InterviewOS

Your AI-Powered Placement Co-Pilot – An advanced, full-stack application designed to help final-year CS students and placement aspirants master interview preparation. It parses PDF resumes, runs mock interview chat sessions, parses GitHub repositories to generate project-specific technical questions, and tracks preparation progress using rich data visualization.

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Features

📄 AI Resume X-Ray

• Text Extraction: Uses pdf-parse to extract clean text from uploaded PDF resumes.
• ATS & Fit Assessment: Calculates ATS compatibility and candidate fit percentages matching target job descriptions.
• Keyword Analysis: Performs keyword coverage analysis, highlighting matching and missing resume keywords.
• Actionable Roadmaps: Generates step-by-step roadmap plans divided into immediate, short-term, medium-term, and long-term milestones.
• Tailored Additions & Removals: Recommends specific bullet points to add (including STAR-structured examples) and low-value content to remove.

🎤 AI Mock Interview Engine

• Interactive Chat Interface: A text-based, interactive mock interview chatbot simulated via Google Gemini AI models.
• Flexible Configurations: Tailors interview focus (Technical, Behavioral, System Design) and difficulty levels (Easy, Medium, Hard).
• STAR-Method Evaluation: Provides granular scoring across relevance, technical accuracy, communication, confidence, structure, and problem solving.
• Action Plan: Outlines a 3-step prioritized study roadmap focusing on key areas for improvement.

🚀 AI Project Prep

• GitHub Integration: Pastes a public GitHub repository URL to fetch codebase metadata, languages, and README files.
• Codebase-Specific Questions: AI reviews project elements to generate specific technical questions on Architecture, Database choice, Security, Performance, Scalability, Deployment, and Design Trade-offs.
• Detailed Hints: Accompanying guidelines for each question to direct the candidate's talking points.

💼 Company Question Bank

• Curated catalog of actual interview questions from top tech companies including Google, Amazon, Microsoft, Meta, Apple, Netflix, and Uber.
• Filters questions by target company and difficulty level.
• Direct external links to LeetCode and System Design forums.

👥 Interactive Prototypes (Local State)

• Peer Review Community: High-fidelity prototype page to share uploaded resumes for community rating, commenting, and likes.
• Admin Dashboard: Frontend management desk to inspect session activities, user registrations, and toggle status blocks.

📊 Progress Analytics Hub

• Real-time visual progress monitoring using Recharts.
• Radar charts for category-wise mock interview skill ratings.
• Line/Area charts showing historical mock interview score trends.

🔐 Secure Authentication

• JWT-based authentication storing tokens in HTTPOnly secure cookies.
• Persistent session storage in React frontend utilizing Redux Toolkit.
• Client-side routing protections separating public and protected pages.

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Tech Stack

Frontend

• Framework: React 18+ (Vite)
• Programming Language: TypeScript
• Styling: Tailwind CSS 3.4
• State Management: Redux Toolkit (auth & session)
• Data Fetching: TanStack Query (React Query)
• Routing: React Router v6
• Data Visualization: Recharts
• Icons: Lucide React
• Notifications: React Hot Toast
• Form Validation: React Hook Form + Zod

Backend

• Runtime: Node.js
• Framework: Express
• Database: MongoDB (Mongoose ODM)
• AI Orchestration: LangChain Core + @langchain/google-genai (Gemini 2.5 Flash)
• PDF Processing: pdf-parse
• File Upload: Multer + Cloudinary (resume hosting)
• Auth Utilities: jsonwebtoken (JWT) + bcryptjs
• Logging: Morgan

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Project Structure

interview-project/
├── Backend/                 # Express backend server
│   ├── src/
│   │   ├── config/          # DB & Cloudinary configuration
│   │   ├── controllers/     # Route controller endpoints
│   │   ├── middlewares/     # Authentication & Multer upload middlewares
│   │   ├── models/          # MongoDB Mongoose schemas
│   │   ├── prompts/         # LangChain AI prompt templates
│   │   ├── routes/          # API route definitions
│   │   ├── services/        # AI, GitHub API, PDF parse & business services
│   │   ├── utils/           # Error handling & API response formatting
│   │   ├── app.js           # Express app setup
│   │   └── server.js        # Main entry point (starts server and DB connection)
│   └── package.json
└── Fronted/                 # React frontend client
    ├── src/
    │   ├── context/         # Redux store configuration & Confirmation context
    │   ├── hooks/           # Custom React hooks (React Query integrations)
    │   ├── layouts/         # App Layout wrapper with sidebar navigation
    │   ├── pages/           # Client views & dashboards
    │   ├── routes/          # Public & protected React Router routes
    │   ├── services/        # Axios API fetch calls
    │   ├── styles/          # Tailwind custom variables & global index.css
    │   ├── App.tsx          # Root React component (restores user sessions)
    │   └── main.tsx         # Application entry point
    └── package.json

## Environment Variables

### Backend (`Backend/.env`)

Configure these keys in a `.env` file under the `/Backend` directory:

| Variable | Description | Example |
|---|---|---|
| `PORT` | Local port for Express API server | `5000` |
| `NODE_ENV` | Mode environment | `development` |
| `CLIENT_URL` | Frontend client origin URL | `http://localhost:5173` |
| `MONGO_URI` | MongoDB connection string | `mongodb://localhost:27017/interviewos` |
| `JWT_SECRET` | Secret key used to sign JWT auth | `your_jwt_secret_key` |
| `GOOGLE_API_KEY` | Google AI Studio developer API key | `AIzaSy...` |
| `CLOUDINARY_CLOUD_NAME` | Cloudinary storage account name | `your_cloud_name` |
| `CLOUDINARY_API_KEY` | Cloudinary API Key | `your_api_key` |
| `CLOUDINARY_API_SECRET` | Cloudinary API Secret | `your_api_secret` |

### Frontend (`Fronted/.env`)

Configure this key in a `.env` file under the `/Fronted` directory:

| Variable | Description | Example |
|---|---|---|
| `VITE_API_BASE_URL` | Base endpoint path for the backend API | `http://localhost:5000/api` |

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## Getting Started

### Prerequisites
- **Node.js** (v18.0 or higher)
- **MongoDB** (Local instance or Atlas cloud URI)
- **Google Gemini API Key** (obtained from [Google AI Studio](https://aistudio.google.com/))
- *(Optional)* **Cloudinary Account** (for saving PDF resumes in the cloud)

### Installation & Run

1. **Clone the repository**:
   ```bash
   git clone https://github.com/yourusername/interview-project.git
   cd interview-project

2. Configure environment variables:

   • Create Backend/.env using Backend/.env.example as a template and fill in your keys.
   • Create Fronted/.env and verify the VITE_API_BASE_URL value.

3. Start the Backend:

   cd Backend
   npm install
   npm run dev

   The backend will run on http://localhost:5000

4. Start the Frontend:

   • Open a separate terminal window at the project root.

   cd Fronted
   npm install
   npm run dev

   The frontend client will run on http://localhost:5173

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Key Modules

• Dashboard: Central dashboard rendering aggregate stats, weekly improvement graphs, radar evaluations, upcoming tasks, and preparation logs.
• Resume X-Ray: Input target job descriptions and upload your resume PDF to receive granular keyword analysis, ATS reports, and structural suggestions.
• Mock Interview: Practice interactive text sessions against an AI interviewer (Technical, Behavioral, System Design) and get graded reports showing suggested model answers.
• Project Prep: Type in a public GitHub URL to inspect your repository's tech stack and immediately generate customized architecture, database, security, and scalability interview questions.
• Question Bank: Explore curated sets of interview questions categorized by top companies and difficulty levels.
• Peer Review & Admin Dashboards: Fully functioning frontend mockup dashboards allowing users to view student resumes, add stars, rate details, and simulate active session logs.

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Screenshots

Dashboard

Placeholder: Dashboard with stats, progress tracking chart, and radar visualization

AI Interview

Placeholder: AI mock interview chat prompt and interactive feedback loop

Project Preparation

Placeholder: Project Prep repository analyzer interface and tech-stack questions list

Mock Interview

Placeholder: Active text mock session screen with timer, hint displays, and answering panel

Presentation Mode

Placeholder: Interactive mock interview report outlining scores and better answer structures

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Future Improvements

• Database Persistence for Peer Reviews: Connect the Peer Review Community module to a persistent backend database schema for sharing actual candidate reviews.
• Verbal Practice (Speech-to-Text): Enable verbal mock interviews using browser speech recognition API to capture spoken answers.
• Live Code Execution Sandbox: Embed a web-based code editor (such as Monaco) to enable real-time programming challenge tests.
• Advanced Admin Management: Implement backend admin routers to manage actual user profiles, view metrics logs, and delete expired session entries.

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License

This project is licensed under the ISC License – see the Backend/package.json for details.