ARahim3/DigUp

选用指南

AI 根据 README 整理 · 2026/10/11 14:56:16

适用场景

适用于需要根据文件内容（如视频中的画面、播客中的话题、PDF中的条款、照片中的物体）而非文件名来查找文件的场景，支持跨语言搜索。

查看 README 依据

<p align="center"><img src="docs/demo.gif" width="800" alt="DigUp's search panel finding a zebra in a video, a podcast moment, a clause in a lease, a dog on the beach in English, Bengali and Arabic, and code that opens in Zed"></p> 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 comfortably on a laptop. DigUp brings that to the files on your Mac. 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. All of it happens on your Mac. ## What you can find - "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, with the words marked - "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, document text

目标用户

面向 Mac 用户，特别是需要高效检索本地大量多媒体和文档文件的个人或开发者。

查看 README 依据

<p align="center"><img src="docs/logo.png" width="96" alt=""></p> <h1 align="center">DigUp</h1> <p align="center"><b>Describe it. Dig it up.</b><br> Search the files on your Mac by what's in them, with Google DeepMind's <a href="https://huggingface.co/google/embeddinggemma-2">EmbeddingGemma 2</a>.</p> <p align="center"><a href="https://github.com/ARahim3/DigUp/releases/latest"><b>Download for Mac</b></a> · Apple Silicon, macOS 14 or later · Free and open source</p>

languages, it's open (Apache 2.0), and at 740M parameters it's small enough to run comfortably on a laptop. DigUp brings that to the files on your Mac. 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. All of it happens on your Mac. ## What you can find - "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

使用方式

通过菜单栏应用使用，按 ⇧⌘Space 打开搜索面板，输入描述即可搜索；也提供命令行工具 digup 用于索引、搜索和运行评估。

查看 README 依据

2. Open it. 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. 3. Press **⇧⌘Space** in any app and describe what you're looking for. DigUp needs an Apple Silicon Mac with macOS 14 or later (it's tested on macOS 26), and it keeps itself up to date. ## Using it | Key | What it does | |---|---| | ⇧⌘Space | Opens the search panel from any app (you can change it in Settings) | | ↓ ↑ | Moves through the results |

switch to Xcode first (`sudo xcode-select -s /Applications/Xcode.app`): they lack the SwiftUI and Swift Testing macros the build needs. ```sh 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 ``` There's also a command-line tool, `.build/release/digup`, that indexes, searches and runs the evals from the terminal

部署要求

需要 Apple Silicon Mac 且 macOS 14 或更高版本；首次使用需下载约 865 MB 的模型文件。

查看 README 依据

<p align="center"><img src="docs/logo.png" width="96" alt=""></p> <h1 align="center">DigUp</h1> <p align="center"><b>Describe it. Dig it up.</b><br> Search the files on your Mac by what's in them, with Google DeepMind's <a href="https://huggingface.co/google/embeddinggemma-2">EmbeddingGemma 2</a>.</p> <p align="center"><a href="https://github.com/ARahim3/DigUp/releases/latest"><b>Download for Mac</b></a> · Apple Silicon, macOS 14 or later · Free and open source</p>

2. Open it. 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. 3. Press **⇧⌘Space** in any app and describe what you're looking for. DigUp needs an Apple Silicon Mac with macOS 14 or later (it's tested on macOS 26), and it keeps itself up to date. ## Using it | Key | What it does | |---|---| | ⇧⌘Space | Opens the search panel from any app (you can change it in Settings) | | ↓ ↑ | Moves through the results |

已知限制

模型在部分语言上表现可能不均衡；屏幕截图中的文字识别仅支持约 25 种语言，且中文、日文、泰文等无空格语言无法按词拆分。

查看 README 依据

**Will it slow my Mac 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: inside

screenshots they're read 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?** 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. ## Thanks DigUp is built on [EmbeddingGemma 2](https://huggingface.co/google/embeddinggemma-2) by Google DeepMind (Apache 2.0),