Class TigrisVectorStore

constructor

• new TigrisVectorStore(embeddings, args): TigrisVectorStore

• Parameters

  • embeddings: EmbeddingsInterface

  • args: TigrisLibArgs

  Returns TigrisVectorStore

Optional index

addDocuments

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

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

  Parameters

  • documents: Document[]

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

  • Optional options: 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[]

    An array of Document instances corresponding to the vectors.

  • Optional options: 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.

similaritySearchVectorWithScore

• similaritySearchVectorWithScore(query, k, filter?): Promise<[Document, 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.

  • Optional filter: object

    Optional filter object to apply during the search.

  Returns Promise<[Document, number][]>

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

Static fromDocuments

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

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

  Parameters

  • docs: Document[]

    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 fromExistingIndex

• 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.

Static fromTexts

• 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.