Mocknetic

AI-powered technical interview and assessment platform for modern learning environments

Mocknetic is a comprehensive student assessment platform that combines classroom management, AI-driven skill evaluation, mock interviews, and code execution in a single unified environment. Built for universities, coding bootcamps, and technical training programs.

Live Demo • Teacher Portal • Report Bug • Request Feature

---

Table of Contents

• Overview
• Key Features
• Tech Stack
• Getting Started
• Project Structure
• Environment Variables
• Related Projects
• License

---

Overview

Mocknetic provides a complete solution for technical assessment and interview preparation:

• For Students: Practice coding, take assessments, prepare for interviews, and track progress.
• For Instructors: Create and manage classrooms via the Teacher Portal, publish assessments, and audit AI evaluations.
• For Institutions: Deploy a scalable, production-ready platform for technical education.

Why Mocknetic?

• Unified Platform: All assessment tools in one place—no need to juggle multiple services.
• AI-Powered: Direct LLM processing for question generation and adaptive interview flows.
• Production-Ready: Built with modern frameworks and hosted on scalable AWS infrastructure.
• Open Architecture: Clean, maintainable codebase with clear domain separation.

---

Key Features

Classroom Management

• Google Classroom-style interface with 6-digit join codes.
• Real-time enrollment and membership management.
• Organized view of all assessments and deadlines.

AI-Powered Assessments

• Dynamic question generation using Groq LLM.
• Multiple question types: MCQ, coding, descriptive, and numerical.
• Timed assessments with automatic submission and instant results.

Mock Interview System

Tailored interview data entry

Initial setup and configuration

Live AI-driven conversational interface

• Adaptive Flow: Powered by a dedicated Python backend hosted on AWS EC2.
• Real-time Interaction: Seamless conversational experience using Socket.IO.
• Comprehensive performance feedback and interview history analytics.

Code Execution Environment

Integrated IDE with multi-language support

Side-by-side problem statement and editor

• Monaco-based code editor with syntax highlighting.
• Support for 50+ programming languages via Judge0 (RapidAPI).
• Real-time test case execution and performance metrics.

Resume Analysis

• PDF upload and parsing using pdf2json.
• Automatic skill extraction and integration with student profiles.

---

Tech Stack

Frontend & Core

• Framework: Next.js 15 (App Router)
• Language: TypeScript 5
• Styling: Tailwind CSS v4 + shadcn/ui
• Authentication: NextAuth v5 (Credentials + Google OAuth)

Backend & Infrastructure

• Primary API: Next.js Route Handlers
• Interview Engine: Python API hosted on AWS EC2
• Database: MongoDB (Native Driver)
• Real-time: Socket.IO Client (for interview sessions)

AI & Execution

• LLM Provider: Groq (via Vercel AI SDK)
• Code Execution: Judge0 API (RapidAPI)
• CI/CD: Automated pipelines for the Python Interview Backend

---

Getting Started

Prerequisites

• Node.js 18+ and npm 10+
• MongoDB instance (Atlas or Local)
• Judge0 API Key (via RapidAPI)
• Groq API key for AI features

Installation

1. Clone the repository

   git clone https://github.com/yourusername/mocknetic.git
   cd mocknetic

2. Install dependencies

   npm install

3. Configure environment variables Create a .env.local file in the root directory. See Environment Variables for details.

4. Start the development server

   npm run dev

---

Project Structure

mocknetic/
├── app/                          # Next.js App Router (Pages & API)
├── components/                   # UI components (shadcn + domain specific)
├── database/                     # Native MongoDB connection and schemas
├── lib/                          # Shared utilities and AI SDK config
├── hooks/                        # Custom hooks (Socket.io, UI state)
├── public/                       # Static assets (Screenshots go here)
└── types/                        # TypeScript definitions

---

Environment Variables

Create a .env.local file with the following:

# Database
MONGODB_URI=your_mongodb_uri

# Authentication (NextAuth v5)
AUTH_SECRET=your_auth_secret
AUTH_GOOGLE_ID=your_google_id
AUTH_GOOGLE_SECRET=your_google_secret

# AI & Execution
GROQ_API_KEY=your_groq_key
JUDGE0_API_KEY=your_rapidapi_key
JUDGE0_HOST=judge0-ce.p.rapidapi.com

# API Endpoints
NEXT_PUBLIC_API_BASE_URL=http://localhost:3000/api
NEXT_PUBLIC_PYTHON_API=http://your-ec2-instance-ip:5000

---

Related Projects

Teacher Portal - Separate React + Vite application for instructors.

• Repository: github.com/yourusername/mocknetic-teacher
• Live: teachers.mocknetic.com

Interview Backend - Python-based core for AI conversations.

• Hosted on: AWS EC2

---

License

This project is licensed under the MIT License.

---

Built with ❤️ for students, by developers