Project Info
Inspiration
Our team wanted to address the growing concern for young adults and college students who are becoming increasingly dependent on food-delivery services like DoorDash and UberEats. This creates unhealthy habits of eating, which will scale into an unfavorable lifestyle in the future. For convenience's sake, we wanted to build a custom user-centric platform that is simple enough that even the least culinary-inclined could embrace the process of preparing a meal that you find delicious.
What it does
MealPrep gathers dishes from the keywords of your choice, steps you through the process of cooking with a voice-dictated AI chatbot, and bookmarks your favorite foods for next time.
How we built it
Built with React.js on the frontend, supported by Vite.js and Tailwind.css, packaged with Node.js, and deployed to Vercel. On the backend, we're using Javascript with Firebase user-authentication and Firestore to store user bookmarks. Our user experience is derived from Groq.AI's lightning responsive LLM responses, as well as Cartesia AI's voice-to-text dictation.
Challenges we ran into
Attempting to deploy on industry-standard technologies like AWS / Docker Trying to integrate Linter in a CI/CD pipeline using GitHub Actions Adding/removing data using Firestore
Accomplishments we're proud of
Creating a unified user-interface that reflects our values and simplistic, modern product vision. Adding dynamic animations that create a smooth navigational experience. Having integrated many technologies that all overlap with each other, consistently researched the docs to see what works best for our code. In the end, our technologies all fit together like a beautiful piece of the puzzle.
What we learned
API's are difficult to implement and wrangle around, and sometimes diving too deep into one solution isn't the most optimal workflow. Always remember to think of different solutions and take yourself outside of the box sometimes. Having a cycle of communication, delegating tasks, and single-focus times worked well for our team's productive workflow. It felt like mini-sprints which organized and allowed us to adapt to our own roles on the team. Taking a step back from coding to brainstorm, draw out our ideas, and have fun with the process is so important to the team's cohesive vision. It allows us to remain on the same page.
What's next
Features like ingredient overlap detection would focus on giving the users a way to see which of their favorite recipes can be built using the same ingredients. Engagement is an important factor for any platform. To add engagement, we want to focus on shifting our platform to social media. Features like a daily popular meal, or community postings where people can share their experiences and advice on meal-prepping would be a fantastic addition. On top of our default guides, we want there to be more interactivity with guides created by users and brands. Speaking of brands, having companies promote their meal-prep-friendly products on our page would be a great monetization strategy.
This project did not link a GitHub repository.
Analysis
No indexed repository for this project, so there are no commit stats to show.
Technology
- ExpressUnchecked
- FirebaseUnchecked
- ReactUnchecked
- Tailwind CSSUnchecked
- VercelUnchecked
No repository was indexed for this project, so these Devpost claims have not been checked against code.
AI coding agents
No repository was indexed, so agent usage could not be checked.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
No repository was indexed, so there is no codebase to measure.
This project did not link a GitHub repository, so there is nothing to diagram.
This project did not link a GitHub repository, so its feature claims have not been checked against code.
Export this project's context (description, README, evidence, key source files) to chat with an AI agent elsewhere.