This repository contains code which demonstrates ML-Ops using a FastAPI
application which predicts the flower class using the IRIS dataset (https://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html)
- Create a fork of the repo using the
fork
button. - Clone your fork using
git clone https://www.github.com/<your-username>/mlops-iris.git
- Install dependencies using
pip3 install -r requirements.txt
- Run application using
python3 main.py
- Run tests using
pytest
build
(test) for all the pull requestsbuild
(test) andupload_zip
for all pushes
- Change this README to add your name here: Nikhil Gopala. Add and commit changes to a new branch and create a pull request ONLY TO YOUR OWN FORK to see the CI/CD build happening. If the build succeeds, merge the pull request with master and see the CI/CD
upload_zip
take place. - Add 2 more unit tests of your choice to
test_app.py
and make sure they are passing. - Add one more classifier to startup and use only the one with better accuracy.
- Add the attribute
timestamp
to the response and return the current time with it.