Class that provides an interface to a Vercel Postgres vector database. It extends the VectorStore base class and implements methods for adding documents and vectors and performing similarity searches.

Hierarchy

Properties

FilterType: Metadata
client: VercelPoolClient
contentColumnName: string
embeddings: Embeddings
idColumnName: string
metadataColumnName: string
pool: VercelPool
tableName: string
vectorColumnName: string
filter?: Metadata

Methods

  • Method to add documents to the vector store. It converts the documents into vectors, and adds them to the store.

    Parameters

    • documents: Document<Record<string, any>>[]

      Array of Document instances.

    • Optional options: {
          ids?: string[];
      }
      • Optional ids?: string[]

    Returns Promise<string[]>

    Promise that resolves when the documents have been added.

  • Method to add vectors to the vector store. It converts the vectors into rows and inserts them into the database.

    Parameters

    • vectors: number[][]

      Array of vectors.

    • documents: Document<Record<string, any>>[]

      Array of Document instances.

    • Optional options: {
          ids?: string[];
      }
      • Optional ids?: string[]

    Returns Promise<string[]>

    Promise that resolves when the vectors have been added.

  • Parameters

    • query: string
    • Optional k: number
    • Optional filter: Metadata
    • Optional _callbacks: Callbacks

    Returns Promise<Document<Record<string, any>>[]>

  • Method to perform a similarity search in the vector store. It returns the k most similar documents to the query vector, along with their similarity scores.

    Parameters

    • query: number[]

      Query vector.

    • k: number

      Number of most similar documents to return.

    • Optional filter: Metadata

      Optional filter to apply to the search.

    Returns Promise<[Document<Record<string, any>>, number][]>

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

  • Parameters

    • query: string
    • Optional k: number
    • Optional filter: Metadata
    • Optional _callbacks: Callbacks

    Returns Promise<[Document<Record<string, any>>, number][]>

  • Return documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.

    Parameters

    Returns Promise<Document<Record<string, any>>[]>

    • List of documents selected by maximal marginal relevance.
  • Static method to create a new VercelPostgres instance from an array of texts and their metadata. It converts the texts into Document instances and adds them to the store.

    Parameters

    • texts: string[]

      Array of texts.

    • metadatas: object | object[]

      Array of metadata objects or a single metadata object.

    • embeddings: Embeddings

      Embeddings instance.

    • Optional dbConfig: Partial<VercelPostgresFields> & {
          postgresConnectionOptions?: VercelPostgresPoolConfig;
      }

    Returns Promise<VercelPostgres>

    Promise that resolves with a new instance of VercelPostgres.

  • Generates the SQL placeholders for a specific row at the provided index.

    Parameters

    • row: (string | Record<string, any>)[]
    • index: number

      The index of the row for which placeholders need to be generated.

    Returns string

    The SQL placeholders for the row values.

  • Constructs the SQL query for inserting rows into the specified table.

    Parameters

    • rows: (string | Record<string, any>)[][]

      The rows of data to be inserted, consisting of values and records.

    • useIdColumn: boolean

    Returns Promise<QueryResult<any>>

    The complete SQL INSERT INTO query string.

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