FODMAP Dietary Suggestion Tool

Navigating the low FODMAP diet for managing IBS or SIBO is hard. Our AI-driven tool makes it easy! Search "nuts" to find "peanut," or "chips" for "potato." Make dietary management simple and effective

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Inspiration

I was really inspired to build the FODMAP Dietary Suggestion Tool because I have dealt with IBS my whole life and following a Low FODMAP diet can be super confusing. There are so many foods, and it's hard to remember what's okay to eat. My big idea was to make a simple tool that helps people quickly find out if a food is IBS-friendly or not.

What it does

This tool is all about making the Low FODMAP diet simpler. It lets you quickly check if a food is IBS-friendly or not. The coolest part is its smart search: if you type "berries," it'll know you mean "strawberry" or "blueberry." Or, if you use a local name like "Ngwaci," it'll understand you mean "sweet potato." This means you don't have to guess or search for exact words – the AI helps you find what you're looking for, making dietary choices much easier.

How we built it

I built this app using Python for the brains of it (that's Flask!). All the food info is stored in MongoDB. The cool part is that I added Google Gemini AI to the search. Now, you don't have to type the exact word. If you search for "berries," it knows you might mean "strawberry." Or, if you type a local name like "Ngwaci," it understands you mean "sweet potato." This makes finding foods much easier. I then used Docker to package everything up and put it live online using Google Cloud Run. This lets anyone use the app right from their browser!

Challenges we ran into

One of the first big hurdles, even before writing much code, was finding reliable data for all the FODMAP foods. I had to pore over a detailed PDF document, carefully extracting each food item, its FODMAP level, and specific details like which FODMAP types were present. This was a long process to gather the foundational information for the database, ensuring the app's core data was accurate. Then came the technical challenges. Getting the database to "talk" to my app once it was online was an adventure. And making sure the AI part had its "secret key" ready to work on the internet was another puzzle piece that took some figuring out. Setting up the deployment to Google Cloud Run with Docker also had its moments, making sure every little configuration was just right.

Accomplishments that we're proud of

But figuring out these tough spots felt incredibly rewarding! Each challenge, from data collection to deployment, taught me so much. I'm really proud of how it all came together, especially seeing the AI make the search feel so smart and intuitive. Building this from scratch was a huge adventure! I learned so much about putting all the pieces of a web app together, from the design you see to the hidden database and AI connections.

What we learned

Building this app taught me a ton! I got hands-on experience connecting a website to a database (MongoDB) and making it all work smoothly online with Google Cloud. The biggest learning curve was definitely integrating the Google Gemini AI to make the search so smart. It was a journey of connecting all these different parts of technology to create one useful tool.

What's next for FODMAP Dietary Suggestion Tool

For the future, I'd love to add even more features! Imagine being able to save your favorite foods or track what works for you. I'd also like to use the AI to suggest low-FODMAP meal ideas, make the food database even bigger, and maybe even create a mobile app so it's always handy on the go!

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