Describe your project

Our project choose healthier mainly focusses on informing the user about the health impact of the selected snack in an easily comprehendable manner. The ingredients or nutrition labels at the back of the pack are not very intuitive for the user to understand it's long-term impact. We also want to take away the cognitive load of having to comply with one's dietery preferences and limitations. All information is shown in 1-2 minutes for the user to make a healthier choice!

1. In scope - focuses on dynamic product data collection from platforms like BigBasket and Blinkit, health analysis of packaged food items, personalized insights based on user preferences, and an intuitive interface for consumer interaction.
2. Out of scope - It does not cover real-time price tracking, purchasing integration, or regulatory compliance checks on food safety and labeling standards.
3. Future scope - It include expanding the product catalog across global platforms, integrating real-time health tracking devices, and providing recommendations tailored to specific medical conditions or fitness goals.

Challenges we ran into

Some of the challenges we faced are as listed below:

1. Collecting or scraping relevant snacks data from quick-commerce websites like BigBasket, Instamart etc.
2. Fine Tuning the LLM prompt to satisfy our various needs like checking the ingredients, health factor, alternative foods and also keeping in mind dietary preferences and limitations.
3. It was our first time working with streamlit and we realised after quite some time that streamlit doesn't support deploying private github repos so that's when we changed the repo scope to public.