AI-Powered Book Reader

An intelligent, AI-powered book reading application that transforms the digital reading experience through advanced natural language processing, text-to-speech, text-to-image generation, and chapter summarization capabilities.

📖 Table of Contents

• Overview
• Features
• Architecture
• Technology Stack
• API Documentation
• Installation
• Usage
• Testing
• Deployment
• Contributing
• Team

🎯 Overview

The AI-Powered Book Reader is a cutting-edge application designed to bridge the gap between traditional digital reading and modern AI capabilities. Built as part of CMPE 273 - Enterprise Distributed Systems, this platform leverages Large Language Models (LLMs) to provide an enhanced, accessible, and interactive reading experience.

Key Objectives

• Enhanced Accessibility: Make reading accessible for visually impaired users through AI-driven features
• Real-Time NLP: Implement LLMs for instant text processing and comprehension
• Open-Source Integration: Seamless access to vast literature collections
• Intuitive Interface: User-friendly design with personalized reading experiences
• AI-Powered Features: Text-to-speech, text-to-image, and intelligent summarization

✨ Features

🤖 AI-Powered Capabilities

• Text-to-Speech (TTS): Convert text to natural-sounding speech using Microsoft Edge TTS
• Text-to-Image (TTI): Generate AI-powered visual representations using Amazon SageMaker Dreamlike Diffusion
• Chapter Summarization: Automated chapter summaries using DistilBART CNN 6-6 model
• Real-Time Processing: Instant AI model responses for enhanced user experience

📚 Content Management

• Multi-Source Integration: Access books from Project Gutenberg (Gutendex API) and WuxiaWorld
• Personal Library: Create custom reading lists and organize books by preferences
• Reading Progress: Track reading history and bookmark favorite passages
• Review System: Rate and review books with community feedback

🔐 Authentication & Security

• Custom Authentication: Secure email/password registration and login
• Google OAuth2: Seamless integration with Google accounts
• Secure Storage: Encrypted credential management and session handling

🎨 User Experience

• Responsive Design: Optimized for desktop, tablet, and mobile devices
• Customizable Interface: Adjustable fonts, themes, and reading preferences
• Offline Support: Client-side caching for uninterrupted reading
• Accessibility Features: High contrast modes, adjustable text sizes, and screen reader support

📸 Demo Images

Here are some screenshots of the application:

Main Page

Single Book Search

Review Page

Library Page

Reading Page – Text to Speech

Reading Page – Text to Image

Reading Page – Customization

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🎥 Demo Video

Watch the demo here:

🏗️ System Architecture

(High-level architecture of the system)

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🔄 Data Flow

(End-to-end data flow from input sources to analytics and output)

🛠️ Technology Stack

Frontend

• React 18: Modern UI framework with hooks and context
• Tailwind CSS: Utility-first CSS framework for responsive design
• IndexedDB: Client-side database for offline functionality
• Webpack: Module bundler and build tool

Backend

• Django 4.0+: Python web framework with REST API support
• Django REST Framework: API development toolkit
• Celery: Asynchronous task processing
• Redis: In-memory data structure store for caching

AI & Machine Learning

• Amazon SageMaker: Managed ML platform for model deployment
• Edge TTS: Microsoft's text-to-speech service integration
• Dreamlike Diffusion 1.0: Text-to-image generation model
• DistilBART CNN 6-6: Text summarization model

Infrastructure

• AWS ECS: Container orchestration service
• AWS RDS: Managed MySQL database
• AWS S3: Object storage for static files
• AWS CloudFront: Content delivery network
• AWS Application Load Balancer: Traffic distribution

📡 API Documentation

Authentication APIs

Endpoint	Method	Parameters	Description	Response
/auth/signup/	POST	{"email": "string", "password": "string", "first_name": "string", "last_name": "string"}	Register new user	{"response.data": true/false, "response.message": "string"}
/auth/login/	POST	{"email": "string", "password": "string"}	User authentication	{"access": "string", "refresh": "string", "response.message": "string"}
/auth/google-login/	POST	{"token": "string"}	Google OAuth validation	{"access": "string", "refresh": "string", "response.message": "string"}

Book Management APIs

Endpoint	Method	Parameters	Description	Response
/main/books/with-genres/	GET	None	Get all books with genres	List of book objects
/main/books/with-genres/<book_id>/	GET	book_id (path)	Get specific book details	Book object
/main/books/with-genres/search/	GET	query=<keyword>	Search books by keyword	List of matching books
/main/reviews/	POST	{"book_id": int, "user_id": int, "review": "string", "rating": int}	Add book review	Success/error message

Library Management APIs

Endpoint	Method	Parameters	Description	Response
/library/get_library_data/	GET	user_id	Get user's library data	Library object with books and shelves
/library/get_shelf_list/	GET	user_id	Get user's shelf list	List of shelf objects
/library/add_shelf/	POST	{"user_id": int, "shelf": {"shelf_id": int, "name": "string"}}	Create new shelf	Success/error message
/library/add_book_to_shelf/	POST	{"user_id": int, "shelf_id": int, "book_id": int}	Add book to shelf	Success/error message
/library/remove_book_from_shelf/	DELETE	{"shelf_id": int, "book_id": int}	Remove book from shelf	Success/error message

Reading & AI APIs

Endpoint	Method	Parameters	Description	Response
/book/{book_id}/{chapter_number}	GET	book_id, chapter_number (path)	Get chapter content	Chapter content object
/book/tts/{book_id}/{chapter_number}	POST	{"chapter_number": int, "book_id": int}	Stream TTS audio	Streaming audio URL and paragraph index
/book/aiimage/{book_id}/{chapter_number}	POST	{"chapter_number": int, "book_id": int}	Generate AI images	JSON with AI-generated chapter images

🚀 Installation

Prerequisites

• Node.js 18+ and npm
• Python 3.8+
• Redis server
• MySQL database
• MongoDB instance

Frontend Setup

1. Clone the repository

   git clone https://github.com/DJJ547/CMPE273-Book-Reader-React.git
   cd cmpe273-book-reader-react

2. Install dependencies

   npm install

3. Environment Configuration

   • Download the .env file from the provided link
   • Place it in the root directory
   • Configure your API endpoints and authentication keys

4. Start development server

   npm start

Backend Setup

1. Clone the backend repository

   git clone https://github.com/DJJ547/CMPE273-Book-Reader-Django.git
   cd cmpe273-book-reader-django

2. Install Python dependencies

   pip install -r requirements.txt

3. Configure database connections

   • Update database settings in settings.py
   • Configure Redis connection
   • Set up AWS credentials for SageMaker

4. Run migrations

   python manage.py migrate

5. Start the server

   python manage.py runserver

📱 Usage

Getting Started

1. Authentication: Sign up with email/password or use Google OAuth
2. Browse Books: Explore trending books and new releases on the main page
3. Search: Use the search functionality to find specific books or genres
4. Reading: Open any book to access AI-powered reading features
5. Library Management: Organize books into custom shelves and track reading progress

AI Features

• Text-to-Speech: Click the TTS button to have the book read aloud
• Text-to-Image: Generate visual representations of chapter content
• Summarization: Get AI-generated chapter summaries for quick understanding

🧪 Testing

Frontend Testing

npm test

Backend Testing

python -m pytest

Load Testing

• JMeter: Configured for up to 200 concurrent users
• Performance: Optimized for sub-2000ms response times

🚀 Deployment

Frontend Deployment

• AWS S3: Static file hosting
• AWS CloudFront: Content delivery network
• CI/CD: Automated deployment pipeline

Backend Deployment

• AWS ECS: Container orchestration
• AWS Application Load Balancer: Traffic distribution
• AWS RDS: Managed MySQL database
• AWS EC2: MongoDB hosting

AI Services

• AWS SageMaker: Model deployment and inference
• AWS Lambda: Serverless AI processing
• API Gateway: RESTful API management

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

👥 Team

CMPE 273 - Enterprise Distributed Systems

• Jiajian Liu - Frontend Development & UI/UX
• Yifu Fang - Backend Development & API Design
• Dina Liao - AI Integration & Machine Learning
• Jiajun Dai - Infrastructure & DevOps

📄 License

This project is developed as part of CMPE 273 coursework at San José State University.

🔗 Links

• Frontend Repository: https://github.com/DJJ547/CMPE273-Book-Reader-React.git
• Backend Repository: https://github.com/DJJ547/CMPE273-Book-Reader-Django.git
• Course: CMPE 273 - Enterprise Distributed Systems
• Instructor: Dr. Chandrasekar Vuppalapati

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Built with ❤️ by the CMPE 273 Team

Fall 2024 • San José State University