Tessera is application that transforms user documents (resumes, certificates, projects, videos) into a visual, AI-enhanced skill profile. Designed for both students and professionals, Tessera extracts, visualizes, and recommends skills and career paths using interactive UI and cutting-edge AI models.
- Modern Landing Page highlighting Tessera’s value proposition
- Dual Authentication Flows: Separate onboarding for students and professionals
- File Upload System integrated with a Flask API for skill extraction
- AI-Powered Skill Extraction using Mistral and LLaMA models
- Dual Visualization Modes: Interactive skill tree and detailed list view
- Skills Comparison Tool: Analyze overlaps and strengths with other users
- Professional Dashboard with real-time skill analytics
- Mobile-Responsive Design with smooth animations and intuitive navigation
- React + TypeScript
- Tailwind CSS
- React Router
- Node.js + Express
- PostgreSQL (via
pgmodule) - JWT Authentication
- Secure password handling with
bcrypt - RESTful APIs
- Flask (API in
FlaskEndpoint/app.py) - Mistral + LLaMA models via OpenRouter/Together API
- Faster Whisper for video/audio transcription
- PDF/Image/Video processing with OpenCV, pdf2image, and MoviePy
- Node.js 18+
- PostgreSQL 14+
- Python 3.9+
# Clone the repo
https://github.com/Neha-2005-VCE/Tessera.git
cd coachinproject
# Setup PostgreSQL
# Create DB and add details in \`.env\`
CREATE DATABASE tessera_db;PORT=3001
DATABASE_URL=postgresql://username:password@localhost:5432/tessera_db
JWT_SECRET=your_super_secret# Start Flask AI API
cd FlaskEndpoint
python app.py
# Start Node.js + React concurrently
cd ..
npm run dev- ✅ Real-time collaboration on skill trees
- ⏳ Resume ranking against job descriptions