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Overview I already have a working Python quiz automation prototype that: • Uses Apple Vision / Tesseract / PaddleOCR for OCR. • Captures screenshots with Quartz (macOS API). • Sends parsed text to OpenAI API for answers. • Runs with a hotkey (/) and quits with ESC. • Installs via [login to view URL] and works inside a virtual environment. The only thing that doesn’t work properly: When there’s a full page of MCQs, the script doesn’t go question by question in order. Instead, it picks and answers them in a random order. I want it to process all MCQs sequentially, top-to-bottom, for the full visible page. ⸻ Requirements Core Fix • Ensure that on a page with multiple MCQs, the tool: • Detects all visible questions and their answer choices. • Processes them in sequence (top-to-bottom), not randomly. • Returns or highlights the correct answer consistently. DOM Parsing (Preferred) • Add Selenium or Playwright to directly parse the webpage DOM. • Extract structured text (questions + choices). • Send each question block to the AI backend. • Much more reliable than OCR-only. OCR Fallback • Keep OCR backends (Apple Vision / PaddleOCR / Tesseract) as fallback. • When DOM parsing fails (e.g., locked exam platforms). • Must still process all questions on the visible page, in order. System Requirements • Must run on macOS Sonoma (Apple Silicon). • Uses Python virtual environment with requirements.txt. • Needs macOS permissions: Accessibility, Screen Recording, Input Monitoring. AI Backend • Uses latest OpenAI SDK. • Configurable model (gpt-4o-mini by default). • API key stored in .env file. Usage • Hotkey (/) to trigger automation. • ESC to quit. • Should highlight/log answers clearly. ⸻ Deliverables 1. Updated [login to view URL] (fixed MCQ ordering). 2. [login to view URL] (with Selenium/Playwright + OCR deps). 3. [login to view URL] (updated bootstrap). 4. Documentation (README + setup guide). 5. Optional: diagnostic tool for backend testing. ⸻ Skills Needed • Python 3 (macOS development). • Selenium / Playwright for DOM automation. • OCR libraries (PaddleOCR, Tesseract, Apple Vision). • Quartz/macOS APIs for screen capture. • OpenAI SDK integration. ⸻ Budget & Terms • The base prototype is already working — just needs this MCQ ordering fix + DOM parsing support. • Looking for a stable and reliable solution. • Please share examples of automation projects you’ve done before.
Project ID: 39749631
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Penryn, United States
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