback and continuous improving your model.

Here are some examples of common applications:

💬 Chatbots

If you are on a GPU instance, check launch_app_gpu.ipynb and see how to launch a chatbot UI using multiple models, and thumb up/down the model answers side by side.
If you are on a CPU instance, check launch_app_api.ipynb and see how to launch a chatbot UI using OpenAI or Amazon Bedrock (:woman_technologist: building now :man_technologist:), and thumb up/down the model answers side by side.

🤓 Dev Setup

If you are interested to contribute to us, here are the preliminary development setup.

Backend Dev Setup

conda create -n pykoi python=3.10
conda activate pykoi
cd pykoi
pip3 install poetry
poetry install --no-root

Frontend Dev Setup

Frontend:

cd frontend
npm install vite
npm run build

asaiacai/pykoi