A class that wraps the FAISS (Facebook AI Similarity Search) vector database for efficient similarity search and clustering of dense vectors.

Hierarchy (view full)

Constructors

Properties

docstore: SynchronousInMemoryDocstore

Accessors

Methods

  • Adds an array of Document objects to the store.

    Parameters

    • documents: Document[]

      An array of Document objects.

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

    Returns Promise<string[]>

    A Promise that resolves when the documents have been added.

  • Adds an array of vectors and their corresponding Document objects to the store.

    Parameters

    • vectors: number[][]

      An array of vectors.

    • documents: Document[]

      An array of Document objects corresponding to the vectors.

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

    Returns Promise<string[]>

    A Promise that resolves with an array of document IDs when the vectors and documents have been added.

  • Method to delete documents.

    Parameters

    • params: {
          ids: string[];
      }

      Object containing the IDs of the documents to delete.

      • ids: string[]

    Returns Promise<void>

    A promise that resolves when the deletion is complete.

  • Merges the current FaissStore with another FaissStore.

    Parameters

    • targetIndex: FaissStore

      The FaissStore to merge with.

    Returns Promise<string[]>

    A Promise that resolves with an array of document IDs when the merge is complete.

  • Saves the current state of the FaissStore to a specified directory.

    Parameters

    • directory: string

      The directory to save the state to.

    Returns Promise<void>

    A Promise that resolves when the state has been saved.

  • Performs a similarity search in the vector store using a query vector and returns the top k results along with their scores.

    Parameters

    • query: number[]

      A query vector.

    • k: number

      The number of top results to return.

    Returns Promise<[Document, number][]>

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

  • Creates a new FaissStore from an array of Document objects and an Embeddings object.

    Parameters

    • docs: Document[]

      An array of Document objects.

    • embeddings: EmbeddingsInterface

      An Embeddings object.

    • OptionaldbConfig: {
          docstore?: SynchronousInMemoryDocstore;
      }

      An optional configuration object for the document store.

      • Optionaldocstore?: SynchronousInMemoryDocstore

    Returns Promise<FaissStore>

    A Promise that resolves with a new FaissStore instance.

  • Creates a new FaissStore from an existing FaissStore and an Embeddings object.

    Parameters

    • targetIndex: FaissStore

      An existing FaissStore.

    • embeddings: EmbeddingsInterface

      An Embeddings object.

    • OptionaldbConfig: {
          docstore?: SynchronousInMemoryDocstore;
      }

      An optional configuration object for the document store.

      • Optionaldocstore?: SynchronousInMemoryDocstore

    Returns Promise<FaissStore>

    A Promise that resolves with a new FaissStore instance.

  • Creates a new FaissStore from an array of texts, their corresponding metadata, and an Embeddings object.

    Parameters

    • texts: string[]

      An array of texts.

    • metadatas: object | object[]

      An array of metadata corresponding to the texts, or a single metadata object to be used for all texts.

    • embeddings: EmbeddingsInterface

      An Embeddings object.

    • OptionaldbConfig: {
          docstore?: SynchronousInMemoryDocstore;
      }

      An optional configuration object for the document store.

      • Optionaldocstore?: SynchronousInMemoryDocstore

    Returns Promise<FaissStore>

    A Promise that resolves with a new FaissStore instance.