Improving healthcare through transparency.
This project was completed as part of CS 205: Software Engineering. We were tasked with taking a large and nebulous problem presentation and drilling it down to a completed piece of software.
On your first run, you'll need to initialize the ML stuff and Python, along with NodeJS. To do this, run:
./build_dev.shKeep in mind, this will build a ML model, so it may take a few minutes.
After this (and each subsequent time), simply start the Python server, then the node server:
cd ml_api
source .venv/bin/activate
python3 app.py# (new session in the main directory)
node serverBuild the production server like this (you only need to do this once):
./build_prod.shTo start it, simply run:
./start_production.shTo kill it, use:
./kill_production.shUnit tests expect the Python server to be running, so ensure you run ./build_dev.sh and start the Flask server before running them, or they will run infinitely.