llm models --options should show supported attachment types, too

[simonw]

Refs:

• Solve multi-modal models with a new concept of "attachments" #587

[simonw]

Had to sort them alphabetically to get the tests to pass reliably.

[simonw]

Example output (from the cog maintained docs):

llm/docs/usage.md

Lines 250 to 282 in 12df1a3

	OpenAI Chat: gpt-4o (aliases: 4o)
	Options:
	temperature: float
	What sampling temperature to use, between 0 and 2. Higher values like
	0.8 will make the output more random, while lower values like 0.2 will
	make it more focused and deterministic.
	max_tokens: int
	Maximum number of tokens to generate.
	top_p: float
	An alternative to sampling with temperature, called nucleus sampling,
	where the model considers the results of the tokens with top_p
	probability mass. So 0.1 means only the tokens comprising the top 10%
	probability mass are considered. Recommended to use top_p or
	temperature but not both.
	frequency_penalty: float
	Number between -2.0 and 2.0. Positive values penalize new tokens based
	on their existing frequency in the text so far, decreasing the model's
	likelihood to repeat the same line verbatim.
	presence_penalty: float
	Number between -2.0 and 2.0. Positive values penalize new tokens based
	on whether they appear in the text so far, increasing the model's
	likelihood to talk about new topics.
	stop: str
	A string where the API will stop generating further tokens.
	logit_bias: dict, str
	Modify the likelihood of specified tokens appearing in the completion.
	Pass a JSON string like '{"1712":-100, "892":-100, "1489":-100}'
	seed: int
	Integer seed to attempt to sample deterministically
	json_object: boolean
	Output a valid JSON object {...}. Prompt must mention JSON.
	Attachment types:
	image/png, image/gif, image/webp, image/jpeg