Defines the filter type used in search and delete operations. Can be an object for structured conditions or a string for simpler filtering.
Embeddings interface for generating vector embeddings from text queries, enabling vector-based similarity searches.
Adds vectors to the Voy database. The vectors are associated with the provided documents.
An array of vectors to be added to the database.
An array of Document
instances associated with the vectors.
Creates a VectorStoreRetriever
instance with flexible configuration options.
Optional
kOrFields: number | Partial<VectorStoreRetrieverInput<VoyVectorStore>>If a number is provided, it sets the k
parameter (number of items to retrieve).
Optional
filter: string | objectOptional filter criteria to limit the items retrieved based on the specified filter type.
Optional
callbacks: CallbacksOptional callbacks that may be triggered at specific stages of the retrieval process.
Optional
tags: string[]Tags to categorize or label the VectorStoreRetriever
. Defaults to an empty array if not provided.
Optional
metadata: Record<string, unknown>Additional metadata as key-value pairs to add contextual information for the retrieval process.
Optional
verbose: booleanIf true
, enables detailed logging for the retrieval process. Defaults to false
.
VectorStoreRetriever
instance based on the provided parameters.Method to delete data from the Voy index. It can delete data based on specific IDs or a filter.
Object that includes either an array of IDs or a filter for the data to be deleted.
Optional
deletePromise that resolves when the deletion is complete.
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.
Searches for documents similar to a text query by embedding the query and performing a similarity search on the resulting vector.
Text query for finding similar documents.
Optional
k: numberNumber of similar results to return. Defaults to 4.
Optional
filter: string | objectOptional filter based on FilterType
.
Optional
_callbacks: CallbacksOptional callbacks for monitoring search progress
A promise resolving to an array of DocumentInterface
instances representing similar documents.
Searches for vectors in the Voy database that are similar to the provided query vector.
The query vector.
The number of similar vectors to return.
A promise that resolves with an array of tuples, each containing a Document
instance and a similarity score.
Searches for documents similar to a text query by embedding the query, and returns results with similarity scores.
Text query for finding similar documents.
Optional
k: numberNumber of similar results to return. Defaults to 4.
Optional
filter: string | objectOptional filter based on FilterType
.
Optional
_callbacks: CallbacksOptional callbacks for monitoring search progress
A promise resolving to an array of tuples, each containing a document and its similarity score.
Static
fromCreates a new VoyVectorStore
instance from an array of Document
instances.
The documents are added to the Voy database.
An array of Document
instances.
An Embeddings
instance used to generate embeddings for the documents.
An instance of Voy client to use in the underlying operations.
A promise that resolves with a new VoyVectorStore
instance.
Static
fromCreates a new VoyVectorStore
instance from an array of text strings. The text
strings are converted to Document
instances and added to the Voy
database.
An array of text strings.
An array of metadata objects or a single metadata object. If an array is provided, it must have the same length as the texts
array.
An Embeddings
instance used to generate embeddings for the documents.
An instance of Voy client to use in the underlying operations.
A promise that resolves with a new VoyVectorStore
instance.
Class that extends
VectorStore
. It allows to perform similarity search using Voi similarity search engine. The class requires passing Voy Client as an input parameter.