agsamantha/node_modules/@langchain/community/dist/vectorstores/milvus.d.ts

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2024-10-02 15:15:21 -05:00
import { MilvusClient, ClientConfig, keyValueObj } from "@zilliz/milvus2-sdk-node";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { VectorStore } from "@langchain/core/vectorstores";
import { Document } from "@langchain/core/documents";
/**
* Interface for the arguments required by the Milvus class constructor.
*/
export interface MilvusLibArgs {
collectionName?: string;
partitionName?: string;
primaryField?: string;
vectorField?: string;
textField?: string;
url?: string;
ssl?: boolean;
username?: string;
password?: string;
textFieldMaxLength?: number;
clientConfig?: ClientConfig;
autoId?: boolean;
indexCreateOptions?: IndexCreateOptions;
partitionKey?: string;
partitionKeyMaxLength?: number;
}
export interface IndexCreateOptions {
index_type: IndexType;
metric_type: MetricType;
params?: keyValueObj;
search_params?: keyValueObj;
}
export type MetricType = "L2" | "IP" | "COSINE";
/**
* Type representing the type of index used in the Milvus database.
*/
type IndexType = "FLAT" | "IVF_FLAT" | "IVF_SQ8" | "IVF_PQ" | "HNSW" | "RHNSW_FLAT" | "RHNSW_SQ" | "RHNSW_PQ" | "IVF_HNSW" | "ANNOY";
/**
* Class for interacting with a Milvus database. Extends the VectorStore
* class.
*/
export declare class Milvus extends VectorStore {
embeddings: EmbeddingsInterface;
get lc_secrets(): {
[key: string]: string;
};
_vectorstoreType(): string;
FilterType: string;
collectionName: string;
partitionName?: string;
numDimensions?: number;
autoId?: boolean;
primaryField: string;
vectorField: string;
textField: string;
textFieldMaxLength: number;
partitionKey?: string;
partitionKeyMaxLength?: number;
fields: string[];
client: MilvusClient;
indexCreateParams: IndexCreateOptions;
indexSearchParams: keyValueObj;
constructor(embeddings: EmbeddingsInterface, args: MilvusLibArgs);
/**
* Adds documents to the Milvus database.
* @param documents Array of Document instances to be added to the database.
* @param options Optional parameter that can include specific IDs for the documents.
* @returns Promise resolving to void.
*/
addDocuments(documents: Document[], options?: {
ids?: string[];
}): Promise<void>;
/**
* Adds vectors to the Milvus database.
* @param vectors Array of vectors to be added to the database.
* @param documents Array of Document instances associated with the vectors.
* @param options Optional parameter that can include specific IDs for the documents.
* @returns Promise resolving to void.
*/
addVectors(vectors: number[][], documents: Document[], options?: {
ids?: string[];
}): Promise<void>;
/**
* Searches for vectors in the Milvus database that are similar to a given
* vector.
* @param query Vector to compare with the vectors in the database.
* @param k Number of similar vectors to return.
* @param filter Optional filter to apply to the search.
* @returns Promise resolving to an array of tuples, each containing a Document instance and a similarity score.
*/
similaritySearchVectorWithScore(query: number[], k: number, filter?: string): Promise<[Document, number][]>;
/**
* Ensures that a collection exists in the Milvus database.
* @param vectors Optional array of vectors to be used if a new collection needs to be created.
* @param documents Optional array of Document instances to be used if a new collection needs to be created.
* @returns Promise resolving to void.
*/
ensureCollection(vectors?: number[][], documents?: Document[]): Promise<void>;
/**
* Ensures that a partition exists in the Milvus collection.
* @returns Promise resolving to void.
*/
ensurePartition(): Promise<void>;
/**
* Creates a collection in the Milvus database.
* @param vectors Array of vectors to be added to the new collection.
* @param documents Array of Document instances to be added to the new collection.
* @returns Promise resolving to void.
*/
createCollection(vectors: number[][], documents: Document[]): Promise<void>;
/**
* Retrieves the fields of a collection in the Milvus database.
* @returns Promise resolving to void.
*/
grabCollectionFields(): Promise<void>;
/**
* Creates a Milvus instance from a set of texts and their associated
* metadata.
* @param texts Array of texts to be added to the database.
* @param metadatas Array of metadata objects associated with the texts.
* @param embeddings Embeddings instance used to generate vector embeddings for the texts.
* @param dbConfig Optional configuration for the Milvus database.
* @returns Promise resolving to a new Milvus instance.
*/
static fromTexts(texts: string[], metadatas: object[] | object, embeddings: EmbeddingsInterface, dbConfig?: MilvusLibArgs): Promise<Milvus>;
/**
* Creates a Milvus instance from a set of Document instances.
* @param docs Array of Document instances to be added to the database.
* @param embeddings Embeddings instance used to generate vector embeddings for the documents.
* @param dbConfig Optional configuration for the Milvus database.
* @returns Promise resolving to a new Milvus instance.
*/
static fromDocuments(docs: Document[], embeddings: EmbeddingsInterface, dbConfig?: MilvusLibArgs): Promise<Milvus>;
/**
* Creates a Milvus instance from an existing collection in the Milvus
* database.
* @param embeddings Embeddings instance used to generate vector embeddings for the documents in the collection.
* @param dbConfig Configuration for the Milvus database.
* @returns Promise resolving to a new Milvus instance.
*/
static fromExistingCollection(embeddings: EmbeddingsInterface, dbConfig: MilvusLibArgs): Promise<Milvus>;
/**
* Deletes data from the Milvus database.
* @param params Object containing a filter to apply to the deletion.
* @returns Promise resolving to void.
*/
delete(params: {
filter?: string;
ids?: string[];
}): Promise<void>;
}
export {};