4 projects for "api wiki" with 2 filters applied:

  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

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    Ship Agents Faster

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  • 1
    A SSH based chatroom framework; inspired by "ssh-chat" project. This framework support not only the IRC-like command line interface, but also custom clients by providing an API. Unlike the public chat-room of ssh-chat, this implementation requiring all users must be authenticated by public key before starting a chat; however public chatrooms are still possible by hacking OpenSSH server, see Wiki page 'Public Chatroom' for details.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2

    SICK

    Unix and GNU/Linux terminal IRC client.

    Sick IRC Client, Kid!, or SICK for short, is a small Unix and GNU/Linux IRC client running from the terminal, written in pure Python. The entire project is licensed under the GNU General Public License, version 2. WARNING: SICK is a WIP, don't expect the experience of a complete IRC client yet. We're working on it. Installation instructions can be found at https://github.com/Weloxux/sick/wiki/Installation ANOTHER WARNING: SourceForge doesn't always get the latest updates on time, for...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    The Floranta libraries provide components for building Rich Client Wikis using AJAX or Java. Floranta clients can be embedded in any webpage (even plain html) and allow users to leave notes, images, cards, etc on the pages. Eg: http://www.floranta.com
    Downloads: 0 This Week
    Last Update:
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  • 4
    PHIL-IP is a complet communities websites system. It's a blogs, chat, cms, forum, links, news system, photo galleries, portals, tags systems, and wiki at the same time or none of the above. It's made for collaboration and communications between users
    Downloads: 0 This Week
    Last Update:
    See Project
  • Stop vibe-debugging. Icon
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    Plug Claude into your app's actual errors.

    AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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