Class ZepVectorStore

constructor

• new ZepVectorStore(embeddings, args): ZepVectorStore

• Parameters

  • embeddings: EmbeddingsInterface

  • args: IZepConfig

  Returns ZepVectorStore

client

collection

addDocuments

• addDocuments(documents): Promise<string[]>

• Adds documents to the collection. The documents are first embedded into vectors using the provided embedding model.

  Parameters

  • documents: Document[]

    The documents to add.

  Returns Promise<string[]>

  • A promise that resolves with the UUIDs of the added documents.

addVectors

• addVectors(vectors, documents): Promise<string[]>

• Adds vectors and corresponding documents to the collection.

  Parameters

  • vectors: number[][]

    The vectors to add.

  • documents: Document[]

    The corresponding documents to add.

  Returns Promise<string[]>

  • A promise that resolves with the UUIDs of the added documents.

delete

• delete(params): Promise<void>

• Deletes documents from the collection.

  Parameters

  • params: IZepDeleteParams

    The list of Zep document UUIDs to delete.

  Returns Promise<void>

maxMarginalRelevanceSearch

• maxMarginalRelevanceSearch(query, options): Promise<Document[]>

• 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<this["FilterType"]>

  Returns Promise<Document[]>

  • List of documents selected by maximal marginal relevance.

similaritySearch

• similaritySearch(query, k?, filter?, _callbacks?): Promise<Document[]>

• Performs a similarity search on the Zep collection.

  Parameters

  • query: string

    The query string to search for.

  • Optional k: number = 4

    The number of results to return. Defaults to 4.

  • Optional filter: unknown = undefined

    An optional set of JSONPath filters to apply to the search.

  • Optional _callbacks: any = undefined

    Optional callbacks. Currently not implemented.

  Returns Promise<Document[]>

  • A promise that resolves to an array of Documents that are similar to the query.

  Async

similaritySearchVectorWithScore

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

• Performs a similarity search in the collection and returns the results with their scores.

  Parameters

  • query: number[]

    The query vector.

  • k: number

    The number of results to return.

  • Optional filter: Record<string, unknown>

    The filter to apply to the search. Zep only supports Record<string, unknown> as filter.

  Returns Promise<[Document, number][]>

  • A promise that resolves with the search results and their scores.

similaritySearchWithScore

• similaritySearchWithScore(query, k?, filter?, _callbacks?): Promise<[Document, number][]>

• Parameters

  • query: string

  • k: number = 4

  • filter: undefined | Record<string, unknown> = undefined

  • _callbacks: undefined = undefined

  Returns Promise<[Document, number][]>

Static fromDocuments

• fromDocuments(docs, embeddings, zepConfig): Promise<ZepVectorStore>

• Creates a new ZepVectorStore instance from an array of Documents. Each Document is added to a Zep collection.

  Parameters

  • docs: Document[]

    The Documents to add.

  • embeddings: EmbeddingsInterface

    The embeddings to use for vectorizing the Document contents.

  • zepConfig: IZepConfig

    The configuration object for the Zep API.

  Returns Promise<ZepVectorStore>

  • A promise that resolves with the new ZepVectorStore instance.

Static fromTexts

• fromTexts(texts, metadatas, embeddings, zepConfig): Promise<ZepVectorStore>

• Creates a new ZepVectorStore instance from an array of texts. Each text is converted into a Document and added to the collection.

  Parameters

  • texts: string[]

    The texts to convert into Documents.

  • metadatas: object | object[]

    The metadata to associate with each Document. If an array is provided, each element is associated with the corresponding Document. If an object is provided, it is associated with all Documents.

  • embeddings: EmbeddingsInterface

    The embeddings to use for vectorizing the texts.

  • zepConfig: IZepConfig

    The configuration object for the Zep API.

  Returns Promise<ZepVectorStore>

  • A promise that resolves with the new ZepVectorStore instance.