Class CloudflareVectorizeStore

constructor

• new CloudflareVectorizeStore(embeddings, args): CloudflareVectorizeStore

• Parameters

  • embeddings: EmbeddingsInterface

  • args: VectorizeLibArgs

  Returns CloudflareVectorizeStore

FilterType

caller

index

textKey

Optional namespace

addDocuments

• addDocuments(documents, options?): Promise<string[]>

• Method that adds documents to the Vectorize database.

  Parameters

  • documents: Document[]

    Array of documents to add.

  • Optional options: string[] | {
        ids?: string[];
    }

    Optional ids for the documents.

  Returns Promise<string[]>

  Promise that resolves with the ids of the added documents.

addVectors

• addVectors(vectors, documents, options?): Promise<string[]>

• Method that adds vectors to the Vectorize database.

  Parameters

  • vectors: number[][]

    Array of vectors to add.

  • documents: Document[]

    Array of documents associated with the vectors.

  • Optional options: string[] | {
        ids?: string[];
    }

    Optional ids for the vectors.

  Returns Promise<string[]>

  Promise that resolves with the ids of the added vectors.

delete

• delete(params): Promise<void>

• Method that deletes vectors from the Vectorize database.

  Parameters

  • params: VectorizeDeleteParams

    Parameters for the delete operation.

  Returns Promise<void>

  Promise that resolves when the delete operation is complete.

similaritySearchVectorWithScore

• similaritySearchVectorWithScore(query, k, filter?): Promise<[Document, number][]>

• 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.

  • Optional filter: VectorizeVectorMetadataFilter

  Returns Promise<[Document, number][]>

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

Static fromDocuments

• fromDocuments(docs, embeddings, dbConfig): Promise<CloudflareVectorizeStore>

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

  Parameters

  • docs: Document[]

    Array of documents to add to the Vectorize database.

  • embeddings: EmbeddingsInterface

    Embeddings to use for the documents.

  • dbConfig: VectorizeLibArgs

    Configuration for the Vectorize database.

  Returns Promise<CloudflareVectorizeStore>

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

Static fromExistingIndex

• fromExistingIndex(embeddings, dbConfig): Promise<CloudflareVectorizeStore>

• Static method that creates a new instance of the CloudflareVectorizeStore class from an existing index.

  Parameters

  • embeddings: EmbeddingsInterface

    Embeddings to use for the documents.

  • dbConfig: VectorizeLibArgs

    Configuration for the Vectorize database.

  Returns Promise<CloudflareVectorizeStore>

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

Static fromTexts

• fromTexts(texts, metadatas, embeddings, dbConfig): Promise<CloudflareVectorizeStore>

• 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.