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NextStep Career AI

AI-powered career platform for resume analysis, job role prediction, and personalized career roadmaps.

Live Demo: https://next-step-career-ai-c5t5.vercel.app/

GitHub: https://github.com/adrian-25/Next-Step-Career-AI


What It Does

  • Analyzes resumes using NLP and ML to extract skills and predict job roles
  • Scores resumes across Skills, Projects, Experience, and Education
  • Generates personalized career roadmaps based on skill gaps
  • Matches resumes against job descriptions
  • Full-text search across resume database
  • AI career chatbot and mentor features

Tech Stack

Layer Technology
Frontend React 18, Vite, TypeScript, Tailwind CSS
UI shadcn/ui, Recharts, Framer Motion
Backend FastAPI (Python 3.11)
ML scikit-learn, TF-IDF, Naive Bayes, Fuzzy Logic
Database PostgreSQL 15 (Supabase)
Auth Supabase Auth + JWT
Deploy Vercel (frontend) + Railway (backend)
CI/CD GitHub Actions

ML Pipeline

Resume text → Skill extraction → TF-IDF vectorization → Naive Bayes role prediction → Fuzzy skill matching → Weighted scoring

Final score = 0.7 × ML score + 0.3 × Fuzzy score


Project Structure

├── src/
│   ├── ai/          # ML models, fuzzy logic, resume parser, skill analyzer
│   ├── data/        # Job roles dataset, learning resources, skill definitions
│   ├── pages/       # 17 page components
│   ├── services/    # Supabase + FastAPI API layer
│   ├── components/  # Reusable UI components
│   └── hooks/       # Custom React hooks
├── backend/
│   ├── main.py      # FastAPI app
│   ├── ml/          # Python ML analyzer and parsers
│   ├── routers/     # resume, match, search, analytics, auth
│   └── Dockerfile
├── supabase/
│   └── migrations/  # 17 SQL migration files
└── .github/
    └── workflows/   # CI/CD pipelines

Getting Started

Frontend

npm install
npm run dev

Backend

cd backend
pip install -r requirements.txt
uvicorn main:app --reload --port 8000

Environment Variables

Copy .env.example to .env and fill in your values:

VITE_SUPABASE_URL=your_supabase_url
VITE_SUPABASE_ANON_KEY=your_anon_key
VITE_API_URL=http://localhost:8000/api

Author

Adrian Dsouza — BTech Computer Engineering, VIT Mumbai


License

MIT