Class MistralAIEmbeddings

Class for generating embeddings using the MistralAI API.

Hierarchy (view full)

Implements

Constructors

constructor

Properties

apiKey batchSize encodingFormat model modelName stripNewLines endpoint?

Methods

embedDocuments embedQuery

Constructors

constructor

Properties

apiKey

apiKey: string

The API key to use.

Default

{process.env.MISTRAL_API_KEY}

batchSize

batchSize: number = 512

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

Default

{512}

encodingFormat

encodingFormat: string = "float"

The format of the output data.

Default

{"float"}

model

model: string = "mistral-embed"

The name of the model to use.

Default

{"mistral-embed"}

modelName

modelName: string = "mistral-embed"

The name of the model to use. Alias for model.

Default

{"mistral-embed"}

stripNewLines

stripNewLines: boolean = true

Whether to strip new lines from the input text. This is recommended, but may not be suitable for all use cases.

Default

{true}

Optionalendpoint

endpoint?: string

Override the default endpoint.

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 MistralAI 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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