QueryCorner

Inspiration

The inspiration for our project, QueryCorner, comes from our experience as students and software developers getting low-quality answers from ChatGPT. Typing out a detailed prompt can be hard and annoying but is often necessary for complex questions or questions requiring a lot of context. We saw an opportunity to create a tool that would empower people to accelerate their research and workflow.

What it Does

Query Corner is a generative AI prompt-sharing / social platform where people can share their prompts and prompt templates. Users can attach tags to their prompts (React, Finance, Health, etc) to help with filtering, and we use embeddings and vector search to implement a robust semantic search. Additional features include search history, saved prompts, likes, and as a stretch goal, comment sections. With QueryCorner, the perfect prompt is always one search away.

How we built it

We built our application using a multitude of services/frameworks/tools:

React.js for the client frontend
NextJS for server-side rendering, file routing, and improved SEO
Tailwind for styling
ShadCN, Framer Motion, and Acernity for animations and UI components
Convex for data storage and our backend server
OpenAI's Text-embedding-3-small embedding model
Clerk for OAuth

Challenges We Ran Into

Learning the basics of NextJS -- this was the first time any of us had used NextJS and it required a lot of learning on everyone's part.
Finding time to work as a team -- we all have busy lives as college students, and finding time to plan how to work asynchronously brought some unique challenges.
Learning how to use ShadCN -- this is a different type of component library as compared to DaisyUI or Chakra

Accomplishments that we're proud of

Finishing our project and getting it working! We were honestly surprised at the progress we made each day and are super proud of the end product.
Learning a ton of new technologies