Class CassandraStore

constructor

• new CassandraStore(embeddings, args): CassandraStore

• Parameters

  • embeddings: EmbeddingsInterface

  • args: CassandraLibArgs

  Returns CassandraStore

FilterType

addDocuments

• addDocuments(documents): Promise<void>

• Method to add documents to the Cassandra database.

  Parameters

  • documents: Document[]

    The documents to add.

  Returns Promise<void>

  Promise that resolves when the documents have been added.

addVectors

• addVectors(vectors, documents): Promise<void>

• Method to save vectors to the Cassandra database.

  Parameters

  • vectors: number[][]

    Vectors to save.

  • documents: Document[]

    The documents associated with the vectors.

  Returns Promise<void>

  Promise that resolves when the vectors have been added.

getCassandraTable

• getCassandraTable(): CassandraTable

• Returns CassandraTable

maxMarginalRelevanceSearch

• maxMarginalRelevanceSearch(query, options): Promise<Document[]>

• Method to search for vectors that are similar to a given query vector, but with the results selected using the maximal marginal relevance.

  Parameters

  • query: string

    The query string.

  • options: MaxMarginalRelevanceSearchOptions<this["FilterType"]>

  Returns Promise<Document[]>

  List of documents selected by maximal marginal relevance.

search

• search(query, k, filter?, includeEmbedding?): Promise<[Document, number][]>

• Helper method to search for vectors that are similar to a given query vector.

  Parameters

  • query: number[]

    The query vector.

  • k: number

    The number of similar Documents to return.

  • Optional filter: Record<string, unknown> | Filter | Filter[]

    Optional filter to be applied as a WHERE clause.

  • Optional includeEmbedding: boolean

    Whether to include the embedding vectors in the results.

  Returns Promise<[Document, number][]>

  Promise that resolves with an array of tuples, each containing a Document and a score.

similaritySearchVectorWithScore

• similaritySearchVectorWithScore(query, k, filter?): Promise<[Document, number][]>

• Method to search for vectors that are similar to a given query vector.

  Parameters

  • query: number[]

    The query vector.

  • k: number

    The number of similar Documents to return.

  • Optional filter: Record<string, unknown> | Filter | Filter[]

    Optional filter to be applied as a WHERE clause.

  Returns Promise<[Document, number][]>

  Promise that resolves with an array of tuples, each containing a Document and a score.

Static fromDocuments

• fromDocuments(docs, embeddings, args): Promise<CassandraStore>

• Static method to create an instance of CassandraStore from documents.

  Parameters

  • docs: Document[]

    The documents to use.

  • embeddings: EmbeddingsInterface

    The embeddings to use.

  • args: CassandraLibArgs

    The arguments for the CassandraStore.

  Returns Promise<CassandraStore>

  Promise that resolves with a new instance of CassandraStore.

Static fromExistingIndex

• fromExistingIndex(embeddings, args): Promise<CassandraStore>

• Static method to create an instance of CassandraStore from an existing index.

  Parameters

  • embeddings: EmbeddingsInterface

    The embeddings to use.

  • args: CassandraLibArgs

    The arguments for the CassandraStore.

  Returns Promise<CassandraStore>

  Promise that resolves with a new instance of CassandraStore.

Static fromTexts

• fromTexts(texts, metadatas, embeddings, args): Promise<CassandraStore>

• Static method to create an instance of CassandraStore from texts.

  Parameters

  • texts: string[]

    The texts to use.

  • metadatas: object | object[]

    The metadata associated with the texts.

  • embeddings: EmbeddingsInterface

    The embeddings to use.

  • args: CassandraLibArgs

    The arguments for the CassandraStore.

  Returns Promise<CassandraStore>

  Promise that resolves with a new instance of CassandraStore.