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Worked in a team to develop a dynamic website during MakeUC Hackathon 2023 that utilizes an AI LLM. This website allows the user to input text and uses AI to generate quiz questions from user given text. Try it out today!

Home Page: https://nekruzash.github.io/QuizGenAI/

License: MIT License

CSS 35.71% HTML 30.46% JavaScript 33.83%
cohere-ai css html javascript

quizgenai's Introduction

QuizGen

Quizgen Website Live try it out now!

Inspiration

As students, we are always trying to find better ways to study and learn new studying techniques, so creating a tool that can help us do that and increase productivity in our everyday life was in our plan.

What it does

In our brainstorming sessions, we came up with this idea to make studying and learning easier. Our product is a website that allows the user to input text and ask for quiz-generated questions based on the inputted text.

How we built it

We built this project using Visual Studio Code, implementing JavaScript, Cohere AI Language Model API, HTML, and CSS.

Challenges we ran into

We faced difficulties and challenges when we were trying to use the Chat GPT API and connecting our files in JavaScript because the keys in Chat GPT were limited and half-way we couldn't test our code because of that. So we decided to use Cohere AI api that was being hosted on their website which saved us time because we were about to host our own LLM in the Google Cloud and then embedd it into our website.

Accomplishments that we're proud of

This whole experience is a great accomplishment for us. From the start of this hackathon, we decided to make a project that we lacked skills for. We did not know much about AI and APIs, most of us had fundamental knowledge of JavaScript. But towards the end of the hackathon, our team knew more about AI and a new programming language and how they can be implemented in everyday life.

What we learned

We learned how the fetch function works when calling an API. Also, we learned that the AI API has its own special parameters and how they can be modified in order to recieve more creative generated text. The LLM also needed to be coded to read the inputted user text, we came up with a solution for that after many tests with our JavaScript code. We learned more about the syntax of the JavaScript language and its async functions.

What's next for QuizGen

Our next goal is to make our product more user-friendly, create a chrome extension, implement new and better AI models such as GPT-4, and add more features to it like user account creation and data tracking that can be stored in Cloud.

quizgenai's People

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