Embeds text with an embedding-capable model and returns one vector per input, in order. The input field takes either a single string or an array of strings, so single and batch embedding share one command. The vector dimension is fixed by the model. Local embedding models require a build with the local execution feature; cloud embedding providers (OpenAI, Google) require the matching provider feature and an API key.

Parameters

Name	Type	Required	Description
model	string	yes	Model spec.
dimensions	integer	no	Truncate to this many dimensions (matryoshka), then renormalize.
input	EmbedInput	yes	Text(s) to embed.
input_type	InputType	no	Query vs document role for instruction-tuned embedders.
instruction	string	no	Explicit instruction prefix override.
normalize	boolean	no	Force L2 normalization on/off (default per-model).

Returns

EmbeddingsResponse.

Errors

• failed_precondition.engine.runtime_closed
• not_found.engine.branch
• inference.unsupported_operation
• inference.missing_model
• inference.model_load_failed
• inference.local_runtime_failed
• inference.missing_api_key
• inference.provider_unavailable
• inference.provider_malformed_response
• inference.unsupported_provider
• inference.unsupported_parameter
• inference.registry_corrupt

Invocation

• CLI: strata inference embed
• Wire type: inference_embed