Downloads video and audio content from hundreds of websites with built in compression and playlist support.

ytDownloader is an open-source desktop app that provides a graphical interface for downloading video and audio content. It supports a wide range of platforms including YouTube, Facebook, Instagram, TikTok, and Twitter. The application is designed for users who want to archive web media or extract audio from streaming sites without interacting with a command line interface.
On Windows, the software can be installed via exe or msi files, or through package managers like Chocolatey, Scoop, and Winget. Linux users have several distribution options, including Flatpak, AppImage, and Snap, with Flatpak being the recommended method. macOS installation requires the manual removal of the quarantine attribute via the terminal and the installation of yt-dlp through Homebrew to function correctly.
The application is built using Electron and Node.js, utilizing yt-dlp and ffmpeg for the underlying processing, downloading, and conversion tasks. This architecture allows the software to maintain compatibility across different operating systems while leveraging the extensive site support of the yt-dlp backend. It includes a comprehensive localization system managed through Crowdin, offering support for over twenty languages including Arabic, Chinese, French, German, and Spanish. This makes the tool accessible to a global audience of creators and archivists.
For those who prefer to build from source, the project requires Node.js and npm. The build process generates platform-specific packages for Linux, Windows, and macOS, provided that ffmpeg is present in the root directory of the project. This flexibility allows developers to customize the build or contribute to the codebase.
It serves as a cross-platform utility for archiving web media and compressing video files.
Back up, organize, and browse personal photo and video libraries on a self-hosted server without cloud access.
Self-hosted photo and video management application using machine learning for automatic tagging and face recognition.
Join our newsletter to get shiny new open source software delivered to your inbox. Unsubscribe anytime.