pudc - A PID 1 process that barks to the internet by mssola

Description

As a fun exercise in order to dig deeper into the Linux kernel, its interfaces, the RISC-V architecture, and all the dragons in between; I'm building a blog site cooked like this:

• The backend is written in a mixture of C and RISC-V assembly.
• The backend is actually PID1 (for real, not within a container).
• We poll and parse incoming HTTP requests ourselves.
• The frontend is a mere HTML page with htmx.

The project is meant to be Linux-specific, so I'm going to use io_uring, pidfs, namespaces, and Linux-specific features in order to drive all of this.

I'm open for suggestions and so on, but this is meant to be a solo project, as this is more of a learning exercise for me than anything else.

Goals

• Have a better understanding of different Linux features from user space down to the kernel internals.
• Most importantly: have fun.

Resources

• https://github.com/mssola/pudc

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x64id: An x86/x64 instruction disassembler by m.crivellari

Description

This is an old side project. An x86/x64 machine code decoder. It is useful to get instructions' length and identify each of its fields.

Example:

C7 85 68 FF FF FF 00 00 00 00

This is the instruction:

MOV DWORD PTR SS:[LOCAL.38],0

What follows are some of the information collected by the disassembler, based on the specific instruction:

RAW bytes (hex): C7 85 68 FF FF FF 00 00 00 00
Instr. length: 10
Print instruction fields:
        Located Prefixes 0:

        OP: 0xC7
        mod_reg_rm: 0x85
        disp (4): 0xFFFFFF68
        Iimm: 0x0

Lacks the mnemonic representation: from the previous machine code is not able to produce the "MOV..." instruction, for example.

Goals

The goal is almost easy: partially implement the mnemonic representation. I have already started during the weekend, likely tomorrow I will push the branch!

Resources

• The project: https://github.com/DispatchCode/x64-Instruction-Decoder/
• This is useful to avoid gdb and objdump in local: https://defuse.ca/online-x86-assembler.htm
• Another interesting resource is https://godbolt.org/

Progress

• An initial implementation can be found at: https://github.com/DispatchCode/x64-Instruction-Decoder/tree/mnemonic-support It is described under the "Mnemonic translation" in the README file!

Let's consider this example:

[...other bytes...] 43 89 44 B5 00 01 00 [...other bytes...]

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Smart lighting with Pico 2 by jmodak

Description

I am trying to create a smart-lighting project with a Raspberry Pi Pico that reacts to a movie's visuals and audio that involves combining two distinct functions: ambient screen lighting(visual response) and sound-reactive lighting(audio response)

Goals

• Visuals: Capturing the screen's colour requires an external device to analyse screen content and send colour data to the MCU via serial communication.
• Audio: A sound sensor module connected directly to the Pico that can detect sound volume.
• Pico 2W: The MCU receives data fro, both inputs and controls an LED strip.

Resources

• Raspberry Pi Pico 2 W
• RGB LED strip
• Sound detecting sensor
• Power supply
• breadboard and wires

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Port OTPClient to GTK >= 4.18 by pstivanin

Project Description

OTPClient is currently using GTK3 and cannot easily be ported to GTK4. Since GTK4 came out, there have been quite some big changes. Also, there are now some new deprecation that will take effect with GTK5 (and are active starting from 4.10 as warnings), so I need to think ahead and port OTPClient without using any of those deprecated features.

Goal for this Hackweek

• fix the last 3 opened issues (https://github.com/paolostivanin/OTPClient/issues/402, https://github.com/paolostivanin/OTPClient/issues/404, https://github.com/paolostivanin/OTPClient/issues/406) and release a new version
• continue the rewrite from where we left last year
• if possible, finally close this 6 years old issue: https://github.com/paolostivanin/OTPClient/issues/123

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Improve the picotm Transaction Manager by tdz

Picotm is a system-level transaction manager. It provides transactional semantics to low-level C operations, such as

• memory access,
• modifying data structures,
• (some) file I/O, and
• common interfaces from the C Standard Library and POSIX.

Picotm also handles error detection and recovery for all it's functionality. It's fully modular, so new functionality can be added.

For the Hackweek, I want to dedicate some time to picotm. I want to finish some of the refactoring work that I have been working on. If there's time left, I'd like to investigate two-phase commits and how to support them in picotm.

Picotm is available at http://picotm.org/.

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OS self documentation, health check and troubleshooting by roseswe

Project Description

The aim of this hackweek project is to improve the utility "cfg2html" so that it is even more usable under SLES and perhaps also under Rancher.

cfg2html (see also https://github.com/cfg2html/cfg2html) itself is a very mature utility for collecting and documenting information of an operating system like Linux, AIX, HP-UX and others.

Goal for this Hackweek

The aim is to extend cfg2html

• for SLES and SLES-for-SAP apps, high availability
• Improve code for MicroOS 5.x, SUMA, Edge and k8s environments
• fix shellbeauity warnings
• possibly add more plugins
• SUMA/Salt integration to collect.

Resources

Required skills: Bash, shell script and the SUSE products mentioned.

https://github.com/cfg2html/cfg2html

https://www.cfg2html.com/

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Update M2Crypto by mcepl

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

• M2Crypto

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.

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Song Search with CLAP by gcolangiuli

Description

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

Goals

Evaluate how CLAP can be used for song searching and determine which types of queries yield the best results by developing a Minimum Viable Product (MVP) in Python. Based on the results of this MVP, future steps could include:

• Music Tagging;
• Free text search;
• Integration with an LLM (for example, with MCP or the OpenAI API) for music suggestions based on your own library.

The code for this project will be entirely written using AI to better explore and demonstrate AI capabilities.

Result

In this MVP we implemented:

• Async Song Analysis with Clap model
• Free Text Search of the songs
• Similar song search based on vector representation
• Containerised version with web interface

We also documented what went well and what can be improved in the use of AI.

You can have a look at the result here:

• Result Presentation
• hw25-song-search Github repo

Future implementation can be related to performance improvement and stability of the analysis.

References

• CLAP: The main model being researched;
• huggingface: Pre-trained models for CLAP;
• Free Music Archive: Creative Commons songs that can be used for testing;

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Improvements to osc (especially with regards to the Git workflow) by mcepl

Description

There is plenty of hacking on osc, where we could spent some fun time. I would like to see a solution for https://github.com/openSUSE/osc/issues/2006 (which is sufficiently non-serious, that it could be part of HackWeek project).

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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.

Goals

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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Liz - Prompt autocomplete by ftorchia

Description

Liz is the Rancher AI assistant for cluster operations.

Goals

We want to help users when sending new messages to Liz, by adding an autocomplete feature to complete their requests based on the context.

Example:

• User prompt: "Can you show me the list of p"
• Autocomplete suggestion: "Can you show me the list of p...od in local cluster?"

Example:

• User prompt: "Show me the logs of #rancher-"
• Chat console: It shows a drop-down widget, next to the # character, with the list of available pod names starting with "rancher-".

Technical Overview

1. The AI agent should expose a new ws/autocomplete endpoint to proxy autocomplete messages to the LLM.
2. The UI extension should be able to display prompt suggestions and allow users to apply the autocomplete to the Prompt via keyboard shortcuts.

Resources

GitHub repository

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