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

Hierarchy

Constructors

Properties

FilterType: string | object
embeddings: Embeddings

Accessors

  • get index(): IndexFlatL2
  • Returns IndexFlatL2

  • set index(index): void
  • Parameters

    • index: IndexFlatL2

    Returns void

Methods

  • Adds an array of Document objects to the store.

    Parameters

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

      An array of Document objects.

    • Optional options: {
          ids?: string[];
      }
      • Optional ids?: 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<Record<string, any>>[]

      An array of Document objects corresponding to the vectors.

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

  • Returns Record<number, string>

  • 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.

  • Parameters

    • query: string
    • k: number = 4
    • filter: undefined | string | object = undefined
    • _callbacks: undefined | Callbacks = undefined

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

  • 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<Record<string, any>>, number][]>

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

  • Parameters

    • query: string
    • k: number = 4
    • filter: undefined | string | object = undefined
    • _callbacks: undefined | Callbacks = undefined

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

    Parameters

    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

    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: Embeddings

      An Embeddings object.

    • Optional dbConfig: {
          docstore?: SynchronousInMemoryDocstore;
      }

      An optional configuration object for the document store.

    Returns Promise<FaissStore>

    A Promise that resolves with a new FaissStore instance.

  • Returns Promise<{
        IndexFlatL2: typeof IndexFlatL2;
    }>

  • Returns Promise<{
        NameRegistry: typeof NameRegistry;
        Parser: typeof Parser;
    }>

  • Loads a FaissStore from a specified directory.

    Parameters

    • directory: string

      The directory to load the FaissStore from.

    • embeddings: Embeddings

      An Embeddings object.

    Returns Promise<FaissStore>

    A Promise that resolves with a new FaissStore instance.

  • Parameters

    Returns Promise<FaissStore>

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