Embedding

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A list of numbers with the AI model that made it.

Use it to store model output, since vectors from different models can't be compared. For the numbers alone, use Vector.

Shape

Field	Type	Required?
`model`	`ModelId`	Yes
`vector`	`Vector`	Yes

example

Embedding {    model: ModelId { provider: "openai" name: "text-embedding-3-small" }    vector: [0.5, -0.25, 1.0]}

== tells you whether two are the same. < and list.sort_by don't take it, so sort by one of its parts instead.

An object of its parts, in a request, a response or json.write:

json

{"model":"openai/text-embedding-3-small","vector":[0.5,-0.25,1]}{"model":"ollama/nomic-embed-text","vector":[0.0123]}

Text form, storage, how it is shown, and operations

Embedding is in the group Maths and data, and has been in Jadpo since 0.1.0.

It has no single text form, so text.from and text.parse don't take it.

It is stored in 3 columns, each named for the field, _ and its suffix. This is {"model":"ollama/nomic-embed-text","vector":[0.0123]}:

text.format(value, locale:) shows it to people in their locale.

With locale: Locale.en_gb:

Value	Shown
`{"model":"openai/text-embedding-3-small","vector":[0.5,-0.25,1]}`	`openai/text-embedding-3-small [0.5; -0.25; 1]`
`{"model":"ollama/nomic-embed-text","vector":[0.0123]}`	`ollama/nomic-embed-text [0.0123]`

It also takes text.format, json.read, json.write and ==. How every standard type behaves says how they work.

Markdown for agents: /docs/types/type-embedding.md.Built from Jadpo main at aee2e8f.