Good Eats

Inspiration

We were inspired by nutrition tracker apps that allow users to keep track of daily nutritional intake. However, we wanted to generate meals for our users as we understand that it can be difficult to think of meals to create.

What it does

Users can log in and input their stats i.e. height, weight, budget, etc. and through the use of Gemini AI it will curate three potential meals with nutritional facts breakdown.

How we built it

We used React and JavaScript for the front end. Then, we used Flask, Python, and MySQL for our back end. We also used Gemini AI and its API to create responses for our prompts. Additionally, we used Bing Image Search API to generate the images for each meal.

Challenges we ran into

Our largest challenge was understanding the syntax that would be needed to have the front end send/receive to and from the back end. We initially thought we didn't need Flask to send requests but realized it was easier after some research.

Accomplishments that we're proud of

We're proud to accomplish our first full-stack project. Not only that but for all of us our first project to incorporate an AI tool to help with our project.

What we learned

We learned how to create a full-stack application with Flask/React, use Gemini API, and incorporate Material UI through React to make our UI unique and welcoming.

What's next for Good Eats

We ran out of time but wanted to incorporate a Favorites feature. This feature allows users to Favorite a meal that was generated and view all favorite meals. Additionally, we want to extend this application to workout suggestions based on the user's goals.

Built With

• axios
• bing-search-api
• flask
• html
• javascript
• mysql
• python
• react