244 lines
13 KiB
TypeScript
244 lines
13 KiB
TypeScript
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import { EmbeddingsInterface } from "@langchain/core/embeddings";
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import { VectorStore } from "@langchain/core/vectorstores";
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import { Cluster } from "couchbase";
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import { Document } from "@langchain/core/documents";
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/**
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* This interface define the optional fields for adding vector
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* - `ids` - vector of ids for each document. If undefined, then uuid will be used
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* - `metadata` - vector of metadata object for each document
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*/
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export interface AddVectorOptions {
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ids?: string[];
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metadata?: Record<string, any>[];
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}
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/**
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* This interface defines the fields required to initialize a vector store
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* These are the fields part of config:
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* @property {Cluster} cluster - The Couchbase cluster that the store will interact with.
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* @property {string} bucketName - The name of the bucket in the Couchbase cluster.
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* @property {string} scopeName - The name of the scope within the bucket.
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* @property {string} collectionName - The name of the collection within the scope.
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* @property {string} indexName - The name of the index to be used for vector search.
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* @property {string} textKey - The key to be used for text in the documents. Defaults to "text".
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* @property {string} embeddingKey - The key to be used for embeddings in the documents. Defaults to "embedding".
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* @property {boolean} scopedIndex - Whether to use a scoped index for vector search. Defaults to true.
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* @property {AddVectorOptions} addVectorOptions - Options for adding vectors with specific id/metadata
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*/
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export interface CouchbaseVectorStoreArgs {
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cluster: Cluster;
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bucketName: string;
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scopeName: string;
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collectionName: string;
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indexName: string;
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textKey?: string;
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embeddingKey?: string;
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scopedIndex?: boolean;
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addVectorOptions?: AddVectorOptions;
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}
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/**
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* This type defines the search filters used in couchbase vector search
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* - `fields`: Optional list of fields to include in the
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* metadata of results. Note that these need to be stored in the index.
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* If nothing is specified, defaults to all the fields stored in the index.
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* - `searchOptions`: Optional search options that are passed to Couchbase search. Defaults to empty object.
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*/
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type CouchbaseVectorStoreFilter = {
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fields?: any;
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searchOptions?: any;
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};
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/**
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* Class for interacting with the Couchbase database. It extends the
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* VectorStore class and provides methods for adding vectors and
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* documents, and searching for similar vectors.
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* Initiate the class using initialize() method.
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*/
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export declare class CouchbaseVectorStore extends VectorStore {
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FilterType: CouchbaseVectorStoreFilter;
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private metadataKey;
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private readonly defaultTextKey;
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private readonly defaultScopedIndex;
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private readonly defaultEmbeddingKey;
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private cluster;
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private _bucket;
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private _scope;
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private _collection;
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private bucketName;
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private scopeName;
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private collectionName;
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private indexName;
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private textKey;
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private embeddingKey;
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private scopedIndex;
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/**
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* The private constructor used to provide embedding to parent class.
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* Initialize the class using static initialize() method
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* @param embedding - object to generate embedding
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* @param config - the fields required to initialize a vector store
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*/
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private constructor();
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/**
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* initialize class for interacting with the Couchbase database.
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* It extends the VectorStore class and provides methods
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* for adding vectors and documents, and searching for similar vectors.
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* This also verifies the params
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*
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* @param embeddings - object to generate embedding
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* @param config - the fields required to initialize a vector store
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*/
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static initialize(embeddings: EmbeddingsInterface, config: CouchbaseVectorStoreArgs): Promise<CouchbaseVectorStore>;
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/**
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* An asynchrononous method to verify the search indexes.
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* It retrieves all indexes and checks if specified index is present.
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*
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* @throws - If the specified index does not exist in the database.
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*
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* @returns - returns promise true if no error is found
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*/
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private checkIndexExists;
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/**
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* An asynchronous method to verify the existence of a bucket.
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* It retrieves the bucket using the bucket manager and checks if the specified bucket is present.
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*
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* @throws - If the specified bucket does not exist in the database.
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*
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* @returns - Returns a promise that resolves to true if no error is found, indicating the bucket exists.
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*/
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private checkBucketExists;
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/**
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* An asynchronous method to verify the existence of a scope and a collection within that scope.
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* It retrieves all scopes and collections in the bucket, and checks if the specified scope and collection are present.
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*
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* @throws - If the specified scope does not exist in the bucket, or if the specified collection does not exist in the scope.
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*
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* @returns - Returns a promise that resolves to true if no error is found, indicating the scope and collection exist.
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*/
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private checkScopeAndCollectionExists;
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_vectorstoreType(): string;
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/**
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* Formats couchbase metadata by removing `metadata.` from initials
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* @param fields - all the fields of row
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* @returns - formatted metadata fields
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*/
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private formatMetadata;
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/**
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* Performs a similarity search on the vectors in the Couchbase database and returns the documents and their corresponding scores.
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*
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* @param queryEmbeddings - Embedding vector to look up documents similar to.
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* @param k - Number of documents to return. Defaults to 4.
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* @param filter - Optional search filter that are passed to Couchbase search. Defaults to empty object.
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* - `fields`: Optional list of fields to include in the
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* metadata of results. Note that these need to be stored in the index.
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* If nothing is specified, defaults to all the fields stored in the index.
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* - `searchOptions`: Optional search options that are passed to Couchbase search. Defaults to empty object.
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*
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* @returns - Promise of list of [document, score] that are the most similar to the query vector.
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*
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* @throws If the search operation fails.
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*/
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similaritySearchVectorWithScore(queryEmbeddings: number[], k?: number, filter?: CouchbaseVectorStoreFilter): Promise<[Document, number][]>;
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/**
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* Return documents that are most similar to the vector embedding.
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*
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* @param queryEmbeddings - Embedding to look up documents similar to.
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* @param k - The number of similar documents to return. Defaults to 4.
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* @param filter - Optional search filter that are passed to Couchbase search. Defaults to empty object.
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* - `fields`: Optional list of fields to include in the
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* metadata of results. Note that these need to be stored in the index.
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* If nothing is specified, defaults to all the fields stored in the index.
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* - `searchOptions`: Optional search options that are passed to Couchbase search. Defaults to empty object.
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*
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* @returns - A promise that resolves to an array of documents that match the similarity search.
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*/
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similaritySearchByVector(queryEmbeddings: number[], k?: number, filter?: CouchbaseVectorStoreFilter): Promise<Document[]>;
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/**
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* Return documents that are most similar to the query.
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*
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* @param query - Query to look up for similar documents
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* @param k - The number of similar documents to return. Defaults to 4.
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* @param filter - Optional search filter that are passed to Couchbase search. Defaults to empty object.
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* - `fields`: Optional list of fields to include in the
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* metadata of results. Note that these need to be stored in the index.
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* If nothing is specified, defaults to all the fields stored in the index.
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* - `searchOptions`: Optional search options that are passed to Couchbase search. Defaults to empty object.
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*
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* @returns - Promise of list of documents that are most similar to the query.
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*/
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similaritySearch(query: string, k?: number, filter?: CouchbaseVectorStoreFilter): Promise<Document[]>;
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/**
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* Return documents that are most similar to the query with their scores.
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*
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* @param query - Query to look up for similar documents
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* @param k - The number of similar documents to return. Defaults to 4.
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* @param filter - Optional search filter that are passed to Couchbase search. Defaults to empty object.
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* - `fields`: Optional list of fields to include in the
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* metadata of results. Note that these need to be stored in the index.
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* If nothing is specified, defaults to all the fields stored in the index.
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* - `searchOptions`: Optional search options that are passed to Couchbase search. Defaults to empty object.
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*
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* @returns - Promise of list of documents that are most similar to the query.
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*/
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similaritySearchWithScore(query: string, k?: number, filter?: CouchbaseVectorStoreFilter): Promise<[Document, number][]>;
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/**
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* upsert documents asynchronously into a couchbase collection
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* @param documentsToInsert Documents to be inserted into couchbase collection with embeddings, original text and metadata
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* @returns DocIds of the inserted documents
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*/
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private upsertDocuments;
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/**
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* Add vectors and corresponding documents to a couchbase collection
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* If the document IDs are passed, the existing documents (if any) will be
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* overwritten with the new ones.
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* @param vectors - The vectors to be added to the collection.
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* @param documents - The corresponding documents to be added to the collection.
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* @param options - Optional parameters for adding vectors.
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* This may include the IDs and metadata of the documents to be added. Defaults to an empty object.
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*
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* @returns - A promise that resolves to an array of document IDs that were added to the collection.
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*/
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addVectors(vectors: number[][], documents: Document[], options?: AddVectorOptions): Promise<string[]>;
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/**
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* Run texts through the embeddings and persist in vectorstore.
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* If the document IDs are passed, the existing documents (if any) will be
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* overwritten with the new ones.
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* @param documents - The corresponding documents to be added to the collection.
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* @param options - Optional parameters for adding documents.
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* This may include the IDs and metadata of the documents to be added. Defaults to an empty object.
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*
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* @returns - A promise that resolves to an array of document IDs that were added to the collection.
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*/
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addDocuments(documents: Document[], options?: AddVectorOptions): Promise<string[]>;
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/**
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* Create a new CouchbaseVectorStore from a set of documents.
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* This function will initialize a new store, add the documents to it, and then return the store.
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* @param documents - The documents to be added to the new store.
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* @param embeddings - The embeddings to be used for the documents.
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* @param config - The configuration for the new CouchbaseVectorStore. This includes the options for adding vectors.
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*
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* @returns - A promise that resolves to the new CouchbaseVectorStore that contains the added documents.
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*/
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static fromDocuments(documents: Document[], embeddings: EmbeddingsInterface, config: CouchbaseVectorStoreArgs): Promise<CouchbaseVectorStore>;
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/**
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* Create a new CouchbaseVectorStore from a set of texts.
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* This function will convert each text and its corresponding metadata into a Document,
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* initialize a new store, add the documents to it, and then return the store.
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* @param texts - The texts to be converted into Documents and added to the new store.
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* @param metadatas - The metadata for each text. If an array is passed, each text will have its corresponding metadata.
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* If not, all texts will have the same metadata.
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* @param embeddings - The embeddings to be used for the documents.
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* @param config - The configuration for the new CouchbaseVectorStore. This includes the options for adding vectors.
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*
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* @returns - A promise that resolves to the new CouchbaseVectorStore that contains the added documents.
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*/
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static fromTexts(texts: string[], metadatas: any, embeddings: EmbeddingsInterface, config: CouchbaseVectorStoreArgs): Promise<CouchbaseVectorStore>;
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/**
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* Delete documents asynchronously from the collection.
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* This function will attempt to remove each document in the provided list of IDs from the collection.
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* If an error occurs during the deletion of a document, an error will be thrown with the ID of the document and the error message.
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* @param ids - An array of document IDs to be deleted from the collection.
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*
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* @returns - A promise that resolves when all documents have been attempted to be deleted. If a document could not be deleted, an error is thrown.
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*/
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delete(ids: string[]): Promise<void>;
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}
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export {};
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