CareerView is an innovative AI-powered platform that helps professionals discover their next career path through intelligent resume analysis, personalized career matching, and interactive AI personas. Built with cutting-edge technologies, it provides comprehensive career guidance tailored to your unique skills and aspirations.

• AI-Powered Analysis: Advanced resume parsing using spaCy and NLP
• Personalized Matches: GPT-4 powered career recommendations
• Skill Gap Analysis: Identify missing skills for your target roles
• Match Scoring: Detailed compatibility scores for each career path

• Future Self Chat: Talk to AI personas representing your target careers
• Voice Conversations: Web-based voice chat using OpenAI's speech APIs
• Personalized Guidance: AI trained on your background and goals
• Real-time Insights: Get instant career advice and industry knowledge

• Learning Roadmaps: GPT-generated personalized learning paths
• Skill Development: Step-by-step skill acquisition plans
• Progress Tracking: Monitor your career transition journey
• Resource Recommendations: Curated learning materials and courses

• Azure Blob Storage: Secure cloud storage for all user data
• Career Matches: Save and revisit your personalized matches
• Learning Paths: Access your customized roadmaps anytime
• Chat History: Preserve conversations with AI personas

• Framework: Next.js with TypeScript
• Styling: Tailwind CSS with modern UI components
• State Management: React hooks and context
• Voice Integration: Web Speech API for voice interactions

• API Framework: FastAPI with async support
• AI Integration: OpenAI GPT-4 for intelligent analysis
• Document Processing: PyPDF2, python-docx for resume parsing
• Storage: Azure Blob Storage for persistent data

• Language Processing: spaCy for NLP and text analysis
• Vector Search: FAISS for semantic similarity matching
• AI Models: OpenAI GPT-4o for career matching and persona generation
• Voice AI: OpenAI Speech Recognition and Synthesis

• Python 3.8+
• Node.js 18+
• Azure Storage Account (optional)
• OpenAI API Key

1. Clone the repository

   git clone https://github.com/saswath-06/CareerView.git
   cd CareerView

2. Backend Setup

   cd backend
   pip install -r requirements.txt

3. Frontend Setup

   cd frontend
   npm install

4. Environment Configuration

   # Backend (.env)
   OPENAI_API_KEY=your_openai_api_key_here
   AZURE_STORAGE_CONNECTION_STRING=your_azure_connection_string
   AZURE_STORAGE_ACCOUNT_NAME=your_storage_account_name

5. Run the Application

   # Terminal 1 - Backend
   cd backend
   python main.py
   
   # Terminal 2 - Frontend
   cd frontend
   npm run dev

6. Access the Application

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:8000
   • API Docs: http://localhost:8000/docs

• Upload your resume (PDF/DOCX)
• AI analyzes your skills, experience, and background
• Get instant feedback on your profile

• View personalized career recommendations
• See compatibility scores and skill gaps
• Explore detailed career descriptions

• Select a career path to explore
• Chat with an AI persona representing that role
• Get personalized advice and insights
• Use voice chat for natural conversations

• Access customized learning roadmaps
• Track your skill development progress
• Get recommended resources and courses

• POST /upload-resume - Upload and analyze resume
• GET /career-matches/{user_id} - Get personalized career matches
• GET /career-path/{career_id} - Get learning roadmap
• POST /voice-chat/openai-chat/{persona_id} - AI voice chat

• GET /personas - List available AI personas
• POST /chat/{persona_id} - Text chat with persona
• POST /voice-chat/{persona_id} - Voice chat with persona

CareerView/
├── backend/                 # FastAPI backend
│   ├── main.py             # Main application
│   ├── resume_parser.py    # Resume analysis
│   ├── gpt4_career_matcher.py # AI matching
│   ├── persona_chat.py     # AI personas
│   ├── azure_storage.py    # Data persistence
│   └── requirements.txt    # Python dependencies
├── frontend/               # Next.js frontend
│   ├── src/
│   │   ├── app/           # Pages and routing
│   │   ├── components/    # React components
│   │   └── lib/          # Utilities
│   └── package.json      # Node dependencies
└── README.md             # This file

• Backend: FastAPI, OpenAI API, Azure Blob Storage, spaCy
• Frontend: Next.js 14, TypeScript, Tailwind CSS, Web Speech API
• AI/ML: GPT-4, FAISS, sentence-transformers, NLP processing

• Environment Variables: All sensitive data stored in environment variables
• Secure Storage: Azure Blob Storage with proper access controls
• API Security: FastAPI with proper validation and error handling
• No Hardcoded Secrets: All API keys and credentials externalized

• Deploy to Azure App Service, AWS Lambda, or similar
• Configure environment variables
• Set up Azure Blob Storage connection

• Deploy to Vercel, Netlify, or similar
• Configure API endpoints
• Set up environment variables

• OpenAI for GPT-4 and speech APIs
• FastAPI for the excellent web framework
• Next.js for the React framework
• Azure for cloud storage services
• spaCy for natural language processing

If you find CareerView helpful, please give it a ⭐ on GitHub!