Class PremEmbeddings

Class for generating embeddings using the Prem AI's API. Extends the Embeddings class and implements PremEmbeddingsParams and

Hierarchy

  • Embeddings
    • PremEmbeddings

Implements

Constructors

constructor

Properties

apiKey? batchSize caller client encoding_format? model project_id

Methods

embedDocuments embedQuery

Constructors

constructor

Properties

OptionalapiKey

apiKey?: string

The Prem API key to use for requests.

Default

process.env.PREM_API_KEY

batchSize

batchSize: number = 128

caller

caller: AsyncCaller

The async caller should be used by subclasses to make any async calls, which will thus benefit from the concurrency and retry logic.

client

client: Prem

Optionalencoding_format

encoding_format?: "base64" | "float"

model

model: string

The model to generate the embeddings.

project_id

project_id: number

The ID of the project to use.

Methods

embedDocuments

  • embedDocuments(texts): Promise<number[][]>

  • Method to generate embeddings for an array of documents. Splits the documents into batches and makes requests to the Prem API to generate embeddings.

    Parameters

    • texts: string[]

      Array of documents to generate embeddings for.

    Returns Promise<number[][]>

    Promise that resolves to a 2D array of embeddings for each document.

embedQuery

  • embedQuery(text): Promise<number[]>

  • Method to generate an embedding for a single document. Calls the embedDocuments method with the document as the input.

    Parameters

    • text: string

      Document to generate an embedding for.

    Returns Promise<number[]>

    Promise that resolves to an embedding for the document.

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