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    Class MistralAIEmbeddings

    Class for generating embeddings using the MistralAI API.

    Hierarchy (View Summary)

    Implements

    Index

    Constructors

    constructor

    Properties

    apiKey batchSize beforeRequestHooks? encodingFormat endpoint httpClient? model modelName requestErrorHooks? responseHooks? serverURL? stripNewLines

    Methods

    addAllHooksToHttpClient embedDocuments embedQuery removeAllHooksFromHttpClient removeHookFromHttpClient

    Constructors

    Properties

    apiKey: string

    The API key to use.

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

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

    {512}
    beforeRequestHooks?: BeforeRequestHook[]

    A list of custom hooks that must follow (req: Request) => Awaitable<Request | void> They are automatically added when a ChatMistralAI instance is created

    encodingFormat: string = "float"

    The format of the output data.

    {"float"}
    endpoint: string

    use serverURL instead

    httpClient?: HTTPClient

    Optional custom HTTP client to manage API requests Allows users to add custom fetch implementations, hooks, as well as error and response processing.

    model: string = "mistral-embed"

    The name of the model to use.

    {"mistral-embed"}
    modelName: string = "mistral-embed"

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

    {"mistral-embed"}
    requestErrorHooks?: RequestErrorHook[]

    A list of custom hooks that must follow (err: unknown, req: Request) => Awaitable They are automatically added when a ChatMistralAI instance is created

    responseHooks?: ResponseHook[]

    A list of custom hooks that must follow (res: Response, req: Request) => Awaitable They are automatically added when a ChatMistralAI instance is created

    serverURL?: string

    Override the default server URL used by the Mistral SDK.

    stripNewLines: boolean = true

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

    {true}

    Methods

    • Returns void

    • 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.

    • 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.

    • Returns void

    • Parameters

      • hook: BeforeRequestHook | RequestErrorHook | ResponseHook

      Returns void

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