Eater Active

Inspiration

Starting a workout routine can feel overwhelming. So many exercises, so many gyms and exercising equipments, conflicting advice, and no clear plan. We wanted to create a tool that removes the uncertainty and makes fitness approachable for everyone. Our goal was to empower users to take control of their health by providing personalized, achievable workout plans based on their own stats and schedules.

What it does

Eater Active generates a fully personalized weekly workout schedule. Users input their age, weight, fitness level, goals, and available gym days. Next, the user selects their preferred gym location. Based on this information, the app creates a detailed day-by-day plan, including exercises, sets, and reps. The workouts are tailored to help users progressively improve, balance muscle groups, and meet their fitness goals. The app removes the guesswork of planning workouts, making it easy for both beginners and experienced users to follow a structured routine.

How we built it

We began by brainstorming real problems students face and quickly focused on the challenge of creating personalized workout plans. After sketching out the app’s layout and user flow, we moved into development. The frontend was built using React to collect user inputs and display workouts through a clean, animated interface. Our backend, built with FastAPI, processes the user data and returns structured JSON schedules. We integrated Gemini (LLM) to generate customized workout plans, and added animations, image overlays, and smooth interactions to make the experience feel modern and engaging.

Challenges we ran into

On the backend, learning new frameworks and understanding how to structure routes, handle requests, and connect everything to the frontend was a major challenge. On the frontend, managing multiple libraries, coordinating components across several files, and keeping everything organized was a significant challenge.

Accomplishments that we're proud of

We created a fully interactive app that generates personalized workouts using an LLM (Gemini) and built an interface that feels clean, intuitive, and engaging. We’re especially proud of bringing together animations and smooth frontend-backend communication into one cohesive experience. As a team new to these frameworks, we’re proud of how much we’ve learned about web development and how far our project has come.

What we learned

We created a fully interactive app that generates personalized workouts using an LLM (Gemini), combining AI-powered recommendations with a clean, modern interface. Along the way, we explored new libraries like React Bootstrap and Framer Motion to enhance our UI and improve user experience. With guidance from our mentor, we learned the core elements of web development, from structuring a React frontend and managing state to building a FastAPI backend capable of handling data and returning dynamic JSON. This project significantly expanded our confidence and skillset as full-stack developers.

What's next for Eater Active

We have several additional features we've envisioned to add to Eater Active:

1. Progress tracking so users can save workouts, log completed sessions, and visualize their improvement over time.
2. A calendar view that maps out each user’s workout plan by date for easier planning and routine building.
3. An integrated fitness chatbot powered by an LLM to answer questions, give tips, and help users stay motivated.

Built With

• css
• gemini
• javascript
• python
• react