🚀 CareerAI — AI-Powered Career Platform

CareerAI is a full-stack career development platform that helps students and fresh graduates become internship-ready using AI. It provides resume analysis, GitHub/LinkedIn profile scoring, AI-generated career roadmaps, smart internship matching, and a career chatbot — all powered by Groq LLM.

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✨ Features

Module	Description
Resume Analyzer	Upload PDF resume → get ATS score, skill gaps & improvement suggestions
GitHub Analyzer	Analyze any GitHub profile — repos, languages, tech stack & recruiter attractiveness score
LinkedIn Analyzer	Paste profile data or upload PDF → headline optimization, skill gaps & networking tips
Internship Finder	AI-matched internships filtered by skills, level & location
AI Career Roadmap	Groq-powered personalized roadmap with phases, resources, projects & chatbot
Career Chatbot	Ask career questions, get interview tips, project ideas & career advice

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🛠️ Tech Stack

Backend

• FastAPI — Python web framework
• SQLAlchemy — ORM (PostgreSQL via Neon / SQLite for local dev)
• Groq API — LLM integration (llama-3.3-70b-versatile)
• spaCy — NLP for skill extraction
• PyGithub — GitHub API integration
• pdfplumber — Resume PDF parsing
• passlib + python-jose — Auth (bcrypt hashing + JWT tokens)

Frontend

• HTML5 + Tailwind CSS + Vanilla JS
• Responsive design with mobile support
• Served via FastAPI StaticFiles

Database

• PostgreSQL (Neon) for production
• SQLite fallback for local development

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📁 Project Structure

career-platform/
├── .gitignore
├── README.md
├── DEPLOYMENT.md
├── backend/
│   ├── main.py              # FastAPI app + routes + static serving
│   ├── database.py           # DB engine (PostgreSQL / SQLite)
│   ├── models.py             # SQLAlchemy User model
│   ├── schemas.py            # Pydantic validation schemas
│   ├── requirements.txt      # Python dependencies
│   ├── Procfile              # Deploy command for Render/Heroku
│   ├── auth/
│   │   ├── router.py         # Register, Login, Logout, /me
│   │   └── utils.py          # Password hashing, JWT, auth dependency
│   ├── api/
│   │   ├── resume.py         # Resume upload & analysis endpoints
│   │   ├── github.py         # GitHub analysis endpoints
│   │   ├── linkedin.py       # LinkedIn analysis endpoints
│   │   ├── internships.py    # Internship finder endpoints
│   │   └── roadmap.py        # AI roadmap + chatbot endpoints
│   └── services/
│       ├── groq_service.py       # Groq LLM integration
│       ├── resume_parser.py      # PDF text extraction
│       ├── skill_extractor.py    # NLP skill extraction
│       ├── ats_scorer.py         # ATS scoring logic
│       ├── github_analyzer.py    # GitHub profile analysis
│       ├── linkedin_analyzer.py  # LinkedIn profile analysis
│       ├── internship_matcher.py # Internship matching
│       └── internship_scraper.py # Internship data collection
└── frontend/
    ├── index.html            # Landing page
    ├── login.html            # Sign in
    ├── register.html         # Create account
    ├── dashboard.html        # User dashboard
    ├── resume.html           # Resume analyzer UI
    ├── github.html           # GitHub analyzer UI
    ├── linkedin.html         # LinkedIn analyzer UI
    ├── internships.html      # Internship finder UI
    └── roadmap.html          # AI roadmap + chatbot UI

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⚡ Quick Start (Local Development)

1. Clone the repo

git clone https://github.com/YOUR_USERNAME/career-platform.git
cd career-platform

2. Set up the backend

cd backend
pip install -r requirements.txt
python -m spacy download en_core_web_sm

3. Configure environment variables

Create a .env file in the backend/ folder:

GROQ_API_KEY=your_groq_api_key
RAPIDAPI_KEY=your_rapidapi_key
JWT_SECRET_KEY=your_random_64_char_secret
DATABASE_URL=sqlite:///./careerai.db
ALLOWED_ORIGINS=*

💡 Generate a secure JWT secret: python -c "import secrets; print(secrets.token_hex(32))"

4. Start the server

uvicorn main:app --reload --port 8000

5. Open the app

• 🌐 App: http://localhost:8000/site/index.html
• 📖 API Docs: http://localhost:8000/docs

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🚀 Deployment (Render)

See DEPLOYMENT.md for full instructions.

Quick steps:

1. Push to GitHub
2. Create a Web Service on Render → connect your repo
3. Root Directory: backend
4. Build Command: pip install -r requirements.txt && python -m spacy download en_core_web_sm
5. Start Command: uvicorn main:app --host 0.0.0.0 --port $PORT
6. Set environment variables in Render dashboard

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🔑 Environment Variables

Variable	Required	Description
GROQ_API_KEY	✅	Groq API key for LLM features
RAPIDAPI_KEY	✅	RapidAPI key for job data
JWT_SECRET_KEY	✅	Secret for JWT token signing
DATABASE_URL	✅	PostgreSQL connection string
ALLOWED_ORIGINS	Optional	CORS origins (comma-separated or *)

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📡 API Endpoints

Method	Endpoint	Description
POST	/auth/register	Register new user
POST	/auth/login	Login & get JWT token
GET	/auth/me	Get current user profile
POST	/resume/analyze	Upload & analyze resume
POST	/github/analyze	Analyze GitHub profile
POST	/linkedin/analyze	Analyze LinkedIn profile
GET	/internships/search	Search internships
POST	/roadmap/generate	Generate AI career roadmap
POST	/roadmap/chat	Career chatbot
GET	/health	Health check

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📄 License

This project is for educational purposes. Built with ❤️ for students.