Meal Planner AI-Powered 🤖

My AI Meal Planner is a full-stack application designed to simplify weekly meal planning through a personalized, AI-driven approach. By collecting essential user information—such as height, weight, daily caloric targets, allergies, and favorite foods—the system generates tailored meal plans for each day of the week. This solution serves not only to provide healthier and convenient meal suggestions but also to showcase my ability to integrate multiple technologies into a cohesive, high-performance product.

Technologies Used

Frontend: Next.js, Tailwind CSS, ChakraUI
Backend: Django, PostgreSQL
AI: OpenAI

Code

The code for the application is available on my GitHub repository.

Challenges

One of the main challenges I faced was integrating the AI component into the application. I had to ensure that the AI model was able to generate meal plans based on the user's input and preferences.
Another challenge was integrating the Django backend with the Next.js frontend. I have experience with Backend development with Nest.js and Node, but I had to learn how to use Django to create a RESTful API.

Django

Django was a powerful tool that allowed me to create a backend for the application. I learned how to use Django's ORM to interact with the database and create a RESTful API.

OpenAI API Integration

I learned how to integrate the OpenAI API into the application with its js library.

I also learned how to structure the response from the API to be used in the frontend with zod to get the data in a structured format.

Tailwind CSS and ChakraUI

With my experience in Tailwind CSS and ChakraUI, I was able to create a modern and user-friendly interface for the application.
I also learned how to use ChakraUI to create a more modern and user-friendly interface for the application.

Supabase

Supabase was a powerful tool that allowed me to host the PostgreSQL database for the application. Its really easy to setup and use.