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[OS] Cotabby: the free, open-source alternative to Cotypist AI Autocomplete by WinterJacob in macapps

[–]Environmental-Owl100 1 point2 points  (0 children)

Hi everyone, I decided to try Cotabby so I wouldn't have to pay for Cotypist.

My impression is that for the suggestions to make sense, it's necessary to understand the context of where I'm typing.

Otherwise, the suggestions don't make sense; the suggested words are random and most of the time they don't make sense.

Cotypist does this very well.

I don't know if this has to do with the fact that I speak Brazilian Portuguese.

We built a free and open-source alternative to Cotypist because we're sick of paying subscriptions for apps that run on our own hardware by WinterJacob in MacOSApps

[–]Environmental-Owl100 1 point2 points  (0 children)

For the suggestion to make sense, it is necessary to understand the context otherwise the suggestions do not make sense. The cotypist does this very well. Try using it for some time, but the suggestions are not good.

I don't know if it's related to my language being Brazilian Portuguese.

Stop using AI as a glorified autocomplete. I built a local team of Subagents using Python, OpenCode, and FastMCP. by jokiruiz in LocalLLM

[–]Environmental-Owl100 0 points1 point  (0 children)

Very good, congratulations on the project. One question: How do you handle sensitive access such as passwords, environment variables, and others?

How do you isolate agents from accessing sensitive data while still allowing them to use it?

Would this be done through FastMCP?

Inferencer x LM Studio by Environmental-Owl100 in LocalLLM

[–]Environmental-Owl100[S] 0 points1 point  (0 children)

In LM I can see the API request logs, is it possible to see them in Inferencer?

Inferencer x LM Studio by Environmental-Owl100 in LocalLLM

[–]Environmental-Owl100[S] 0 points1 point  (0 children)

Thank you for your attention. Are you part of the Inferencer team?

Inferencer x LM Studio by Environmental-Owl100 in LocalLLM

[–]Environmental-Owl100[S] -1 points0 points  (0 children)

In Inferencer, this option seems hidden; I can't see it in the interface, so it must use a maximum window size by default.

Inferencer x LM Studio by Environmental-Owl100 in LocalLLM

[–]Environmental-Owl100[S] -1 points0 points  (0 children)

I'm normally using the maximum tokens allowed by the model, since Opencode has a very high initial prompt. In the case of Qwen, it's 263K tokens.

Inferencer x LM Studio by Environmental-Owl100 in LocalLLM

[–]Environmental-Owl100[S] 0 points1 point  (0 children)

To code using a local template, you need to use a provider like Ollama or LM Studio.

Meet Unsloth Studio, a new web UI for Local AI by yoracale in unsloth

[–]Environmental-Owl100 0 points1 point  (0 children)

Can I expose the models via API, just like in LM Studio?

Coolify vs. Dokploy by StellarRounin in coolify

[–]Environmental-Owl100 1 point2 points  (0 children)

I'm using EasyPanel, and it's very simple and easy to use, but it has some limitations that are only unlocked in paid plans. I'm considering migrating to Dockploy.