Class IndexedDBVectorStore

new IndexedDBVectorStore(
    embeddings: EmbeddingsInterface<number[]>,
    args?: IndexedDBVectorStoreArgs,
): IndexedDBVectorStore

addDocuments(documents: Document<Record<string, any>>[]): Promise<void>

addVectors(
    vectors: number[][],
    documents: Document<Record<string, any>>[],
): Promise<void>

clear(): Promise<void>

close(): Promise<void>

count(): Promise<number>

maxMarginalRelevanceSearch(
    query: string,
    options: {
        fetchK?: number;
        filter?: IndexedDBVectorStoreFilter;
        k: number;
        lambda?: number;
    },
): Promise<Document<Record<string, any>>[]>

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

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

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

fromDocuments(
    documents: Document<Record<string, any>>[],
    embeddings: EmbeddingsInterface<number[]>,
    args?: IndexedDBVectorStoreArgs,
): Promise<IndexedDBVectorStore>

fromExistingIndex(
    embeddings: EmbeddingsInterface<number[]>,
    args?: IndexedDBVectorStoreArgs,
): Promise<IndexedDBVectorStore>

fromTexts(
    texts: string[],
    metadatas: object | object[],
    embeddings: EmbeddingsInterface<number[]>,
    args?: IndexedDBVectorStoreArgs,
): Promise<IndexedDBVectorStore>