InterviewIQ 🚀

InterviewIQ is an AI-powered desktop application designed to help tech professionals prepare for interviews. Built with Python and Tkinter, it provides a comprehensive suite of tools including AI-simulated mock interviews, resume parsing and insights, and MCQ practice tests tailored specifically for roles in Data Science, AI, and Software Engineering.

✨ Features

• User Authentication & Profiles: Secure login and signup system with SQLite.
• Smart Resume Parsing: Upload your PDF resume during registration. The app uses pypdf to extract your text, skills, and profile photo.
• AI Mock Interviews: An interactive chat interface that simulates technical interviews. It asks role-specific questions (e.g., AI Engineer, NLP Researcher, Computer Vision Specialist) and evaluates your responses based on depth and keyword matching.
• Resume Insights: Get a dynamic "Strength Score" dial, extracted core skills, and AI-generated optimization tips based on your uploaded resume.
• Performance Dashboard: Track your daily streak, overall progress, strengths, weaknesses, and follow a recommended training roadmap.
• MCQ Practice: Take technical multiple-choice quizzes to sharpen your fundamentals.

🛠️ Tech Stack

• Language: Python 3.x
• GUI Framework: Tkinter (Standard GUI library for Python)
• Database: SQLite3
• PDF Parsing: pypdf
• Image Processing: Pillow (PIL)

📁 Project Structure

• main.py - Application entry point and window manager.
• login.py - Authentication screens (Welcome, Login, Signup) and resume upload logic.
• menu.py - Base layout (Sidebar), Main Dashboard, and Resume Insights view.
• interview.py - The core AI mock interview chat interface and evaluation logic.
• roadmap.py - MCQ practice flow and performance tracking dashboard.
• database.py - SQLite database initialization and CRUD operations.
• skills.json - Data store for multiple-choice questions.

🚀 Installation & Setup

1. Clone the repository (or download the source code):

   git clone <repository-url>
   cd InterviewIQ

2. Create a virtual environment (Optional but recommended):

   python -m venv .venv
   # On Windows
   .venv\Scripts\activate
   # On macOS/Linux
   source .venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Run the application:

   python main.py

   (Note: The SQLite database interview_iq.db will be automatically initialized on the first run with a demo user).