Class SingleStoreVectorStore

constructor

• new SingleStoreVectorStore(
      embeddings: EmbeddingsInterface,
      config: SingleStoreVectorStoreConfig,
  ): SingleStoreVectorStore

  Parameters

  • embeddings: EmbeddingsInterface
  • config: SingleStoreVectorStoreConfig

  Returns SingleStoreVectorStore

connectionPool

contentColumnName

distanceMetric

idColumnName

metadataColumnName

searchConfig

tableName

useFullTextIndex

useVectorIndex

vectorColumnName

vectorIndexName

vectorIndexOptions

vectorSize

_vectorstoreType

• _vectorstoreType(): string

  Returns string

addDocuments

• addDocuments(documents: Document[]): Promise<void>

  Adds new documents to the SingleStoreDB database.

  Parameters

  • documents: Document[]

    An array of Document objects.

  Returns Promise<void>

addVectors

• addVectors(vectors: number[][], documents: Document[]): Promise<void>

  Adds new vectors to the SingleStoreDB database.

  Parameters

  • vectors: number[][]

    An array of vectors.

  • documents: Document[]

    An array of Document objects.

  Returns Promise<void>

createTableIfNotExists

• createTableIfNotExists(): Promise<void>

  Creates a new table in the SingleStoreDB database if it does not already exist.

  Returns Promise<void>

end

• end(): Promise<void>

  Ends the connection to the SingleStoreDB database.

  Returns Promise<void>

setSearchConfig

• setSearchConfig(config: SearchConfig): Promise<void>

  Sets the search configuration for the SingleStoreVectorStore instance.

  Parameters

  • config: SearchConfig

    A SearchConfig object.

  Returns Promise<void>

similaritySearch

• similaritySearch(
      query: string,
      k?: number,
      filter?: Metadata,
      _callbacks?: any,
  ): Promise<DocumentInterface<Metadata>[]>

  Performs a similarity search on the texts stored in the SingleStoreDB

  Parameters

  • query: string

    A string representing the query text.

  • Optionalk: number

    The number of nearest neighbors to return. By default, it is 4.

  • Optionalfilter: Metadata

    Optional metadata to filter the texts by.

  • Optional_callbacks: any

    Callbacks object, not used in this implementation.

  Returns Promise<DocumentInterface<Metadata>[]>

  Top matching documents

similaritySearchTextAndVectorWithScore

• similaritySearchTextAndVectorWithScore(
      query: string,
      vector: number[],
      k: number,
      filter?: Metadata,
  ): Promise<[Document, number][]>

  Performs a similarity search on the texts stored in the SingleStoreDB using the specified search strategy and distance metric.

  Parameters

  • query: string

    A string representing the query text.

  • vector: number[]

    An array of numbers representing the query vector.

  • k: number

    The number of nearest neighbors to return.

  • Optionalfilter: Metadata

    Optional metadata to filter the texts by.

  Returns Promise<[Document, number][]>

  Top matching documents with score

similaritySearchVectorWithScore

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

  Performs a similarity search on the vectors stored in the SingleStoreDB database.

  Parameters

  • query: number[]

    An array of numbers representing the query vector.

  • k: number

    The number of nearest neighbors to return.

  • Optionalfilter: Metadata

    Optional metadata to filter the vectors by.

  Returns Promise<[Document, number][]>

  Top matching vectors with score

similaritySearchWithScore

• similaritySearchWithScore(
      query: string,
      k?: number,
      filter?: Metadata,
      _callbacks?: any,
  ): Promise<[DocumentInterface<Metadata>, number][]>

  Performs a similarity search on the texts stored in the SingleStoreDB

  Parameters

  • query: string

    A string representing the query text.

  • Optionalk: number

    The number of nearest neighbors to return. By default, it is 4.

  • Optionalfilter: Metadata

    Optional metadata to filter the texts by.

  • Optional_callbacks: any

  Returns Promise<[DocumentInterface<Metadata>, number][]>

  Top matching documents with score

StaticfromDocuments

• fromDocuments(
      docs: Document[],
      embeddings: EmbeddingsInterface,
      dbConfig: SingleStoreVectorStoreConfig,
  ): Promise<SingleStoreVectorStore>

  Creates a new instance of the SingleStoreVectorStore class from a list of Document objects.

  Parameters

  • docs: Document[]

    An array of Document objects.

  • embeddings: EmbeddingsInterface

    An Embeddings object.

  • dbConfig: SingleStoreVectorStoreConfig

    A SingleStoreVectorStoreConfig object.

  Returns Promise<SingleStoreVectorStore>

  A new SingleStoreVectorStore instance

StaticfromTexts

• fromTexts(
      texts: string[],
      metadatas: object[],
      embeddings: EmbeddingsInterface,
      dbConfig: SingleStoreVectorStoreConfig,
  ): Promise<SingleStoreVectorStore>

  Creates a new instance of the SingleStoreVectorStore class from a list of texts.

  Parameters

  • texts: string[]

    An array of strings.

  • metadatas: object[]

    An array of metadata objects.

  • embeddings: EmbeddingsInterface

    An Embeddings object.

  • dbConfig: SingleStoreVectorStoreConfig

    A SingleStoreVectorStoreConfig object.

  Returns Promise<SingleStoreVectorStore>

  A new SingleStoreVectorStore instance