Class TigrisVectorStore

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

Hierarchy

  • VectorStore
    • TigrisVectorStore

Constructors

constructor

Properties

FilterType embeddings index?

Methods

addDocuments addVectors asRetriever delete maxMarginalRelevanceSearch? similaritySearch similaritySearchVectorWithScore similaritySearchWithScore toJSON toJSONNotImplemented fromDocuments fromExistingIndex fromTexts

Constructors

constructor

Properties

FilterType

FilterType: string | object

embeddings

embeddings: EmbeddingsInterface

Optionalindex

index?: any

Methods

addDocuments

  • addDocuments(documents, options?): Promise<void>

  • 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.

addVectors

  • addVectors(vectors, documents, options?): Promise<void>

  • 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.

asRetriever

  • asRetriever(kOrFields?, filter?, callbacks?, tags?, metadata?, verbose?): VectorStoreRetriever<TigrisVectorStore>

  • Parameters

    • OptionalkOrFields: number | Partial<VectorStoreRetrieverInput<TigrisVectorStore>>
    • Optionalfilter: string | object
    • Optionalcallbacks: Callbacks
    • Optionaltags: string[]
    • Optionalmetadata: Record<string, unknown>
    • Optionalverbose: boolean

    Returns VectorStoreRetriever<TigrisVectorStore>

delete

  • delete(_params?): Promise<void>

  • Parameters

    • Optional_params: Record<string, any>

    Returns Promise<void>

OptionalmaxMarginalRelevanceSearch

  • maxMarginalRelevanceSearch(query, options, _callbacks): Promise<DocumentInterface<Record<string, any>>[]>

  • 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.

similaritySearch

  • similaritySearch(query, k?, filter?, _callbacks?): Promise<DocumentInterface<Record<string, any>>[]>

  • Parameters

    • query: string
    • Optionalk: number
    • Optionalfilter: string | object
    • Optional_callbacks: Callbacks

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

similaritySearchVectorWithScore

  • similaritySearchVectorWithScore(query, k, filter?): Promise<[Document<Record<string, any>>, number][]>

  • 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.

similaritySearchWithScore

  • similaritySearchWithScore(query, k?, filter?, _callbacks?): Promise<[DocumentInterface<Record<string, any>>, number][]>

  • Parameters

    • query: string
    • Optionalk: number
    • Optionalfilter: string | object
    • Optional_callbacks: Callbacks

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

toJSON

  • toJSON(): Serialized

  • Returns Serialized

toJSONNotImplemented

StaticfromDocuments

  • fromDocuments(docs, embeddings, dbConfig): Promise<TigrisVectorStore>

  • 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.

StaticfromExistingIndex

  • fromExistingIndex(embeddings, dbConfig): Promise<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.

StaticfromTexts

  • fromTexts(texts, metadatas, embeddings, dbConfig): Promise<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.

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