The simplest way to publish your Logseq graph online

Exporting a Logseq graph into a shareable, navigable website is far simpler than relying on GitHub workflows: the workflow hinges on exporting “public pages” from Logseq, then deploying the resulting static folder to a hosting service like Netlify. The payoff is immediate—anyone can browse and search the graph’s content through an interactive, Logseq-style interface, without being able to edit it.

The process starts with configuring what shows up on the site. In Logseq, the homepage and sidebar labels are controlled via the config file. By editing settings such as “default home” and “page home” (including the line that defines the homepage name and the sidebar name), the exported site will open to the intended landing page rather than the default Daily Journal. The transcript also notes that the homepage can be set by specifying the desired page name in the config, which then becomes the page the website loads.

Next comes the export step. From the graph’s three-dots menu, choosing “export public pages” produces a folder containing the static site assets. The export can be directed into a chosen directory (for example, a demo export folder). After exporting, Logseq’s editor settings must be aligned with publishing behavior—turning on “all pages public when publishing” ensures the content needed for the site is included. The exported folder structure includes items like assets, a static 404 page, and an index.html file.

Opening index.html in a browser confirms the result: the site loads the configured homepage on the left and the selected content on the right, with navigation that mirrors Logseq’s browsing experience. The content is organized into pages such as “updated” and “added,” presented in reverse chronological order. The transcript highlights that new features and lessons appear as separate pages, and that content discovery works through search-like navigation (including Ctrl+K) and through query/tag-based browsing—such as listing pages tagged with “queries” or selecting a tag like “tags versus backlinks” to jump directly to the relevant lesson.

Finally, the static folder is deployed to the internet. The approach described avoids GitHub entirely and instead uses Netlify for manual deploys. After logging into Netlify and creating a site, the user selects “deploy manually” and uploads the exported folder via drag-and-drop. Once deployed, the graph becomes accessible at a public URL, and a custom domain can redirect visitors to the Netlify-hosted site. The end result is a “quick and dirty” publishing method for wikis or knowledge bases where others need read-only access to the same interactive navigation they would have inside Logseq—without editing privileges.