import { SharedV2ProviderMetadata, LanguageModelV2, EmbeddingModelV2, ImageModelV2, ProviderV2 } from '@ai-sdk/provider';
import { FetchFunction } from '@ai-sdk/provider-utils';
import { z, ZodType } from 'zod/v4';

type OpenAICompatibleChatModelId = string;
declare const openaiCompatibleProviderOptions: z.ZodObject<{
    user: z.ZodOptional<z.ZodString>;
    reasoningEffort: z.ZodOptional<z.ZodString>;
}, z.core.$strip>;
type OpenAICompatibleProviderOptions = z.infer<typeof openaiCompatibleProviderOptions>;

declare const openaiCompatibleErrorDataSchema: z.ZodObject<{
    error: z.ZodObject<{
        message: z.ZodString;
        type: z.ZodOptional<z.ZodNullable<z.ZodString>>;
        param: z.ZodOptional<z.ZodNullable<z.ZodAny>>;
        code: z.ZodOptional<z.ZodNullable<z.ZodUnion<readonly [z.ZodString, z.ZodNumber]>>>;
    }, z.core.$strip>;
}, z.core.$strip>;
type OpenAICompatibleErrorData = z.infer<typeof openaiCompatibleErrorDataSchema>;
type ProviderErrorStructure<T> = {
    errorSchema: ZodType<T>;
    errorToMessage: (error: T) => string;
    isRetryable?: (response: Response, error?: T) => boolean;
};

/**
Extracts provider-specific metadata from API responses.
Used to standardize metadata handling across different LLM providers while allowing
provider-specific metadata to be captured.
*/
type MetadataExtractor = {
    /**
     * Extracts provider metadata from a complete, non-streaming response.
     *
     * @param parsedBody - The parsed response JSON body from the provider's API.
     *
     * @returns Provider-specific metadata or undefined if no metadata is available.
     *          The metadata should be under a key indicating the provider id.
     */
    extractMetadata: ({ parsedBody, }: {
        parsedBody: unknown;
    }) => Promise<SharedV2ProviderMetadata | undefined>;
    /**
     * Creates an extractor for handling streaming responses. The returned object provides
     * methods to process individual chunks and build the final metadata from the accumulated
     * stream data.
     *
     * @returns An object with methods to process chunks and build metadata from a stream
     */
    createStreamExtractor: () => {
        /**
         * Process an individual chunk from the stream. Called for each chunk in the response stream
         * to accumulate metadata throughout the streaming process.
         *
         * @param parsedChunk - The parsed JSON response chunk from the provider's API
         */
        processChunk(parsedChunk: unknown): void;
        /**
         * Builds the metadata object after all chunks have been processed.
         * Called at the end of the stream to generate the complete provider metadata.
         *
         * @returns Provider-specific metadata or undefined if no metadata is available.
         *          The metadata should be under a key indicating the provider id.
         */
        buildMetadata(): SharedV2ProviderMetadata | undefined;
    };
};

type OpenAICompatibleChatConfig = {
    provider: string;
    headers: () => Record<string, string | undefined>;
    url: (options: {
        modelId: string;
        path: string;
    }) => string;
    fetch?: FetchFunction;
    includeUsage?: boolean;
    errorStructure?: ProviderErrorStructure<any>;
    metadataExtractor?: MetadataExtractor;
    /**
     * Whether the model supports structured outputs.
     */
    supportsStructuredOutputs?: boolean;
    /**
     * The supported URLs for the model.
     */
    supportedUrls?: () => LanguageModelV2['supportedUrls'];
};
declare class OpenAICompatibleChatLanguageModel implements LanguageModelV2 {
    readonly specificationVersion = "v2";
    readonly supportsStructuredOutputs: boolean;
    readonly modelId: OpenAICompatibleChatModelId;
    private readonly config;
    private readonly failedResponseHandler;
    private readonly chunkSchema;
    constructor(modelId: OpenAICompatibleChatModelId, config: OpenAICompatibleChatConfig);
    get provider(): string;
    private get providerOptionsName();
    get supportedUrls(): Record<string, RegExp[]> | PromiseLike<Record<string, RegExp[]>>;
    private getArgs;
    doGenerate(options: Parameters<LanguageModelV2['doGenerate']>[0]): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>>;
    doStream(options: Parameters<LanguageModelV2['doStream']>[0]): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>>;
}

type OpenAICompatibleCompletionModelId = string;
declare const openaiCompatibleCompletionProviderOptions: z.ZodObject<{
    echo: z.ZodOptional<z.ZodBoolean>;
    logitBias: z.ZodOptional<z.ZodRecord<z.ZodString, z.ZodNumber>>;
    suffix: z.ZodOptional<z.ZodString>;
    user: z.ZodOptional<z.ZodString>;
}, z.core.$strip>;
type OpenAICompatibleCompletionProviderOptions = z.infer<typeof openaiCompatibleCompletionProviderOptions>;

type OpenAICompatibleCompletionConfig = {
    provider: string;
    includeUsage?: boolean;
    headers: () => Record<string, string | undefined>;
    url: (options: {
        modelId: string;
        path: string;
    }) => string;
    fetch?: FetchFunction;
    errorStructure?: ProviderErrorStructure<any>;
    /**
     * The supported URLs for the model.
     */
    supportedUrls?: () => LanguageModelV2['supportedUrls'];
};
declare class OpenAICompatibleCompletionLanguageModel implements LanguageModelV2 {
    readonly specificationVersion = "v2";
    readonly modelId: OpenAICompatibleCompletionModelId;
    private readonly config;
    private readonly failedResponseHandler;
    private readonly chunkSchema;
    constructor(modelId: OpenAICompatibleCompletionModelId, config: OpenAICompatibleCompletionConfig);
    get provider(): string;
    private get providerOptionsName();
    get supportedUrls(): Record<string, RegExp[]> | PromiseLike<Record<string, RegExp[]>>;
    private getArgs;
    doGenerate(options: Parameters<LanguageModelV2['doGenerate']>[0]): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>>;
    doStream(options: Parameters<LanguageModelV2['doStream']>[0]): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>>;
}

type OpenAICompatibleEmbeddingModelId = string;
declare const openaiCompatibleEmbeddingProviderOptions: z.ZodObject<{
    dimensions: z.ZodOptional<z.ZodNumber>;
    user: z.ZodOptional<z.ZodString>;
}, z.core.$strip>;
type OpenAICompatibleEmbeddingProviderOptions = z.infer<typeof openaiCompatibleEmbeddingProviderOptions>;

type OpenAICompatibleEmbeddingConfig = {
    /**
  Override the maximum number of embeddings per call.
     */
    maxEmbeddingsPerCall?: number;
    /**
  Override the parallelism of embedding calls.
    */
    supportsParallelCalls?: boolean;
    provider: string;
    url: (options: {
        modelId: string;
        path: string;
    }) => string;
    headers: () => Record<string, string | undefined>;
    fetch?: FetchFunction;
    errorStructure?: ProviderErrorStructure<any>;
};
declare class OpenAICompatibleEmbeddingModel implements EmbeddingModelV2<string> {
    readonly specificationVersion = "v2";
    readonly modelId: OpenAICompatibleEmbeddingModelId;
    private readonly config;
    get provider(): string;
    get maxEmbeddingsPerCall(): number;
    get supportsParallelCalls(): boolean;
    constructor(modelId: OpenAICompatibleEmbeddingModelId, config: OpenAICompatibleEmbeddingConfig);
    private get providerOptionsName();
    doEmbed({ values, headers, abortSignal, providerOptions, }: Parameters<EmbeddingModelV2<string>['doEmbed']>[0]): Promise<Awaited<ReturnType<EmbeddingModelV2<string>['doEmbed']>>>;
}

type OpenAICompatibleImageModelId = string;

type OpenAICompatibleImageModelConfig = {
    provider: string;
    headers: () => Record<string, string | undefined>;
    url: (options: {
        modelId: string;
        path: string;
    }) => string;
    fetch?: FetchFunction;
    errorStructure?: ProviderErrorStructure<any>;
    _internal?: {
        currentDate?: () => Date;
    };
};
declare class OpenAICompatibleImageModel implements ImageModelV2 {
    readonly modelId: OpenAICompatibleImageModelId;
    private readonly config;
    readonly specificationVersion = "v2";
    readonly maxImagesPerCall = 10;
    get provider(): string;
    constructor(modelId: OpenAICompatibleImageModelId, config: OpenAICompatibleImageModelConfig);
    doGenerate({ prompt, n, size, aspectRatio, seed, providerOptions, headers, abortSignal, }: Parameters<ImageModelV2['doGenerate']>[0]): Promise<Awaited<ReturnType<ImageModelV2['doGenerate']>>>;
}

interface OpenAICompatibleProvider<CHAT_MODEL_IDS extends string = string, COMPLETION_MODEL_IDS extends string = string, EMBEDDING_MODEL_IDS extends string = string, IMAGE_MODEL_IDS extends string = string> extends Omit<ProviderV2, 'imageModel'> {
    (modelId: CHAT_MODEL_IDS): LanguageModelV2;
    languageModel(modelId: CHAT_MODEL_IDS): LanguageModelV2;
    chatModel(modelId: CHAT_MODEL_IDS): LanguageModelV2;
    completionModel(modelId: COMPLETION_MODEL_IDS): LanguageModelV2;
    textEmbeddingModel(modelId: EMBEDDING_MODEL_IDS): EmbeddingModelV2<string>;
    imageModel(modelId: IMAGE_MODEL_IDS): ImageModelV2;
}
interface OpenAICompatibleProviderSettings {
    /**
  Base URL for the API calls.
     */
    baseURL: string;
    /**
  Provider name.
     */
    name: string;
    /**
  API key for authenticating requests. If specified, adds an `Authorization`
  header to request headers with the value `Bearer <apiKey>`. This will be added
  before any headers potentially specified in the `headers` option.
     */
    apiKey?: string;
    /**
  Optional custom headers to include in requests. These will be added to request headers
  after any headers potentially added by use of the `apiKey` option.
     */
    headers?: Record<string, string>;
    /**
  Optional custom url query parameters to include in request urls.
     */
    queryParams?: Record<string, string>;
    /**
  Custom fetch implementation. You can use it as a middleware to intercept requests,
  or to provide a custom fetch implementation for e.g. testing.
     */
    fetch?: FetchFunction;
    /**
  Include usage information in streaming responses.
     */
    includeUsage?: boolean;
}
/**
Create an OpenAICompatible provider instance.
 */
declare function createOpenAICompatible<CHAT_MODEL_IDS extends string, COMPLETION_MODEL_IDS extends string, EMBEDDING_MODEL_IDS extends string, IMAGE_MODEL_IDS extends string>(options: OpenAICompatibleProviderSettings): OpenAICompatibleProvider<CHAT_MODEL_IDS, COMPLETION_MODEL_IDS, EMBEDDING_MODEL_IDS, IMAGE_MODEL_IDS>;

export { type MetadataExtractor, OpenAICompatibleChatLanguageModel, type OpenAICompatibleChatModelId, OpenAICompatibleCompletionLanguageModel, type OpenAICompatibleCompletionModelId, type OpenAICompatibleCompletionProviderOptions, OpenAICompatibleEmbeddingModel, type OpenAICompatibleEmbeddingModelId, type OpenAICompatibleEmbeddingProviderOptions, type OpenAICompatibleErrorData, OpenAICompatibleImageModel, type OpenAICompatibleProvider, type OpenAICompatibleProviderOptions, type OpenAICompatibleProviderSettings, type ProviderErrorStructure, createOpenAICompatible };