UofTHacks 2023, theme Nostalgia in collaboration with Harpuneet Singh, Arahan Kadakia, and Cedric Wang.
Gramma Cooked is an AI-driven chatbot designed to transform a list of ingredients or an uploaded photo into a personalized culinary experience. By leveraging advanced image recognition and natural language processing, the chatbot identifies available ingredients, asks for your preferred cuisine or cultural flavors, and generates traditional recipes rooted in nostalgia. Users can customize their requests with tags or comments to refine their results, making it a versatile tool for rediscovering the joy of home-cooked meals.
This project was built using a tech stack that included Flask for the backend, React and TypeScript for the frontend, and Cohere's NLP tools for language processing. Our team also integrated APIs to handle real-time image-to-ingredient recognition and connected a curated recipe database to deliver accurate and culturally rich results.
The development process involved overcoming challenges like fine-tuning image recognition models, building a responsive user interface, and ensuring the recipe suggestions were authentic and diverse. Through this project, I strengthened my skills in full-stack development, machine learning integration, and cross-functional collaboration in a high-pressure hackathon environment.
Stack used: Flask, Cohere, React, JavaScript, TypeScript