Wonder

Inspiration

For the functionality of this project, I was heavily inspired by search programs like Raycast and the search function in Linear, both of which interpret natural language.

What it does

Wonder parses natural language prompts relating to simple calculations and quickly displays the solution to what you're asking. For example, if you ask it "Could you please tell me what 32 times 4 is?" the program will respond accordingly.

How we built it

Wonder was built fully through HTML, CSS, and Javascript. I considered using a framework like Django, as I'm more familiar with back-end Python, but I decided against it given the time constraints.

Challenges we ran into

The time constraint was definitely the biggest issue I faced during this project. I envisioned a lot with Wonder and, while I was unable to integrate all of the functionality, I’m very proud of the final product.

Accomplishments that we're proud of

The simple, intuitive design of the website, including the animations, is something I'm very proud of. Additionally, my system for separating relevant information within natural language prompts was challenging but rewarding to construct.

What we learned

Before this project, I had never created a very Javascript-heavy site before, so I learned a lot about . And, even though the brainstormed APIs did not appear in the final product, I did do research on each of them and plan on using them for future projects.

What's next for Wonder

I have a lot of visions for expanding this project through the use of various APIs, so it get information from Wikipedia, surface images, get the weather, and make more calculations. The foundations I've created with the current version will be very helpful in expanding to future functionality.

Built With

• css3
• figma
• html5
• javascript