Inspiration
Many students and beginners struggle to stay consistent with fitness due to lack of personalized guidance, time constraints, and confusing online resources. I wanted to build a simple and accessible solution that acts like a personal fitness coach, helping users stay consistent and make better health decisions.
What it does
FitGenie AI is an AI-powered fitness web application that generates personalized workout plans and nutrition suggestions based on user input such as fitness goals, experience level, and available time. It also allows users to track their progress and stay motivated with daily recommendations.
How I built it
I built this project using the MERN stack (MongoDB, Express.js, React.js, Node.js). The frontend was developed with React and styled using Tailwind CSS for a clean and responsive UI. The backend was built using Node.js and Express, with MongoDB for storing user data.
The Gemini API was integrated to generate personalized workout routines and meal suggestions dynamically. Structured prompts were used to ensure accurate and useful responses.
Challenges I ran into
One of the main challenges was designing effective prompts for the Gemini API to generate structured and relevant fitness plans. Ensuring consistency in AI responses and formatting them properly for the UI was also challenging.
Another challenge was managing full-stack integration within a limited hackathon timeframe while keeping the application simple yet functional.
Accomplishments that I'm proud of
- Successfully integrated Gemini API for real-time AI-generated fitness plans
- Built a full-stack application within a short time
- Created a clean and user-friendly interface
- Developed a meaningful solution with real-world impact
What I learned
- How to integrate AI APIs into full-stack applications
- Prompt engineering for generating structured outputs
- Managing time and prioritizing features during a hackathon
- Improving frontend-backend communication
What's next for FitGenie AI
- Add real-time progress tracking with analytics
- Include video-based exercise guidance
- Improve personalization using user history
- Deploy the app for public use
Built With
- axios
- express.js
- framermotion
- googlegeminiapi
- jwtauthetication
- mongodb
- mongoose
- node.js
- react.js
- tailwindcss
- vite
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