Skip to content

KumarSubodh12/appraisal-system

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 

Repository files navigation

AppraisalAI — ML-Based Employee Appraisal System

AppraisalAI

A premium, ML-powered employee performance appraisal system built with Next.js

Live Demo GitHub Made By


✨ Features

  • 🧠 ML Score Engine — Weighted ensemble model evaluating 6 performance dimensions
  • 📊 Real-time Dashboard — Live charts with Radar, Line, Bar & Pie visualizations
  • 🔒 Role-Based Auth — Admin, Manager & Employee roles via NextAuth
  • 📧 Email Notifications — Automated appraisal emails via Resend
  • 📁 File Uploads — Secure document management via Uploadthing
  • 💳 Stripe Integration — Payment gateway ready
  • Real-time Updates — Live notifications via Pusher
  • 🎨 Premium UI — Custom gold cursor, particle animations, scroll effects
  • 🌑 Dark Theme — Obsidian + Gold premium design system
  • 💧 Watermark — "Made by Kumar Subodh" on every page

🚀 Live Demo

🔗 https://appraisal-system-theta.vercel.app

Demo Credentials:

Field Value
Email admin@company.com
Password admin123

🛠️ Tech Stack

Category Technology
Framework Next.js 14 (App Router) + TypeScript
Styling Tailwind CSS + Custom Design System
Database PostgreSQL (Neon)
ORM Prisma
Auth NextAuth.js
Charts Recharts
Real-time Pusher
Email Resend
File Upload Uploadthing
Payments Stripe
Deployment Vercel
Package Manager pnpm

📁 Project Structure

appraisal-system/
├── app/
│   ├── api/
│   │   ├── auth/          # NextAuth routes
│   │   ├── appraisals/    # Appraisal CRUD APIs
│   │   ├── employees/     # Employee management APIs
│   │   ├── ml/score/      # ML scoring engine
│   │   ├── email/         # Email notifications
│   │   └── notify/        # Pusher real-time
│   ├── dashboard/         # Main dashboard
│   ├── employees/         # Employee listing
│   ├── appraisals/        # Appraisal management
│   ├── analytics/         # Advanced analytics
│   ├── profile/           # User profile
│   └── settings/          # App settings
├── components/
│   ├── layout/Sidebar.tsx # Navigation sidebar
│   └── ui/                # Reusable UI components
├── lib/prisma.ts          # Database client
├── prisma/schema.prisma   # Database schema
└── types/index.ts         # TypeScript types

⚙️ Setup & Installation

Prerequisites

  • Node.js 18+
  • pnpm
  • PostgreSQL database (Neon recommended)

1. Clone the repository

git clone https://github.com/KumarSubodh12/appraisal-system.git
cd appraisal-system/appraisal-system

2. Install dependencies

pnpm install

3. Setup environment variables

cp .env.example .env

Fill in your .env:

DATABASE_URL="your-neon-postgresql-url"
NEXTAUTH_SECRET="your-secret-key"
NEXTAUTH_URL="http://localhost:3000"
RESEND_API_KEY="your-resend-key"
UPLOADTHING_SECRET="your-uploadthing-secret"
STRIPE_SECRET_KEY="your-stripe-key"
PUSHER_APP_ID="your-pusher-app-id"
PUSHER_KEY="your-pusher-key"
PUSHER_SECRET="your-pusher-secret"
PUSHER_CLUSTER="ap2"

4. Setup database

npx prisma migrate dev --name init
npx prisma generate

5. Run development server

pnpm dev

Open http://localhost:3000


🧠 ML Scoring Algorithm

The ML engine uses a weighted ensemble model across 6 dimensions:

Dimension Weight
Performance 25%
Productivity 20%
Teamwork 15%
Leadership 15%
Innovation 15%
Communication 10%

Grade Scale:

  • 🌟 Outstanding — 90-100
  • Excellent — 80-89
  • 👍 Good — 70-79
  • 📈 Satisfactory — 60-69
  • ⚠️ Needs Improvement — Below 60

📸 Screenshots

Page Description
Landing Premium hero with particle animations
Dashboard Real-time charts and KPI cards
Appraisals ML-scored employee appraisals
Analytics Advanced data visualizations
New Appraisal Interactive ML scoring form

🚀 Deployment

This project is deployed on Vercel with automatic deployments on every push to main.

# Deploy manually
git add .
git commit -m "your changes"
git push
# Vercel auto-deploys!

👨‍💻 Author

Kumar Subodh

GitHub

Made with ❤️ and lots of ☕


© 2025 AppraisalAI — Made by Kumar Subodh

About

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

No releases published

Packages

 
 
 

Contributors