AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
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尚未偵測到更新。GitHub 發布版本後會顯示在這裡。
個人 GitHub 帳號下公開儲存庫的擁有者可以登入並驗證所有權,自行管理介紹,無需管理員核准。
登入並產生驗證檔案,在 30 分鐘內將其提交至此儲存庫的預設分支。其他分支或分叉儲存庫中的檔案無效。然後在下方檢查檔案,即可無需管理員核准直接管理專案。請保留檔案以維持管理權限。
如需登入,將前往登入頁面。登入後請回到此處,再次點擊所選的驗證按鈕。
在專案資料夾中執行 /nomorevibe verify,即可驗證所有權並自行管理介紹。
一分鐘完成驗證The official website's repository for the Snap store
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取自儲存庫 README
正在載入完整 README。
檢視完整 README ↗Snaps are applications packaged with all their dependencies to run on all popular Linux distributions from a single build. They update automatically and roll back gracefully. This repo is the application for the snapcraft.io website.
If you are interested in Snaps, Snapping and Snapcraft, there is an active discourse forum that we encourage developers to join.
The site is largely maintained by the Web and Design team at Canonical. It is a stateless website project based on Flask and hosted on a Charmed Kubernetes cluster.
If you have found a bug on the site or have an idea for a new feature, feel free to create a new issue, or suggest a fix by creating a pull request. You can also find a link to create issues in the footer of every page of the site itself.
If you have found a bug elsewhere in the snap world:
snap info and use the contact information to find where you can get help.The simplest way to run the site locally is using dotrun:
dotrun
Once the server has started, you can visit http://127.0.0.1:8004 in your browser. You stop the server using <ctrl>+c.
If you're running dotrun on macOS or Windows, you will have to use a different command to launch dotrun with an additional argument in order to get JavaScript code working:
dotrun -p 5004:5004
For more detailed local development instructions, see HACKING.md.
Another development tool you can use to run this project is Workshop. Launch the Workshop by running
workshop launch # you only need to do this the first time
and start the server with
workshop run start
Workshop depends on LXD, which is only available on Linux. If you're running macOS or Windows, you can use Workshop inside a
MultipassVM. Beware: this setup is even more experimental and you might encounter strange issues. Configure Multipass to use the VirtualBox virtualization driver and allocate at least 4GB RAM and 10GB disk for the VM; after setting up the workshop in the VM, enable port forwarding for ports 8004 and 5004.
The content of this project is licensed under the Creative Commons Attribution-ShareAlike 4.0 International license, and the underlying code used to format and display that content is licensed under the LGPLv3 by Canonical Ltd.
With ♥ from Canonical