That's very cool. Thanks, I'll have to check that out.

I didn't mention this part, but while writing this I realized I could easily add a skill to hit the Forgejo PR API. There's no forgejo CLI like there is with GitHub sadly.

I just use the tea CLI. There is pretty good compatibility between tea and forgejo. The only place I’ve found it to be incomplete is forgejo’s actions api was missing some endpoints.

There is: https://forgejo.org/docs/latest/admin/command-line/

That's not an API tool. It performs direct database access for administrative functions on the Forgejo server.

But there is a different tool that is an API accessing CLI: https://codeberg.org/forgejo-contrib/forgejo-cli

There is, but it's limited. For example Forgejo does not expose CI build logs via the API so it's hard to make Claude auto-fix a build issue.

I still need to find the time to get into the Forgejo code and add that endpoint.

That seems like a problem an LLM could solve. ;) (Assuming Forgejo has a reasonable REST/whatever API.)

I recently setup Arcane and started migrating stuff from Truenas apps, they were all deployed as custom docker compose services so it worked out. Arcane supports Git syncs to auto deploy compose stacks, https://getarcane.app/docs/features/projects#sync-from-git I'll write up some posts on my full setup soon.

What _IS_ Arcane? I fail to understand from their website https://getarcane.app/

Is it a deployment automation platform where it can run a project’s docker services, with rollback and all?

so, the project is pretty much vibe coded, including the docs. It makes a lot more sense if you play around with it. It's just a docker host management UI, I like using it. It has gitops built in and a nice container log view. It doesn't do rollbacks, it only seems to sync from git and run compose up.

Is it analogous to portainer with a git-pull-compose-apply loop?

I looked into running local models last month. They just aren't quite there for agentic tool use workflows without spending a small fortune. I'm hopeful smaller local models get much better soon.

I was also hoping to put out another post on my homelab setup, it has some neat stuff, but I haven't had a chance to finish it.

I think it heavily depends on what you're asking the model to do. Qwen3.6, both 27B and 35B-A3B, do agentic tool use very well. Their decision making is sus, but the dense model is decent in that way. A 4-bit quant for either of those can run on many home systems with a bit of configuration.

The biggest issue I've noticed is that the chat templates for open models are really hit or miss. The default Qwen3.6 chat template mostly works these days, but depending on your workload it may cause major issues. There are plenty of "fixed" chat templates on hugging face, but people report mixed success. It really seems to depend a lot on what the tool you're using expects.

My workflow is too different right now (gradually constrained to network less builds for reasons) but I am really enjoying how zeds agents have worked out in the past few weeks.

I have 27b, 35B-A3B and a cpu backed gpt-oss configured and use them in parallel, checking if one is getting ratholed and adding context or manual fixes.

I had various other systems setup and commercial models but really don’t use them.

It may be too interactive for some people, but it is a good mix of fail fast and often the places qwen3.6 was failing was eventually problems with the frontier models.

And this is with the unsloth defaults and hardened llama.cpp podman containers.

I do sometimes load other models or honestly just feed things into google’s free agent. But that is rare and to be honest manually fixing is typically faster and less error prone

Any artifacts or blogs I can check out? I'm curious how you manage to make them all useful in parallel. I have a hard enough time getting one instance of Qwen3.6-27B being useful full time haha.

I'll verify the PR code myself before merging, but that's usually a quick skim.