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📚 Smart Study Companion (SSC)

Smart Study Companion (SSC) is a fully local, privacy first study assistant designed for university students who want fast, accurate answers directly from their own lecture PDFs without relying on cloud-based AI services or file upload limits.

This project was built to solve a real academic problem:

LLM platforms are powerful, but lecture notes are often too large, restricted, or privacy sensitive to upload.

SSC removes that limitation entirely.


🚀 Why Smart Study Companion?

  • 🔒 100% Local & Secure : no data leaves your machine
  • 📄 Built for real lecture PDFs (large, detailed, multi file)
  • 🚫 No AI APIs, no subscriptions, no upload caps
  • 🧠 Context aware answers from your own notes
  • 🗂️ Multiple chat sessions, each with its own PDFs and history

Built by a university student, for university students.


✨ Key Features

  • Upload multiple PDFs per study session
  • Ask natural language questions based on lecture content
  • Get concise, relevant answers with source attribution
  • Separate chat sessions for different modules
  • Chat history preserved per session (while server runs)
  • Modern, animated UI with smooth UX

🛠️ Technology Stack (Toolkit)

Backend

  • Python
  • Flask (REST API & session handling)

Document Processing

  • PyMuPDF (fitz) : local PDF text extraction

Search & Ranking

  • TF-IDF Vectorization (scikit learn)
  • Cosine Similarity for relevance scoring

Frontend

  • HTML
  • CSS (custom dark UI & animations)
  • Vanilla JavaScript

Security & Design

  • Fully offline
  • No external APIs
  • No cloud services
  • No data sharing

🧠 How It Works (High Level)

  1. PDFs are uploaded and processed locally
  2. Text is chunked and indexed using TF-IDF
  3. User questions are vectorized and compared using cosine similarity
  4. The most relevant section is returned as a concise answer
  5. Each chat session maintains its own PDFs and history

📦 Installation & Setup

Prerequisites

  • Python 3.9+
  • pip

Install dependencies

pip install flask pymupdf scikit-learn

🎯 Use Cases

•	University lecture revision
•	Exam preparation
•	Large module handouts
•	Privacy-sensitive academic notes
•	Offline studying

🔐 Privacy & Security

SSC is privacy first by design:

•	No internet connection required after setup
•	No third party APIs
•	No telemetry or tracking
•	All data stays on your local machine

👨‍💻 Author

Mohammed Zuoriki Cybersecurity Student | Aspiring Cloud Security Architect
LinkedIn: https://www.linkedin.com/in/mohammed-zuoriki-856133250/

⭐ Contributing

Contributions, feedback, and ideas are welcome. Feel free to fork the repository or open an issue.

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