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

86 lines
2.7 KiB
TypeScript

import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";
export interface DeepInfraEmbeddingsRequest {
inputs: string[];
normalize?: boolean;
image?: string;
webhook?: string;
}
/**
* Input parameters for the DeepInfra embeddings
*/
export interface DeepInfraEmbeddingsParams extends EmbeddingsParams {
/**
* The API token to use for authentication.
* If not provided, it will be read from the `DEEPINFRA_API_TOKEN` environment variable.
*/
apiToken?: string;
/**
* The model ID to use for generating completions.
* Default: `sentence-transformers/clip-ViT-B-32`
*/
modelName?: string;
/**
* The maximum number of texts to embed in a single request. This is
* limited by the DeepInfra API to a maximum of 1024.
*/
batchSize?: number;
}
/**
* Response from the DeepInfra embeddings API.
*/
export interface DeepInfraEmbeddingsResponse {
/**
* The embeddings generated for the input texts.
*/
embeddings: number[][];
/**
* The number of tokens in the input texts.
*/
input_tokens: number;
/**
* The status of the inference.
*/
request_id?: string;
}
/**
* A class for generating embeddings using the DeepInfra API.
* @example
* ```typescript
* // Embed a query using the DeepInfraEmbeddings class
* const model = new DeepInfraEmbeddings();
* const res = await model.embedQuery(
* "What would be a good company name for a company that makes colorful socks?",
* );
* console.log({ res });
* ```
*/
export declare class DeepInfraEmbeddings extends Embeddings implements DeepInfraEmbeddingsParams {
apiToken: string;
batchSize: number;
modelName: string;
/**
* Constructor for the DeepInfraEmbeddings class.
* @param fields - An optional object with properties to configure the instance.
*/
constructor(fields?: Partial<DeepInfraEmbeddingsParams> & {
verbose?: boolean;
});
/**
* Generates embeddings for an array of texts.
* @param inputs - An array of strings to generate embeddings for.
* @returns A Promise that resolves to an array of embeddings.
*/
embedDocuments(inputs: string[]): Promise<number[][]>;
/**
* Generates an embedding for a single text.
* @param text - A string to generate an embedding for.
* @returns A Promise that resolves to an array of numbers representing the embedding.
*/
embedQuery(text: string): Promise<number[]>;
/**
* Generates embeddings with retry capabilities.
* @param request - An object containing the request parameters for generating embeddings.
* @returns A Promise that resolves to the API response.
*/
private embeddingWithRetry;
}