Save pytorch models in OCI registries by jguilhermevanz

Description

A prerequisite for running applications in a cloud environment is the presence of a container registry. Another common scenario is users performing machine learning workloads in such environments. However, these types of workloads require dedicated infrastructure to run properly. We can leverage these two facts to help users save resources by storing their machine learning models in OCI registries, similar to how we handle some WebAssembly modules. This approach will save users the resources typically required for a machine learning model repository for the applications they need to run.

Goals

Allow PyTorch users to save and load machine learning models in OCI registries.

Resources

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Mortgage Plan Analyzer by RMestre

https://github.com/rjpmestre/mortgage-plan-analyzer

Project Description

Many people face challenges when trying to renegotiate their mortgages with different banks. They receive offers from multiple lenders and struggle to compare them effectively. Each proposal may have slightly different terms and data presentation, making it hard to make informed decisions. Additionally, understanding the impact of various taxes and variables can be complex. The Mortgage Plan Analyzer project aims to address these issues.

Project Overview:

The Mortgage Plan Analyzer is a web-based tool built using PHP, Laravel, Livewire, and AdminLTE/bootstrap. It provides a user-friendly platform for individuals to input basic specifications about their mortgage, adjust taxes and variables, and obtain short-term projections for each proposal. Users can also compare multiple mortgage offers side by side, enabling them to make informed decisions about their mortgage renegotiation.

Why Start This Project:

I found myself in this position and most tools I found around are either for marketing/selling purposes or not flexible enough. As i was starting getting lost in a jungle of spreadsheets i thought I could just create a tool to help me and others that may be experiencing the same struggles to provide clarity and transparency in the decision-making process.

Hackweek 25 ideas (to refine still :) )

• Euribor Trends in Projections
• - Use historical Euribor data to model optimistic and pessimistic scenarios for variable-rate loans.
• Use the annual summaries (installments, amortizations, etc) and run some analysis to highlight key differences, like short-term savings vs. long-term costs
• Financial plan can be hard/boring to follow. Create a simple viewing mode that summarizes monthly values and their annual sums.

Hackweek 24 update

• Improved summaries graphs by adding:
• - Line graph;
• - Accumulated line graph;
• - Set the range to short/mid/long term;
• - Highlight best simulation and value per year;
• Improve the general behaviour of the forms:
• - Simulations name setting;
• - Cloning simulations;
• - Adjust update timing on input changes;
• Show/Hide big tables;
• Support multi languages (added english);
• Added examples;
• Adjustments to fonts and sizes;
• Fixed loading screen;
• Dependencies adjustments;

Hackweek 23 initial release

• Developed a base site that:
• - Allows adding up to 3 simulations;
• - Create financial plans;
• - Simulations comparison graph for the first 4 years;
• Created Github project @ https://github.com/rjpmestre/mortgage-plan-analyzer ;
• Launched a demo instance using Oracle Cloud Free Tier currently @ http://138.3.251.182/

Resources

• Banco de Portugal: Main simulator all portuguese banks have to follow ( https://clientebancario.bportugal.pt/credito-habitacao )
• Laravel: A PHP web application framework for building robust and scalable applications. ( https://laravel.com/ )
• Livewire: A Laravel library for building dynamic interfaces without writing JavaScript. ( https://livewire.laravel.com/ )
• AdminLTE: A responsive admin dashboard template for creating a visually appealing interface. ( https://adminlte.io/ )

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Hack on isotest-ng - a rust port of isotovideo (os-autoinst aka testrunner of openQA) by szarate

Description

Some time ago, I managed to convince ByteOtter to hack something that resembles isotovideo but in Rust, not because I believe that Perl is dead, but more because there are certain limitations in the perl code (how it was written), and its always hard to add new functionalities when they are about implementing a new backend, or fixing bugs (Along with people complaining that Perl is dead, and that they don't like it)

In reality, I wanted to see if this could be done, and ByteOtter proved that it could be, while doing an amazing job at hacking a vnc console, and helping me understand better what RuPerl needs to work.

I plan to keep working on this for the next few years, and while I don't aim for feature completion or replacing isotovideo tih isotest-ng (name in progress), I do plan to be able to use it on a daily basis, using specialized tooling with interfaces, instead of reimplementing everything in the backend

Todo

• Add make targets for testability, e.g "spawn qemu and type"
• Add image search matching algorithm
• Add a Null test distribution provider
• Add a Perl Test Distribution Provider
• Fix unittests https://github.com/os-autoinst/isotest-ng/issues/5
• Research OpenTofu how to add new hypervisors/baremetal to OpenTofu
• Add an interface to openQA cli

Goals

• Implement at least one of the above, prepare proposals for GSoC
• Boot a system via it's BMC

Resources

See https://github.com/os-autoinst/isotest-ng

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Yearly Quality Engineering Ask me Anything - AMA for not-engineering by szarate

Goal

Get a closer look at how developers work on the Engineering team (R & D) of SUSE, and close the collaboration gap between GSI and Engineering

Why?

Santiago can go over different development workflows, and can do a deepdive into how Quality Engineering works (think of my QE Team, the advocates for your customers), The idea of this session is to help open the doors to opportunities for collaboration, and broaden our understanding of SUSE as a whole.

Objectives

• Give $audience a small window on how to get some questions answered either on the spot or within days of how some things at engineering are done
• Give Santiago Zarate from Quality Engineering a look into how $audience sees the engineering departments, and find out possibilities of further collaboration

How?

By running an "Ask me Anything" session, which is a format of a kind of open Q & A session, where participants ask the host multiple questions.

How to make it happen?

I'm happy to help joining a call or we can do it async (online/in person is more fun). Ping me over email-slack and lets make the magic happen!. Doesn't need to be during hackweek, but we gotta kickstart the idea during hackweek ;)

Rules

The rules are simple, the more questions the more fun it will be; while this will be only a window into engineering, it can also be the place to help all of us get to a similar level of understanding of the processes that are behind our respective areas of the organization.

Dynamics

The host will be monitoring the questions on some pre-agreed page, and try to answer to the best of their knowledge, if a question is too difficult or the host doesn't have the answer, he will do his best to provide an answer at a later date.

Atendees are encouraged to add questions beforehand; in the case there aren't any, we would be looking at how Quality Engineering tests new products or performs regression tests

Agenda

• Introduction of Santiago Zarate, Product Owner of Quality Engineering Core team
• Introduction of the Group/Team/Persons interested
• Ice breaker
• AMA time! Add your questions $PAGE
• Looking at QE Workflows: How is
  • A maintenance update being tested before being released to our customers
  • Products in development are tested before making it generally available
• Engineering Opportunity Board

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Drag Race - comparative performance testing for pull requests by balanza

Description

«Sophia, a backend developer, submitted a pull request with optimizations for a critical database query. Once she pushed her code, an automated load test ran, comparing her query against the main branch. Moments later, she saw a new comment automatically added to her PR: the comparison results showed reduced execution time and improved efficiency. Smiling, Sophia messaged her team, “Performance gains confirmed!”»

Goals

• To have a convenient and ergonomic framework to describe test scenarios, including environment and seed;
• to compare results from different tests
• to have a GitHub action that executes such tests on a CI environment

Resources

The MVP will be built on top of Preevy and K6.

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Make more sense of openQA test results using AI by livdywan

Description

AI has the potential to help with something many of us spend a lot of time doing which is making sense of openQA logs when a job fails.

User Story

Allison Average has a puzzled look on their face while staring at log files that seem to make little sense. Is this a known issue, something completely new or maybe related to infrastructure changes?

Goals

• Leverage a chat interface to help Allison
• Create a model from scratch based on data from openQA
• Proof of concept for automated analysis of openQA test results

Bonus

• Use AI to suggest solutions to merge conflicts
  • This would need a merge conflict editor that can suggest solving the conflict
• Use image recognition for needles

Resources

• TensorFlow
• open-webui
• openQA instance of openSUSE
• openQA documentation

Timeline

Day 1

• Conversing with open-webui to teach me how to create a model based on openQA test results
  • Asking for example code using TensorFlow in Python
  • Discussing log files to explore what to analyze
  • Drafting a new project called Testimony (based on Implementing a containerized Python action) - the project name was also suggested by the assistant

Day 2

• Using NotebookLLM (Gemini) to produce conversational versions of blog posts
  • Writing openQA tests in Python
  • Developing in distrobox containers
• Researching the possibility of creating a project logo with AI
  • Asking open-webui, persons with prior experience and conducting a web search for advice

Highlights

• I briefly tested compared models to see if they would make me more productive. Between llama, gemma and mistral there was no amazing difference in the results for my case.
• Convincing the chat interface to produce code specific to my use case required very explicit instructions.
• Asking for advice on how to use open-webui itself better was frustratingly unfruitful both in trivial and more advanced regards.
• Documentation on source materials used by LLM's and tools for this purpose seems virtually non-existent - specifically if a logo can be generated based on particular licenses

Outcomes

• Chat interface-supported development is providing good starting points and open-webui being open source is more flexible than Gemini. Although currently some fancy features such as grounding and generated podcasts are missing.
• Allison still has to be very experienced with openQA to use a chat interface for test review. Publicly available system prompts would make that easier, though.

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Automated Test Report reviewer by oscar-barrios

Description

In SUMA/Uyuni team we spend a lot of time reviewing test reports, analyzing each of the test cases failing, checking if the test is a flaky test, checking logs, etc.

Goals

Speed up the review by automating some parts through AI, in a way that we can consume some summary of that report that could be meaningful for the reviewer.

Resources

No idea about the resources yet, but we will make use of:

• HTML/JSON Report (text + screenshots)
• The Test Suite Status GithHub board (via API)
• The environment tested (via SSH)
• The test framework code (via files)

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