Skip to main content
A free-form chat-completions LLM (optionally vision-capable) — the JS analogue of the ask primitive. Given a prompt, optional accessibility/structural text, and zero or more images, [AskModel.ask] returns the model’s response as a plain string. The wire format is OpenAI-compatible chat completions, so any provider config that points at such an endpoint works.

​
Constructor

​
Returns

AskModel

​
Properties

​
string
required
The wire-level model identifier sent in the request body.

​
Methods

​
ask()

Ask the model a question, optionally grounded in accessibility text and/or images.
  • prompt: the question or task to answer.
  • text: optional accessibility-tree (or any) text included as structural context. Pass null / omit to skip.
  • images: zero or more images to attach. Each is encoded as a base64 data URL in a model-supported format and sent as an image_url chat content part. Pass null / omit for none.
Returns the trimmed assistant response on success.

​
Parameters

​
string
required
​
null | string
​
null | Image[]

​
Returns

string

​
availableAliases()

Every LLM model alias accepted by byAlias on this machine, deduplicated and sorted alphabetically. Use to discover what aliases the loaded config (bundled defaults plus any user provider files) advertises.

​
Returns

string[]

​
byAlias()

Resolve a model alias against the loaded config (e.g. "openrouter_gpt_4o_mini" / "openrouter_claude_opus" from the bundled openrouter provider, or any alias declared by a user provider). Throws if the alias is unknown.

​
Parameters

​
string
required

​
Returns

AskModel

​
checkAuth()

Check that the API key works. Throws if it doesn’t. Call right after creating the model so a bad key fails fast, before any UI automation has had a chance to steal focus:

​
default()

First LLM model advertised by the first LLM-capable provider in the loaded configuration whose credentials are currently available. Providers with missing credentials are skipped; throws if no provider remains available.

​
Returns

AskModel