Recipe Picker
Project Overview
A personalized recipe recommendation platform that helps users discover new recipes based on their available ingredients, cuisines, and dietary preferences. Users can easily add recipes to their cart and organize them for the week. Additionally, the platform uses AI-powered suggestions to generate recipes tailored to individual preferences, making meal planning even easier and more convenient.
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Problem
Many people struggle with meal planning due to busy lifestyles, often feeling frustrated by the challenge of deciding what to cook and finding recipes that match their dietary needs and available ingredients. Traditional recipe websites can be overwhelming, as they often ignore personal preferences and dietary restrictions.
Goal
The goal is to create an intelligent recipe recommendation system that simplifies meal planning. By providing users the flexibility to filter recipes based on their dietary needs and available ingredients and plan their meals for the week, the platform helps users make better decisions and ultimately more satisfied with their meals.
Technical Details
The application leverages modern web technologies and AI to deliver personalized recipe recommendations. The frontend is built with React and Tailwind CSS for a responsive and intuitive user interface, while the backend uses Java Spring Boot for efficient API endpoints and secure database integration.
Spring Boot was chosen for its robust backend capabilities including database integration (Hibernate) and secure authentication (Spring Security). It also offers better performance than Python due to its compiled nature and optimizations in the JVM. Cookie based authentication was used for the login system as it has builtin browser support and session persistenc.
As for the database, I used MySQL for its scalability and performance. The database schema design is shown below.
System architecture showing the recommendation engine and API integration
I wanted to design the layout of the website to be as user-friendly and intuitive as possible. It is responsive and can be used on any device. The user can easily add recipes to their cart and organize them for the week. The user can also increase the quantity of each recipe chosen. When searching for recipes, the user can filter them based on the ingredients, cuisines, and dietary preferences.
System architecture showing the recommendation engine and API integration
Key Features
- Personalized recipe suggestions
- Keyword-based recipe search
- Ingredient, cuisine, and dietary restriction filtering
- Cart based meal planning system
- Mobile-responsive design
Results
The Recipe Picker platform has successfully made my meal planning process much more efficient and enjoyable!
Demo video showcasing the recipe picker in action