/** * This file was auto-generated by Fern from our API Definition. */ /** * Type of the input text. Defaults to `null`. Other options: `query`, `document`. *

When input_type is null, the embedding model directly converts your input data into numerical vectors. For retrieval/search purposes—where an input (called a "query") is used to search for relevant pieces of information (referred to as "documents")—we recommend specifying whether your inputs are intended as queries or documents by setting input_type to query or document, respectively. In these cases, Voyage prepends a prompt to your input before vectorizing it, helping the model create more effective vectors tailored for retrieval/search tasks. Since inputs can be multimodal, queries and documents can be text, images, or an interleaving of both modalities. Embeddings generated with and without the input_type argument are compatible.
For transparency, the following prompts are prepended to your input.

For query, the prompt is "Represent the query for retrieving supporting documents: ".
For document, the prompt is "Represent the query for retrieving supporting documents: ".

*/ export declare type MultimodalEmbedRequestInputType = "query" | "document"; export declare const MultimodalEmbedRequestInputType: { readonly Query: "query"; readonly Document: "document"; };