TalentForge

End-to-end technical interview management platform — from scheduling and live interviews to AI-generated feedback and candidate practice.

🚀 Live Demo  ·  GitHub

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What is TalentForge?

TalentForge connects recruiters, interviewers, and candidates on a single platform. Recruiters request and manage interviews, interviewers submit scored reports, and candidates track their progress — with AI feedback summaries, mock interview sessions, and a role-based practice question bank built in.

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Features

	Feature	Description
🔐	Role-based access	Four roles — admin, recruiter, interviewer, candidate — each with a dedicated dashboard
📋	Interview management	Create, assign, schedule, and track interviews through a full status lifecycle
📅	Smart scheduling	Interviewers publish availability slots; recruiters use smart-match to find the right fit
📝	Scored reports	Multi-dimension scoring and written reports, published to candidates by recruiters
🤖	AI feedback	Generates summaries, strengths, and weaknesses from interview scores
🔔	Notifications	In-app notification system with unread counts and mark-all-read
🎥	Recording upload	Interview recordings stored and linked via Cloudinary
🎯	Mock interviews	Candidate-initiated solo practice sessions with AI evaluation
📚	Practice questions	Question bank filterable by job role, difficulty, and category

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Tech stack

Backend — Flask 3 · PostgreSQL · SQLAlchemy · Alembic · Flask-JWT-Extended · Marshmallow · Gunicorn

Frontend — React 18 · Vite 5 · React Router 6 · Axios · Tailwind CSS 3 · date-fns

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Project structure

TalentForge/
├── backend/
│   ├── app/
│   │   ├── auth/              # JWT routes + decorators
│   │   ├── users/             # User profile management
│   │   ├── interviews/        # Interview CRUD + lifecycle
│   │   ├── scheduling/        # Availability slots + smart match
│   │   ├── reports/           # Scored reports
│   │   ├── notifications/     # In-app notifications
│   │   ├── ai_feedback/       # AI summary generation
│   │   ├── mock_interviews/   # Mock interview sessions
│   │   ├── practice/          # Practice question bank
│   │   ├── models/            # SQLAlchemy models
│   │   ├── schemas/           # Marshmallow schemas
│   │   ├── services/          # Business logic layer
│   │   └── utils/             # Errors, pagination, validators
│   ├── migrations/            # Alembic versions
│   └── requirements.txt
│
└── frontend/
    └── src/
        ├── components/        # Layout, auth guards, shared UI
        ├── context/           # AuthContext
        ├── hooks/             # Custom React hooks
        ├── pages/             # Route-level page components
        ├── services/          # Axios API modules
        └── utils/             # Shared helpers

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Getting started

Prerequisites

• Python 3.11+
• Node.js 18+
• PostgreSQL database (local or Supabase)
• Cloudinary account
• OpenAI API key (optional — a rule-based fallback is included)

Backend

cd TalentForge/backend

python -m venv venv
source venv/bin/activate          # Windows: venv\Scripts\activate

pip install -r requirements.txt
cp .env.example .env              # fill in your values

flask db upgrade
python run.py

API runs at http://localhost:5000.

Frontend

cd TalentForge/frontend

npm install
echo "VITE_API_URL=http://localhost:5000/api" > .env.local
npm run dev

App runs at http://localhost:5173.

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Environment variables

Copy backend/.env.example to backend/.env and fill in the following:

FLASK_ENV=development
SECRET_KEY=your-secret-key
JWT_SECRET_KEY=your-jwt-secret-key

DATABASE_URL=postgresql://user:password@host:5432/talentforge

CLOUDINARY_CLOUD_NAME=your-cloud-name
CLOUDINARY_API_KEY=your-api-key
CLOUDINARY_API_SECRET=your-api-secret

OPENAI_API_KEY=your-openai-api-key       # optional

MAIL_SERVER=smtp.gmail.com               # optional
MAIL_PORT=587
MAIL_USERNAME=your@email.com
MAIL_PASSWORD=your-app-password

FRONTEND_URL=http://localhost:5173

In production set FLASK_ENV=production and rotate all secret keys.

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API overview

Base URL: https://<your-app>.onrender.com/api

All authenticated endpoints require Authorization: Bearer <access_token>.

Module	Base path	Key actions
Auth	/api/auth	register, login, refresh, change-password
Users	/api/users	profile, admin user management, interviewer approval
Interviews	/api/interviews	create, assign, complete, cancel
Scheduling	/api/scheduling	availability slots, smart-match interviewers
Reports	/api/reports	submit, edit, publish, AI generate
Notifications	/api/notifications	list, mark read, unread count
AI Feedback	/api/feedback	generate summary, preview
Mock Interviews	/api/mock-interviews	start session, submit answers, get AI feedback
Practice Questions	/api/practice	browse by role, difficulty, category

Interview status lifecycle

pending ──► scheduled ──► completed ──► report_pending ──► published
   │             │              │               │
   └─────────────┴──────────────┴───────────────┘
                         cancelled

Role permission matrix

Action	admin	recruiter	interviewer	candidate
Create / assign interview	✓	✓	✗	✗
Complete interview + scores	✓	✗	✓	✗
Submit / publish report	✓	publish only	submit only	✗
View report	✓	✓	✓	published only
Generate AI feedback	✓	✓	✓	✗
Manage availability slots	✓	view only	✓	✗
Mock interviews	✗	✗	✗	✓
Practice questions	✗	✗	✗	✓
Approve interviewers	✓	✗	✗	✗

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Deployment

Backend → Render

1. Create a Web Service pointing to backend/
2. Build command: pip install -r requirements.txt && flask db upgrade
3. Start command: gunicorn run:app
4. Add all env variables from .env.example

Frontend → Vercel

1. Import repo and set root directory to frontend/
2. Add env variable: VITE_API_URL=https://<your-render-app>.onrender.com/api
3. Deploy — Vercel auto-detects Vite and runs npm run build

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Author

Kamal Sharma

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Built with Flask · React · PostgreSQL