A path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.
Optional namespaceA map of aliases for constructor args. Keys are the attribute names, e.g. "foo". Values are the alias that will replace the key in serialization. This is used to eg. make argument names match Python.
A map of additional attributes to merge with constructor args. Keys are the attribute names, e.g. "foo". Values are the attribute values, which will be serialized. These attributes need to be accepted by the constructor as arguments.
The final serialized identifier for the module.
A map of secrets, which will be omitted from serialization. Keys are paths to the secret in constructor args, e.g. "foo.bar.baz". Values are the secret ids, which will be used when deserializing.
Method that adds documents to the Vectorize database.
Array of documents to add.
Optional options: string[] | { Optional ids for the documents.
Promise that resolves with the ids of the added documents.
Method that adds vectors to the Vectorize database.
Array of vectors to add.
Array of documents associated with the vectors.
Optional options: string[] | { Optional ids for the vectors.
Promise that resolves with the ids of the added vectors.
Optional kOrFields: number | Partial<VectorStoreRetrieverInput<CloudflareVectorizeStore>>Optional filter: string | objectOptional callbacks: CallbacksOptional tags: string[]Optional metadata: Record<string, unknown>Optional verbose: booleanMethod that deletes vectors from the Vectorize database.
Parameters for the delete operation.
Promise that resolves when the delete operation is complete.
Method that performs a similarity search in the Vectorize database and returns the results along with their scores.
Query vector for the similarity search.
Number of top results to return.
Promise that resolves with an array of documents and their scores.
Optional maxReturn documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.
Text to look up documents similar to.
Static fromStatic method that creates a new instance of the CloudflareVectorizeStore class from documents.
Array of documents to add to the Vectorize database.
Embeddings to use for the documents.
Configuration for the Vectorize database.
Promise that resolves with a new instance of the CloudflareVectorizeStore class.
Static fromStatic method that creates a new instance of the CloudflareVectorizeStore class from an existing index.
Embeddings to use for the documents.
Configuration for the Vectorize database.
Promise that resolves with a new instance of the CloudflareVectorizeStore class.
Static fromStatic method that creates a new instance of the CloudflareVectorizeStore class from texts.
Array of texts to add to the Vectorize database.
Metadata associated with the texts.
Embeddings to use for the texts.
Configuration for the Vectorize database.
Promise that resolves with a new instance of the CloudflareVectorizeStore class.
Static lc_Generated using TypeDoc
Class that extends the VectorStore class and provides methods to interact with the Cloudflare Vectorize vector database.