Project overview
Logseq is an open-source knowledge management and collaboration platform focused on privacy, longevity and user control. It provides note organization, PDF annotation and task management, supports file formats including Markdown and Org-mode, and offers plugins and themes to extend workflows and appearance. The repository lists Clojure as its primary language and AGPL-3.0 as its license.
Use cases
Students can use Logseq to organize study notes and annotate PDFs. In work settings, it can support recording ideas, organizing project material and managing tasks. Users who want to adjust their workflows through plugins and themes can also explore its extension ecosystem.
The database version introduces DB graphs, a new form of knowledge base, and RTC real-time collaboration for syncing graphs across devices or collaborating with others. The README labels the database version as beta and its new mobile app and RTC as alpha. Data loss is possible, so important material should not be used directly for experimentation.
What it does and problems it solves
Logseq helps users organize ideas and material by structuring notes. PDF annotation supports recording observations while reading, and task management supports tracking to-do items. Markdown and Org-mode support provides different text-format options, while plugins and themes extend functionality and adjust appearance.
RTC in the database version addresses cross-device synchronization and collaboration needs, but its testing status makes backups particularly important.
How to use
1. After installation, launch Logseq and start writing notes. This is the basic getting-started workflow provided by the README.
2. For detailed instructions on organizing notes, annotating PDFs or managing tasks, open Documentation or FAQ from the original repository below. The supplied README does not provide step-by-step instructions for these features.
3. To try the database version, find the web trial entry in the original repository's Database Version section, or obtain a desktop test build as described in the installation section.
4. When testing the database version, follow the README's recommendation to create a dedicated test graph and choose a noncritical project. Consult its instructions for automated backups or regular SQLite database backups. The same section provides participation entries for the new mobile app and RTC alpha tests.
Installation
1. Open the Download or Releases entry from the original repository below to obtain the latest version. The README's basic installation flow is to download, install on your device and launch the application, but it does not provide screen-by-screen instructions for each operating system.
2. Linux users can find an automated installer script in the original repository's How can I use it? section. The README also provides options for installing a specific version and installing for the current user without administrator privileges. Obtain the exact commands from the original repository.
3. To try the database desktop version, open the release page marked nightly from the original repository and download the artifact for your operating system. This route is for testing the database version and should be used with the testing risks and backup guidance described above in mind.
4. To build from source, consult the repository's development guides: `docs/develop-logseq.md` for macOS/Linux and `docs/develop-logseq-on-windows.md` for Windows. The README identifies `test/db` as the more stable, slower-updating branch and `master` as the faster-updating branch with potentially more bugs. The supplied material does not list complete dependencies or build commands, so consult the relevant guide for those details.
Source and usage notes
- Original repository: https://github.com/logseq/logseq
- Source revision: 408198a4feba58788e9163b35ae5f44aca9451d3
This listing links to the upstream repository. It does not provide a verified download package, and the complete workflow has not been independently validated.
This description was organized and translated with AI from public upstream material. Refer to the original repository for capabilities, setup requirements, costs, and license terms. 
