Embeddings interface for generating vector embeddings from text queries, enabling vector-based similarity searches.
Method to add vectors to the ClickHouse database.
The vectors to add.
The documents associated with the vectors.
Promise that resolves when the vectors have been added.
Creates a VectorStoreRetriever
instance with flexible configuration options.
Optional
kOrFields: number | Partial<VectorStoreRetrieverInput<ClickHouseStore>>If a number is provided, it sets the k
parameter (number of items to retrieve).
Optional
filter: ClickHouseFilterOptional 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.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: ClickHouseFilterOptional 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 to search for vectors that are similar to a given query vector.
The query vector.
The number of similar vectors to return.
Optional
filter: ClickHouseFilterOptional filter for the search results.
Promise that resolves with an array of tuples, each containing a Document and a 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: ClickHouseFilterOptional 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 ClickHouseStore from documents.
The documents to use.
The embeddings to use.
The arguments for the ClickHouseStore.
Promise that resolves with a new instance of ClickHouseStore.
Static
fromStatic method to create an instance of ClickHouseStore from an existing index.
The embeddings to use.
The arguments for the ClickHouseStore.
Promise that resolves with a new instance of ClickHouseStore.
Static
fromStatic method to create an instance of ClickHouseStore from texts.
The texts to use.
The metadata associated with the texts.
The embeddings to use.
The arguments for the ClickHouseStore.
Promise that resolves with a new instance of ClickHouseStore.
Class for interacting with the ClickHouse database. It extends the VectorStore class and provides methods for adding vectors and documents, searching for similar vectors, and creating instances from texts or documents.