I'm glad to say that I'll participate again in the GSoC, as
mentor. This year we will try to improve the RPM packaging workflow
using AI, as part of the openSUSE project.
So this summer I'll be mentoring an intern that will research how to
integrate Log Detective with openSUSE tooling to improve the
packager workflow to maintain rpm packages.
Log Detective
Log Detective is an initiative created by the Fedora project,
with the goal of
"Train an AI model to understand RPM build logs and explain the
failure in simple words, with recommendations how to fix it. You
won't need to open the logs at all."
As a project that was promoted by Fedora, it's highly integrated with
the build tools around this distribution and RPM packages. But RPM
packages are used in a lot of different distributions, so this
"expert" LLM will be helpful for everyone doing RPM, and everyone
doing RPM, should contribute to it.
This is open source, so if, at openSUSE, we want to have something
similar to improve the OBS, we don't need to reimplement it, we
can collaborate. And that's the idea of this GSoC project.
We want to use Log Detective, but also collaborate with failures from
openSUSE to improve the training and the AI, and this should benefit
openSUSE but also will benefit Fedora and all other RPM based
distributions.
The intern
The selected intern is Aazam Thakur. He studies at University of
Mumbai, India. He has experience in using SUSE as he has previously
worked on SLES 15.6 during his previous summer mentorship at
OpenMainFrame Project for RPM packaging.
I'm sure that he will be able to achieve great things during these
three months. The project looks very promising and it's one of the
things where AI and LLM will shine, because digging into logs is
always something difficult and if we train a LLM with a lot of data it
can be really useful to categorize failures and give a short
description of what's happening.
There are comments.
