Class that provides an interface to a Postgres vector database. It extends the VectorStore base class and implements methods for adding documents and vectors, performing similarity searches, and ensuring the existence of a table in the database.

Hierarchy (view full)

Constructors

Properties

FilterType: Metadata
chunkSize: number = 500
collectionMetadata: null | Metadata
collectionName: string = "langchain"
contentColumnName: string
extensionSchemaName: null | string
idColumnName: string
metadataColumnName: string
pool: Pool
schemaName: null | string
tableName: string
vectorColumnName: string
client?: PoolClient
collectionTableName?: string
distanceStrategy?: DistanceStrategy = "cosine"
filter?: Metadata

Accessors

Methods

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

    Parameters

    • documents: Document[]

      Array of Document instances.

    • Optionaloptions: {
          ids?: string[];
      }

      Optional arguments for adding documents

      • Optionalids?: string[]

    Returns Promise<void>

    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[]

      Array of Document instances.

    • Optionaloptions: {
          ids?: string[];
      }

      Optional arguments for adding documents

      • Optionalids?: string[]

    Returns Promise<void>

    Promise that resolves when the vectors have been added.

  • Method to create the HNSW index on the vector column.

    Parameters

    • config: {
          dimensions: number;
          distanceFunction?: string;
          efConstruction?: number;
          m?: number;
          namespace?: string;
      }
      • dimensions: number
      • OptionaldistanceFunction?: string
      • OptionalefConstruction?: number
      • Optionalm?: number
      • Optionalnamespace?: string

    Returns Promise<void>

    Promise that resolves with the query response of creating the index.

  • Method to delete documents from the vector store. It deletes the documents that match the provided ids or metadata filter. Matches ids exactly and metadata filter according to postgres jsonb containment. Ids and filter are mutually exclusive.

    Parameters

    • params: {
          filter?: Metadata;
          ids?: string[];
      }

      Object containing either an array of ids or a metadata filter object.

      • Optionalfilter?: Metadata
      • Optionalids?: string[]

    Returns Promise<void>

    Promise that resolves when the documents have been deleted.

    Error if neither ids nor filter are provided, or if both are provided.

    await vectorStore.delete({ ids: ["id1", "id2"] });
    
    await vectorStore.delete({ filter: { a: 1, b: 2 } });
    
  • Method to ensure the existence of the collection table in the database. It creates the table if it does not already exist.

    Returns Promise<void>

    Promise that resolves when the collection table has been ensured.

  • Method to ensure the existence of the table in the database. It creates the table if it does not already exist.

    Returns Promise<void>

    Promise that resolves when the table has been ensured.

  • Inserts a row for the collectionName provided at initialization if it does not exist and returns the collectionId.

    Returns Promise<string>

    The collectionId for the given collectionName.

  • 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.

    • Optionalfilter: Metadata

      Optional filter to apply to the search.

    Returns Promise<[Document, number][]>

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

  • Static method to create a new PGVectorStore instance from an array of Document instances. It adds the documents to the store.

    Parameters

    • docs: Document[]

      Array of Document instances.

    • embeddings: EmbeddingsInterface

      Embeddings instance.

    • dbConfig: PGVectorStoreArgs

      PGVectorStoreArgs instance.

    Returns Promise<PGVectorStore>

    Promise that resolves with a new instance of PGVectorStore.

  • Static method to create a new PGVectorStore 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: EmbeddingsInterface

      Embeddings instance.

    • dbConfig: PGVectorStoreArgs

      PGVectorStoreArgs instance.

    Returns Promise<PGVectorStore>

    Promise that resolves with a new instance of PGVectorStore.