Chef Kit
Built as a university group project by a team of four, Chef Kit was created to solve a common daily struggle: helping mothers find the best recipes using their existing ingredients in the shortest time. The platform respects custom dietary, nutritional, and time constraints for cooking. The solution comprises a Flutter-based mobile application, a promotional Next.js website, and a Flask backend integrating AI models for recipe recommendation. It received an outstanding grade of over 100% (above full marks), with the professor praising it as one of the best projects ever delivered in the module.
About This Project
Helping mothers quickly discover recipes using only available ingredients, matching strict constraints like nutritional value, dietary goals, and maximum preparation time.
Developed a collaborative system: a Flutter mobile application, an advocacy website built with Next.js, and a Flask backend implementing AI recommendation models to match ingredient lists with recipes.
Awarded an exceptional grade above 100% (full marks), highlighted by the course professor as one of the best-ever project submissions in the module's history.
Full-stack Developer
2024
Public
University
Technology Stack
Project Story
Helping mothers quickly discover recipes using only available ingredients, matching strict constraints like nutritional value, dietary goals, and maximum preparation time.
Developed a collaborative system: a Flutter mobile application, an advocacy website built with Next.js, and a Flask backend implementing AI recommendation models to match ingredient lists with recipes.
Awarded an exceptional grade above 100% (full marks), highlighted by the course professor as one of the best-ever project submissions in the module's history.
Insights & Takeaways
Highlights
- University group project delivered by a four-member team.
- Earned above 100% (bonus marks) for outstanding project execution and design.
- Dual-client architecture: cross platform Flutter mobile application and a Next.js promotional web portal.
Challenges
- Structuring real time ingredient matching algorithms to query recipe datasets based on multiple dynamic constraints (time, nutrition).
- Bridging multiple clients (Flutter mobile app & Next.js website) to a singular Flask API backend.
Lessons Learned
- User-centered design focused on real-world constraints (like mothers cooking at home) results in highly practical and well-received product features.
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