Project Info

MessageMinder

Inspiration

Are you a bad texter? Do you not know what to say to your friends over text? MessageMinder tries to help maintain meaningful connections with friends by suggesting responses to difficult texts.

What it does

MessageMinder finds meaningful responses to difficult texts. MessageMinder gets your friend's texts that you haven't replied to, and based on your thoughts on the texts and from learning your texting style/mannerisms, suggests responses to text your friends back.

How we built it

We built the frontend using NextJS and power our response suggestion engine with a LLM using Together.ai.

Challenges we ran into

Prompt engineering was a large challenge, and a lot of effort was put into fine-tuning our prompts to yield the most clean and relevant response suggestions.

What's next

We want to integrate MessageMinder with messaging platforms such as iMessage, Whatsapp, etc, so you can view all your messages in one place, and directly send suggestions from the app.

This is a Next.js project bootstrapped with create-next-app.

Getting Started

First, run the development server:

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

You can start editing the page by modifying app/page.js. The page auto-updates as you edit the file.

This project uses next/font to automatically optimize and load Inter, a custom Google Font.

Learn More

To learn more about Next.js, take a look at the following resources:

Next.js Documentation - learn about Next.js features and API.
Learn Next.js - an interactive Next.js tutorial.

You can check out the Next.js GitHub repository - your feedback and contributions are welcome!

Deploy on Vercel

The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.

Check out our Next.js deployment documentation for more details.

Analysis

Compare with all teams

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Metric

hmarch
6
Yifei Lu
1

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

CSSIn code
JavaScriptIn code
Next.jsIn code
ReactIn code
Tailwind CSSIn code

5 of 5 appear in the indexed code.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

12 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.