This is a **Quiz Helper Application** built in Python that assists users with quiz questions through screenshot capture, text analysis, and AI-powered responses. Let me break down how each component works: ## 🏗️ **Application Architecture** The app follows a modular structure: - `main.py` - Entry point and setup - `src/app.py` - Core application logic - `src/ui/` - User interface components - `src/api/` - AI API integration - `src/utils/` - Utility functions ## 📋 **Core Functionality** ### **1. Screenshot Capture System** The app can capture screenshots of quiz questions on screen: **How it works:** - Press F1 or click "Take Screenshot" - Creates a transparent overlay window covering the entire screen - User clicks and drags to select an area - Captures that specific region as an image - Uses OCR (Optical Character Recognition) to extract text from the image **Technical implementation:** ```python # Creates fullscreen transparent overlay self.overlay_window = tk.Toplevel() self.overlay_window.attributes('-fullscreen', True) self.overlay_window.attributes('-alpha', 0.3) # Semi-transparent # Captures selected area screenshot = pyautogui.screenshot(region=(x1, y1, x2-x1, y2-y1)) # Extracts text using Tesseract OCR extracted_text = pytesseract.image_to_string(screenshot) ``` ### **2. AI-Powered Question Analysis** Uses Grok AI API to analyze quiz questions and provide answers: **Process:** 1. Takes question text (from screenshot OCR or manual input) 2. Sends to Grok API with specialized prompt 3. Receives structured answer with explanation 4. Displays results in the interface **API Integration:** ```python data = { 'messages': [ { 'role': 'system', 'content': 'You are a helpful quiz assistant...' }, { 'role': 'user', 'content': question_text } ], 'model': 'grok-3-latest', 'temperature': 0.7 } ``` ### **3. Web Scraping Capability** Can analyze quiz content directly from web URLs: **How it works:** - Takes a quiz website URL - Scrapes the webpage content - Identifies quiz questions using CSS selectors - Sends content to AI for analysis ## 🧩 **Key Components Breakdown** ### **`main.py` - Application Entry Point** - Displays setup instructions for first-time users - Loads API keys from environment variables (`.env.local`) - Initializes and starts the main application window ### **`src/app.py` - Core Application Logic** This is the heart of the application containing: **UI Components:** - Screenshot capture interface - Text input/output areas - API key configuration - Control buttons **Screenshot System:** - Global hotkey detection (F1) - Mouse event handling for area selection - OCR text extraction using Tesseract - Image processing with PIL **API Integration:** - Threaded API calls to prevent UI freezing - Error handling and status updates - Response formatting and display ### **`src/ui/main_window.py` - Main Interface** - Uses `ttkthemes` for modern UI styling - Handles URL-based quiz analysis - Manages threading for non-blocking operations - Integrates with core app functionality ### **`src/api/grok_client.py` - AI API Client** Simple wrapper for Grok API: ```python def analyze_question(self, content: str) -> dict: # Sends structured request to Grok API # Returns AI analysis of the question ``` ### **`src/utils/web_scraper.py` - Web Content Extraction** - Uses `requests` and `BeautifulSoup` for web scraping - Attempts multiple CSS selectors to find quiz content - Handles different quiz website formats - Returns structured content for AI analysis ### **`src/utils/screenshot.py` - Screenshot Utilities** Provides screenshot capture functionality: - `ScreenshotTool` - Basic screenshot capture - `ScreenshotSelector` - Interactive area selection with visual feedback ## 🔧 **Technical Features** ### **Threading and Performance** - All AI API calls run in separate threads to prevent UI freezing - Thread cleanup on application exit - Status updates during long operations ### **Error Handling** - Network error handling for API calls - Missing dependency detection - User-friendly error messages ### **Security** - API keys stored in environment variables - Masked API key display in UI - No hardcoded credentials ### **Cross-Platform Design** - Uses standard Python libraries - Configurable OCR engine paths - OS-specific setup instructions ## 🎯 **User Workflow** 1. **Setup**: Install dependencies, get API key, configure Tesseract OCR 2. **Capture**: Take screenshot of quiz question OR paste text OR enter URL 3. **Analyze**: AI processes the question and provides answer + explanation 4. **Results**: View formatted answer with reasoning ## 📦 **Dependencies** **Core Libraries:** - `tkinter` - GUI framework - `PIL` - Image processing - `pytesseract` - OCR text extraction - `pyautogui` - Screenshot capture - `requests` - HTTP requests for API calls **Additional Features:** - `ttkthemes` - Modern UI themes - `beautifulsoup4` - HTML parsing for web scraping - `pynput` - Global hotkey detection - `python-dotenv` - Environment variable management The application is designed to be user-friendly while providing powerful quiz assistance capabilities through computer vision, web scraping, and AI analysis.