Track
This project is under the Personal Knowledge Management Track.
Inspiration
The inspiration behind this app was that I have spent plenty of time practicing technical interview questions as well as participate in UCI's competitive programming club, ACM and I thought it would be helpful to have a note analyzer for this subject since it is very tricky a lot of the time.
What it does
You can upload or write notes and you can either generate a summary of your notes or have the app suggest new topics to study.
How we built it
It was built using Flask for the backend, HTML/CSS for the front-end and Bedrock and S3 was used for the generative responses.
Challenges we ran into
Some of the challenges that were encountered were issues with the authentication and the app being able to successfully use the AWS credentials. It was also a challenge being able to integrate the AWS services with the flask app.
Accomplishments that we're proud of
Accomplishments that I am most proud of is getting the bedrock to successfully generate responses from a given prompt and making it visible.
What we learned
I learned how to use Bedrock and how it can use content from S3 buckets to generate a response from popular models such as Claude and DeepSeek. This was also my first time using Flask to build a web app.
What's next for AlgoNotes
AlgoNotes has quite the room for expansion as it can be possibly integrated with more AWS services such as Lambda and features such as allowing users to see their notes in raw form to be implemented.
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