Improve OpenStack documentation and tools used by it.
Major idea: Improve openSUSE documentation Patches sent upstream:
- Dependency checking of modified files
- Remove obsolete file
- Add package info, make guide openSUSE version independent
- Improve output of test.py
- Add package info, make guide openSUSE version independent
- Number chapters and appendix for Install Guide
- ...
Blog posts:
- http://jaegerandi.blogspot.de/2013/10/improving-openstack-documentation-build.html
- http://jaegerandi.blogspot.de/2013/10/easily-read-locally-build-openstack.html
The guides at docs.openstack.org/trunk have been improved, especially the openSUSE Install Guide. Note that the Install Guide is undergoing heavy editing for the Havana release.
This project is part of:
Hack Week 10
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Bring to Cockpit + System Roles capabilities from YAST by miguelpc
Bring to Cockpit + System Roles features from YAST
Cockpit and System Roles have been added to SLES 16 There are several capabilities in YAST that are not yet present in Cockpit and System Roles We will follow the principle of "automate first, UI later" being System Roles the automation component and Cockpit the UI one.
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The idea is to implement service configuration in System Roles and then add an UI to manage these in Cockpit. For some capabilities it will be required to have an specific Cockpit Module as they will interact with a reasource already configured.
Resources
A plan on capabilities missing and suggested implementation is available here: https://docs.google.com/spreadsheets/d/1ZhX-Ip9MKJNeKSYV3bSZG4Qc5giuY7XSV0U61Ecu9lo/edit
Linux System Roles:
- https://linux-system-roles.github.io/
- https://build.opensuse.org/package/show/openSUSE:Factory/ansible-linux-system-roles Package on sle16 ansible-linux-system-roles
First meeting Hackweek catchup
- Monday, December 1 · 11:00 – 12:00
- Time zone: Europe/Madrid
- Google Meet link: https://meet.google.com/rrc-kqch-hca
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Contrastive Language-Audio Pretraining (CLAP) is an open-source library that enables the training of a neural network on both Audio and Text descriptions, making it possible to search for Audio using a Text input. Several pre-trained models for song search are already available on huggingface
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You can have a look at the result here:
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