This is a side project developed to explore the capabilities of Google AI Studio and modern Android development practices. The app serves as a dynamic recipe aggregator, specifically designed to showcase how AI-assisted development can streamline the creation of complex data-driven applications.
The primary goal of this project was to build a functional, beautiful, and "smart" recipe application while experimenting with advanced tooling. The app focuses on healthy living, nutrition tracking, and dynamic content discovery.
The app leverages high-quality culinary content from EatingWell (along with other healthy eating sites like Skinnytaste and Budget Bytes) as its primary source of recipe data.
- Dynamic Recipe Crawling: Implements a two-phase crawler using Jsoup:
- RSS Discovery: Monitors feeds for the latest healthy recipes.
- Deep Extraction: Uses structured data (LD+JSON) and HTML scraping to pull full ingredients, instructions, and nutritional facts directly from the source websites.
- Infinite Scrolling (Paging): Automatically fetches and appends more recipes from the web as the user scrolls, providing a seamless browsing experience.
- AI-Assisted Development: Built using logic and architectural patterns explored through Google AI Studio.
- Modern UI: Developed entirely with Jetpack Compose, featuring a vibrant, responsive design with full Dark Mode support.
- Nutrition Tracking: Includes a built-in journal for logging calories and water intake.
- Language: Kotlin
- UI Framework: Jetpack Compose
- Concurrency: Kotlin Coroutines & Flow
- Networking/Parsing: Jsoup (for HTML/XML), org.json (for JSON-LD)
- Image Loading: Coil
- Architecture: MVVM with StateFlow
Note: This project is for educational and exploration purposes, demonstrating the integration of web-crawled content into a modern Android architecture.