Katana project is a template for ASAP π ML application deployment
Checkout demo at- https://katana-demo.herokuapp.com/
- Flask RestX for ReSTFul requests
- Swagger UI and gunicorn integration
- Colored logging with custom handlers
- Docker ready configuration
- Integrated GitHub actions
- Production ready code π
We recommend using flask default serving for development and gunicorn server for production
We included following setup instructions;
- Local development
- Docker supported deployment
- Clone this repo with
git@github.com:shaz13/katana.git
- Set up environment using
python3 -m venv .env
- Activate envrionment using
# Linux / Mac / Unix
$ source .env/bin/activate
# Windows
$ \.env\Scripts\activate
- Install requirements using
pip install -r requirements.txt
- For debugging run from root -
python main.py
- Deploy using
Procfile
orbash scripts/start.sh
- Your API is being served at
localhost:9000
- Clone this repo with
git@github.com:shaz13/katana.git
- Install docker in your system
- Run
docker-compose up
- Your local port is mapped and being served at
localhost:9000
- Mohammad Shahebaz - @shaz13, @shaz13-socgen
- Aditya Soni - @AdityaSoni19031997
MIT License