Language models

Podlibre completes every step of the workflow without a model. Where one is available it writes show notes, proposes chapters, drafts posts for social networks, and answers questions in the command palette.

Ollama on the user's own machine is the recommended path and the default. Nothing leaves the computer, there is no account and no bill. External providers — Anthropic, OpenAI — are supported on the user's own key for those who want them.

What a plugin may ask for

Three ways, in descending order of politeness:

Request	Example	When to use it
A capability	summarise, long_context	Almost always. The user's existing model probably qualifies.
A recommended model	"works best with qwen2.5:14b"	When you have tested one and it is clearly better.
An exact model	llama3.1:8b	Only when nothing else will do.

The gate resolves the request against what the user has installed and offers to install what is missing. A plugin that names an exact model on a machine that cannot run it is a plugin the user cannot use, which is why the capability form is preferred.

Installing models

Podlibre lists the models a user has, the ones their installed plugins ask for, and what each would cost in disk space and memory. Installing is one button; Ollama does the work in a task like any other, with a progress bar and a Stop button.

What it costs

Every call is recorded against the plugin that made it: the model, tokens in, tokens out, and the cost where the provider charges for it. Preferences shows the month's spending per plugin.

Local calls cost nothing and are still counted, because knowing that a plugin is chatty matters even when it is free — it is the user's memory and battery either way.

A plugin granted llm.remote can be held to a monthly ceiling in euros. Past it, the capability stops answering, and the plugin is told so in a way it can handle.