agsamantha/node_modules/@langchain/community/dist/embeddings/gradient_ai.d.ts
2024-10-02 15:15:21 -05:00

48 lines
1.9 KiB
TypeScript

import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";
/**
* Interface for GradientEmbeddings parameters. Extends EmbeddingsParams and
* defines additional parameters specific to the GradientEmbeddings class.
*/
export interface GradientEmbeddingsParams extends EmbeddingsParams {
/**
* Gradient AI Access Token.
* Provide Access Token if you do not wish to automatically pull from env.
*/
gradientAccessKey?: string;
/**
* Gradient Workspace Id.
* Provide workspace id if you do not wish to automatically pull from env.
*/
workspaceId?: string;
}
/**
* Class for generating embeddings using the Gradient AI's API. Extends the
* Embeddings class and implements GradientEmbeddingsParams and
*/
export declare class GradientEmbeddings extends Embeddings implements GradientEmbeddingsParams {
gradientAccessKey?: string;
workspaceId?: string;
batchSize: number;
model: any;
constructor(fields: GradientEmbeddingsParams);
/**
* Method to generate embeddings for an array of documents. Splits the
* documents into batches and makes requests to the Gradient API to generate
* embeddings.
* @param texts Array of documents to generate embeddings for.
* @returns Promise that resolves to a 2D array of embeddings for each document.
*/
embedDocuments(texts: string[]): Promise<number[][]>;
/**
* Method to generate an embedding for a single document. Calls the
* embedDocuments method with the document as the input.
* @param text Document to generate an embedding for.
* @returns Promise that resolves to an embedding for the document.
*/
embedQuery(text: string): Promise<number[]>;
/**
* Method to set the model to use for generating embeddings.
* @sets the class' `model` value to that of the retrieved Embeddings Model.
*/
setModel(): Promise<void>;
}