A wrapper for an open-source database for vector-search with persistent storage. It simplifies retrieval, filtering, and management of embeddings.

Hierarchy

Constructors

Properties

FilterType: string | object

Methods

  • Adds vectors and their corresponding documents to the database.

    Parameters

    • vectors: number[][]

      The vectors to be added.

    • documents: Document<Record<string, any>>[]

      The corresponding documents to be added.

    Returns Promise<void>

    A Promise that resolves when the vectors and documents have been added.

  • Parameters

    • Optional _params: Record<string, any>

    Returns Promise<void>

  • Parameters

    • query: string
    • Optional k: number
    • Optional filter: string | object
    • Optional _callbacks: Callbacks

    Returns Promise<DocumentInterface<Record<string, any>>[]>

  • Performs a similarity search on the vectors in the database and returns the documents and their scores.

    Parameters

    • query: number[]

      The query vector.

    • k: number

      The number of results to return.

    Returns Promise<[Document<Record<string, any>>, number][]>

    A Promise that resolves with an array of tuples, each containing a Document and its score.

  • Parameters

    • query: string
    • Optional k: number
    • Optional filter: string | object
    • Optional _callbacks: Callbacks

    Returns Promise<[DocumentInterface<Record<string, any>>, number][]>

  • Return documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.

    Parameters

    Returns Promise<DocumentInterface<Record<string, any>>[]>

    • List of documents selected by maximal marginal relevance.

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