Project Description

The goal is to have a language model, that is able to answer technical questions on Uyuni. Uyuni documentation is too large for in-context processing, so finetuning is the way to go.

Goal for this Hackweek

Finetune a model based on llama-2-7b.

Resources

github repo

Looking for hackers with the skills:

ai uyuni

This project is part of:

Hack Week 23

Activity

  • about 2 years ago: nadvornik added keyword "ai" to this project.
  • about 2 years ago: nadvornik added keyword "uyuni" to this project.
  • about 2 years ago: nadvornik originated this project.

  • Comments

    Be the first to comment!

    Similar Projects

    Explore LLM evaluation metrics by thbertoldi

    Description

    Learn the best practices for evaluating LLM performance with an open-source framework such as DeepEval.

    Goals

    Curate the knowledge learned during practice and present it to colleagues.

    -> Maybe publish a blog post on SUSE's blog?

    Resources

    https://deepeval.com

    https://docs.pactflow.io/docs/bi-directional-contract-testing


    MCP Server for SCC by digitaltomm

    Description

    Provide an MCP Server implementation for customers to access data on scc.suse.com via MCP protocol. The core benefit of this MCP interface is that it has direct (read) access to customer data in SCC, so the AI agent gets enhanced knowledge about individual customer data, like subscriptions, orders and registered systems.

    Architecture

    Schema

    Goals

    We want to demonstrate a proof of concept to connect to the SCC MCP server with any AI agent, for example gemini-cli or codex. Enabling the user to ask questions regarding their SCC inventory.

    For this Hackweek, we target that users get proper responses to these example questions:

    • Which of my currently active systems are running products that are out of support?
    • Do I have ready to use registration codes for SLES?
    • What are the latest 5 released patches for SLES 15 SP6? Output as a list with release date, patch name, affected package names and fixed CVEs.
    • Which versions of kernel-default are available on SLES 15 SP6?

    Technical Notes

    Similar to the organization APIs, this can expose to customers data about their subscriptions, orders, systems and products. Authentication should be done by organization credentials, similar to what needs to be provided to RMT/MLM. Customers can connect to the SCC MCP server from their own MCP-compatible client and Large Language Model (LLM), so no third party is involved.

    Milestones

    [x] Basic MCP API setup
      MCP endpoints
      [x] Products / Repositories
      [x] Subscriptions / Orders 
      [x] Systems
      [x] Packages
    [x] Document usage with Gemini CLI, Codex
    

    Resources

    Gemini CLI setup:

    ~/.gemini/settings.json:


    Try out Neovim Plugins supporting AI Providers by enavarro_suse

    Description

    Experiment with several Neovim plugins that integrate AI model providers such as Gemini and Ollama.

    Goals

    Evaluate how these plugins enhance the development workflow, how they differ in capabilities, and how smoothly they integrate into Neovim for day-to-day coding tasks.

    Resources


    "what is it" file and directory analysis via MCP and local LLM, for console and KDE by rsimai

    Description

    Users sometimes wonder what files or directories they find on their local PC are good for. If they can't determine from the filename or metadata, there should an easy way to quickly analyze the content and at least guess the meaning. An LLM could help with that, through the use of a filesystem MCP and to-text-converters for typical file types. Ideally this is integrated into the desktop environment but works as well from a console. All data is processed locally or "on premise", no artifacts remain or leave the system.

    Goals

    • The user can run a command from the console, to check on a file or directory
    • The filemanager contains the "analyze" feature within the context menu
    • The local LLM could serve for other use cases where privacy matters

    TBD

    • Find or write capable one-shot and interactive MCP client
    • Find or write simple+secure file access MCP server
    • Create local LLM service with appropriate footprint, containerized
    • Shell command with options
    • KDE integration (Dolphin)
    • Package
    • Document

    Resources


    Docs Navigator MCP: SUSE Edition by mackenzie.techdocs

    MCP Docs Navigator: SUSE Edition

    Description

    Docs Navigator MCP: SUSE Edition is an AI-powered documentation navigator that makes finding information across SUSE, Rancher, K3s, and RKE2 documentation effortless. Built as a Model Context Protocol (MCP) server, it enables semantic search, intelligent Q&A, and documentation summarization using 100% open-source AI models (no API keys required!). The project also allows you to bring your own keys from Anthropic and Open AI for parallel processing.

    Goals

    • [ X ] Build functional MCP server with documentation tools
    • [ X ] Implement semantic search with vector embeddings
    • [ X ] Create user-friendly web interface
    • [ X ] Optimize indexing performance (parallel processing)
    • [ X ] Add SUSE branding and polish UX
    • [ X ] Stretch Goal: Add more documentation sources
    • [ X ] Stretch Goal: Implement document change detection for auto-updates

    Coming Soon!

    • Community Feedback: Test with real users and gather improvement suggestions

    Resources


    Uyuni Saltboot rework by oholecek

    Description

    When Uyuni switched over to the containerized proxies we had to abandon salt based saltboot infrastructure we had before. Uyuni already had integration with a Cobbler provisioning server and saltboot infra was re-implemented on top of this Cobbler integration.

    What was not obvious from the start was that Cobbler, having all it's features, woefully slow when dealing with saltboot size environments. We did some improvements in performance, introduced transactions, and generally tried to make this setup usable. However the underlying slowness remained.

    Goals

    This project is not something trying to invent new things, it is just finally implementing saltboot infrastructure directly with the Uyuni server core.

    Instead of generating grub and pxelinux configurations by Cobbler for all thousands of systems and branches, we will provide a GET access point to retrieve grub or pxelinux file during the boot:

    /saltboot/group/grub/$fqdn and similar for systems /saltboot/system/grub/$mac

    Next we adapt our tftpd translator to query these points when asked for default or mac based config.

    Lastly similar thing needs to be done on our apache server when HTTP UEFI boot is used.

    Resources


    Set Uyuni to manage edge clusters at scale by RDiasMateus

    Description

    Prepare a Poc on how to use MLM to manage edge clusters. Those cluster are normally equal across each location, and we have a large number of them.

    The goal is to produce a set of sets/best practices/scripts to help users manage this kind of setup.

    Goals

    step 1: Manual set-up

    Goal: Have a running application in k3s and be able to update it using System Update Controler (SUC)

    • Deploy Micro 6.2 machine
    • Deploy k3s - single node

      • https://docs.k3s.io/quick-start
    • Build/find a simple web application (static page)

      • Build/find a helmchart to deploy the application
    • Deploy the application on the k3s cluster

    • Install App updates through helm update

    • Install OS updates using MLM

    step 2: Automate day 1

    Goal: Trigger the application deployment and update from MLM

    • Salt states For application (with static data)
      • Deploy the application helmchart, if not present
      • install app updates through helmchart parameters
    • Link it to GIT
      • Define how to link the state to the machines (based in some pillar data? Using configuration channels by importing the state? Naming convention?)
      • Use git update to trigger helmchart app update
    • Recurrent state applying configuration channel?

    step 3: Multi-node cluster

    Goal: Use SUC to update a multi-node cluster.

    • Create a multi-node cluster
    • Deploy application
      • call the helm update/install only on control plane?
    • Install App updates through helm update
    • Prepare a SUC for OS update (k3s also? How?)
      • https://github.com/rancher/system-upgrade-controller
      • https://documentation.suse.com/cloudnative/k3s/latest/en/upgrades/automated.html
      • Update/deploy the SUC?
      • Update/deploy the SUC CRD with the update procedure


    Ansible to Salt integration by vizhestkov

    Description

    We already have initial integration of Ansible in Salt with the possibility to run playbooks from the salt-master on the salt-minion used as an Ansible Control node.

    In this project I want to check if it possible to make Ansible working on the transport of Salt. Basically run playbooks with Ansible through existing established Salt (ZeroMQ) transport and not using ssh at all.

    Goals

    • [v] Prepare the testing environment with Salt and Ansible installed
    • [v] Discover Ansible codebase to figure out possible ways of integration
    • [v] Create Salt/Uyuni inventory module
    • [v] Make basic modules to work with no using separate ssh connection, but reusing existing Salt connection
    • [v] Test some most basic playbooks

    Resources

    GitHub page

    Video of the demo


    Move Uyuni Test Framework from Selenium to Playwright + AI by oscar-barrios

    Description

    This project aims to migrate the existing Uyuni Test Framework from Selenium to Playwright. The move will improve the stability, speed, and maintainability of our end-to-end tests by leveraging Playwright's modern features. We'll be rewriting the current Selenium code in Ruby to Playwright code in TypeScript, which includes updating the test framework runner, step definitions, and configurations. This is also necessary because we're moving from Cucumber Ruby to CucumberJS.

    If you're still curious about the AI in the title, it was just a way to grab your attention. Thanks for your understanding.

    Nah, let's be honest add-emoji AI helped a lot to vibe code a good part of the Ruby methods of the Test framework, moving them to Typescript, along with the migration from Capybara to Playwright. I've been using "Cline" as plugin for WebStorm IDE, using Gemini API behind it.


    Goals

    • Migrate Core tests including Onboarding of clients
    • Improve test reliabillity: Measure and confirm a significant reduction of flakiness.
    • Implement a robust framework: Establish a well-structured and reusable Playwright test framework using the CucumberJS

    Resources


    Uyuni Health-check Grafana AI Troubleshooter by ygutierrez

    Description

    This project explores the feasibility of using the open-source Grafana LLM plugin to enhance the Uyuni Health-check tool with LLM capabilities. The idea is to integrate a chat-based "AI Troubleshooter" directly into existing dashboards, allowing users to ask natural-language questions about errors, anomalies, or performance issues.

    Goals

    • Investigate if and how the grafana-llm-app plug-in can be used within the Uyuni Health-check tool.
    • Investigate if this plug-in can be used to query LLMs for troubleshooting scenarios.
    • Evaluate support for local LLMs and external APIs through the plugin.
    • Evaluate if and how the Uyuni MCP server could be integrated as another source of information.

    Resources

    Grafana LMM plug-in

    Uyuni Health-check