Describe it. Dig it up.
Search the files on your computer by what's in them, with Google DeepMind's EmbeddingGemma 2.

Download for Mac · Windows (beta) · Linux (beta)
_{Free and open source. Everything runs on your computer.}

EmbeddingGemma 2 is the multimodal embedding model Google DeepMind released in October 2026. It puts text, images, audio and video into one shared space: a photo of a dog on a beach lands next to the words "a dog on the beach", and a recording of someone talking about sleep lands next to "where they talk about sleep". It understands more than 100 languages, it's open (Apache 2.0), and at 740M parameters it's small enough to run on a laptop.

DigUp brings that to the files on your computer, on a Mac, on Windows or on Linux. Pick the folders to search, and it reads the pictures, PDFs, documents, recordings and videos in them. Then describe what you're looking for, in your own words, and it finds the match, whatever kind of file it is.

• "zebra in a video" opens the clip at the moment the zebra shows up
• "where they talk about sleep" jumps to that minute of a podcast
• "the clause about pets in the lease" shows the PDF page
• "a dog on the beach" finds the photo, and "payment declined error" the screenshot
• a search in English can find a note written in Bengali, Arabic or any of the model's 100+ languages, and the other way around
• "code: retry a failed call with backoff" finds the function in your projects, if you turn on code search

Exact words count too. Invoice numbers, error codes and names are matched as written, in file names and document text, so a search gets both the meaning and the exact string. On a Mac that includes the text inside screenshots.

Nothing you index leaves your computer. DigUp goes online only to download the model once and to check for updates once a day. The update check sends nothing about your files, and you can turn it off. No account, no telemetry.

Mac. Download the DMG from Releases and drag DigUp to Applications, or use Homebrew: brew install --cask arahim3/tap/digup. It needs an Apple Silicon Mac with macOS 14 or later.

Windows. Download DigUp_x.y.z_x64-setup.exe from the beta release and run it. It installs for you only, with no admin rights. Windows may say it doesn't recognize the app, because the installer isn't signed yet: choose More info, then Run anyway. It needs 64-bit Windows 10 or 11.

Linux. On Ubuntu, Debian, Mint and the like, download the .deb and install it:

sudo apt install ./DigUp_x.y.z_amd64.deb

The package is called dig-up, because Debian already has an unrelated digup. Anywhere else, download the AppImage, make it executable and run it. Both are for 64-bit Intel and AMD processors and work on Ubuntu 22.04, Debian 12, Mint 21 and newer.

Then, on any of them:

1. Open DigUp. While the model downloads (865 MB, once), pick the folders to search: whole folders, or only some of their subfolders. DigUp shows how long the first pass will take for each, measured on your computer.
2. Press the shortcut in any app and describe what you're looking for: ⇧⌘Space on a Mac, Ctrl+Shift+Space on Windows and Linux.

DigUp keeps itself up to date: the Mac app, the Windows installer and the AppImage install updates with one click. With the .deb, DigUp tells you when there's a new version and opens its release page.

DigUp lives in the menu bar on a Mac and in the tray on Windows and Linux, where you can see how indexing is going, pause it, or open Settings. Opening it from the Start menu or your app list shows the search window.

A few things differ by system:

• On a Mac, a video opens at its moment in QuickTime Player (macOS asks once whether DigUp may control it) or IINA, and a PDF opens in Preview with your words in its search. On Windows and Linux, PDFs open at the page in your PDF viewer if it's one that can be told a page (Edge, Chrome, Firefox, Acrobat, SumatraPDF, Evince, Okular), and recordings and videos at the moment in VLC, mpv or MPC-HC. Other apps open the file from the start; the big preview plays it from the moment either way.
• On GNOME and KDE under Wayland, which don't let apps set their own shortcuts, DigUp adds Ctrl+Shift+Space to the desktop's keyboard settings during setup, and you change it there. On other Wayland desktops, Settings shows the command to give a shortcut of your own.
• On GNOME, the tray icon needs the AppIndicator extension, which Ubuntu includes. Without it, the window's ⋯ menu has the same items.

Only the folders you choose:

• pictures and screenshots (JPEG, PNG, HEIC, WebP and more), by what they show, and on a Mac screenshots by their text too
• PDFs, page by page, scans included. A long one gets its first 30 pages right away and the rest once everything else is in (up to 5,000 pages a file)
• documents: txt, md, typ, rtf, docx, odt, html, and on a Mac doc, long ones the same way. Text that's mostly numbers, like a data export, is matched by its exact text only
• spreadsheets and presentations: xlsx, ods, pptx and odp, read for their text: each sheet's name and rows, each slide's text and speaker notes
• audio of any length: the model listens to 30 seconds at a time, so DigUp takes overlapping 30-second windows and a match points to its moment
• video of any length: a frame every few seconds, one per shot, plus the soundtrack the same way as audio

Outside the folders you pick for code search, it never reads code, and inside a code project (a folder with .git, package.json and the like) it reads only screenshots. It never reads keys, certificates, password files, hidden folders like .ssh, apps or caches. It skips folders that look like datasets, and never downloads files that only live in the cloud (iCloud on a Mac, OneDrive on Windows). You can skip more folders or file types in Settings. DigUp only reads your files; it never changes, moves or uploads them.

The first pass happens once. On a Mac it takes a few minutes for a few hundred files and can take an hour for a big Downloads folder. On Windows and Linux, DigUp runs the model on the graphics card where that's faster and on the processor otherwise; on a processor alone a picture takes a few seconds (about five on a 2017 laptop's Core i5), so a large photo library can take hours, which is why setup shows the time first. After that, a new file is searchable a few seconds after it lands.

EmbeddingGemma 2 reads code too, so DigUp can search your projects. Code search is off until you turn it on, in Settings → Code or during setup, for the folders you pick. Each repo shows how long reading it takes and how much room its index needs. Then start a search with code: and say what the code does, or type a name that's in it:

• "code: retry a failed call with backoff" finds the function, whatever it's called
• "code: refreshAccessToken" goes to the line that defines it, not the places that call it
• "code: plot how many examples each class has" finds the notebook cell

Results open in your editor at the line: Zed, VS Code, Cursor, Sublime Text, JetBrains IDEs and a few more, Xcode on a Mac and Notepad++ on Windows (pick one in Settings). Code has an index of its own and never shows up in other searches. DigUp reads source files, notebooks (without their outputs) and a repo's own docs. It skips what git ignores, vendored and generated code, data files, and anything that looks like a key or a password. While you're working on code, the index catches up a minute after things go quiet.

On a Mac, reading code takes about 20 seconds for a small app, and about 20 minutes and 130 MB of index for all of llama.cpp.

your folders ─► readers that turn files into pictures, text and sound
             ─► EmbeddingGemma 2 on llama.cpp, in a helper process that quits when it's done
             ─► one SQLite file: a vector for every picture, page, passage, video frame and 30 s of sound,
                plus a keyword index (code search keeps a second one, for code)
your words   ─► the same model's text part (~250 MB, only while you search) ─► nearest vectors + exact words

DigUp runs ggml-org's 8-bit build of EmbeddingGemma 2 through llama.cpp: on the Mac's GPU with Metal, and on Windows and Linux on the GPU with Vulkan when a quick check at setup finds it faster than the processor and getting the same results. Every vector lives in the same 768-dimensional space, which is why one query can rank a video frame against a PDF page. A search embeds your words in milliseconds and compares them with everything in the index. Exact-word matches get a boost, because no embedding holds an invoice number exactly.

The search engine is the same Swift code on every system. On a Mac it reads files with macOS's own frameworks (ImageIO, PDFKit, AVFoundation, and Vision for the text in screenshots) and the app is SwiftUI. On Windows and Linux it reads them with PDFium, ffmpeg, stb and miniz, and the app around it is built with Tauri.

The index remembers which model version made its vectors. An update that leaves the vectors unchanged keeps your index, and a test checks every llama.cpp update against stored reference vectors before it ships.

On a Mac you'll need Xcode 26, git, and CMake (or uv) for llama.cpp. If xcode-select -p shows the Command Line Tools, switch to Xcode first (sudo xcode-select -s /Applications/Xcode.app): they lack the SwiftUI and Swift Testing macros the build needs.

git clone https://github.com/ARahim3/DigUp && cd DigUp
scripts/build-llama.sh            # llama.cpp at a pinned tag, with a one-line patch (a few minutes)
swift build -c release && swift test
./build.sh                        # → build.noindex/DigUp.app

On Windows and Linux you'll need Swift 6.4, Rust and Node; on Windows also Visual Studio's C++ build tools, with the commands run in Git for Windows' bash. scripts/fetch-vendor.sh and scripts/build-llama.sh get the libraries, then scripts/package-linux.sh makes the .deb and the AppImage, and scripts/package-windows.sh the installer. The packages workflow has every step, down to the packages each system needs.

There's also a command-line tool, .build/release/digup, that indexes, searches and runs the evals from the terminal (digup --help). scripts/make-testbed.sh builds a folder of test files to try it on on a Mac (it needs ffmpeg), and evals/ holds the queries ranking changes are measured with.

How is this different from Spotlight or Windows Search? They find files by their names, text and metadata. DigUp also finds them by what they show or say, and takes you to the page or moment. They work fine side by side.

What's different on Windows and Linux? The search is the same: the same model, the same results. Two things are missing for now. The text inside screenshots isn't read yet, so a screenshot is found by what it shows rather than by an exact code typed into the search. And doc files from old Word versions, RAW photos and SVG pictures are only read on a Mac.

Why is the download 865 MB? That's the model: the text part (310 MB) and the image and audio encoders (555 MB). The app itself is about 20 MB on a Mac, and on Windows and Linux 40 to 140 MB depending on the package, since those carry their own PDF, video and image readers.

Will it slow my computer down? Only the first pass is heavy. After that it reads new files only. The model runs in a separate process that quits when it's done, and the search side only loads while you're searching.

Which languages? The model knows more than 100, and DigUp searches in all of them, across languages too. The evals cover only English, Bengali and Arabic because those are the languages of the files DigUp was tested on, and Google notes that the model isn't equally strong in every language. Two limits apply to exact words, not to meaning: the text inside screenshots is read only on a Mac, by Apple's text recognition, which knows about 25 languages, and languages written without spaces, like Chinese, Japanese and Thai, aren't split into words.

How do I remove it? On a Mac, quit it, then delete DigUp.app and ~/Library/Application Support/DigUp, which holds the model and the indexes. Its settings are in ~/Library/Preferences/com.abdurrahim.DigUp.plist. With Homebrew, brew uninstall --cask --zap digup removes all of it. On Windows, uninstall it in Settings → Apps; tick "Delete the application data" to remove the model and the index too. On Linux, sudo apt remove dig-up (or delete the AppImage), then delete ~/.local/share/digup (the model and the index), ~/.config/com.abdurrahim.DigUp, ~/.local/share/com.abdurrahim.DigUp and, if it opened at login, ~/.config/autostart/DigUp.desktop. On GNOME, also remove its shortcut in Settings → Keyboard.

DigUp is free and open source, and it stays that way. If it helps you and you'd like to support it, you can buy me a coffee.

DigUp is built on EmbeddingGemma 2 by Google DeepMind (Apache 2.0) and llama.cpp (MIT). The Mac app uses Sparkle (MIT) for updates. The Windows and Linux app is built with Tauri (MIT or Apache 2.0) and reads files with PDFium (BSD), FFmpeg (LGPL), stb (public domain) and miniz (MIT). Their license notices ship with the app.

DigUp isn't affiliated with Google, Apple or Microsoft. Gemma is a trademark of Google LLC; Mac and Spotlight are trademarks of Apple Inc.; Windows is a trademark of Microsoft Corporation.

MIT