SRS Introduction Demo 2 - COS301-SE-2026/Mealchemy GitHub Wiki

Introduction

Mealchemy is an intelligent recipe management and meal planning system that is designed to reduce meal-time decision fatigue and simplify the cooking process amongst users of the application.

Many users struggle to decide what to cook despite already having ingredients in their fridge or pantry. Existing recipe solutions often fail to provide personalisation, recommendations accounting for ingredient availability, or integrated meal-planning support. This results in wasted time, inefficient grocery shopping, repetitive meal choices, and fragmented recipe storage.

The business need for Mealchemy arises from the growing demand for a centralised and intelligent meal-planning solution that assists users throughout the entire meal decision cycle. Users require a system that stores and organises recipes, and recommends meals based on available ingredients, dietary restrictions, allergies, flavour preferences, nutritional goals, and shopping requirements.

Mealchemy addresses these challenges by combining recipe management, pantry tracking, recommendation systems, guided recipe discovery, shopping list generation, and nutritional analysis into a mobile application. The system enables users to create and manage personal recipe vaults, maintain pantry inventories, receive personalised recipe recommendations, interact with a swipe-based discovery interface, automatically generate shopping lists from missing ingredients, and calculate nutritional information for meals.

The scope of this project includes:

  • User authentication and profile management
  • Dietary preference and allergy management
  • Personal, shared, and global recipe vaults
  • Pantry and ingredient inventory management
  • Heuristic-based recipe recommendation
  • Guided recipe discovery and interaction
  • Shopping list generation and management
  • Nutritional calculation and meal analysis
  • Interactive recipe editing and organisation

The platform is implemented using a modern technology stack consisting of Flutter for the frontend mobile application, Spring Boot for backend services, PostgreSQL for data management, and Python for recommendation and heuristic processing. Together, these components provide a scalable and extensible foundation for a personalised meal decision support system.