Inspiration

I thought it would be helpful since sometimes we may not be the best at time management

What it does

This website uses an LLM model to help you generate optimized schedule to help you go along with your week and tasks

How we built it

I used FastAPI for the backend to command routing and handles methods. This made handling and parsing data between the frontend and backend relatively easy, leaving me to focus solely on the logic. I decided to go with plain HTML/CSS/JS for this project. I would have loved to use React but unfortunately I haven't learnt enough of it to utilize it for this project. However I think using the plain languages wasn't much of a drawback since I had full control over the website and now which variable interacts with which

Achievements

Able to have integrated the Gemini LLM into my project and rather seamlessly because the response actually worked amazingly well despite me not interacting with the genai library for a long time

Challenges we ran into

I mostly struggled with the frontend (because I am not specialised in the frontend). For example, handling sorting tasks for the appropriate days of the week which had logic that I wouldn't have been able to figure out alone. Additionally, there are still some (frontend) bugs and edge cases that I haven't really been able to get into because of time constraint and problem solving (it's 1:30 AM as of writing this)

Accomplishments that we're proud of

The fact that I was able to integrate an LLM model into helping optimizing the a schedule because of its extensive algorithmic mind The fact that my frontend managed to hold up

What we learned

  1. That frontend are x100 harder to work with than backend (if we are talking solely about logic and handling) because sometimes things just does not go your way
  2. FastAPI is actually pretty useful for backend development ## What's next for El Calendarios I will hopefully be able to fix the bugs that I have previously mentioned while also adding new UI/UX features to make the calendar more dynamic

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