Vital AI - Health & Wellness Platform

• Personalized meal suggestions with complete nutritional information
• Indian Cuisine Focus with authentic recipes using Google's Gemini API
• Advanced filtering by diet type, spice level, and nutritional needs
• Ingredient-based recipe search for practical meal planning

Health Monitoring Dashboard

• Unified view of all vital health metrics
• Water intake tracking with customizable goals
• Fasting schedule management
• Sleep quality monitoring and recommendations

Technology Stack

• Framework: Next.js 15
• Frontend: React 19, TypeScript, Tailwind CSS
• UI Components: shadcn/ui with custom dark theme
• Authentication: Supabase Auth
• Database: PostgreSQL (Supabase)
• AI Services: Google Gemini API
• Visualization: Framer Motion, Three.js
• 3D Health Visualizations: React Three Fiber
• API Integration: Google Fit, RapidAPI (workout database)

Getting Started

Prerequisites

• Node.js 20+
• pnpm (recommended) or npm
• Google Gemini API key
• Supabase account

Installation

1. Clone the repository

   git clone https://github.com/your-username/vital-ai.git
   cd vital-ai

2. Install dependencies

   pnpm install

3. Set up environment variables

   • Copy .env.local.example to .env.local
   • Add your Gemini API key
   • Set up Supabase credentials

4. Initialize the database

   • Run the SQL setup scripts from the supabase/ directory in your Supabase dashboard

5. Start the development server

   pnpm dev

Feature Highlights

Indian Cuisine Recipe Engine

The Indian cuisine feature showcases authentic recipes with proper regional classification and spice level indicators. The integration with Google's Gemini API enables:

• Region-specific recipes (North, South, East, West, Central Indian)
• Spice level customization (Mild 🌶️, Medium 🌶️🌶️, Hot 🌶️🌶️🌶️)
• Detailed nutritional breakdown with macros
• Dietary preference filtering (vegetarian, vegan, keto, etc.)
• Step-by-step instructions with ingredient lists

The recipe system includes a robust fallback mechanism that serves curated content when API services are unavailable, ensuring users always have access to quality recipes.

Predictive Health Analysis

The platform's predictive health analysis module evaluates various health markers to identify potential risks before they become problematic:

• Diabetes risk assessment based on lifestyle factors and metrics
• Cardiovascular health analysis with personalized recommendations
• Mental health monitoring with stress and sleep quality insights
• Skin condition analysis through visual pattern recognition
• Allergy risk evaluation based on environmental and genetic factors

Each analysis module provides actionable insights rather than just raw data, helping users make meaningful lifestyle adjustments.

Project Structure

The application follows a modular architecture for maintainability and scalability:

• /src/components - UI components organized by feature
• /src/app - Next.js app router pages and API routes
• /src/lib - Shared utilities, services, and API clients
• /src/contexts - React context providers for state management
• /src/data - Static data and fallback content
• /src/styles - Global styles and theme configuration
• /supabase - Database schema and migration scripts

API Integration

Google Gemini API

Used for generating personalized recipe suggestions and health insights. Set up your API key in the .env.local file:

GEMINI_API_KEY=your_api_key_here

Workout Database (RapidAPI)

Provides exercise information and workout plans. Configure in .env.local:

NEXT_PUBLIC_RAPIDAPI_KEY=your_api_key_here

Troubleshooting

API Connection Issues

If you experience problems with the Gemini API:

1. Verify your API key is correctly set in .env.local
2. Check your API quota and usage limits
3. Test the connection using the diagnostic tools in /src/lib/api/gemini-test.ts