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

89 lines
3.1 KiB
TypeScript

import { Embeddings, type EmbeddingsParams } from "@langchain/core/embeddings";
/**
* Interface for TogetherAIEmbeddingsParams parameters. Extends EmbeddingsParams and
* defines additional parameters specific to the TogetherAIEmbeddings class.
*/
export interface TogetherAIEmbeddingsParams extends EmbeddingsParams {
/**
* The API key to use for the TogetherAI API.
* @default {process.env.TOGETHER_AI_API_KEY}
*/
apiKey?: string;
/**
* Model name to use
* Alias for `model`
* @default {"togethercomputer/m2-bert-80M-8k-retrieval"}
*/
modelName?: string;
/**
* Model name to use
* @default {"togethercomputer/m2-bert-80M-8k-retrieval"}
*/
model?: string;
/**
* Timeout to use when making requests to TogetherAI.
* @default {undefined}
*/
timeout?: number;
/**
* The maximum number of documents to embed in a single request.
* @default {512}
*/
batchSize?: number;
/**
* Whether to strip new lines from the input text. May not be suitable
* for all use cases.
* @default {false}
*/
stripNewLines?: boolean;
}
/**
* Class for generating embeddings using the TogetherAI API. Extends the
* Embeddings class and implements TogetherAIEmbeddingsParams.
* @example
* ```typescript
* const embeddings = new TogetherAIEmbeddings({
* apiKey: process.env.TOGETHER_AI_API_KEY, // Default value
* model: "togethercomputer/m2-bert-80M-8k-retrieval", // Default value
* });
* const res = await embeddings.embedQuery(
* "What would be a good company name a company that makes colorful socks?"
* );
* ```
*/
export declare class TogetherAIEmbeddings extends Embeddings implements TogetherAIEmbeddingsParams {
modelName: string;
model: string;
apiKey: string;
batchSize: number;
stripNewLines: boolean;
timeout?: number;
private embeddingsAPIUrl;
constructor(fields?: Partial<TogetherAIEmbeddingsParams>);
private constructHeaders;
private constructBody;
/**
* Method to generate embeddings for an array of documents. Splits the
* documents into batches and makes requests to the TogetherAI 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
* embeddingWithRetry method with the document as the input.
* @param {string} text Document to generate an embedding for.
* @returns {Promise<number[]>} Promise that resolves to an embedding for the document.
*/
embedQuery(text: string): Promise<number[]>;
/**
* Private method to make a request to the TogetherAI API to generate
* embeddings. Handles the retry logic and returns the response from the
* API.
* @param {string} input The input text to embed.
* @returns Promise that resolves to the response from the API.
* @TODO Figure out return type and statically type it.
*/
private embeddingWithRetry;
}