Sloth Notes: paste it, get the gist, all offline in your browser

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady

What I Built

Sloth Notes is a single web page that does the boring part of reading for you. Paste a lecture transcript, a long group chat or an article, pick what you want, and it gives you:

• a two-line summary
• a list of action items and deadlines
• six flashcards for revising

I built it for students like me who end up with hours of lecture transcripts and 400-message group chats that never get read. Paste, click, done.

Everything runs inside the browser tab. There's no backend, no API key and no account.

Demo

Live: https://jhashashwat25-creator.github.io/Sloth-Notes/

It needs a recent Chrome or Edge on a laptop or desktop, because the model runs on WebGPU. The first load downloads the model (roughly 0.4 to 1.5 GB depending on which one you pick). After that it is cached and works with Wi-Fi off.

Code

jhashashwat25-creator / Sloth-Notes

Sloth-Notes

View on GitHub

The whole app is one index.html file with no build step, released under the MIT license.

How I Built It

• Models: open-weight models in 4-bit quantised form: Qwen2.5 0.5B and 1.5B, Llama 3.2 1B, and Gemma 2 2B.
• Runtime: WebLLM, an open-source inference engine that runs these models in the browser through WebGPU.
• App: plain HTML, CSS and JavaScript. There's a model dropdown, a text box, three output modes (summary, action items, flashcards), and streamed output with a stop button.
• How it works: the page loads the chosen model once and caches it in the browser. Each mode is a short system prompt, and the pasted text is the user message. The answer streams back token by token.
• Keeping small models honest: I kept temperature low (0.3), capped the input length, and told the model to use only the text provided, which reduces made-up details. Small models can still miss things, so the page says to check anything important against the original.

Why Does Open Innovation Matter?

• Privacy: lecture recordings and group chats are personal. With an open-weight model running in the tab, the text never leaves the device. A closed API would mean sending it to someone else's server.
• Works offline: after the first download, there's no network dependency. That matters for students with patchy internet.
• Zero running cost: there's no API bill and no rate limit, so there's no reason to ration it.
• Swappable models: the dropdown switches between four open models. I can trade speed for quality on the same text, and a single closed API doesn't offer that choice.
• Free to host: inference happens on the user's device, so the site is just a static file on GitHub Pages.

The Lazy Payoff

The point of the project is that reading is the part you keep putting off. Sloth Notes turns a wall of text into something you can read in seconds, and it does that without sending anything off your machine. Once the model is cached, using it takes one paste and one click.