import { type LanguageModel } from "ai";
import type { AIProviderName } from "../constants/enums.js";
import { BaseProvider } from "../core/baseProvider.js";
import type { NeurolinkCredentials, StreamOptions, StreamResult, ValidationSchema } from "../types/index.js";
/**
 * Cohere Provider
 *
 * Routes Command R / Command R+ chat completions through Cohere's OpenAI-
 * compatible endpoint. Embed v3 and Rerank v3 are top-tier for RAG but are
 * accessed via the Cohere native SDK / dedicated embedding routes (out of
 * scope for the LLM provider).
 *
 * @see https://docs.cohere.com/docs/compatibility-api
 */
export declare class CohereProvider extends BaseProvider {
    private model;
    private apiKey;
    private baseURL;
    constructor(modelName?: string, sdk?: unknown, _region?: string, credentials?: NeurolinkCredentials["cohere"]);
    protected executeStream(options: StreamOptions, _analysisSchema?: ValidationSchema): Promise<StreamResult>;
    private executeStreamInner;
    protected getProviderName(): AIProviderName;
    protected getDefaultModel(): string;
    protected getAISDKModel(): LanguageModel;
    protected formatProviderError(error: unknown): Error;
    validateConfiguration(): Promise<boolean>;
    getConfiguration(): {
        provider: AIProviderName;
        model: string;
        defaultModel: string;
        baseURL: string;
    };
    /**
     * Default embedding model for Cohere.
     */
    protected getDefaultEmbeddingModel(): string;
    /**
     * Generate an embedding for a single text via Cohere's native /v2/embed
     * endpoint. Returns the float[] embedding vector.
     *
     * The shared OpenAI-compatible /compatibility/v1 path is chat-only; embed
     * lives on the native API (POST /v2/embed). Documented at
     * https://docs.cohere.com/reference/embed.
     */
    embed(text: string, modelName?: string): Promise<number[]>;
    /**
     * Batch embedding via Cohere's native /v2/embed endpoint. Cohere caps at
     * 96 inputs per request; larger batches are chunked.
     */
    embedMany(texts: string[], modelName?: string): Promise<number[][]>;
}
export default CohereProvider;