import usearch from "usearch";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { SaveableVectorStore } from "@langchain/core/vectorstores";
import { Document } from "@langchain/core/documents";
import { SynchronousInMemoryDocstore } from "../stores/doc/in_memory.js";
/**
 * Interface that defines the arguments that can be passed to the
 * `USearch` constructor. It includes optional properties for a
 * `docstore`, `index`, and `mapping`.
 */
export interface USearchArgs {
    docstore?: SynchronousInMemoryDocstore;
    index?: usearch.Index;
    mapping?: Record<number, string>;
}
/**
 * Class that extends `SaveableVectorStore` and provides methods for
 * adding documents and vectors to a `usearch` index, performing
 * similarity searches, and saving the index.
 */
export declare class USearch extends SaveableVectorStore {
    _index?: usearch.Index;
    _mapping: Record<number, string>;
    docstore: SynchronousInMemoryDocstore;
    args: USearchArgs;
    _vectorstoreType(): string;
    constructor(embeddings: EmbeddingsInterface, args: USearchArgs);
    /**
     * Method that adds documents to the `usearch` index. It generates
     * embeddings for the documents and adds them to the index.
     * @param documents An array of `Document` instances to be added to the index.
     * @returns A promise that resolves with an array of document IDs.
     */
    addDocuments(documents: Document[]): Promise<string[]>;
    get index(): usearch.Index;
    private set index(value);
    /**
     * Method that adds vectors to the `usearch` index. It also updates the
     * mapping between vector IDs and document IDs.
     * @param vectors An array of vectors to be added to the index.
     * @param documents An array of `Document` instances corresponding to the vectors.
     * @returns A promise that resolves with an array of document IDs.
     */
    addVectors(vectors: number[][], documents: Document[]): Promise<string[]>;
    /**
     * Method that performs a similarity search in the `usearch` index. It
     * returns the `k` most similar documents to a given query vector, along
     * with their similarity scores.
     * @param query The query vector.
     * @param k The number of most similar documents to return.
     * @returns A promise that resolves with an array of tuples, each containing a `Document` and its similarity score.
     */
    similaritySearchVectorWithScore(query: number[], k: number): Promise<[Document<Record<string, any>>, number][]>;
    /**
     * Method that saves the `usearch` index and the document store to disk.
     * @param directory The directory where the index and document store should be saved.
     * @returns A promise that resolves when the save operation is complete.
     */
    save(directory: string): Promise<void>;
    /**
     * Static method that creates a new `USearch` instance from a list of
     * texts. It generates embeddings for the texts and adds them to the
     * `usearch` index.
     * @param texts An array of texts to be added to the index.
     * @param metadatas Metadata associated with the texts.
     * @param embeddings An instance of `Embeddings` used to generate embeddings for the texts.
     * @param dbConfig Optional configuration for the document store.
     * @returns A promise that resolves with a new `USearch` instance.
     */
    static fromTexts(texts: string[], metadatas: object[] | object, embeddings: EmbeddingsInterface, dbConfig?: {
        docstore?: SynchronousInMemoryDocstore;
    }): Promise<USearch>;
    /**
     * Static method that creates a new `USearch` instance from a list of
     * documents. It generates embeddings for the documents and adds them to
     * the `usearch` index.
     * @param docs An array of `Document` instances to be added to the index.
     * @param embeddings An instance of `Embeddings` used to generate embeddings for the documents.
     * @param dbConfig Optional configuration for the document store.
     * @returns A promise that resolves with a new `USearch` instance.
     */
    static fromDocuments(docs: Document[], embeddings: EmbeddingsInterface, dbConfig?: {
        docstore?: SynchronousInMemoryDocstore;
    }): Promise<USearch>;
}