Class for managing and operating vector search applications with Tigris, an open-source Serverless NoSQL Database and Search Platform.

Hierarchy

  • VectorStore
    • TigrisVectorStore

Constructors

Properties

FilterType: string | object

Defines the filter type used in search and delete operations. Can be an object for structured conditions or a string for simpler filtering.

embeddings: EmbeddingsInterface

Embeddings interface for generating vector embeddings from text queries, enabling vector-based similarity searches.

index?: any

Methods

  • Method to add an array of documents to the Tigris database.

    Parameters

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

      An array of Document instances to be added to the Tigris database.

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

      Optional parameter that can either be an array of string IDs or an object with a property 'ids' that is an array of string IDs.

    Returns Promise<void>

    A Promise that resolves when the documents have been added to the Tigris database.

  • Method to add vectors to the Tigris database.

    Parameters

    • vectors: number[][]

      An array of vectors to be added to the Tigris database.

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

      An array of Document instances corresponding to the vectors.

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

      Optional parameter that can either be an array of string IDs or an object with a property 'ids' that is an array of string IDs.

    Returns Promise<void>

    A Promise that resolves when the vectors have been added to the Tigris database.

  • Creates a VectorStoreRetriever instance with flexible configuration options.

    Parameters

    • OptionalkOrFields: number | Partial<VectorStoreRetrieverInput<TigrisVectorStore>>

      If a number is provided, it sets the k parameter (number of items to retrieve).

      • If an object is provided, it should contain various configuration options.
    • Optionalfilter: string | object

      Optional filter criteria to limit the items retrieved based on the specified filter type.

    • Optionalcallbacks: Callbacks

      Optional callbacks that may be triggered at specific stages of the retrieval process.

    • Optionaltags: string[]

      Tags to categorize or label the VectorStoreRetriever. Defaults to an empty array if not provided.

    • Optionalmetadata: Record<string, unknown>

      Additional metadata as key-value pairs to add contextual information for the retrieval process.

    • Optionalverbose: boolean

      If true, enables detailed logging for the retrieval process. Defaults to false.

    Returns VectorStoreRetriever<TigrisVectorStore>

    • A configured VectorStoreRetriever instance based on the provided parameters.

    Basic usage with a k value:

    const retriever = myVectorStore.asRetriever(5);
    

    Usage with a configuration object:

    const retriever = myVectorStore.asRetriever({
    k: 10,
    filter: myFilter,
    tags: ['example', 'test'],
    verbose: true,
    searchType: 'mmr',
    searchKwargs: { alpha: 0.5 },
    });
  • Deletes documents from the vector store based on the specified parameters.

    Parameters

    • Optional_params: Record<string, any>

      Flexible key-value pairs defining conditions for document deletion.

    Returns Promise<void>

    A promise that resolves once the deletion is complete.

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

    Parameters

    • query: string

      Text to look up documents similar to.

    • options: MaxMarginalRelevanceSearchOptions<string | object>
    • _callbacks: undefined | Callbacks

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

    • List of documents selected by maximal marginal relevance.
  • Searches for documents similar to a text query by embedding the query and performing a similarity search on the resulting vector.

    Parameters

    • query: string

      Text query for finding similar documents.

    • Optionalk: number

      Number of similar results to return. Defaults to 4.

    • Optionalfilter: string | object

      Optional filter based on FilterType.

    • Optional_callbacks: Callbacks

      Optional callbacks for monitoring search progress

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

    A promise resolving to an array of DocumentInterface instances representing similar documents.

  • Method to perform a similarity search in the Tigris database and return the k most similar vectors along with their similarity scores.

    Parameters

    • query: number[]

      The query vector.

    • k: number

      The number of most similar vectors to return.

    • Optionalfilter: object

      Optional filter object to apply during the search.

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

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

  • Searches for documents similar to a text query by embedding the query, and returns results with similarity scores.

    Parameters

    • query: string

      Text query for finding similar documents.

    • Optionalk: number

      Number of similar results to return. Defaults to 4.

    • Optionalfilter: string | object

      Optional filter based on FilterType.

    • Optional_callbacks: Callbacks

      Optional callbacks for monitoring search progress

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

    A promise resolving to an array of tuples, each containing a document and its similarity score.

  • Returns Serialized

  • Static method to create a new instance of TigrisVectorStore from an array of Document instances.

    Parameters

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

      An array of Document instances to be added to the Tigris database.

    • embeddings: EmbeddingsInterface

      An instance of Embeddings to be used for embedding the documents.

    • dbConfig: TigrisLibArgs

      An instance of TigrisLibArgs to be used for configuring the Tigris database.

    Returns Promise<TigrisVectorStore>

    A Promise that resolves to a new instance of TigrisVectorStore.

  • Static method to create a new instance of TigrisVectorStore from an existing index.

    Parameters

    • embeddings: EmbeddingsInterface

      An instance of Embeddings to be used for embedding the documents.

    • dbConfig: TigrisLibArgs

      An instance of TigrisLibArgs to be used for configuring the Tigris database.

    Returns Promise<TigrisVectorStore>

    A Promise that resolves to a new instance of TigrisVectorStore.

  • Static method to create a new instance of TigrisVectorStore from an array of texts.

    Parameters

    • texts: string[]

      An array of texts to be converted into Document instances and added to the Tigris database.

    • metadatas: object | object[]

      Either an array of metadata objects or a single metadata object to be associated with the texts.

    • embeddings: EmbeddingsInterface

      An instance of Embeddings to be used for embedding the texts.

    • dbConfig: TigrisLibArgs

      An instance of TigrisLibArgs to be used for configuring the Tigris database.

    Returns Promise<TigrisVectorStore>

    A Promise that resolves to a new instance of TigrisVectorStore.