Clone the repo and cd into nwHacks24-project\frontend. Then run with "npm i" then "npm start", the backend is running on port 3000, Installing packages may take a while. We are also able to successfully send an API request to our REST API's!

Task Trove came to life because we wanted to bring back that tight-knit community feeling in our neighborhoods. Nowadays, it seems like people aren't as connected with their neighbors as they used to be. So, we came up with this app to spice things up a bit and boost connections through games and cool rewards!

TaskTrove lets community members lend a hand to others in a fun and gamified way. On TaskTrove, users can throw out a problem or project they need help with and rally the community to come to the rescue. You can jump in, tackle tasks, and earn points! These points are your ticket to snagging rewards from local businesses, like coupons or gift cards. With our app, neighbors can forge connections and make memories that last!

hard work and dedication. On a technical note we built it using a MERN stack with UI design done in Figma and Authentication done with Auth0. We also used Github for collaboration!

Finding a place to sit with power. We also struggled to learn how to use the MERN stack and implementing out desired UI from Figma into the code using React.

We're pumped about what we've put together! We genuinely think our idea is a game-changer for building community. Plus, it was our first try at using the MERN stack, and pulling everything together successfully? That feeling is just awesome!

In constructing our project, we delved into the the complex world of the MERN stack. It was the initial foray into MERN for our group, and we can confidently say we navigated it successfully. We also gained skills in crafting components in React along the way.

Looking ahead with TaskTrover, our next steps include giving the user interface a polished look inspired by our mock-ups. We're also focused on beefing up user safety with more features. To make things smoother, we're thinking of bringing in an AI model to help gauge task difficulty, taking some weight off users. And to keep things transparent, we're considering a review feature where users can share their thoughts on the folks who pitched in and vice versa.