⚡ InterviewIQ

AI-powered technical interview prep tailored to your target companies

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What It Does

InterviewIQ is a full-stack mock interview platform that:

• Generates company-specific coding and systems design problems (Google, Amazon, Meta, Apple, Microsoft, Netflix) using GPT-4o
• Provides a VS Code-style Monaco editor with a 45-minute countdown timer
• Delivers structured AI feedback scoring correctness, time/space complexity, edge cases, and optimizations
• Tracks your progress by company, difficulty, and topic with an Interview Readiness Score

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Project Structure

interviewiq/
├── backend/
│   ├── app.py                    # Flask entry point
│   ├── database.py               # SQLite schema + helpers
│   ├── company_problem_profiles.py  # Company → topic tendencies
│   ├── requirements.txt
│   ├── .env.example
│   └── routes/
│       ├── generate.py           # POST /generate-problems
│       ├── feedback.py           # POST /submit-solution
│       └── progress.py          # GET  /progress
│
└── frontend/
    ├── package.json
    ├── .env.example
    ├── public/
    │   └── index.html
    └── src/
        ├── App.jsx               # Router shell
        ├── index.js
        ├── api.js                # Fetch helpers → Flask
        ├── constants.js          # Companies, colors, templates
        ├── styles/
        │   └── global.css
        ├── components/
        │   ├── UI.jsx            # Spinner, Button, Card, TopNav, ProblemCard…
        │   ├── CodeEditor.jsx    # Monaco editor with custom theme
        │   └── FeedbackPanel.jsx # AI feedback display
        └── pages/
            ├── Home.jsx
            ├── Generate.jsx
            ├── Workspace.jsx
            └── Dashboard.jsx

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Tech Stack

Layer	Tech
Frontend	React 18, React Router v6
Editor	Monaco Editor (@monaco-editor/react)
Backend	Python 3.11, Flask 3
AI	llama 3.3
Database	SQLite (via sqlite3)
Deploy FE	Vercel
Deploy BE	Render