## Inspiration

We got our inspiration from the countless calorie tracking apps. First of all, there isn't a single website we could find that tracked calories. There are a ton of apps, but not one website. Secondly, None of them offered recipes built in. In our website, the user can search for food items, and directly look at their recipes. Lastly, our nutrition analysis app analyses any food item you've ever heard of.

## What it does

Add food you eat in a day, track your calories, track fat%, and other nutrients, search recipes, and get DETAILED info about any food item/recipe.

## How we built it

Html, min.css, min.js, js, were planning on using deso/auth0 for login but couldnt due to time constraints.

## Challenges we ran into

We initially used react, but couldn't make the full app using react since we used static html to interact with the food apis. We also had another sole recipe finder app which we removed due to it being react only. Integrating the botdoc api was a MAJOR challenge, since we had no prior experience, and had no idea what we were doing basically. A suggestion to the BotDoc team would be to add demo apps to their documentation/tutorials, since currently theres literally nothing available except the documentation. The api is quite unheard of too as of now.

## Accomplishments that we're proud of

Making the website working, and getting it up and running using a github pages deployment

## What we learned

A LOT about botdoc, and refreshed our knowledge of html, css, js.

## What's next for Foodify

Improving the css firstly lol, right now its REALLY REALLY BAD.
## Inspiration

We recognized how much time meal planning can cause, especially for busy young professionals and students who have little experience cooking. We wanted to provide an easy way to buy healthy, sustainable meals for the week, without compromising the budget or harming the environment.

## What it does

Similar to services like "Hello Fresh", this is a webapp for finding recipes and delivering the ingredients to your house. This is where the similarities end, however. Instead of shipping the ingredients to you directly, our app makes use of local grocery delivery services, such as the one provided by Loblaws. The advantages to this are two-fold: first, it helps keep the price down, as your main fee is for the groceries themselves, instead of paying large amounts in fees to a meal kit company. Second, this is more eco-friendly. Meal kit companies traditionally repackage the ingredients in house into single-use plastic packaging, before shipping it to the user, along with large coolers and ice packs which mostly are never re-used. Our app adds no additional packaging beyond that the groceries initially come in.

## How We built it

We made a web app, with the client side code written using React. The server was written in python using Flask, and was hosted on the cloud using Google App Engine. We used MongoDB Atlas, also hosted on Google Cloud.

On the server, we used the Spoonacular API to search for recipes, and Instacart for the grocery delivery.

## Challenges we ran into

The Instacart API is not publicly available, and there are no public API's for grocery delivery, so we had to reverse engineer this API to allow us to add things to the cart. The Spoonacular API was down for about 4 hours on Saturday evening, during which time we almost entirely switched over to a less functional API, before it came back online and we switched back.

## Accomplishments that we're proud of

Created a functional prototype capable of facilitating the order of recipes through Instacart. Learning new skills, like Flask, Google Cloud and for some of the team React.

## What we've learned

How to reverse engineer an API, using Python as a web server with Flask, Google Cloud, new API's, MongoDB

## What's next for Fiscal Fresh

Add additional functionality on the client side, such as browsing by popular recipes
## Inspiration

I was cooking at home one day and I kept noticing we had half a carrot, half an onion, and like a quarter of a pound of ground pork lying around all the time. More often than not it was from me cooking a fun dish that my mother have to somehow clean up over the week. So I wanted to create an app that would help me use those ingredients that I have neglected so that even if both my mother and I forget about it we would not contribute to food waste.

## What it does

Our app uses a database to store our user's fridge and keeps track of the food in their fridge. When the user wants a food recipe recommendation our app will help our user finish off their food waste. Using the power of chatGPT our app is super flexable and all the unknown food and food that you are too lazy to measure the weight of can be quickly put into a flexible and delicious recipe.

## How we built it

Using figma for design, react.JS bootstrap for frontend, flask backend, a mongoDB database, and openAI APIs we were able to create this stunning looking demo.

## Challenges we ran into

We messed up our database schema and poor design choices in our APIs resulting in a complete refactor. Our group also ran into problems with react being that we were relearning it. OpenAI API gave us inconsistency problems too. We pushed past these challenges together by dropping our immediate work and thinking of a solution together.

## Accomplishments that we're proud of

We finished our demo and it looks good. Our dev-ops practices were professional and efficient, our kan-ban board saved us a lot of time when planning and implementing tasks. We also wrote plenty of documentations where after our first bout of failure we planned out everything with our group.

## What we learned

We learned the importance of good API design and planning to save headaches when implementing out our API endpoints. We also learned much about the nuance and intricacies when using CORS technology. Another interesting thing we learned is how to write detailed prompts to retrieve formatted data from LLMs.

## What's next for Food ResQ : AI Recommended Recipes To Reduce Food Waste

We are planning to add a receipt scanning feature so that our users would not have to manually add in each ingredients into their fridge. We are also working on a feature where we would prioritize ingredients that are closer to expiry. Another feature we are looking at is notifications to remind our users that their ingredients should be used soon to drive up our engagement more. We are looking for payment processing vendors to allow our users to operate the most advanced LLMs at a slight premium for less than a coffee a month.

## Challenges, themes, prizes we are submitting for

Sponsor Challenges: None
Themes: Artificial Intelligence & Sustainability
Prizes: Best AI Hack, Best Sustainability Hack, Best Use of MongoDB Atlas, Most Creative Use of Github, Top 3 Prize