Method that adds documents to AstraDB.
Array of documents to add to AstraDB.
Optional
options: string[]Optional ids for the documents.
Promise that resolves the documents have been added.
Method to save vectors to AstraDB.
Vectors to save.
The documents associated with the vectors.
Optional
options: string[]Promise that resolves when the vectors have been added.
Creates a VectorStoreRetriever
instance with flexible configuration options.
Optional
kOrFields: number | Partial<VectorStoreRetrieverInput<AstraDBVectorStore>>If a number is provided, it sets the k
parameter (number of items to retrieve).
Optional
filter: CollectionFilterOptional 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 that deletes documents from AstraDB.
AstraDeleteParameters for the delete.
Promise that resolves when the documents have been deleted.
Return 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: CollectionFilterOptional filter based on FilterType
.
Optional
_callbacks: CallbacksOptional callbacks for monitoring search progress
A promise resolving to an array of DocumentInterface
instances representing similar documents.
Method that performs a similarity search in AstraDB and returns and similarity scores.
Query vector for the similarity search.
Number of top results to return.
Optional
filter: CollectionFilterOptional filter to apply to the search.
Promise that resolves with an array of documents and their scores.
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: CollectionFilterOptional 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
fromStatic method to create an instance of AstraDBVectorStore from documents.
The Documents to use.
The embeddings to use.
The arguments for the AstraDBVectorStore.
Promise that resolves with a new instance of AstraDBVectorStore.
Static
fromStatic method to create an instance of AstraDBVectorStore from an existing index.
The embeddings to use.
The arguments for the AstraDBVectorStore.
Promise that resolves with a new instance of AstraDBVectorStore.
Static
fromStatic method to create an instance of AstraDBVectorStore from texts.
The texts to use.
The metadata associated with the texts.
The embeddings to use.
The arguments for the AstraDBVectorStore.
Promise that resolves with a new instance of AstraDBVectorStore.
Embeddings interface for generating vector embeddings from text queries, enabling vector-based similarity searches.