## **Inspiration**

Ever had to wipe your hands constantly to search for recipes and ingredients while cooking?
Ever wondered about the difference between your daily nutrition needs and the nutrition of your diets?
Vocal Recipe is an integrated platform where users can easily find everything they need to know about home-cooked meals! Information includes recipes with nutrition information, measurement conversions, daily nutrition needs, cooking tools, and more! The coolest feature of Vocal Recipe is that users can access the platform through voice control, which means they do not need to constantly wipe their hands to search for information while cooking. Our platform aims to support healthy lifestyles and make cooking easier for everyone.

## **How we built Vocal Recipe**

Recipes and nutrition information is implemented by retrieving data from Spoonacular - an integrated food and recipe API.
The voice control system is implemented using Dasha AI - an AI voice recognition system that supports conversation between our platform and the end user.
The measurement conversion tool is implemented using a simple calculator.

## **Challenges and Learning Outcomes**

One of the main challenges we faced was the limited trials that Spoonacular offers for new users. To combat this difficulty, we had to switch between team members' accounts to retrieve data from the API.
Time constraint is another challenge that we faced. We do not have enough time to formulate and develop the whole platform in just 36 hours, thus we broke down the project into stages and completed the first three stages.
It is also our first time using Dasha AI - a relatively new platform which little open source code could be found. We got the opportunity to explore and experiment with this tool. It was a memorable experience.
## Inspiration

Partially inspired by the Smart Cities track, we wanted our app to have the direct utility of ordering food, while still being fun to interact with. We aimed to combine convenience with entertainment, making the experience more enjoyable than your typical drive-through order.

## What it does

You interact using only your voice. The app automatically detects when you start and stop talking, uses AI to transcribe what you say, figures out the food items (with modifications) you want to order, and adds them to your current order. It even handles details like size and flavor preferences. The AI then generates text-to-speech audio, which is played back to confirm your order in a humorous, engaging way. There is absolutely zero set-up or management necessary, as the program will completely ignore all background noises and conversation. Even then, it will still take your order with staggering precision.

## How we built it

The frontend of the app is built with React and TypeScript, while the backend uses Flask and Python. We containerized the app using Docker and deployed it using Defang. The design of the menu is also done in Canva with a dash of Harvard colors.

## Challenges we ran into

One major challenge was getting the different parts of the app—frontend, backend, and AI—to communicate effectively. From media file conversions to AI prompt engineering, we worked through each of the problems together. We struggled particularly with maintaining smooth communication once the app was deployed. Additionally, fine-tuning the AI to accurately extract order information from voice inputs while keeping the interaction natural was a big hurdle.

## Accomplishments that we're proud of

We're proud of building a fully functioning product that successfully integrates all the features we envisioned. We also managed to deploy the app, which was a huge achievement given the complexity of the project. Completing our initial feature set within the hackathon timeframe was a key success for us. Trying to work with Python data type was difficult to manage, and we were proud to navigate around that. We are also extremely proud to meet a bunch of new people and tackle new challenges that we were not previously comfortable with.

## What we learned

We honed our skills in React, TypeScript, Flask, and Python, especially in how to make these technologies work together. We also learned how to containerize and deploy applications using Docker and Docker Compose, as well as how to use Defang for cloud deployment.

## What's next for Harvard Burger

Moving forward, we want to add a business-facing interface, where restaurant staff would be able to view and fulfill customer orders. There will also be individual kiosk devices to handle order inputs. These features would allow *Harvard Burger* to move from a demo to a fully functional app that restaurants could actually use. Lastly, we can sell the product by designing marketing strategies for fast food chains.
## Inspiration

We were inspired by our collective experiences as college students always struggling to find a way to use ingredients that we have at home but it's always hard to find what's doable with the current inventory. Most times, those ingredients are left to waste because we don't know how to incorporate different ingredients for a meal. So we searched for recipe APIs to see how we could solve this problem.

## What it does

It is a website that returns a list of recipe titles and links for users to follow based on the ingredients that they enter in the search bar.

## How we built it

We used Spoonacular API to get the recipe titles and links based on the ingredients entered. We used HTML/CSS/JS to form the website.

## Challenges we ran into

Trying to get the API to work from the HTML/JS code. Authorization errors kept coming up. It was also really difficult to find a feasible idea with our current skill set as beginners. We had to pivot several times until we ended up here.

## Accomplishments that we're proud of

We're proud that we got the API to work and connect with our website. We're proud that the project works and that it's useful.

## What we learned

We learned how to use APIs and how to make websites.

## What's next for SpoonFULL

Having more features that can make the website nicer. Having more parameters in the apiURL to make it more specific. We also aim to better educate college students about sustainability and grocery buying habits through this website.