Class VectorStoreAbstract

constructor

• new VectorStore(embeddings, dbConfig): VectorStore

• Parameters

  • embeddings: EmbeddingsInterface

  • dbConfig: Record<string, any>

  Returns VectorStore

FilterType

embeddings

Abstract addDocuments

• addDocuments(documents, options?): Promise<void | string[]>

• Parameters

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

  • Optional options: AddDocumentOptions

  Returns Promise<void | string[]>

Abstract addVectors

• addVectors(vectors, documents, options?): Promise<void | string[]>

• Parameters

  • vectors: number[][]

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

  • Optional options: AddDocumentOptions

  Returns Promise<void | string[]>

asRetriever

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

• Parameters

  • Optional kOrFields: number | Partial<BaseRetrieverInput & {
        vectorStore: VectorStore;
        filter?: string | object;
        k?: number;
        searchType?: "similarity";
    }> | Partial<BaseRetrieverInput & {
        searchType: "mmr";
        vectorStore: VectorStore;
        filter?: string | object;
        k?: number;
        searchKwargs?: VectorStoreRetrieverMMRSearchKwargs;
    }>

  • Optional filter: string | object

  • Optional callbacks: CallbackManager | (BaseCallbackHandlerMethodsClass | BaseCallbackHandler)[]

  • Optional tags: string[]

  • Optional metadata: Record<string, unknown>

  • Optional verbose: boolean

  Returns VectorStoreRetriever<VectorStore>

delete

• delete(_params?): Promise<void>

• Parameters

  • Optional _params: Record<string, any>

  Returns Promise<void>

similaritySearch

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

• Parameters

  • query: string

  • k: number = 4

  • filter: undefined | string | object = undefined

  • _callbacks: undefined | CallbackManager | (BaseCallbackHandlerMethodsClass | BaseCallbackHandler)[] = undefined

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

Abstract similaritySearchVectorWithScore

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

• Parameters

  • query: number[]

  • k: number

  • Optional filter: string | object

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

similaritySearchWithScore

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

• Parameters

  • query: string

  • k: number = 4

  • filter: undefined | string | object = undefined

  • _callbacks: undefined | CallbackManager | (BaseCallbackHandlerMethodsClass | BaseCallbackHandler)[] = undefined

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

Optional maxMarginalRelevanceSearch

• 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 | CallbackManager | (BaseCallbackHandlerMethodsClass | BaseCallbackHandler)[]

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

  • List of documents selected by maximal marginal relevance.

Static fromDocuments

• fromDocuments(_docs, _embeddings, _dbConfig): Promise<VectorStore>

• Parameters

  • _docs: DocumentInterface<Record<string, any>>[]

  • _embeddings: EmbeddingsInterface

  • _dbConfig: Record<string, any>

  Returns Promise<VectorStore>

Static fromTexts

• fromTexts(_texts, _metadatas, _embeddings, _dbConfig): Promise<VectorStore>

• Parameters

  • _texts: string[]

  • _metadatas: object | object[]

  • _embeddings: EmbeddingsInterface

  • _dbConfig: Record<string, any>

  Returns Promise<VectorStore>