📄 zeba_academy_smart_pdf

Advanced PDF Intelligence Layer for Flutter applications.

zeba_academy_smart_pdf provides powerful tools to extract, analyze, and intelligently process PDF documents for educational, enterprise, and AI‑ready applications.

✨ Features

✅ Text Extraction from PDFs ✅ Smart Keyword Search Engine ✅ Highlight Matching Support ✅ Chapter Auto‑Detection ✅ AI Summary Integration Ready ✅ Clean Modular Architecture ✅ Lightweight & Fast Processing

🚀 Installation

Add dependency to your pubspec.yaml:

dependencies:
  zeba_academy_smart_pdf: ^1.0.0

Then run:

flutter pub get

📦 Import

import 'package:zeba_academy_smart_pdf/zeba_academy_smart_pdf.dart';

🧠 Quick Start

1️⃣ Create Controller

final controller = SmartPdfController();

2️⃣ Load PDF

await controller.loadPdf("assets/sample.pdf");

3️⃣ Search Keyword

final results = controller.search("flutter");

4️⃣ Detect Chapters

final chapters = controller.detectChapters();

5️⃣ Access Full Extracted Text

print(controller.fullText);

🔍 Smart Keyword Search

Search is case‑insensitive and scans across all pages.

final matches = controller.search("education");

Each result contains:

  • Page number
  • Matched text
  • Text index position

📘 Chapter Auto Detection

Automatically detects headings like:

  • Chapter 1
  • Chapter 2
  • Unit 1
  • Unit 2
final chapters = controller.detectChapters();

🎯 Highlight Matching

Utility helper for UI highlighting:

String highlightText(String text, String keyword) {
  return text.replaceAllMapped(
    RegExp(keyword, caseSensitive: false),
    (match) => "[[${match.group(0)}]]",
  );
}

UI layers can style highlighted tokens visually.

🤖 AI Summary Integration (Ready)

The package includes an adapter interface for future AI integrations.

abstract class AISummaryAdapter {
  Future<String> summarize(String text);
}

You can plug in:

  • OpenAI
  • Gemini
  • Local LLMs
  • Custom APIs

without modifying core logic.

🏗 Architecture

PDF → Loader → Text Extractor → Intelligence Layer → AI Adapter

Modules

lib/
 └── src/
     ├── controller/
     ├── models/
     └── services/
  • Controller → Public API
  • Services → Processing engines
  • Models → Data structures

📱 Example

final controller = SmartPdfController();

await controller.loadPdf("assets/book.pdf");

final results = controller.search("flutter");
final chapters = controller.detectChapters();

print(results.length);
print(chapters);

🧪 Testing

Run tests using:

flutter test

Tests include:

  • Controller initialization
  • Keyword search validation
  • Chapter detection logic

⚡ Use Cases

  • Educational apps
  • Ebook readers
  • Smart study platforms
  • AI document assistants
  • Notes extraction systems
  • Knowledge indexing apps

🛣 Roadmap

  • Semantic search (vector indexing)
  • Offline caching
  • Auto notes generation
  • Question generation
  • AI summarization plugins
  • PDF annotation layer

🤝 Contributing

Contributions are welcome!

  1. Fork repository
  2. Create feature branch
  3. Commit changes
  4. Submit pull request

📄 License

GPL‑3.0 License

👨‍💻 Author

Zeba Academy

Built with ❤️ using Flutter.

Libraries

zeba_academy_smart_pdf