Install and import from "@langchain/cloudflare" instead.

Class that extends the VectorStore class and provides methods to interact with the Cloudflare Vectorize vector database.

Hierarchy

  • VectorStore
    • CloudflareVectorizeStore

Constructors

Properties

FilterType: string | object
caller: AsyncCaller
embeddings: EmbeddingsInterface
index: VectorizeIndex
namespace?: string
textKey: string

Methods

  • Method that adds documents to the Vectorize database.

    Parameters

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

      Array of documents to add.

    • Optionaloptions: string[] | {
          ids?: string[];
      }

      Optional ids for the documents.

    Returns Promise<string[]>

    Promise that resolves with the ids of the added documents.

  • Method that adds vectors to the Vectorize database.

    Parameters

    • vectors: number[][]

      Array of vectors to add.

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

      Array of documents associated with the vectors.

    • Optionaloptions: string[] | {
          ids?: string[];
      }

      Optional ids for the vectors.

    Returns Promise<string[]>

    Promise that resolves with the ids of the added vectors.

  • Parameters

    • OptionalkOrFields: number | Partial<VectorStoreRetrieverInput<CloudflareVectorizeStore>>
    • Optionalfilter: string | object
    • Optionalcallbacks: Callbacks
    • Optionaltags: string[]
    • Optionalmetadata: Record<string, unknown>
    • Optionalverbose: boolean

    Returns VectorStoreRetriever<CloudflareVectorizeStore>

  • 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<string | object>
    • _callbacks: undefined | Callbacks

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

    • List of documents selected by maximal marginal relevance.
  • Parameters

    • query: string
    • Optionalk: number
    • Optionalfilter: string | object
    • Optional_callbacks: Callbacks

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

  • Method that performs a similarity search in the Vectorize database and returns the results along with their scores.

    Parameters

    • query: number[]

      Query vector for the similarity search.

    • k: number

      Number of top results to return.

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

    Promise that resolves with an array of documents and their scores.

  • Parameters

    • query: string
    • Optionalk: number
    • Optionalfilter: string | object
    • Optional_callbacks: Callbacks

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

  • Returns Serialized

  • Static method that creates a new instance of the CloudflareVectorizeStore class from texts.

    Parameters

    • texts: string[]

      Array of texts to add to the Vectorize database.

    • metadatas: Record<string, VectorizeVectorMetadata> | Record<string, VectorizeVectorMetadata>[]

      Metadata associated with the texts.

    • embeddings: EmbeddingsInterface

      Embeddings to use for the texts.

    • dbConfig: VectorizeLibArgs

      Configuration for the Vectorize database.

    Returns Promise<CloudflareVectorizeStore>

    Promise that resolves with a new instance of the CloudflareVectorizeStore class.