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From: Roman Gushchin In-Reply-To: <20260517183959.37441984@foz.lan> Date: Sun, 17 May 2026 11:17:06 -0700 Cc: Greg KH , Krzysztof Kozlowski , debarbos@redhat.com, Arnaldo Carvalho de Melo , Konstantin Ryabitsev , Guenter Roeck , sashiko-bot@kernel.org, sashiko-reviews@lists.linux.dev, sashiko@lists.linux.dev, Linux Kernel Workflows , Linux Kernel Mailing List , devicetree@vger.kernel.org, kfree@google.com Message-Id: References: <20260517183959.37441984@foz.lan> To: Mauro Carvalho Chehab X-Migadu-Flow: FLOW_OUT > On May 17, 2026, at 9:40=E2=80=AFAM, Mauro Carvalho Chehab wrote: >=20 > =EF=BB=BFOn Sun, 17 May 2026 12:12:00 +0200 > Greg KH wrote: >=20 >>> On Sun, May 17, 2026 at 12:05:56PM +0200, Mauro Carvalho Chehab wrote: >>> On Sat, 16 May 2026 14:59:44 -0700 >>> Roman Gushchin wrote: >>>=20 >>>>> On May 16, 2026, at 2:33=E2=80=AFPM, Krzysztof Kozlowski wrote: >>>>>=20 >>>>> I find it opposite: clogging commits with useless information, because= >>>>> some arbitrary and completely closed-source tool did analysis means >>>>> nothing to me one year later when I look at the commit in the Git hist= ory. =20 >>>>=20 >>>> This is simple not true: Sashiko is fully open-source, under Apache 2.0= license >>>> and the code belongs to LF. =20 >>>=20 >>>> Yes, the instance behind sashiko.dev is using >>>> Gemini 3.1 Pro LLM, which is not open-source, but it=E2=80=99s not a fu= ndamental limitation - >>>> Sashiko is supporting various LLMs, including open models - it=E2=80=99= s just a practical >>>> choice: to my knowledge the quality of open models is not on par with f= rontier closed >>>> models =20 >>>=20 >>> I would very much prefer using an open source LLM, even if not in pair >>> with latest paid models. >>>=20 >>>> and it would require a non-trivial amount of hardware and infrastructur= e to run >>>> an open model at the required scale. =20 >>>=20 >>> IMHO the best would be to have them running on some infra that would acc= ept >>> open source models (*). If there aren't enough resources to have our own= >>> infra, there are offers out there which allows running open source model= s >>> like https://ollama.com/pricing (I never used myself). >>>=20 >>> (*) For instance, Qwen3.6 is brand new and licensed under apache-2.0. >>> Not bad on my tests running it locally. =20 >>=20 >> You can run the tool locally, with whatever model you want, if you want >> to. >>=20 >> But for now, let's just take the free credits that Google is willing to >> throw at this thing and let it give us reviews IF the maintainer of the >> subsystem feels it is something they want to do. No one is forcing >> maintainers to do this. >=20 > If Google and/or others are willing to give free credits on their cloud, > they could instead or in addition give free credits to run ollama > there, allowing us to use different models. >=20 > =46rom my side, while I won't personally object getting reviews from > Sashiko/Gemini, this is something I can't reproduce locally. I would > very much want something where I can select my LLM preferred model > and run on my ollama docker container on my own GPU, in a way that > I could run it locally before even sending a patch series. 2 thoughts here: 1) I actually tried to run it with ollama on my personal framework 13. Addin= g nominal support is trivial, but the whole thing is not really useful: I can get maybe few hundreds token= s per second using a quantified model with reduced quality; an average sashiko review is consum= ing 3.5 millions tokens (with Gemini 3.1 pro, it=E2=80=99s also model-dependent). I=E2=80=99m personally all in on having the entire thing as open as possible= and I believe Sashiko is what=20 is realistically the best at this moment - a fully open-source harness and s= et of prompts which=20 can work with a variety of models. I=E2=80=99m happy to merge a support for any LLM model which can produce dec= ent review results. 2) Due to probabilistic nature of LLMs, nothing is reproducible in a strict s= ense of the word. Even with exactly the same model/harness/prompts you=E2=80=99ll get differen= t results every time you run it. It=E2=80=99s unfortunate, but it is what it is at the moment.