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Masham
Masham

Posted on AI-assisted

Deadline Guardian : Built for my All-Nighter friend

#hf26challenge #ai #programming #webdev

Every semester, my college friend and I face the exact same chaos before our exams: piles of slides and notes, scanned PDFs, previous-year papers, syllabi, and only a few hours left.

When you're pulling a deadline all-nighter, reading through hundreds of slides line-by-line is impossible. Asking a standard LLM often leads to generic fluff or hallucinated answers with zero references.

That's why I built Deadline Guardian, a RAG-based project for the DEV Hacktoberfest Weekend Challenge — "Build for a Friend"!

We can all work together on this project to improve this small Deadline Guardian for all of us!

🚀 Key Features

  • ❓ Ask Anything (Grounded RAG with Citations): Answers questions strictly using your uploaded notes, complete with exact inline file and page citations such as [ch4.pptx p.11].
  • 📝 High-Yield Cheat Sheets: Condenses dense chapters into quick, digestible revision cheat sheets.
  • ⏱️ Deadline Panic Plan: Tell it how many hours you have left before the exam. It automatically prioritizes topics into tiers — 🔴 High-Yield, 🟡 Medium, and 🟢 Low — and generates an hour-by-hour actionable timetable.
  • 📂 Multi-Format Support: Parses digital PDFs, PPT/PPTX slide decks, plain text notes, Markdown files, and photos of handwritten pages or diagrams.
  • 🧮 LaTeX Math & Compilable Code: Renders mathematical equations using KaTeX and formats programming algorithms such as Peterson's Solution and CPU scheduling as compilable C/C++ code blocks.

Deadline Guardian UI

Deadline Guardian RAG Interface

🔗 Links

GitHub Repository:

https://github.com/Masham-0/deadline-guardian

Live Demo:

https://deadline-guardian-3195.onrender.com/

🧠 Tech Stack

  • LLM: Gemma 2B
  • Embeddings: BGE-small
  • Architecture: Retrieval-Augmented Generation (RAG)

⚙️ Steps to Run Locally

1. Clone the Repository 

git clone https://github.com/Masham-0/deadline-guardian.git
cd deadline-guardian
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
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2. Configure Environment

Create a .env file:

LLM_BASE_URL=https://generativelanguage.googleapis.com/v1beta/openai/
LLM_API_KEY=your_api_key_here
LLM_MODEL=gemma-2-9b-it
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3. Start the Server

For the Google API setup:

uvicorn main:app --reload --host 127.0.0.1 --port 8000
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For a local Ollama setup:

ollama pull gemma:2b
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Then start the server with:

LLM_BASE_URL=http://localhost:11434/v1 \
LLM_API_KEY=ollama \
LLM_MODEL=gemma:2b \
uvicorn main:app --reload
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👨‍💻 Author & Credits

Developer: Mohammad Masham

Email: mohd.masham@gmail.com

Institution: Netaji Subhas University of Technology (NSUT)

Hackathon: DEV Hacktoberfest Weekend Challenge 2026 — Build for a Friend

If you find Deadline Guardian helpful for your exam prep, feel free to drop a ⭐ on the GitHub repository!

Happy studying! 📚

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