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PrepAI 🚀

GSSoC'26 License: MIT

PrepAI is a client-side placement preparation platform designed to help you get ready for job interviews.

GirlScript Summer of Code (GSSoC 2026) 🌸

This project is officially part of GirlScript Summer of Code 2026! We welcome all contributors to help build and scale PrepAI.

How to Contribute under GSSoC:

  1. Browse our active GitHub Issues.
  2. Comment on the issue you wish to solve to request assignment. (Do not start working until assigned).
  3. Follow the development guidelines in our CONTRIBUTING.md file.
  4. Open a Pull Request linking the issue (e.g. Closes #1).

Difficulty Levels:

  • level-1 (Easy/Docs/Simple changes - e.g. Issue #4: PDF Export)
  • level-2 (Medium/UX enhancements/Roadmap features)
  • level-3 (Hard/Complex integrations - e.g. Issue #1: Live LLM backend, Issue #2: Sandbox compiler execution)

Features 🌟

  • Personalized Roadmaps: Custom step-by-step prep timelines based on your target industry.
  • AI Mock Interviews: Interactive mock interviews with simulated feedback.
  • Resume ATS Scanner: Upload your resume (PDF, DOCX, or TXT) to scan for missing keywords and get an ATS compatibility score.
  • AI Resume Refiner: See a side-by-side comparison of your original resume versus an optimized version with target keywords automatically added.
  • Interactive Code Sandbox: Open coding questions in a fullscreen code editor with a simulated compiler console to test your answers.
  • Friendly Chatbot Assistant: Click the chat button in the bottom-right corner to ask questions, check missing keywords, or get tips on boosting your score.

Technologies Used 🛠️

  • Core: HTML, CSS, JavaScript (Pure Vanilla).
  • Icons: Lucide Icons.
  • Document Parsers: Local PDF.js and Mammoth.js libraries (for reading PDF and DOCX files client-side).

How to Run it Locally 💻

  1. Install a local web server (for example, http-server using Node.js):
    npm install -g http-server
  2. Open your terminal in this project folder and run:
    http-server -p 8005
  3. Open your browser and visit: http://localhost:8005

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