@langchain/community
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Third-party integrations for LangChain.js
144 lines (143 loc) • 6.64 kB
TypeScript
import { IVectorIndexClient } from "@gomomento/sdk-core";
import { Document } from "@langchain/core/documents";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { MaxMarginalRelevanceSearchOptions, VectorStore } from "@langchain/core/vectorstores";
export interface DocumentProps {
ids: string[];
}
export interface MomentoVectorIndexLibArgs {
/**
* The Momento Vector Index client.
*/
client: IVectorIndexClient;
/**
* The name of the index to use to store the data.
* Defaults to "default".
*/
indexName?: string;
/**
* The name of the metadata field to use to store the text of the document.
* Defaults to "text".
*/
textField?: string;
/**
* Whether to create the index if it does not already exist.
* Defaults to true.
*/
ensureIndexExists?: boolean;
}
export interface DeleteProps {
/**
* The ids of the documents to delete.
*/
ids: string[];
}
/**
* A vector store that uses the Momento Vector Index.
*
* @remarks
* To sign up for a free Momento account, visit https://console.gomomento.com.
*/
export declare class MomentoVectorIndex extends VectorStore {
private client;
private indexName;
private textField;
private _ensureIndexExists;
_vectorstoreType(): string;
/**
* Creates a new `MomentoVectorIndex` instance.
* @param embeddings The embeddings instance to use to generate embeddings from documents.
* @param args The arguments to use to configure the vector store.
*/
constructor(embeddings: EmbeddingsInterface, args: MomentoVectorIndexLibArgs);
/**
* Returns the Momento Vector Index client.
* @returns The Momento Vector Index client.
*/
getClient(): IVectorIndexClient;
/**
* Creates the index if it does not already exist.
* @param numDimensions The number of dimensions of the vectors to be stored in the index.
* @returns Promise that resolves to true if the index was created, false if it already existed.
*/
private ensureIndexExists;
/**
* Converts the documents to a format that can be stored in the index.
*
* This is necessary because the Momento Vector Index requires that the metadata
* be a map of strings to strings.
* @param vectors The vectors to convert.
* @param documents The documents to convert.
* @param ids The ids to convert.
* @returns The converted documents.
*/
private prepareItemBatch;
/**
* Adds vectors to the index.
*
* @remarks If the index does not already exist, it will be created if `ensureIndexExists` is true.
* @param vectors The vectors to add to the index.
* @param documents The documents to add to the index.
* @param documentProps The properties of the documents to add to the index, specifically the ids.
* @returns Promise that resolves when the vectors have been added to the index. Also returns the ids of the
* documents that were added.
*/
addVectors(vectors: number[][], documents: Document<Record<string, any>>[], documentProps?: DocumentProps): Promise<void | string[]>;
/**
* Adds vectors to the index. Generates embeddings from the documents
* using the `Embeddings` instance passed to the constructor.
* @param documents Array of `Document` instances to be added to the index.
* @returns Promise that resolves when the documents have been added to the index.
*/
addDocuments(documents: Document[], documentProps?: DocumentProps): Promise<void>;
/**
* Deletes vectors from the index by id.
* @param params The parameters to use to delete the vectors, specifically the ids.
*/
delete(params: DeleteProps): Promise<void>;
/**
* Searches the index for the most similar vectors to the query vector.
* @param query The query vector.
* @param k The number of results to return.
* @returns Promise that resolves to the documents of the most similar vectors
* to the query vector.
*/
similaritySearchVectorWithScore(query: number[], k: number): Promise<[Document<Record<string, any>>, number][]>;
/**
* Return documents selected using the maximal marginal relevance.
* Maximal marginal relevance optimizes for similarity to the query AND diversity
* among selected documents.
*
* @param {string} query - Text to look up documents similar to.
* @param {number} options.k - Number of documents to return.
* @param {number} options.fetchK - Number of documents to fetch before passing to the MMR algorithm.
* @param {number} options.lambda - Number between 0 and 1 that determines the degree of diversity among the results,
* where 0 corresponds to maximum diversity and 1 to minimum diversity.
* @param {this["FilterType"]} options.filter - Optional filter
* @param _callbacks
*
* @returns {Promise<Document[]>} - List of documents selected by maximal marginal relevance.
*/
maxMarginalRelevanceSearch(query: string, options: MaxMarginalRelevanceSearchOptions<this["FilterType"]>): Promise<Document[]>;
/**
* Stores the documents in the index.
*
* Converts the documents to vectors using the `Embeddings` instance passed.
* @param texts The texts to store in the index.
* @param metadatas The metadata to store in the index.
* @param embeddings The embeddings instance to use to generate embeddings from the documents.
* @param dbConfig The configuration to use to instantiate the vector store.
* @param documentProps The properties of the documents to add to the index, specifically the ids.
* @returns Promise that resolves to the vector store.
*/
static fromTexts(texts: string[], metadatas: object[] | object, embeddings: EmbeddingsInterface, dbConfig: MomentoVectorIndexLibArgs, documentProps?: DocumentProps): Promise<MomentoVectorIndex>;
/**
* Stores the documents in the index.
* @param docs The documents to store in the index.
* @param embeddings The embeddings instance to use to generate embeddings from the documents.
* @param dbConfig The configuration to use to instantiate the vector store.
* @param documentProps The properties of the documents to add to the index, specifically the ids.
* @returns Promise that resolves to the vector store.
*/
static fromDocuments(docs: Document[], embeddings: EmbeddingsInterface, dbConfig: MomentoVectorIndexLibArgs, documentProps?: DocumentProps): Promise<MomentoVectorIndex>;
}