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 _indexA 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 usearch index. It generates
embeddings for the documents and adds them to the index.
An array of Document instances to be added to the index.
A promise that resolves with an array of document IDs.
Method that adds vectors to the usearch index. It also updates the
mapping between vector IDs and document IDs.
An array of vectors to be added to the index.
An array of Document instances corresponding to the vectors.
A promise that resolves with an array of document IDs.
Optional kOrFields: number | Partial<VectorStoreRetrieverInput<USearch>>Optional filter: string | objectOptional callbacks: CallbacksOptional tags: string[]Optional metadata: Record<string, unknown>Optional verbose: booleanMethod that performs a similarity search in the usearch index. It
returns the k most similar documents to a given query vector, along
with their similarity scores.
The query vector.
The number of most similar documents to return.
A promise that resolves with an array of tuples, each containing a Document and its similarity score.
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 USearch instance from a list of
documents. It generates embeddings for the documents and adds them to
the usearch index.
An array of Document instances to be added to the index.
An instance of Embeddings used to generate embeddings for the documents.
Optional dbConfig: { Optional configuration for the document store.
Optional docstore?: SynchronousInMemoryDocstoreA promise that resolves with a new USearch instance.
Static fromStatic method that creates a new USearch instance from a list of
texts. It generates embeddings for the texts and adds them to the
usearch index.
An array of texts to be added to the index.
Metadata associated with the texts.
An instance of Embeddings used to generate embeddings for the texts.
Optional dbConfig: { Optional configuration for the document store.
Optional docstore?: SynchronousInMemoryDocstoreA promise that resolves with a new USearch instance.
Static lc_Static loadGenerated using TypeDoc
Class that extends
SaveableVectorStoreand provides methods for adding documents and vectors to ausearchindex, performing similarity searches, and saving the index.