Zariya - AI Career Counseling Platform

A comprehensive career guidance platform that helps students make informed decisions about their education and career paths through AI-powered recommendations, aptitude assessments, and personalized guidance.

Features

🎯 Aptitude & Interest-Based Course Suggestion

• Comprehensive quiz assessing interests, strengths, and personality traits
• AI-driven course recommendations based on quiz results
• Career path comparisons and suggestions

📊 Course-to-Career Path Mapping

• Visual charts showing degree-to-career mappings
• Industry insights and job market trends
• Salary information and growth projections
• Required skills and certifications

🏛️ Nearby Government Colleges Directory

• Location-based college search
• Detailed college information including programs, cut-offs, facilities
• Contact information and application links
• Facility filters (hostel, library, labs, etc.)

📅 Timeline Tracker

• Personalized timeline management
• Important dates tracking (admissions, exams, scholarships)
• Notification system for upcoming deadlines
• Progress tracking and reminders

🎨 Customization and Personalization

• User profile creation with age, gender, class, interests
• AI-driven recommendations based on profile
• Personalized study materials and career suggestions
• Adaptive learning paths

💬 AI-Powered Career Counseling

• Interactive chat interface with Gemini AI
• Context-aware conversations using user profile
• Memory retention for consistent guidance
• Personalized recommendations integration

Tech Stack

Backend

• Node.js with Express.js
• MongoDB with Mongoose
• JWT for authentication
• bcryptjs for password hashing
• Google Generative AI for AI responses

Frontend

• React with React Router
• Tailwind CSS for styling
• Lucide React for icons
• Axios for API calls
• React Toastify for notifications

Prerequisites

• Node.js (v16 or higher)
• MongoDB (local or cloud instance)
• npm or yarn package manager
• Google AI API key for Gemini

Installation

1. Clone the Repository

git clone https://github.com/ultroi/SixBits.git
cd SixBits

2. Backend Setup

cd backend

# Install dependencies
npm install

# Create environment file
cp .env.example .env

# Update .env with your configuration
MONGODB_URI=mongodb://localhost:27017/Zariya
JWT_SECRET=your_jwt_secret_here
GOOGLE_AI_API_KEY=your_google_ai_api_key
PORT=5000

3. Frontend Setup

cd ../frontend

# Install dependencies
npm install

4. Database Setup

cd ../backend

# Seed the database with sample data
npm run seed

Running the Application

Local Development (Backend + Frontend)

Quick Start

# Install all dependencies
npm run install:all

# Start both backend and frontend
npm start

Manual Setup

Backend:

cd backend
npm install
npm run dev

Server will run on http://localhost:5000

Frontend:

cd frontend
npm install
npm start

Application will run on http://localhost:3000

Vercel Deployment

Prerequisites

• Vercel account
• MongoDB Atlas or cloud database
• Google AI API key

Deployment Steps

1. Install Vercel CLI

npm install -g vercel

2. Login to Vercel

vercel login

3. Deploy to Vercel

# From the root directory
vercel

# For production deployment
npm run vercel-deploy

4. Set Environment Variables in Vercel

   • Go to your Vercel dashboard
   • Select your project
   • Go to Settings → Environment Variables
   • Add the following variables:

     MONGODB_URI=your_mongodb_connection_string
     JWT_SECRET=your_jwt_secret_key
     GEMINI_API_KEY=your_google_ai_api_key
     NODE_ENV=production
     

5. Redeploy

vercel --prod

Environment Configuration

For Local Development

Create .env files in both backend/ and frontend/ directories:

backend/.env:

PORT=5000
MONGODB_URI=mongodb://localhost:27017/Zariya
JWT_SECRET=your_jwt_secret_here
GEMINI_API_KEY=your_google_ai_api_key

frontend/.env:

REACT_APP_API_URL=http://localhost:5000/api

For Vercel Production

• Set environment variables in Vercel dashboard
• Remove REACT_APP_API_URL from frontend/.env (it will default to /api)
• Use MongoDB Atlas for database (not local MongoDB)

Vercel Configuration

The project includes vercel.json with the following configuration:

• Frontend builds from frontend/ directory
• API routes handled by serverless functions in frontend/api/
• Static files served from frontend/build/
• Node.js 18 runtime for serverless functions

Post-Deployment

• Frontend will be available at your Vercel domain
• API endpoints will be accessible at /api/*
• Database connections use environment variables
• All routes are configured for SPA routing

API Endpoints

Authentication

• POST /api/auth/register - User registration with profile
• POST /api/auth/login - User login

Quiz

• GET /api/quiz - Get all quizzes
• GET /api/quiz/:id - Get quiz by ID
• POST /api/quiz/submit - Submit quiz answers

Courses

• GET /api/courses - Get courses (with filters)
• GET /api/courses/:id - Get course by ID
• GET /api/courses/:id/career-paths - Get career paths for course

Colleges

• GET /api/colleges - Get colleges (with filters)
• GET /api/colleges/location - Get colleges by location
• GET /api/colleges/:id - Get college by ID

Timeline

• GET /api/timeline/:userId - Get user timeline
• POST /api/timeline - Create timeline entry
• PUT /api/timeline/:id - Update timeline entry
• DELETE /api/timeline/:id - Delete timeline entry
• GET /api/timeline/:userId/upcoming - Get upcoming events

Chat

• POST /api/chat/message - Send message to AI

User Flow

1. Landing Page → Introduction to Zariya platform
2. Signup/Login → Create account with profile information
3. Dashboard → Central hub with personalized recommendations
4. Aptitude Quiz → Take comprehensive assessment
5. Course Explorer → Browse courses with career mappings
6. College Directory → Find nearby government colleges
7. Timeline Manager → Track important dates and deadlines
8. AI Chat → Get personalized career guidance

Database Models

User

• Personal information (name, email, age, gender, class)
• Academic interests
• Quiz results history
• Location coordinates

Quiz

• Questions with multiple choice options
• Categories (interest, strength, personality)
• Scoring system

Course

• Degree and stream information
• Career paths with salary data
• Entrance exams and eligibility
• Higher education options
• Entrepreneurship opportunities

College

• Location and contact information
• Programs offered with cut-offs
• Facilities and ratings
• Government/Private classification

Timeline

• User-specific events
• Types (exam, admission, scholarship, etc.)
• Priority levels and completion status
• Reminder system

Features in Detail

Aptitude Assessment

• 9 comprehensive questions across 3 categories
• Visual results with percentage breakdowns
• AI-powered course recommendations
• Results stored in user profile

Course Recommendations

• Filter by stream, degree, duration
• Career path visualization with salary data
• Required skills and growth projections
• Entrance exam information

College Search

• Location-based search (within 50km radius)
• Facility filters (hostel, library, labs, internet, sports)
• Program-specific search
• Direct application links and contact information

Timeline Management

• Automated event creation from quiz/course selections
• Priority-based notifications (high/medium/low)
• Progress tracking and completion status
• Custom event addition with date reminders

AI Personalization

• Context-aware conversations using user profile
• Quiz result integration for recommendations
• Personalized study plans and career advice
• Memory retention across sessions

Project Structure

Frontend

frontend/
  ├── public/
  ├── src/
  │   ├── components/    # Reusable UI components
  │   ├── context/       # React context for state management
  │   ├── pages/         # Page components (Dashboard, Quiz, Courses, etc.)
  │   ├── services/      # API service functions
  │   ├── App.js         # Main application component
  │   └── index.js       # Application entry point
  └── package.json

Backend

backend/
  ├── controllers/       # Request handlers
  ├── middleware/        # Custom middleware functions
  ├── models/            # MongoDB models
  ├── routes/            # API routes
  ├── services/          # Business logic services
  ├── server.js          # Server entry point
  ├── seed.js            # Database seeding script
  └── package.json

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

This project is licensed under the MIT License.

Support

For support or questions, please contact the development team or create an issue in the repository.

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Made with ❤️ for career growth