import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";

//#region src/embeddings.d.ts
interface FireworksEmbeddingsParams extends EmbeddingsParams {
  /**
   * The Fireworks API key to use.
   */
  apiKey?: string;
  /**
   * The model name to use.
   * @default "nomic-ai/nomic-embed-text-v1.5"
   */
  model?: string;
  /**
   * The maximum number of documents to embed in a single request.
   * Fireworks currently limits this to 8.
   * @default 8
   */
  batchSize?: number;
  /**
   * Override the Fireworks base URL.
   * @default "https://api.fireworks.ai/inference/v1"
   */
  basePath?: string;
  /**
   * Additional headers to include with embedding requests.
   */
  headers?: Record<string, string>;
}
interface CreateFireworksEmbeddingRequest {
  model: string;
  input: string | string[];
}
/**
 * Fireworks embeddings integration.
 *
 * Setup:
 *
 * ```bash
 * npm install @langchain/fireworks @langchain/core
 * export FIREWORKS_API_KEY="your-api-key"
 * ```
 *
 * @example
 * ```typescript
 * import { FireworksEmbeddings } from "@langchain/fireworks";
 *
 * const embeddings = new FireworksEmbeddings();
 * const vector = await embeddings.embedQuery("hello world");
 * ```
 */
declare class FireworksEmbeddings extends Embeddings implements FireworksEmbeddingsParams {
  static lc_name(): string;
  lc_namespace: string[];
  lc_serializable: boolean;
  model: string;
  batchSize: number;
  apiKey: string;
  basePath: string;
  apiUrl: string;
  headers?: Record<string, string>;
  constructor(fields?: Partial<FireworksEmbeddingsParams>);
  get lc_secrets(): {
    [key: string]: string;
  } | undefined;
  embedDocuments(texts: string[]): Promise<number[][]>;
  embedQuery(text: string): Promise<number[]>;
  private embeddingWithRetry;
}
//#endregion
export { CreateFireworksEmbeddingRequest, FireworksEmbeddings, FireworksEmbeddingsParams };
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