I got too lazy to name my files, so a local AI does it now.

A developer built Sloth Sorter, an MIT-licensed desktop app that uses Google's open-weight Gemma 3 model (gemma3:4b) running locally through Ollama to read, rename and sort messy files into folders such as Bills & Receipts, Work and Photos. The Electron app previews every change before anything moves, offers one-click undo, and includes a background "Sleep mode" that tidies only files left untouched for several minutes. It ships installers for Windows, macOS and Linux with no account, subscription or API key, and files never leave the machine.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady https://dev.to/challenges/hacktoberfest-week3-2026-10-19 Everyone has a Downloads folder like mine: IMG 2231.png , document 1 .docx , scan0412.pdf , asdf.png , and a manual named just manual.pdf . Tidying it by hand means opening every file to remember what it is. So I never do it. Sloth Sorter is a desktop app that does it for you. You pick a folder, and an AI that runs on your own computer reads what is inside each file, gives the cryptic ones a readable name, and sorts everything into sensible folders: Bills & Receipts, School, Work, Photos, and so on. Nothing moves until you have looked at the plan. You can edit any name, change any folder, or untick files you want left alone. Once you press Tidy , one click on Undo puts everything back. The laziest part is Sleep mode : switch it on, close the window, and the app quietly tidies your Downloads folder in the background, only touching files you have left alone for a few minutes. Every automatic tidy shows up in History, where you can undo it. It is meant for people who do not want to touch a terminal. It installs like any other program on Windows, macOS and Linux, and a guided first-run screen walks you through setting up the AI. There is no account, no subscription, and no API key. The screenshots use a folder of made-up demo files. The video walks through the Windows installer: first-run setup, scanning a folder, reviewing the plan, tidying, and undoing. You can also download the installer yourself from the latest release https://github.com/Brage1025/sloth-sorter/releases/latest , and try it safely on the sample-files https://github.com/Brage1025/sloth-sorter/tree/main/sample-files folder in the repo. It is a made-up messy folder with invoices, a scanned receipt, and a manual whose product name only appears on the last page. A lazy, private file tidier. An AI that lives on your computer reads your messy folder, renames the cryptic files, sorts everything into sensible folders, and lets you undo it all with one click. No account. No subscription. No internet needed after setup. Your files never leave your computer. The screenshots show the app in its default dark look, on a folder of made-up demo files. Light mode is one click away in Settings. Open that page, scroll to Assets , and download the file for your computer: | Your computer | Download | |---|---| | Windows 10 or 11 | Sloth-Sorter-1.0.0-win-x64.exe | | Mac with an Apple chip 2020 and newer | Sloth-Sorter-1.0.0-mac-arm64.dmg | | Mac with an Intel chip | Sloth-Sorter-1.0.0-mac-x64.dmg | | Linux | Sloth-Sorter-1.0.0-linux-x86 64.AppImage | The version number in the file name changes with each release. Don't download "Source code" unless you want to build it yourself see below . MIT licensed. The README has install steps for every system and an honest "what it can't do yet" section. The open model. Sloth Sorter runs Gemma 3 https://ai.google.dev/gemma gemma3:4b , Google's open-weight model through Ollama https://ollama.com . It is small enough for an ordinary laptop, and it can look at pictures as well as read text. The app lets you pick any other model from the Ollama library in Settings, so a better small model next month is a one-line change. The app. Electron for the window, tray icon and installers, with a plain HTML, CSS and JavaScript interface no build step, no CDN, so it works offline . The code that decides things lives in a separate folder with no Electron in it, which is what makes it testable. How a file gets classified: What real testing taught me. My first version looked fine in a mock and then did silly things on real files. A few fixes that mattered: Safety, because it touches real files. It never deletes or overwrites anything a name clash gets a 2 , only touches the top level of the chosen folder, skips hidden files and unfinished downloads, never changes a file extension, and writes every move to an undo history. The destination of every move is rebuilt from validated pieces, so a clever file name cannot escape the target folder. Testing, and what it doesn't prove. There are 28 automated tests. They run on Windows, macOS and Linux for every push, and they use a mock Ollama server instead of a real model. That checks the app's logic and safety rules, not the AI's judgement. I checked the quality of the real model's names and folders by hand on real files. The cross-platform tests were worth it: they caught a bug where files created a moment ago were skipped on Windows and macOS because of clock rounding, and a PDF that one PDF engine would not open on Windows. A file tidier has to read your files : invoices, lease letters, tax papers, receipts. That is exactly what you should not upload to someone else's server, and it is why this project only works with an open model: The honest numbers: on my computer, which has no supported graphics card, the AI takes roughly 20 seconds per text file and about a minute per photo. My first full test of 18 mixed files took around 15 minutes. That sounds slow, but it is 15 minutes I did not spend. I pressed a button and walked away. With a graphics card it is much faster, and Sleep mode makes the speed almost irrelevant, because it works in the background while you do something else. The real saving is attention. The files in my test folder were the kind I would never have renamed by hand: receipts called download 1 .png , a manual called manual.pdf , a story called asdgawgwagasdf.docx . Afterwards they were named and filed. The one thing I never had to do was decide, file by file, what to call them. I also listed the limits in the README slow on computers without a graphics card, small models can still get a name wrong, only the top level of a folder is tidied, unsigned installers . That is why the app shows you the plan first and keeps an undo history.