voyage-ai-provider
Version:
Voyage AI Provider for running Voyage AI models with Vercel AI SDK
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TypeScript
import { ProviderV1, EmbeddingModelV1 } from '@ai-sdk/provider';
import { FetchFunction } from '@ai-sdk/provider-utils';
type VoyageEmbeddingModelId = 'voyage-3-large' | 'voyage-3' | 'voyage-3-lite' | 'voyage-code-3' | 'voyage-finance-2' | 'voyage-multilingual-2' | 'voyage-law-2' | 'voyage-code-2' | 'voyage-large-2-instruct' | 'voyage-large-2' | 'voyage-2' | 'voyage-02' | 'voyage-01' | 'voyage-lite-01' | (string & NonNullable<unknown>);
interface VoyageEmbeddingSettings {
/**
* The input type for the embeddings. Defaults to "query".
* For query, the prompt is "Represent the query for retrieving supporting documents: ".
* For document, the prompt is "Represent the document for retrieval: ".
*/
inputType?: 'query' | 'document';
/**
* The number of dimensions for the resulting output embeddings.
*
* If not specified (defaults to null), the resulting output embeddings dimension is the default for the model.
* `voyage-code-3` supports the following `outputDimension` values: 2048, 1024 (default), 512, and 256.
* `voyage-3-large` supports the following `outputDimension` values: 2048, 1024 (default), 512, and 256.
*
* please refer to the model documentation for the supported values.
* https://docs.voyageai.com/docs/embeddings
*/
outputDimension?: number;
/**
* The data type for the resulting output embeddings.
*
* Defaults to 'float'.
*
* Other options: 'int8', 'uint8', 'binary', 'ubinary'.
* - 'float' is supported by all models.
* - 'float': Each returned embedding is a list of 32-bit (4-byte) single-precision floating-point numbers.
* - 'int8', 'uint8', 'binary', and 'ubinary' are supported by 'voyage-code-3'.
* - 'int8' and 'uint8': Each returned embedding is a list of 8-bit (1-byte) integers ranging from -128 to 127 and 0 to 255, respectively.
* - 'binary' and 'ubinary': Each returned embedding is a list of 8-bit integers that represent bit-packed, quantized single-bit embedding values:
* 'int8' for 'binary' and 'uint8' for 'ubinary'.
* The length of the returned list of integers is 1/8 of outputDimension (which is the actual dimension of the embedding).
* The 'binary' type uses the offset binary method.
*
* https://docs.voyageai.com/docs/faq#what-is-quantization-and-output-data-types
*/
outputDtype?: 'float' | 'int8' | 'uint8' | 'binary' | 'ubinary';
/**
* Whether to truncate the input texts to fit within the context length.
*/
truncation?: boolean;
}
interface VoyageProvider extends ProviderV1 {
(modelId: VoyageEmbeddingModelId, settings?: VoyageEmbeddingSettings): EmbeddingModelV1<string>;
/**
@deprecated Use `textEmbeddingModel()` instead.
*/
embedding(modelId: VoyageEmbeddingModelId, settings?: VoyageEmbeddingSettings): EmbeddingModelV1<string>;
/**
@deprecated Use `textEmbeddingModel()` instead.
*/
textEmbedding(modelId: VoyageEmbeddingModelId, settings?: VoyageEmbeddingSettings): EmbeddingModelV1<string>;
textEmbeddingModel: (modelId: VoyageEmbeddingModelId, settings?: VoyageEmbeddingSettings) => EmbeddingModelV1<string>;
}
interface VoyageProviderSettings {
/**
Use a different URL prefix for API calls, e.g. to use proxy servers.
The default prefix is `https://api.voyageai.com/v1`.
*/
baseURL?: string;
/**
API key that is being send using the `Authorization` header.
It defaults to the `VOYAGE_API_KEY` environment variable.
*/
apiKey?: string;
/**
Custom headers to include in the requests.
*/
headers?: Record<string, string>;
/**
Custom fetch implementation. You can use it as a middleware to intercept requests,
or to provide a custom fetch implementation for e.g. testing.
*/
fetch?: FetchFunction;
}
/**
Create a Voyage AI provider instance.
*/
declare function createVoyage(options?: VoyageProviderSettings): VoyageProvider;
/**
Default Voyage provider instance.
*/
declare const voyage: VoyageProvider;
export { type VoyageProvider, type VoyageProviderSettings, createVoyage, voyage };