Pretty impressive results, we were at 500+ open PRs 2 days ago and now we are 
at ~430 open PRs. Bravo!

On 2026/03/11 14:51:36 Kevin Yang wrote:
> Thanks for the feedback! More than happy if I could implement these options
> and integrations. I will look into the current implementation and draft PRs
> by the upcoming week.
> 
> Best,
> Kevin Yang
> 
> On Wed, Mar 11, 2026 at 4:05 AM Jarek Potiuk <[email protected]> wrote:
> 
> > You can absolutely add the  option to use any agent or model to the tool I
> > created. Currently it can use copilot, Claude, codex - but you can add PR
> > to use any model - it is build for that purpose.
> >
> > This is integrated with breeze uatctually even automatically stores which
> > model you use and continue using it. The interface to LLm ia super Simple.
> > It does not even use Pydantic AI - it just generates prompt and parses the
> > output. so by all means - adding a way to use any other LLM.
> >
> > 90% of the work done by the tool is deterministic; it only asks the LLM
> > when it is in doubt.
> >
> > So - by all means, PRs to use any other LLMs - whether local or remote -
> > are most welcome. Also we can add opencode and ollama integration
> >
> > [image: image.png]
> >
> > J.
> >
> > On Wed, Mar 11, 2026, 03:32 Kevin Yang <[email protected]> wrote:
> >
> >> Hi Jarek,
> >>
> >> Thank you very much for all the efforts in building the solutions. I
> >> recently also read through the following discussions [1,2,3], and think
> >> about whether there is a good approach on tackling the challenge.
> >>
> >> I believe integrating with LLM is a good approach, especially can leverage
> >> its reasoning capabilities to provide a better triage. Existing products
> >> such as Copilot Code Review can also provide insightful triage as
> >> previously proposed by Kaxil.
> >>
> >> I also find another direction that also looks promising to me is to
> >> use a *small
> >> language model (SLM)*, a model with 2-4 B parameters, which can be run on
> >> standard Github runners, using CPU-only, to triage issues and PRs. I've
> >> built a github action *SLM Triage* (
> >> https://github.com/marketplace/actions/slm-triage).
> >>
> >> What advantages does SLM offer?
> >> * It can be run on a standard GitHub runner, on CPU, and finish execution
> >> in around 3 - 5 minutes
> >> * There is no API cost, billing set up with LLM service
> >> * It runs on GitHub events, when an issue or PR is opened, and capable to
> >> triage issues as long as there are GitHub runners available
> >> * It can be simply integrated into GitHub Actions without infrastructure,
> >> or local setup.
> >>
> >> What are the current limitations?
> >> * It doesn't have enough domain knowledge about a specific codebase, so it
> >> can only triage based on high-level context, and relevancy between context
> >> information and code changes
> >> * It has limited reasoning capability
> >> * It has limited context window (128k context window size, some might have
> >> ~256k)
> >>
> >> Why I think it can be a potential direction
> >> * I feel some issues or PRs can be triage based on some basic heuristics
> >> and rules
> >> * Even though context window is limited, if the process is triggered when
> >> issue opened, the context window is good enough to capture issue
> >> description, pr description, and even code change
> >> * It is easier to set up for a broader open-source community, and probably
> >> more cost efficient, it can scale based on workflow adoption
> >> * It can take action through API such as comment on an issue, add label,
> >> close an issue or PR, etc. based on the triage result.
> >>
> >> I also attempted to triage multiple issues and PRs on airflow repository,
> >> and check the actual issues/PRs (I created a script to dry-run and inspect
> >> the triage result and reasoning). The result looks promising, but
> >> sometimes
> >> I found it is "a bit strict" and needs some improvements in terms of
> >> prompting.
> >>
> >> I wonder if this is a valid idea, but it would be great if the idea can
> >> potentially help.
> >>
> >> Thanks,
> >> Kevin Yang
> >>
> >> [1] https://github.com/orgs/community/discussions/185387
> >> [2] https://github.com/ossf/wg-vulnerability-disclosures/issues/178
> >> [3]
> >>
> >> https://www.reddit.com/r/opensource/comments/1q3f89b/open_source_is_being_ddosed_by_ai_slop_and_github/#:~:text=FunBrilliant5713-,Open%20source%20is%20being%20DDoSed%20by%20AI%20slop%20and%20GitHub,which%20submissions%20came%20from%20Copilot
> >> .
> >>
> >> On Tue, Mar 10, 2026 at 9:13 PM Jarek Potiuk <[email protected]> wrote:
> >>
> >> > Just to update everyone: I've auto-triaged a bunch of PRs—the tool works
> >> > very well IMHO, but we will know after the authors see them and review
> >> >
> >> > Some stats (I will gather more in the next days as I am adding timing
> >> and
> >> > further improvements):
> >> >
> >> > * I triaged about 100 PRs in under an hour of elapsed time (I
> >> > also corrected, improved and noted some fixes, so it will be faster)
> >> > * I converted 30 of those into Drafts and closed a few
> >> > * I have not marked any as ready to review yet, but I will do that
> >> tomorrow
> >> > * The LLM (Claude) assessment is quite fast - faster than I thought.
> >> > Parallelizing it also helps. LLM assessment takes between 20 s and 2
> >> > minutes (elapsed), but usually, only a few pull requests (15% or less)
> >> are
> >> > LLM assessed  in a batch, so this is not a bottleneck. I will also
> >> modify
> >> > the tool to start reviewing deterministic things before LLMs complete -
> >> > which should speed up the whole process even more
> >> > * The LLM assessments are pretty good - but a few were significantly
> >> wrong
> >> > and I would not post them. It's good we have Human-In-The-Loop and in
> >> the
> >> > driver's seat.
> >> >
> >> > Overall - I think the tool is doing very well what I wanted. But let's
> >> see
> >> > the improvements over the next few days, observe how authors react, and
> >> > determine if it can actually help maintainers
> >> >
> >> > I added a few PRs as improvements; looking forward to reviews, :
> >> >
> >> > * https://github.com/apache/airflow/pull/63318
> >> > * https://github.com/apache/airflow/pull/63317
> >> > * https://github.com/apache/airflow/pull/63315
> >> > * https://github.com/apache/airflow/pull/63319
> >> > * https://github.com/apache/airflow/pull/63320
> >> >
> >> > J.
> >> >
> >> >
> >> >
> >> > On Tue, Mar 10, 2026 at 10:18 PM Jarek Potiuk <[email protected]> wrote:
> >> >
> >> > > Lazy consensus reached. I will try it out tonight. I added more
> >> signals
> >> > > (unresolved review comments)  and filtering options (
> >> > > https://github.com/apache/airflow/pull/63300) that will be useful
> >> during
> >> > > this phase.
> >> > >
> >> > > On Fri, Mar 6, 2026 at 9:08 PM Jarek Potiuk <[email protected]> wrote:
> >> > >
> >> > >> Hello here,
> >> > >>
> >> > >> I am asking a lazy consensus on the approach proposed in
> >> > >> https://lists.apache.org/thread/ly6lrm2gc4p7p54vomr8621nmb1pvlsk
> >> > >> regarding our approach to triaging PRs.
> >> > >>
> >> > >> The lazy consensus will last till  Tuesday 10 pm CEST (
> >> > >>
> >> >
> >> https://www.timeanddate.com/countdown/generic?iso=20260310T22&p0=262&font=cursive
> >> > >> )
> >> > >>
> >> > >> Summary of the proposal
> >> > >>
> >> > >> This is the proposed update to the PR contributing guidelines:
> >> > >>
> >> > >> > Start with **Draft**: Until you are sure that your PR passes all
> >> the
> >> > >> quality checks and tests, keep it in **Draft** status. This will
> >> signal
> >> > to
> >> > >> maintainers that the PR is not yet ready for review and it will
> >> prevent
> >> > >> maintainers from accidentally merging it before it's ready. Once you
> >> are
> >> > >> sure that your PR is ready for review, you can mark it as "Ready for
> >> > >> review" in the GitHub UI. Our regular check will convert all PRs from
> >> > >> non-collaborators that do not pass our quality gates to Draft status,
> >> > so if
> >> > >> you see that your PR is in Draft status and you haven't set it to
> >> Draft.
> >> > >> Check the comments to see what needs to be fixed.
> >> > >>
> >> > >> That's a "broad" description of the process; details will be worked
> >> out
> >> > >> while testing the solution.
> >> > >>
> >> > >> The PR: https://github.com/apache/airflow/pull/62682
> >> > >>
> >> > >> My testing approach is to start with individual areas, update and
> >> > perfect
> >> > >> the tool, gradually increase the reach of it and engage others -
> >> then we
> >> > >> might think about more regular process involving more maintainers.
> >> > >>
> >> > >> J.
> >> > >>
> >> > >
> >> >
> >>
> >
> 

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