/**
 * Cloudflare Workers AI Provider for embeddings and language models
 *
 * Provides embedding and language models via Cloudflare Workers AI API.
 * Default embedding model: @cf/baai/bge-m3
 * Default language model: @cf/meta/llama-3.3-70b-instruct-fp8-fast
 *
 * For language models, uses Cloudflare's OpenAI-compatible endpoint.
 *
 * @packageDocumentation
 */
import type { EmbeddingModel, LanguageModel } from 'ai';
/**
 * Default Cloudflare embedding model
 */
export declare const DEFAULT_CF_EMBEDDING_MODEL = "@cf/baai/bge-m3";
export declare const DEFAULT_CF_LANGUAGE_MODEL = "@cf/openai/gpt-oss-120b";
/**
 * Cloudflare Workers AI configuration
 */
export interface CloudflareConfig {
    /** Cloudflare Account ID */
    accountId?: string | undefined;
    /** Cloudflare API Token */
    apiToken?: string | undefined;
    /** AI Gateway (optional) */
    gateway?: string | undefined;
    /** Base URL override */
    baseUrl?: string | undefined;
}
/**
 * Cloudflare embedding model implementation (AI SDK v5 compatible)
 */
declare class CloudflareEmbeddingModel {
    readonly specificationVersion: "v2";
    readonly modelId: string;
    readonly provider = "cloudflare";
    readonly maxEmbeddingsPerCall = 100;
    readonly supportsParallelCalls = true;
    private config;
    private ai;
    constructor(modelId?: string, config?: CloudflareConfig, ai?: Ai | undefined);
    doEmbed(options: {
        values: string[];
        abortSignal?: AbortSignal | undefined;
        headers?: Record<string, string> | undefined;
    }): Promise<{
        embeddings: number[][];
        usage?: {
            tokens: number;
        } | undefined;
        response?: {
            headers?: Record<string, string> | undefined;
            body?: unknown;
        } | undefined;
    }>;
    private embedWithBinding;
    private embedWithRest;
}
/**
 * Create a Cloudflare Workers AI embedding model
 *
 * @example
 * ```ts
 * // Using REST API (outside Workers)
 * import { cloudflareEmbedding, embed } from 'ai-functions'
 *
 * const model = cloudflareEmbedding('@cf/baai/bge-m3')
 * const { embedding } = await embed({ model, value: 'hello world' })
 *
 * // Using AI binding (inside Workers)
 * const model = cloudflareEmbedding('@cf/baai/bge-m3', {}, env.AI)
 * ```
 */
export declare function cloudflareEmbedding(modelId?: string, config?: CloudflareConfig, ai?: Ai | undefined): EmbeddingModel<string>;
/**
 * Create a Cloudflare Workers AI language model using OpenAI-compatible endpoint
 *
 * Cloudflare provides an OpenAI-compatible API for language models at:
 * https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1
 *
 * @example
 * ```ts
 * import { cloudflareLanguageModel } from 'ai-providers'
 * import { generateText } from 'ai'
 *
 * const model = await cloudflareLanguageModel('@cf/meta/llama-3.3-70b-instruct-fp8-fast')
 * const { text } = await generateText({ model, prompt: 'Hello!' })
 * ```
 */
export declare function cloudflareLanguageModel(modelId?: string, config?: CloudflareConfig): Promise<LanguageModel>;
/**
 * Cloudflare Workers AI provider
 */
export declare const cloudflare: {
    /**
     * Create an embedding model
     */
    embedding: typeof cloudflareEmbedding;
    /**
     * Alias for embedding
     */
    textEmbeddingModel: typeof cloudflareEmbedding;
    /**
     * Create a language model (async - uses OpenAI-compatible endpoint)
     */
    languageModel: typeof cloudflareLanguageModel;
};
declare global {
    interface Ai {
        run<T = unknown>(model: string, inputs: unknown): Promise<T>;
    }
    type BaseAiTextEmbeddingsModels = '@cf/baai/bge-small-en-v1.5' | '@cf/baai/bge-base-en-v1.5' | '@cf/baai/bge-large-en-v1.5' | '@cf/baai/bge-m3' | (string & {});
}
export type { CloudflareEmbeddingModel };
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