Class BaiduQianfanEmbeddings

⚠️ Deprecated ⚠️

Install and import from @langchain/baidu-qianfan instead.

This feature is deprecated and will be removed in the future.

It is not recommended for use.

Hierarchy (view full)

Implements

Constructors

constructor

Properties

accessToken baiduApiKey baiduSecretKey batchSize modelName stripNewLines

Methods

embedDocuments embedQuery

Constructors

constructor

Properties

accessToken

accessToken: string

baiduApiKey

baiduApiKey: string

baiduSecretKey

baiduSecretKey: string

batchSize

batchSize: number = 16

The maximum number of characters allowed for embedding in a single request varies by model:

  • Embedding-V1 model: up to 1000 characters
  • bge-large-zh model: up to 2000 characters
  • bge-large-en model: up to 2000 characters
  • tao-8k model: up to 28000 characters

Note: These limits are model-specific and should be adhered to for optimal performance.

modelName

modelName: "embedding-v1" | "bge_large_zh" | "bge-large-en" | "tao-8k" = "embedding-v1"

Model name to use

stripNewLines

stripNewLines: boolean = true

Whether to strip new lines from the input text.

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 BaiduQianFan 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 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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