🎯 InterviewLens AI

AI-Powered Interview Failure Analyzer & Personalized Interview Coach

InterviewLens AI is a full-stack MERN application that analyzes interview performance using AI. It compares a candidate's Resume, Job Description, and Interview Responses to identify weaknesses, missing skills, recruiter expectations, and provides an actionable improvement roadmap.

🚀 Live Demo

🌐 Frontend: https://interviewlens-ai.netlify.app/

💻 Backend API: Deployed on AWS EC2

📦 Dockerized: Multi-stage Docker setup for frontend (Nginx) and backend (Node.js + Express) using Docker Compose.

🔄 CI/CD: Automated backend deployment using GitHub Actions with a self-hosted runner on AWS EC2 and PM2.

⭐ Key Highlights

🤖 AI-powered Interview Performance Analyzer
📄 Resume vs Job Description Skill Gap Analysis
📊 Analytics Dashboard with Performance Tracking
📚 AI-generated Practice Questions & Model Answers
🗺️ Personalized 7-Day Improvement Roadmap
🔐 JWT Authentication & Email OTP Recovery
📑 Downloadable PDF Interview Reports
🐳 Fully Dockerized (Docker + Docker Compose + Nginx)
☁️ Frontend deployed on Netlify
🔄 Automated CI/CD using GitHub Actions
☁️ Backend deployed on AWS EC2
🗄️ MongoDB Atlas database

Screenshots

📌 Problem Statement

Many candidates fail interviews without understanding why they were rejected.

InterviewLens AI bridges this gap by providing:

Resume vs Job Description analysis
Interview answer evaluation
Recruiter-style feedback
AI-generated practice questions
Personalized improvement roadmap

✨ Features

🔐 Authentication

JWT Authentication
Secure Login & Signup
Forgot Password via Email OTP
Protected Routes

📄 Resume Processing

Upload Resume (PDF)
Paste Resume Manually
Resume Parsing
Resume Storage

💼 Interview Analysis

Analyze interviews using:

Resume
Job Description
Questions & Answers

AI generates:

✅ Interview Readiness Score
✅ Pass Probability
✅ Strengths
✅ Weaknesses
✅ Missing Skills
✅ Interview Mistakes
✅ Recruiter Insights
✅ Personalized Feedback

🗺️ 7-Day Improvement Roadmap

Personalized roadmap generated by AI:

Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
Day 7

🎯 AI Practice Questions

Based on interview performance, InterviewLens AI generates:

Personalized Interview Questions
AI Model Answers
Practice Suggestions

📈 Analytics Dashboard

Track interview performance over time.

Includes:

Total Interviews
Average Score
Best Score
Improvement Percentage
Score Trend Graph

📚 Interview History

Every interview is saved automatically.

Features include:

View Previous Analyses
Generate AI Answers Again
Download PDF Report
Delete History
Performance Tracking

📄 PDF Report Generation

Download complete interview reports containing:

Interview Score
Probability
Strengths
Weaknesses
Missing Skills
Mistakes
Roadmap
Practice Questions

👤 Profile Dashboard

Displays:

User Details
Total Interviews
Average Score
Best Score
Overall Improvement

📱 Responsive Design

Fully responsive across:

Desktop
Tablet
Mobile

Built using Tailwind CSS.

🛠️ Tech Stack

🎨Frontend

React.js
React Router DOM
Tailwind CSS
Axios
Recharts
React Icons
React Toastify

⚙️Backend

Node.js
Express.js
JWT Authentication
bcrypt.js
Multer
Nodemailer
Groq API
Docker
Docker Compose

🗄️Database

MongoDB
Mongoose

🧠AI Integration

Groq API (Llama Model)

Used for:

Interview Analysis
Feedback Generation
Skill Gap Detection
Roadmap Generation
Practice Questions
Model Answers

🐳 DevOps

Docker
Docker Compose
Nginx
AWS EC2
Linux / Ubuntu
GitHub Actions
Self-Hosted GitHub Actions Runner
PM2

☁️ Deployment

Frontend:

Netlify

Backend:

Platform: AWS EC2
OS: Ubuntu
Runtime: Node.js
Process Manager: PM2
Reverse Proxy / Web Server: Nginx
CI/CD: GitHub Actions
Runner: Self-hosted GitHub Actions Runner

Database:

MongoDB Atlas

Containerization:

Docker
Docker Compose

Web Server:

Nginx

CI/CD

The backend deployment is automated using GitHub Actions.

  Developer
      │
      │ git push
      ▼
  GitHub Repository
      │
      ▼
  GitHub Actions
      │
      ▼
  Self-Hosted Runner
      │
      │ AWS EC2
      ▼
  Checkout Latest Code
      │
      ▼
  npm ci
      │
      ▼
  Restore Production Environment
      │
      ▼
  Build Application
      │
      ▼
  PM2 Restart
      │
      ▼
  Updated Backend

The workflow runs automatically when code is pushed to the main branch.

CI/CD Responsibilities

  The pipeline performs:
  
  - Source-code checkout
  - Node.js environment setup
  - Clean dependency installation using npm ci
  - Production environment restoration
  - Application build
  - Backend restart using PM2
  - Automatic deployment to AWS EC2

Environment & Secret Management

  Production environment variables are not committed to GitHub.
  
  Sensitive configuration such as:
  
  GROQ_API_KEY
  MONGO_URI
  JWT_SECRET
  EMAIL_USER
  EMAIL_PASS
  
  is stored separately on the EC2 server and restored during deployment.
  
  This prevents sensitive credentials from being exposed in the Git repository while allowing the deployment pipeline to recreate the required runtime environment.

Deployment Architecture

                    GitHub
                      │
                git push main
                      │
             ┌────────┴────────┐
             │                 │
             ▼                 ▼
      GitHub Actions         Netlify
             │                 │
             ▼                 ▼
    Self-Hosted Runner      React Frontend
        AWS EC2                  │
             │                   │
             ▼                   │
          PM2                    │
             │                   │
             ▼                   │
      Express Backend ◄──────────┘
             │
       ┌─────┴─────┐
       ▼           ▼
 MongoDB Atlas   Groq API

Result: A push to the main branch automatically updates the backend running on AWS EC2, while the frontend is deployed separately through Netlify.

📂 Project Structure

InterviewLens-AI/
|
├── .github/
│   └── workflows/
│       └── cicd.yml
|
|
├── client
│   ├── Dockerfile
│   ├── nginx.conf
│   ├── src/
│   │   ├── components/
│   │   ├── pages/
│   │   ├── utils/
│   │   ├── App.jsx
│   │   └── main.jsx
│
├── server
│   ├── Dockerfile
│   ├── controllers/
│   ├── routes/
│   ├── middleware/
│   ├── models/
│   ├── utils/
│   ├── config/
│   └── server.js
│
├── docker-compose.yml
│
└── README.md

🏗️ Architecture

        React + Tailwind CSS
                 │
                 ▼
          Axios REST API
                 │
                 ▼
     Express.js + Node.js
                 │
      ┌──────────┴──────────┐
      ▼                     ▼
 MongoDB Atlas         Groq AI API
      │                     │
      └──────────┬──────────┘
                 ▼
      AI Interview Analysis

🔌 API Overview

Method	Endpoint	Description
POST	`/api/auth/signup`	Register User
POST	`/api/auth/login`	Login User
POST	`/api/analyze`	Analyze Interview
POST	`/api/upload-resume`	Upload Resume
GET	`/api/history`	Interview History
GET	`/api/analytics`	Analytics Dashboard

⚙️ Installation

Clone Repository

git clone https://github.com/aakanshimalik/InterviewLens-AI.git

cd interviewlens-ai

Install Frontend

cd client

npm install

npm run dev

Install Backend

cd server

npm install

npm run dev

🐳 Docker Support

InterviewLens AI is fully containerized for consistent local development and production deployment.

Run using Docker

docker compose up --build

Application URLs:

Service	URL
Frontend	http://localhost:5173
Backend	http://localhost:5000

Stop containers:

docker compose down

Docker Features

Multi-stage frontend build
Nginx production server
Backend container with Express.js
Docker Compose orchestration
Environment variable support

🔑 Environment Variables

Create a .env file inside the server folder.

PORT=5000

MONGO_URI=YOUR_MONGODB_URL

JWT_SECRET=YOUR_SECRET_KEY

GROQ_API_KEY=YOUR_GROQ_KEY

EMAIL_USER=YOUR_EMAIL

EMAIL_PASS=YOUR_APP_PASSWORD

Demo Credentials

Create your own account using Signup.

📊 Future Improvements

AI Mock Interview (Voice)
Speech Analysis
Facial Emotion Detection
ATS Resume Scoring
Recruiter Dashboard
Company-wise Interview Preparation
Multi-language Support
AI Career Advisor
Interview Performance Comparison

🎓 Key Learning Outcomes

MERN Stack Architecture
RESTful API Design
JWT Authentication & Authorization
AI API Integration
Resume Parsing
MongoDB Data Modeling
Docker & Containerization
AWS EC2 Deployment
Linux Server Management
CI/CD with GitHub Actions
Self-Hosted GitHub Actions Runners
PM2 Process Management
Production Deployment
Responsive UI Development
Analytics Dashboard Design
PDF Report Generation

👩‍💻 Author

Aakanshi Malik

📧 Email: aakanshimalik54@gmail.com

💼 LinkedIn: https://www.linkedin.com/in/aakanshi-malik-996738298

💻 GitHub: https://github.com/aakanshimalik

📄 License

This project is licensed under the MIT License.

⭐ If you like this project...

Give this repository a ⭐ Star and feel free to fork it!

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
client		client
server		server
LICENSE		LICENSE
README.md		README.md
docker-compose.yml		docker-compose.yml

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