langchain.js
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    Class TensorFlowEmbeddings

    Class that extends the Embeddings class and provides methods for generating embeddings using the Universal Sentence Encoder model from TensorFlow.js.

    const embeddings = new TensorFlowEmbeddings();
    const store = new MemoryVectorStore(embeddings);

    const documents = [
      "A document",
      "Some other piece of text",
      "One more",
      "And another",
    ];

    await store.addDocuments(
      documents.map((pageContent) => new Document({ pageContent }))
    );

    Hierarchy (View Summary)

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    Constructors

    constructor

    Properties

    _cached

    Methods

    embedDocuments embedQuery

    Constructors

    Properties

    _cached

    _cached: Promise<UniversalSentenceEncoder>

    Methods

    • Method that takes an array of documents as input and returns a promise that resolves to a 2D array of embeddings for each document. It calls the _embed method with the documents as the input and processes the result to return the embeddings.

      Parameters

      • documents: string[]

        Array of documents to generate embeddings for.

      Returns Promise<number[][]>

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

    • Method that takes a document as input and returns a promise that resolves to an embedding for the document. It calls the _embed method with the document as the input and processes the result to return a single embedding.

      Parameters

      • document: string

        Document to generate an embedding for.

      Returns Promise<number[]>

      Promise that resolves to an embedding for the input document.

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