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    Class TogetherAIEmbeddings

    Class for generating embeddings using the TogetherAI API. Extends the Embeddings class and implements TogetherAIEmbeddingsParams.

    const embeddings = new TogetherAIEmbeddings({
      apiKey: process.env.TOGETHER_AI_API_KEY, // Default value
      model: "togethercomputer/m2-bert-80M-8k-retrieval", // Default value
    });
    const res = await embeddings.embedQuery(
      "What would be a good company name a company that makes colorful socks?"
    );

    Hierarchy (View Summary)

    Implements

    Index

    Constructors

    constructor

    Properties

    apiKey batchSize model modelName stripNewLines timeout?

    Methods

    embedDocuments embedQuery

    Constructors

    Properties

    apiKey: string

    The API key to use for the TogetherAI API.

    {process.env.TOGETHER_AI_API_KEY}
    batchSize: number = 512

    The maximum number of documents to embed in a single request.

    {512}
    model: string = "togethercomputer/m2-bert-80M-8k-retrieval"

    Model name to use

    {"togethercomputer/m2-bert-80M-8k-retrieval"}
    modelName: string = "togethercomputer/m2-bert-80M-8k-retrieval"

    Model name to use Alias for model

    {"togethercomputer/m2-bert-80M-8k-retrieval"}
    stripNewLines: boolean = false

    Whether to strip new lines from the input text. May not be suitable for all use cases.

    {false}
    timeout?: number

    Timeout to use when making requests to TogetherAI.

    {undefined}

    Methods

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

    • Method to generate an embedding for a single document. Calls the embeddingWithRetry 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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