Food Mood is a web app that takes your photo, detects your visible mood, and suggests a restaurant based off of that mood!

The frontend is written in React.js, while the backend uses Express.js and Node.js. The backend is a Lambda function hosted on AWS Lambda, which makes a call to Yelp's Fusion API and Amazon's Rekognition API.

v3: My current and most likely final iteration of Food Mood is v3. I completely revamped the way the website looks, making it more visually appealing. I also switched over from hosting on AWS EC2 to AWS Amplify to see what Amplify is like.

v2: The frontend is built with React.js, while the backend uses Express.js and Node.js. The emotions are detected from the photo using Amazon's Rekognition API, and then I search for a restaurant using Yelp's Fusion API. The website is deployed on an AWS EC2 instance, using Nginx as a reverse proxy. Updates to the application are automatically deployed with AWS CodePipeline and CodeDeploy.

v1: The original Food Mood was my first ever website, and I built it as an entry to Capital One's Software Engineering Summit challenge. I originally was going to use solely HTML, CSS, and JavaScript, but I quickly learned that I had no way of hiding my API keys from the client. After much frustration, I found Node.js and Express.js and decided to hail mary it and learn how to create a backend. I'm really proud of this project, because I decided to pursue this project at the last minute and had less than two days to complete it. After the competition ended (I was accepted into the summit!), I decided to continue working on this project. I revamped the whole website with React and deployed it on an AWS EC2 Ubuntu instance to avoid the yucky slow loading times of Heroku.