Binder.ai

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Inspiration

We got really interested in building this tool because it takes a lot of time to keep track of all the classes we're taking with the course info scattered around different places - canvas, website, syllabus, etc. We want to take advantage of LLMs to help students better visualize and digest their course load so that they can better use their time and focus on what's most important - learning materials.

What it does

It takes in the user's course syllabi and uses Large Language Models to extract meaningful information including class schedules, assignments, and exam information. Then it produces 1) a timeline visualization for students to see their assignments and exam progress throughout the semester. 2) a daily digest of the work that students should focus on

How we built it

First, we ideated a prototype using Figma with the main features that we think students would like. Then we built the front-end using next.js, and then the back-end with firebase. We query the openai API using the firebase cloud functions.

Challenges we ran into

The blocker that we ran into is deploying the firebase cloud functions. We had finished developing both on the front-end and back-end and just needed to integrate by deploying the firebase cloud functions to connect both. But we weren't able to connect these two pieces. I think we should spend more time to study the firebase documentation(there are very limited resources for it online, especially for fireabse v9)