MLSA SRM Recruitment Portal

AI-Powered Club Recruitment Platform

Streamlining club recruitment with intelligent automation and seamless user experience

🚀 Live Demo • 📖 Documentation • 🐛 Report Bug • ✨ Request Feature

📋 Table of Contents

🎯 Overview
✨ Features
🛠️ Tech Stack
🚀 Quick Start
📁 Project Structure
🤖 AI Integration
🗄️ Database Schema
🔌 API Reference

🎯 Overview

The MLSA SRM Recruitment Portal is a comprehensive, AI-powered platform designed to streamline the recruitment process for Microsoft Student Ambassadors (MSA) at SRM University. Built with modern web technologies and powered by Google Gemini AI, it provides intelligent automation for task management, submission review, and candidate evaluation.

🎯 Key Objectives

Automate Recruitment: Reduce manual effort in reviewing applications
Intelligent Evaluation: AI-powered scoring and feedback system
Enhanced UX: Modern, responsive interface for all users
Scalable Architecture: Built to handle high-volume recruitment cycles
Data-Driven Insights: Analytics and reporting for recruitment teams

✨ Features

👥 For Applicants

Feature	Description	Benefits
Smart Task Discovery	Filter by domain, subdomain, and target year	Find relevant opportunities quickly
Flexible Submissions	GitHub repos, portfolios, documents, and custom fields	Submit work in preferred format
AI-Powered Feedback	Instant scoring and detailed review	Get constructive feedback immediately
Progress Tracking	Real-time status updates and notifications	Stay informed about application status
Personal Dashboard	View all submissions and feedback history	Track progress across multiple applications

🔧 For Administrators

Feature	Description	Benefits
Task Management	Create and manage recruitment positions	Customize requirements and deadlines
AI Review System	Automated scoring with detailed feedback	Consistent, unbiased evaluation
Advanced Filtering	Filter by year, domain, status, and scores	Efficient candidate screening
Analytics Dashboard	Real-time insights and statistics	Data-driven recruitment decisions
Bulk Operations	Export shortlisted candidates as CSV	Streamline final selection process
Real-time Notifications	Instant alerts for new submissions	Stay updated on application activity

🔒 Security & Privacy

Row Level Security (RLS): Database-level access control
Role-based Access: Separate permissions for applicants and admins
Secure Authentication: Supabase Auth integration
Encrypted Storage: All data encrypted in transit and at rest
Privacy Compliance: GDPR-ready data handling

🛠️ Tech Stack

🎨 Frontend

Framework: Next.js 15.5.2 (App Router)
Language: TypeScript 5.0+
Styling: Tailwind CSS 4.0
UI Components: Shadcn/ui + Radix UI
Icons: Lucide React
Forms: React Hook Form + Zod validation

⚙️ Backend & Database

Backend: Next.js API Routes
Database: Supabase (PostgreSQL)
Authentication: Supabase Auth
Real-time: Supabase Realtime
Storage: Supabase Storage

🤖 AI & External APIs

AI Model: Google Gemini 1.5 Flash
GitHub Integration: Octokit
Web Scraping: Cheerio
Data Processing: PapaParse (CSV)

🛠️ Development Tools

Linting: ESLint 9
Type Checking: TypeScript
Environment: T3 Env
Package Manager: Yarn

🚀 Quick Start

📋 Prerequisites

Requirement	Version	Description
Node.js	18+	JavaScript runtime
Yarn	1.22+	Package manager
Supabase Account	Latest	Database & Auth
Google AI API Key	Latest	Gemini API access

🔧 Installation

Clone the repository

git clone https://github.com/MLSA-SRM/recruitment-portal.git
cd recruitment-portal

Install dependencies
```
yarn install
```
Environment Setup
```
cp .env.local.example .env.local
```

Configure your environment variables:

# Supabase Configuration
NEXT_PUBLIC_SUPABASE_URL=your_supabase_project_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key

# AI & External APIs
GEMINI_API_KEY=your_gemini_api_key
GITHUB_TOKEN=your_github_personal_access_token

# Optional: Analytics, Monitoring, etc.
NEXT_PUBLIC_APP_URL=http://localhost:3000

Database Setup

# Run Supabase migrations
npx supabase db push

Start Development Server
```
yarn dev
```

Your app will be available at http://localhost:3000

📜 Available Scripts

# Development
yarn dev          # Start development server
yarn build        # Build for production
yarn start        # Start production server
yarn lint         # Run ESLint

# Database
yarn db:push      # Push schema changes
yarn db:reset     # Reset database
yarn db:seed      # Seed with sample data

📁 Project Structure

recruitment-portal/
├── src/
│   ├── app/                    # Next.js App Router
│   │   ├── admin/             # Admin dashboard pages
│   │   │   ├── dashboard/     # Analytics & overview
│   │   │   ├── tasks/         # Task management
│   │   │   ├── submission/    # Submission review
│   │   │   └── export/        # Data export
│   │   ├── api/               # API routes
│   │   │   ├── submissions/   # Submission endpoints
│   │   │   ├── tasks/         # Task endpoints
│   │   │   └── submission-status/ # Status updates
│   │   ├── auth/              # Authentication pages
│   │   ├── apply/             # Application pages
│   │   ├── dashboard/         # User dashboard
│   │   └── profile/           # Profile management
│   ├── components/            # Reusable components
│   │   ├── ui/               # Shadcn/ui components
│   │   ├── admin-layout.tsx  # Admin layout wrapper
│   │   ├── navigation.tsx    # Navigation component
│   │   └── skeleton-*.tsx    # Loading components
│   └── lib/                  # Utilities & configurations
│       ├── ai.ts            # AI integration
│       ├── supabase.ts      # Database client
│       ├── types.ts         # TypeScript definitions
│       ├── constants.ts     # App constants
│       └── utils.ts         # Helper functions
├── supabase/                 # Database migrations
│   └── migrations/          # SQL migration files
├── public/                  # Static assets
└── Configuration files      # package.json, tsconfig.json, etc.

🤖 AI Integration

🧠 Intelligent Review System

The platform uses Google Gemini 1.5 Flash for automated submission evaluation with specialized prompts for different submission types:

📊 Evaluation Criteria

Submission Type	Focus Areas	Key Metrics
Technical (1st Year)	Fundamentals, effort, learning potential	Code quality, functionality, documentation
Technical (2nd Year)	Architecture, best practices, task compliance	Framework usage, performance, deployment
Corporate	Business suitability, strategic thinking	Feasibility, clarity, persuasion, creativity

🎯 Scoring Algorithm

Technical Proficiency: 40% weight
Code Quality: 30% weight
Documentation: 15% weight
Innovation: 15% weight

📈 Score Interpretation

Score Range	Performance Level	Action Required
900-1000	Exceptional	Immediate shortlist
800-899	Excellent	Strong candidate
700-799	Good	Review required
600-699	Average	May need improvement
< 600	Below Average	Requires significant work

🔍 Advanced Features

URL Validation: Intelligent detection of legitimate vs. placeholder submissions
Content Analysis: Detection of AI-generated or template content
Flexible Evaluation: Handles mixed-quality submissions gracefully
Structured Output: JSON-formatted responses for consistent parsing

🗄️ Database Schema

📋 Core Tables

Table	Purpose	Key Fields
`profiles`	User information	id, name, email, department, year, is_admin
`tasks`	Recruitment positions	id, title, description, domain, deadline
`submissions`	User applications	id, task_id, applicant_id, status, ai_score
`submission_fields`	Custom form fields	id, task_id, field_name, field_type, is_required

🔐 Security Model

Policy Type	Scope	Permissions
User Profiles	Own data only	Read, Update
Submissions	Own submissions	Read, Create
Tasks	All users	Read
Admin Access	All data	Full CRUD

🔄 Key Relationships

erDiagram
    profiles ||--o{ submissions : "creates"
    tasks ||--o{ submissions : "receives"
    tasks ||--o{ submission_fields : "contains"
    profiles ||--o{ tasks : "creates (admin)"

🔌 API Reference

🎯 Core Endpoints

Method	Endpoint	Description	Access
`POST`	`/api/submissions`	Submit application	Authenticated users
`GET`	`/api/submissions/:id`	Get submission details	Owner/Admin
`PUT`	`/api/submissions/:id/status`	Update status	Admin only
`GET`	`/api/tasks`	List available tasks	All users
`POST`	`/api/tasks`	Create new task	Admin only
`GET`	`/api/admin/export`	Export candidates CSV	Admin only
`POST`	`/api/submissions/:id/trigger-ai`	Trigger AI review	Admin only

🔐 Authentication

Bearer Token: Supabase JWT in Authorization header
Session-based: Automatic via Supabase client
Role-based: Admin endpoints require is_admin: true

📝 Request/Response Examples

Submit Application

POST /api/submissions
{
  "task_id": 123,
  "submission_data": {
    "github_url": "https://github.com/user/repo",
    "description": "Project description"
  }
}

AI Review Response

{
  "score": 850,
  "review": "## Code Review - Excellent Implementation\n\n### Summary\nWell-structured React application with modern practices...",
  "recommendation": "shortlist"
}

Name		Name	Last commit message	Last commit date
Latest commit History 46 Commits
public		public
src		src
supabase		supabase
.env.example		.env.example
.gitignore		.gitignore
README.md		README.md
components.json		components.json
eslint.config.mjs		eslint.config.mjs
next.config.ts		next.config.ts
package.json		package.json
postcss.config.mjs		postcss.config.mjs
tsconfig.json		tsconfig.json
yarn.lock		yarn.lock

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MLSA SRM Recruitment Portal

📋 Table of Contents

🎯 Overview

🎯 Key Objectives

✨ Features

👥 For Applicants

🔧 For Administrators

🔒 Security & Privacy

🛠️ Tech Stack

🎨 Frontend

⚙️ Backend & Database

🤖 AI & External APIs

🛠️ Development Tools

🚀 Quick Start

📋 Prerequisites

🔧 Installation

📜 Available Scripts

📁 Project Structure

🤖 AI Integration

🧠 Intelligent Review System

📊 Evaluation Criteria

🎯 Scoring Algorithm

📈 Score Interpretation

🔍 Advanced Features

🗄️ Database Schema

📋 Core Tables

🔐 Security Model

🔄 Key Relationships

🔌 API Reference

🎯 Core Endpoints

🔐 Authentication

📝 Request/Response Examples

Submit Application

AI Review Response

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