Ultimate Meal Planner

Inspiration

We are active and engaged college students with constant need of energy and refreshment. And our primary source of nourishment is OUR MEALS that we eat. However, the food on campus is not necessarily cheap nor healthy but is sort of has become a ready default for many of us. We think we know why, it's because of the lack of planning and the tyranny of choice. If a student does not know what to cook he will waste considerable amount of time just thinking and researching food ideas on random places. Instead they can use this to get accurate recipes from verified datasets which they can query with natural language. PLUS they only have to upload the receipt and not even type anything. except for the chat.

What it does

This web app allows users to upload the receipt of their grocery shopping and it allows them to create weekly meal plans based on their tastes and preference. Plus they can interact with it in a much more human way.

How we built it

We used a boiler plate RAG system with langchain and easy to set up UI integration with streamlit. We also stored the embeddings in chromadb.

Challenges we ran into

We had problem setting up the OCR and how to use it properly but we eventually figured it out. We also had problems setting up the Intel trial notebooks.

Accomplishments that we're proud of

We are proud that we managed to create an app that was eventually scaled to a web application that not only included a good User Interface, but also implementing a chat bot that we customary trained as an integral part to it.

What we learned

How to train a chat bot with large data sets How to combine a chat bot with a working web application to have a good user experience Learning how to decode words on an image and then scraping those words and eventually feeding it into the chat bot to process Learning how to create a good user interface that is easy for the user to navigate and figure out how to use.

What's next for Ultimate Meal Planner

Scale it to a Viable Web Application: Expand the functionality to make it accessible on various devices. This would involve creating a responsive, user-friendly interface and improving the performance to handle larger user traffic. Additional features could include personalized recommendations, meal-planning suggestions based on dietary preferences, or integrating with other services like grocery delivery platforms.

Set Up AWS for Scalability: Implement AWS services to manage cloud storage, processing, and hosting. AWS Lambda could handle the computation of recipe generation, while S3 might store scanned grocery lists or images. This would allow for faster processing, better resource management, and increased scalability as the user base grows. Enhance AI Capabilities Personalized AI Recommendations: Integrate machine learning to offer personalized recipe suggestions based on user preferences, dietary restrictions, or past behaviors. Using AI, you could even predict future grocery needs based on past grocery lists. NLP for Recipe Queries: Implement natural language processing (NLP) so users can interact with the app via voice commands or ask questions about specific ingredients or meal preparation steps.

Expand Recipe Database & Partner Integrations: Crowdsource Recipes: Allow users to upload their own recipes and share them within the app. Implement a rating system so users can upvote/downvote recipes. Partnerships: Partner with popular cooking websites, grocery stores, or meal kit services to expand the variety of recipes and potentially automate grocery ordering through API integrations.

Nutritional Analysis and Meal Planning: Nutritional Information Integration: Add a feature that calculates the nutritional content of meals based on ingredients. This would be a useful tool for users interested in calorie tracking or specific dietary goals. Smart Meal Planning: Create a weekly meal planner feature that helps users organize their groceries and meals for the week, providing a full breakdown of costs, portions, and nutritional intake.

Optimize for Mobile and IoT Integration Mobile App Development: Develop a mobile app version of the platform to make it even more accessible. Push notifications could remind users of groceries to buy or meals to prepare based on expiration dates. Smart Device Integration: Integrate with smart kitchen appliances (e.g., Amazon Alexa, smart fridges) to help users prepare meals more seamlessly or notify them when they are running low on certain ingredients.