Description

This project is meant to fight the loneliness of the support team members, providing them an AI assistant (hopefully) capable of scraping supportconfigs in a RAG fashion, trying to answer specific questions.

Goals

  • Setup an Ollama backend, spinning one (or more??) code-focused LLMs selected by license, performance and quality of the results between:
  • Setup a Web UI for it, choosing an easily extensible and customizable option between:
  • Extend the solution in order to be able to:
    • Add ZIU/Concord shared folders to its RAG context
    • Add BZ cases, splitted in comments to its RAG context
      • A plus would be to login using the IDP portal to ghostwrAIter itself and use the same credentials to query BZ
    • Add specific packages picking them from IBS repos
      • A plus would be to login using the IDP portal to ghostwrAIter itself and use the same credentials to query IBS
      • A plus would be to desume the packages of interest and the right channel and version to be picked from the added BZ cases

Looking for hackers with the skills:

ai support

This project is part of:

Hack Week 24

Activity

  • 12 months ago: paolodepa started this project.
  • about 1 year ago: m.crivellari liked this project.
  • about 1 year ago: HvdHeuvel liked this project.
  • about 1 year ago: livdywan liked this project.
  • about 1 year ago: lthadeus liked this project.
  • about 1 year ago: paolodepa added keyword "support" to this project.
  • about 1 year ago: paolodepa added keyword "ai" to this project.
  • about 1 year ago: paolodepa originated this project.

  • Comments

    • paolodepa
      12 months ago by paolodepa | Reply

      The project soon moved to CLI, as the skills for integrating a WEB-UI are not my cup of tea :-/
      Its description and source code can be found at ghostwrAIter

      I tested the listed LLMs and also the following embedding models: mxbai-embed-large, nomic-embed-text, all-minilm.
      My impression is that the current state of the art for the really open-source llms and embedding models is not still mature and ready for production grade and that a big gap exists with the most well-known commercial product.

      Hopefully will run a refresh for the next hackweek.

    Similar Projects

    Update M2Crypto by mcepl

    There are couple of projects I work on, which need my attention and putting them to shape:

    Goal for this Hackweek

    • Put M2Crypto into better shape (most issues closed, all pull requests processed)
    • More fun to learn jujutsu
    • Play more with Gemini, how much it help (or not).
    • Perhaps, also (just slightly related), help to fix vis to work with LuaJIT, particularly to make vis-lspc working.


    AI-Powered Unit Test Automation for Agama by joseivanlopez

    The Agama project is a multi-language Linux installer that leverages the distinct strengths of several key technologies:

    • Rust: Used for the back-end services and the core HTTP API, providing performance and safety.
    • TypeScript (React/PatternFly): Powers the modern web user interface (UI), ensuring a consistent and responsive user experience.
    • Ruby: Integrates existing, robust YaST libraries (e.g., yast-storage-ng) to reuse established functionality.

    The Problem: Testing Overhead

    Developing and maintaining code across these three languages requires a significant, tedious effort in writing, reviewing, and updating unit tests for each component. This high cost of testing is a drain on developer resources and can slow down the project's evolution.

    The Solution: AI-Driven Automation

    This project aims to eliminate the manual overhead of unit testing by exploring and integrating AI-driven code generation tools. We will investigate how AI can:

    1. Automatically generate new unit tests as code is developed.
    2. Intelligently correct and update existing unit tests when the application code changes.

    By automating this crucial but monotonous task, we can free developers to focus on feature implementation and significantly improve the speed and maintainability of the Agama codebase.

    Goals

    • Proof of Concept: Successfully integrate and demonstrate an authorized AI tool (e.g., gemini-cli) to automatically generate unit tests.
    • Workflow Integration: Define and document a new unit test automation workflow that seamlessly integrates the selected AI tool into the existing Agama development pipeline.
    • Knowledge Sharing: Establish a set of best practices for using AI in code generation, sharing the learned expertise with the broader team.

    Contribution & Resources

    We are seeking contributors interested in AI-powered development and improving developer efficiency. Whether you have previous experience with code generation tools or are eager to learn, your participation is highly valuable.

    If you want to dive deep into AI for software quality, please reach out and join the effort!

    • Authorized AI Tools: Tools supported by SUSE (e.g., gemini-cli)
    • Focus Areas: Rust, TypeScript, and Ruby components within the Agama project.

    Interesting Links


    MCP Server for SCC by digitaltomm

    Description

    Provide an MCP Server implementation for customers to access data on scc.suse.com via MCP protocol. 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.

    Schema

    Goals

    We want to demonstrate a proof of concept to connect to the SCC MCP server with any AI agent, like gemini-cli, copilot or Claude desktop. Enabling the user to ask questions regarding their SCC inventory, like "When do I need to re-new my SLES subscription", "Do I have active systems running on unsupported operating systems?".

    Milestones

    [ ] Basic MCP API setup
    [ ] MCP endpoints
      [ ] Products / Repositories
      [ ] Subscriptions / Orders 
      [ ] Systems
    [ ] Document usage with VSCode Copilot, Claude Desktop, Gemini CLI
    

    Example

    Resources


    SUSE Edge Image Builder MCP by eminguez

    Description

    Based on my other hackweek project, SUSE Edge Image Builder's Json Schema I would like to build also a MCP to be able to generate EIB config files the AI way.

    Realistically I don't think I'll be able to have something consumable at the end of this hackweek but at least I would like to start exploring MCPs, the difference between an API and MCP, etc.

    Goals

    • Familiarize myself with MCPs
    • Unrealistic: Have an MCP that can generate an EIB config file

    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