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Archivy is a self-hostable knowledge repository that allows you to learn and retain information in your own personal and extensible wiki.

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Archivy

Archivy is a self-hostable knowledge repository that allows you to learn and retain information in your own personal and extensible wiki.

Features:

  • If you add bookmarks, their web-pages contents' will be saved to ensure that you will always have access to it, following the idea of digital preservation. Archivy is also easily integrated with other services and your online accounts.
  • Knowledge base organization with bidirectional links between notes, and embedded tags.
  • Everything is a file! For ease of access and editing, all the content is stored in extended markdown files with yaml front matter. This format supports footnotes, LaTeX math rendering, syntax highlighting and more.
  • Extensible plugin system and API for power users to take control of their knowledge process
  • syncing options
  • Powerful and advanced search.
  • Image upload

demo video

Roadmap

Upcoming:

  • Annotations
  • Multi User System with permission setup.

Quickstart

Install archivy with pip install archivy. Other installations methods are listed here, including Docker.

Run the archivy init command to setup you installation.

Then run this and enter a password to create a new user:

$ archivy create-admin <username>

Finally, execute archivy run to serve the app. You can open it at https://localhost:5000 and login with the credentials you entered before.

You can then use archivy to create notes, bookmarks and then organize and store information.

See the official docs for information on other installation methods.

Community

Archivy is dedicated to building open and quality knowledge base software through collaboration and community discussion.

To get news and updates on Archivy and its development, you can watch the archivy repository or follow @uzpg_ on Twitter.

You can interact with us through the issue board and the more casual discord server.

Note: If you're interested in the applications of AI to knowledge management, we're also working on this with Espial.