LanguageBooster

LanguageBooster is a web application that transforms your personal study materials into customized language flashcards using AI. Simply paste text or upload a PDF, and let the app generate a new learning deck for you in seconds.

Project Description

This project aims to solve a common problem for language learners: the time-consuming process of creating personalized study materials. LanguageBooster streamlines this by allowing users to generate contextual flashcards directly from their own content, like a book chapter, article, or personal notes.

Key Features

• AI-Powered Generation: Automatically creates flashcards from user-provided text or PDF files.
• Language Autodetection: Intelligently detects the source language of your material.
• Customizable Decks: Choose the base and target languages (supports Polish, English, Spanish, and German for the MVP).
• Simple Learning Interface: Study your flashcards with a straightforward "I know / I don't know" system.
• Secure and Personal: User accounts are managed through Supabase & Spring Security, ensuring that your collections are private.

Tech Stack

Category	Technology
Backend	Java (Spring Boot)
Frontend	Angular (^17.3.0), TypeScript (~5.4.2), TailwindCSS
Database	PostgreSQL
Authentication	Supabase (with Spring Security)
Containerization	Docker, Docker Compose
Backend Testing	JUnit 5, Mockito, Spring Test, Testcontainers, REST Assured
Frontend Testing	Jest, Playwright, ESLint
CI/CD	GitHub Actions

Testing

The project follows a comprehensive testing strategy to ensure quality, stability, and security. Testing is performed at multiple levels for both the backend and frontend, as outlined in the detailed test plans.

Backend Testing Strategy

• Unit Tests: Using JUnit 5 and Mockito to verify individual classes and methods in isolation.
• Integration Tests: With Spring Test, MockMvc, and Testcontainers to test the collaboration of components within the Spring context, including database interactions.
• API (E2E) Tests: Using REST Assured to test the public API endpoints from a client's perspective.
• Security Tests: Planned to verify authentication, authorization, and data isolation between users.

Frontend Testing Strategy

• Unit & Component Tests: Using Jest and Angular's TestBed to test components, services, and pipes in isolation.
• End-to-End (E2E) Tests: Using Playwright to simulate full user scenarios in a real browser.
• Manual Tests: Including UI/UX validation against mockups, and cross-browser compatibility checks (Chrome, Firefox, Safari).

Getting Started Locally

Follow these instructions to set up and run the project on your local machine.

Prerequisites

• Java (JDK 17 or newer)
• Node.js (Check the .nvmrc file for the specific version, or use a recent LTS release)
• Docker and Docker Compose
• Maven (The project includes a Maven wrapper)

Setup and Execution

1. Clone the repository:

   git clone <repository-url>
   cd language-booster

2. Run the Backend: Navigate to the backend directory and use the Maven wrapper to start the Spring Boot application.

   cd backend/main
   ./mvnw spring-boot:run

   The backend server should now be running.

3. Run the Frontend: In a new terminal, navigate to the frontend directory, install dependencies, and start the Angular development server.

   cd frontend
   npm install
   npm start

   The application will be available at http://localhost:4200/. The proxy.conf.json file handles proxying API requests to the backend.

Available Scripts

The following scripts are available for the frontend application and can be run with npm run <script-name>.

Script	Description
start	Runs the application in development mode (ng serve).
build	Builds the application for production.
test	Runs unit tests with Jest and generates a coverage report.
lint	Lints the codebase using ESLint.
watch	Builds the app and watches for file changes.

Project Scope

In Scope (MVP Features)

• User registration and login (email/password).
• Flashcard collection creation from pasted text or a single PDF (up to 5MB).
• Management of flashcard collections (view, edit, delete).
• A simple learning mode to review flashcards.
• Support for Polish, English, Spanish, and German.

Out of Scope

• Advanced Spaced Repetition System (SRS) algorithms.
• Importing multiple files or other formats (e.g., DOCX, EPUB).
• Sharing collections between users.
• Mobile applications (the MVP is web-only).
• Gamification features like points or leaderboards.

Project Status

MVP (Minimum Viable Product)

This project is currently in the MVP stage. The core functionalities are implemented and usable, but it is not yet a full-featured product. Future development will focus on expanding features, improving the learning algorithm, and enhancing the user experience.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.