langchain.js
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    Hierarchy (View Summary)

    Implements

    Index

    Constructors

    Properties

    apiKey: string
    batchSize: number = 24

    The maximum number of documents to embed in a single request. This is limited by the AlibabaTongyi API to a maximum of 2048.

    modelName: "text-embedding-v2"

    Model name to use

    parameters: undefined | { text_type?: "query" | "document" }

    Type Declaration

    • undefined
    • { text_type?: "query" | "document" }
      • Optionaltext_type?: "query" | "document"

        取值:query 或者 document,默认值为 document 说明:文本转换为向量后可以应用于检索、聚类、分类等下游任务, 对检索这类非对称任务为了达到更好的检索效果建议区分查询文本(query)和 底库文本(document)类型, 聚类、分类等对称任务可以不用特殊指定, 采用系统默认值"document"即可

    stripNewLines: boolean = true

    Whether to strip new lines from the input text.

    Methods

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