Typesense vector store.

Hierarchy

Constructors

Properties

FilterType: Partial<MultiSearchRequestSchema>
embeddings: Embeddings

Methods

  • Add documents to the vector store. Will be updated if in the metadata there is a document with the same id if is using the default import function. Metadata will be added in the columns of the schema based on metadataColumnNames.

    Parameters

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

      Documents to add.

    Returns Promise<void>

  • Adds vectors to the vector store.

    Parameters

    • vectors: number[][]

      Vectors to add.

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

      Documents associated with the vectors.

    Returns Promise<void>

  • Parameters

    • Optional _params: Record<string, any>

    Returns Promise<void>

  • Delete documents from the vector store.

    Parameters

    • documentIds: string[]

      ids of the documents to delete

    Returns Promise<void>

  • Parameters

    • query: string
    • k: number = 4
    • filter: undefined | Partial<MultiSearchRequestSchema> = undefined
    • _callbacks: undefined | Callbacks = undefined

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

  • Search for similar documents with their similarity score.

    Parameters

    • vectorPrompt: number[]

      vector to search for

    • Optional k: number

      amount of results to return

    • filter: Partial<MultiSearchRequestSchema> = {}

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

    similar documents with their similarity score

  • Parameters

    • query: string
    • k: number = 4
    • filter: undefined | Partial<MultiSearchRequestSchema> = undefined
    • _callbacks: undefined | Callbacks = undefined

    Returns Promise<[Document<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

    • query: string

      Text to look up documents similar to.

    • options: MaxMarginalRelevanceSearchOptions<Partial<MultiSearchRequestSchema>>
    • _callbacks: undefined | Callbacks

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

    • List of documents selected by maximal marginal relevance.
  • Create a vector store from documents.

    Parameters

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

      documents

    • embeddings: Embeddings

      embeddings

    • config: TypesenseConfig

      Typesense configuration

    Returns Promise<Typesense>

    Typesense vector store

    Warning

    You can omit this method, and only use the constructor and addDocuments.

  • Create a vector store from texts.

    Parameters

    • texts: string[]
    • metadatas: object[]
    • embeddings: Embeddings
    • config: TypesenseConfig

    Returns Promise<Typesense>

    Typesense vector store

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