☁️ Cloud Document Analytics Platform

A modern, AI-powered platform for uploading, searching, classifying, and analyzing documents in the cloud.

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🚀 Live Demo

🌐 Try it online now: Cloud Document Analytics Platform

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📚 Table of Contents

• Features Overview
• Feature Comparison Table
• Screenshots
• How It Works
• Installation & Setup
• Usage Guide
• Tech Stack
• Security
• Contributing
• License
• Credits
• Project Requirements & Approach
• Algorithms & Platform Choices
• Documentation & Reporting

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✨ Features Overview

• Drag-and-Drop Upload: Upload PDF, DOC, DOCX, TXT, and more with a modern interface
• Web Scraping: Extract and analyze content directly from web pages via URL
• AI-Powered Classification: Automatic, explainable document categorization with multiple algorithms (AI, rule-based, hybrid)
• Advanced Search: Full-text, fuzzy, and filtered search with instant results
• Analytics Dashboard: Visualize document types, upload trends, and category distributions
• Secure Cloud Storage: All files and metadata stored securely with Supabase
• User Authentication: Secure sign-up, login, and access control
• Responsive UI: Works beautifully on desktop and mobile
• Download & Delete: Manage your documents with ease
• Explainable AI: See why documents are classified a certain way
• Category Tree: Hierarchical classification for academic, technical, business, and legal documents
• Real-Time Feedback: Toasts and progress indicators for all actions
• Persistent Stats: Track your document stats over time
• Role-Based Access: Admin and user roles supported
• Live Demo: Always-available online version for instant access

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📊 Feature Comparison Table

Feature	Local Version	Online Demo	Description
Drag-and-Drop Upload	✅	✅	Upload documents from your device
Web Scraping (URL Import)	✅	✅	Import and analyze web pages
AI Classification	✅	✅	Automatic, explainable document categorization
Advanced Search	✅	✅	Full-text, fuzzy, and filtered search
Analytics Dashboard	✅	✅	Visualize document types, trends, and categories
Secure Cloud Storage	✅	✅	Files and metadata stored in Supabase
User Authentication	✅	✅	Sign up, login, and access control
Download & Delete	✅	✅	Manage your documents
Explainable AI	✅	✅	See classification confidence and rationale
Category Tree	✅	✅	Hierarchical document classification
Real-Time Feedback	✅	✅	Toasts, progress bars, and instant updates
Persistent Stats	✅	✅	Track document stats over time
Role-Based Access	✅	✅	Admin and user roles
Mobile Responsive	✅	✅	Works on all devices
Live Demo	❌	✅	No setup required, use instantly online

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🛠️ How It Works

1. Sign Up & Login:
   • Secure authentication with Supabase Auth
   • Role-based access for users and admins
2. Upload Documents:
   • Drag and drop files or select from your device
   • Supported formats: PDF, DOC, DOCX, TXT, XLSX, PPTX, images, and more
   • Optionally, enter a URL to scrape and analyze web content
3. AI Classification:
   • Choose your preferred classification method (AI, rule-based, hybrid)
   • Documents are categorized into Academic, Technical, Business, Legal, and subcategories
   • Confidence scores and algorithm details are shown
4. Search & Filter:
   • Use the search bar to find documents by content, title, or metadata
   • Apply filters by type, category, or upload date
   • Sort results and view document details
5. Analytics Dashboard:
   • Visualize your document collection with bar, pie, and line charts
   • See trends, type distributions, and category breakdowns
6. Manage Documents:
   • Download, delete, or view details for each document
   • Real-time feedback for all actions

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📦 Installation & Setup

1. Clone the repository

git clone git@github.com:Yosef-AlSabbah/Cloud-Based-Document-Analytics-Service.git
cd Cloud-Based-Document-Analytics-Service

2. Install dependencies

npm install

3. Configure environment variables

• Copy .env.example to .env and fill in your Supabase credentials

4. Start the development server

npm run dev

5. Access the app

• Open http://localhost:5173 in your browser

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📝 Usage Guide

1. Sign Up & Login

• Create an account or log in securely

2. Upload Documents

• Drag and drop files or select from your device
• Optionally, enter a URL to scrape and analyze web content
• Choose your preferred classification method (AI, rule-based, hybrid)

3. Search & Filter

• Use the search bar to find documents by content, title, or metadata
• Apply filters by type, category, or upload date

4. View & Manage

• Browse your documents in a sortable, filterable list
• Download, delete, or view details for each document

5. Classification & Analytics

• See automatic document categorization with confidence scores
• Explore analytics: document type distribution, upload trends, and more

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🛠️ Tech Stack

Layer	Technology/Service
Frontend	React, TypeScript, Vite
UI	Shadcn/UI, Lucide Icons, Tailwind
Backend	Supabase (Postgres, Auth, Storage)
AI/ML	Custom & hybrid classification
Deployment	Vercel (CI/CD, CDN, Analytics)

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🔒 Security

• All data is protected with Supabase Auth and Row Level Security
• Files are stored in user-specific buckets for privacy
• Environment variables are required for all sensitive credentials
• HTTPS enforced on the online demo
• User actions are logged for auditability

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🤝 Contributing

1. Fork the repo and create your branch
2. Make your changes and add tests if needed
3. Open a pull request with a clear description
4. Follow the code style and best practices

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📄 License

MIT License. See LICENSE for details.

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🙏 Credits

• Developed by Yousef M. Y. Al Sabbah
• Islamic University of Gaza - Faculty of Information Technology

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📖 Project Requirements & Approach

This project was developed as a cloud-based program for basic data analytics, document search, sorting, and classification. Below is a summary of the requirements and how they are addressed in this platform:

Requirements Addressed

Requirement	How It Is Addressed
Collect a large number of PDF/Word documents	Upload via drag-and-drop, file picker, or web scraping from URLs.
Store documents in the cloud	Uses Supabase for secure, scalable cloud storage and database.
Update collection anytime	Upload new documents or scrape new sources at any time via the interface.
Sort documents by title (extracted from document, not filename)	Title extraction from document content; sorting and filtering in the UI.
Search documents for text/keywords	Full-text and fuzzy search with instant results; highlights found keywords in document previews.
Highlight search text in output documents	Search results show highlighted keywords in context.
Classify documents by a predefined tree using any algorithm	Hierarchical classification tree (Academic, Technical, Business, Legal, etc.) with AI, rule-based, or hybrid methods.
Provide statistics (size, number, search/sort/classify time, etc.)	Analytics dashboard shows document count, size, upload trends, and operation timings.
Use any programming language and cloud platform	Built with React/TypeScript (frontend), Supabase (cloud backend), Vercel (deployment).
Well-documented, readable, and maintainable source code	Modular, commented codebase; clear folder structure; usage and contribution guides in README.
GitHub repository and cloud program link	GitHub Source Code and Live Demo
Write a report describing algorithms, platform, and usage	See below for a summary of algorithms and platform choices.

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🧠 Algorithms & Platform Choices

• Title Extraction:
  • Extracts the actual document title from PDF/Word content using custom parsing utilities.
• Sorting:
  • Sorts documents by extracted title, not just filename, for more meaningful organization.
• Search:
  • Supports keyword, phrase, and fuzzy search. Highlights found terms in document previews.
• Classification:
  • Uses a hybrid approach: combines AI/ML (e.g., text embeddings, TF-IDF) with rule-based logic for robust, explainable classification.
  • Classification tree includes Academic, Technical, Business, Legal, and their subcategories.
• Analytics:
  • Tracks and displays statistics: document count, total size, upload/search/classification times, and trends over time.
• Cloud Platform:
  • Supabase for authentication, storage, and database; Vercel for deployment and CDN; React/TypeScript for frontend.

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📑 Documentation & Reporting

• The source code is fully documented and organized for easy understanding and extension.
• This README serves as both a user and developer guide.
• For a detailed report on algorithms, platform decisions, and usage, see the attached project report template (if provided by your instructor).
• GitHub Repository: https://github.com/Yosef-AlSabbah/Cloud-Based-Document-Analytics-Service
• Live Cloud Program: https://cloud-based-document-analytics-serv.vercel.app

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Last updated: June 8, 2025