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.
A 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.
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: booleanPerforms 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
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
Static
lc_Generated using TypeDoc
Class for interacting with SingleStoreDB, a high-performance distributed SQL database. It provides vector storage and vector functions.