🌐 TalentSphere

TalentSphere is an AI-Powered Recruitment and Talent Management Platform developed as part of the SE205.3 Software Architecture coursework. It streamlines the hiring process by intelligently matching candidates to jobs and leveraging generative AI for tailored interview generation.

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🚀 Features

• 🧠 AI-Powered Resume Parsing: Automatically extracts text, identifies skills, and estimates years of experience.
• ⚡ Smart Candidate Matching: Matches candidates to job requirements using configurable strategies (e.g., Skill Overlap, Experience-Weighted).
• 🤖 Generative AI Interview Questions: Integrates with Google's Gemini API to automatically generate role-specific interview questions, evaluation criteria, and rationales.
• 🔐 Role-Based Access Control: Secure, partitioned workflows for Admins, Recruiters, Hiring Managers, and Candidates.
• 📊 Real-Time Analytics Dashboard: Comprehensive metrics and insights for organizational management.

🏗️ Architecture Overview

The system is built as a distributed application with a clear separation of concerns:

• Frontend: A modern, responsive SPA built with React and Vite, featuring state management with Zustand and styling with Ant Design/Framer Motion.
• Backend: A robust API built on ASP.NET Core 9 following Clean Architecture principles:
  • Domain: Core entities and enums.
  • Application: Business logic, DTOs, and abstract interfaces.
  • Infrastructure: Entity Framework Core, SQL Server (LocalDB), Identity, JWT, and AI service implementations.
  • API: Controllers and middleware.

🛠️ Getting Started

Prerequisites

• Node.js (v18+) and npm
• .NET 9 SDK
• SQL Server LocalDB
• dotnet-ef global tool (dotnet tool install --global dotnet-ef)

1. Backend Setup

cd backend

# Apply EF Core migrations to create and seed the database
dotnet ef database update --project TalentSphere.Infrastructure --startup-project TalentSphere.Infrastructure

# Run the API
dotnet run --project TalentSphere.API

The API runs at http://localhost:5185 with Swagger UI at /swagger.

(Optional) Gemini AI Integration: For the AI interview question generator, provide a Google AI Studio API key via user secrets:

cd backend/TalentSphere.API
dotnet user-secrets set "Gemini:ApiKey" "<your-key>"

2. Frontend Setup

cd frontend

# Install dependencies
npm install

# Start the dev server
npm run dev

The frontend runs at http://localhost:5173.

🧪 Demo Accounts

The database is seeded with demo accounts on the first run. The default passwords are as follows:

Role	Email	Password
Admin	admin@talentsphere.local	Admin@12345
Recruiter	recruiter@talentsphere.local	Recruiter@12345
Hiring Manager	manager@talentsphere.local	Manager@12345
Candidate	candidate@talentsphere.local	Candidate@12345

📁 Repository Structure

TalentSphere/
├── backend/            # .NET 9 Clean Architecture Solution
│   ├── TalentSphere.API/
│   ├── TalentSphere.Application/
│   ├── TalentSphere.Domain/
│   ├── TalentSphere.Infrastructure/
│   └── TalentSphere.Tests/
└── frontend/           # React + Vite Application
    ├── src/
    └── public/

📝 License

This project is licensed under the MIT License.