Acharya - AI Career Mentoring Assistant

An intelligent voice-powered career mentor that helps students discover their career paths through conversational AI.

🎯 Core Architecture

Three Main Senses:

• Ear (ASR): Speech-to-Text using OpenAI Whisper
• Brain (LLM + RAG): Gemini Pro API with Retrieval-Augmented Generation
• Voice (TTS): Human-like text-to-speech using ElevenLabs

🚀 Features

1. Student Profiling & Interest Mapping

   • Vocal interview instead of forms
   • Named Entity Recognition (NER) to extract skills
   • Automated profile building

2. Industry Integration

   • Real-time job market data via APIs
   • Salary trends and demand analysis
   • Location-specific insights

3. Career Simulation

   • Roleplay scenarios for different careers
   • Real-time feedback and scoring
   • Practical skill assessment

4. Roadmap & Portfolio Builder

   • Auto-generated PDF career roadmaps
   • Personalized learning paths
   • Email delivery system

🛠 Tech Stack

Component	Technology	Purpose
Logic/Brain	Gemini Pro API	Reasoning and conversation
Voice Input	OpenAI Whisper	Accurate speech recognition
Voice Output	ElevenLabs	Human-like voice synthesis
Database	MySQL	User profiles and analytics
Backend	FastAPI	High-performance API server
Frontend	React + Vite	Modern, beautiful UI
PDF Generation	ReportLab	Career roadmap PDFs
NER	spaCy	Skill extraction from speech

🎨 New React Frontend

A beautiful, modern frontend has been created with:

• Glass-morphism Design - Stunning visual effects
• Smooth Animations - Powered by Framer Motion
• Voice & Text Chat - Full AI interaction
• Career Simulations - Interactive practice scenarios
• Personalized Roadmaps - Visual career paths

Quick Start:

# Windows - Just double-click:
start-react-frontend.bat

# Or manually:
cd frontend
npm install
npm run dev

Visit: http://localhost:3000

📚 See FRONTEND_QUICKSTART.md for details.

📋 Prerequisites

• Python 3.10+
• MySQL 8.0+
• Node.js 16+ (for React frontend)
• API Keys:
  • Google Gemini API
  • ElevenLabs API
  • Job Market APIs (Adzuna, JobsPikr, or LinkedIn)

🔧 Installation

Backend Setup

1. Clone the repository:

git clone <repository-url>
cd Skill-Marg

2. Create virtual environment:

python -m venv venv
venv\Scripts\activate  # Windows

3. Install dependencies:

pip install -r requirements.txt

4. Set up environment variables:

cp .env.example .env
# Edit .env with your API keys

5. Initialize database:

python scripts/init_db.py

6. Run the backend:

python main.py

Frontend Setup

1. Quick start (Windows):

# Just double-click:
start-react-frontend.bat

2. Manual setup:

cd frontend
npm install
cp .env.example .env
npm run dev

The frontend will open at http://localhost:3000 The backend API runs at http://localhost:8000

🌐 API Endpoints

Student Management

• POST /api/student - Create student profile
• GET /api/student/{id} - Get student profile
• PUT /api/student/{id} - Update student profile

Conversation

• POST /api/conversation/chat - Chat with AI mentor
• POST /api/conversation/transcribe - Transcribe audio
• POST /api/conversation/synthesize - Text-to-speech

Simulation

• POST /api/simulation/start - Start career simulation
• POST /api/simulation/{id}/respond - Send simulation response
• POST /api/simulation/{id}/end - End simulation
• GET /api/simulation/{id}/feedback - Get feedback

Roadmap

• POST /api/roadmap/generate - Generate career roadmap
• POST /api/roadmap/{id}/email - Email roadmap PDF

📁 Project Structure

Skill-Marg/
├── backend/
│   ├── api/              # FastAPI routes
│   │   ├── conversation.py  # Chat endpoints
│   │   ├── student.py       # Profile endpoints
│   │   ├── simulation.py    # Simulation endpoints
│   │   ├── roadmap.py       # Roadmap endpoints
│   │   └── voice.py         # Voice endpoints
│   ├── core/             # Core components
│   │   ├── asr.py           # Speech recognition
│   │   ├── tts.py           # Text-to-speech
│   │   ├── llm.py           # AI/LLM integration
│   │   ├── ner.py           # Named entity recognition
│   │   └── database.py      # Database connection
│   ├── models/           # Database models
│   ├── services/         # Business logic
│   └── utils/            # Utility functions
├── frontend/             # React Frontend ✨NEW✨
│   ├── src/
│   │   ├── components/      # React components
│   │   ├── pages/          # Page components
│   │   │   ├── Home.jsx       # Landing page
│   │   │   ├── Chat.jsx       # Chat interface
│   │   │   ├── Profile.jsx    # Profile management
│   │   │   ├── Simulation.jsx # Career simulation
│   │   │   └── Roadmap.jsx    # Career roadmap
│   │   ├── services/       # API integration
│   │   └── store/          # State management
│   ├── package.json
│   └── README.md
├── scripts/              # Setup scripts
├── docs/                 # Documentation
├── FRONTEND_QUICKSTART.md    # Frontend quick start
├── FRONTEND_REACT_GUIDE.md   # Complete frontend guide
├── FRONTEND_VISUAL_GUIDE.md  # Visual design guide
├── start-react-frontend.bat  # Windows launcher
├── main.py              # Backend entry point
└── README.md            # This file

🔒 Security

• All API keys stored in environment variables
• Database credentials encrypted
• HTTPS enforced in production
• Rate limiting on API endpoints

📝 License

MIT License

🤝 Contributing

Contributions welcome! Please read CONTRIBUTING.md for details.

📧 Contact

For questions or support, reach out to [morawalpunit@gmail.com]