Adds new documents to the SingleStoreDB database.
An array of Document objects.
Adds new vectors to the SingleStoreDB database.
An array of vectors.
An array of Document objects.
Optional kOrFields: number | Partial<VectorStoreRetrieverInput<SingleStoreVectorStore>>Optional filter: string | objectOptional callbacks: CallbacksOptional tags: string[]Optional metadata: Record<string, unknown>Optional verbose: booleanOptional k: numberOptional filter: string | objectOptional _callbacks: CallbacksPerforms a similarity search on the vectors stored in the SingleStoreDB database.
An array of numbers representing the query vector.
The number of nearest neighbors to return.
Optional filter: MetadataOptional metadata to filter the vectors by.
Top matching vectors with score
Optional k: numberOptional filter: string | objectOptional _callbacks: CallbacksOptional 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 fromCreates a new instance of the SingleStoreVectorStore class from a list of Document objects.
An array of Document objects.
An Embeddings object.
A SingleStoreVectorStoreConfig object.
A new SingleStoreVectorStore instance
Static fromCreates a new instance of the SingleStoreVectorStore class from a list of texts.
An array of strings.
An array of metadata objects.
An Embeddings object.
A SingleStoreVectorStoreConfig object.
A new SingleStoreVectorStore instance
Generated using TypeDoc
Class for interacting with SingleStoreDB, a high-performance distributed SQL database. It provides vector storage and vector functions.