WordPecker App offers a personalized language learning experience by allowing users to create custom vocabulary lists from their reading or viewing contexts. It targets language learners seeking to improve vocabulary retention through Duolingo-style lessons and interactive quizzes, leveraging AI for dynamic content generation.

How It Works

The application uses a frontend built with React.js and TypeScript, communicating with a backend powered by Express.js. Vocabulary lists are stored in a Supabase PostgreSQL database, with authentication handled by Supabase Auth. New words are added to contextual lists (e.g., from books, articles), and the app automatically fetches definitions. AI, specifically the OpenAI API, is used to generate lessons and exercises, with plans to integrate LiteLLM for broader LLM support.

Quick Start & Requirements

• Installation: Clone the repository, install backend (npm install in backend) and frontend (npm install in frontend) dependencies.
• Prerequisites: Node.js >= 16, npm or yarn, a Supabase account, and an OpenAI API key.
• Database Setup: Requires running provided SQL schema on a Supabase instance.
• Configuration: Set up .env files for both backend and frontend with API keys and Supabase details.
• Development: Start backend with npm run dev in backend, and frontend with npm run dev in frontend.
• Demo: A live demo version is planned.

Highlighted Details

• Combines Duolingo-style lessons with user-curated vocabulary.
• AI-powered lesson generation and definition fetching.
• Contextual learning by linking words to their original source.
• Currently supports text-based multiple-choice questions.

Maintenance & Community

The project is actively being developed with a list of prioritized features for upcoming days, including LiteLLM integration and customizable language preferences. Contributions are welcomed via standard GitHub pull request workflows.

Licensing & Compatibility

The project is licensed under the MIT license, which permits commercial use and linking with closed-source projects.

Limitations & Caveats

Currently, only text-based multiple-choice questions are supported, with plans to add more exercise types. Progress tracking features like mastery percentage are planned but not yet implemented. Integration with external platforms like e-readers is also a future consideration.