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@langchain/community

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import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings"; //#region src/embeddings/zhipuai.d.ts /** * Interface that extends EmbeddingsParams and defines additional * parameters specific to the ZhipuAIEmbeddingsParams class. */ interface ZhipuAIEmbeddingsParams extends EmbeddingsParams { /** * Model Name to use */ modelName?: "embedding-2" | "embedding-3"; /** * ZhipuAI API key to use */ apiKey?: string; /** * Whether to strip new lines from the input text. */ stripNewLines?: boolean; } interface EmbeddingData { embedding: number[]; index: number; object: string; } interface TokenUsage { completion_tokens: number; prompt_tokens: number; total_tokens: number; } interface ZhipuAIEmbeddingsResult { model: string; data: EmbeddingData[]; object: string; usage: TokenUsage; } declare class ZhipuAIEmbeddings extends Embeddings implements ZhipuAIEmbeddingsParams { modelName: ZhipuAIEmbeddingsParams["modelName"]; apiKey?: string; stripNewLines: boolean; private embeddingsAPIURL; constructor(fields?: ZhipuAIEmbeddingsParams); private embeddingWithRetry; /** * 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[]>; /** * Method that takes an array of documents as input and returns a promise * that resolves to a 2D array of embeddings for each document. It calls * the embedQuery method for each document in the array. * @param documents Array of documents for which to generate embeddings. * @returns Promise that resolves to a 2D array of embeddings for each input document. */ embedDocuments(documents: string[]): Promise<number[][]>; } //#endregion export { ZhipuAIEmbeddings, ZhipuAIEmbeddingsParams, ZhipuAIEmbeddingsResult }; //# sourceMappingURL=zhipuai.d.ts.map