/**
 * Provider-specific type definitions for NeuroLink
 */
import type { UnknownRecord, JsonValue, StreamingCapability } from "./common.js";
import type { ProviderError } from "./errors.js";
import { AIProviderName, AnthropicModels, BedrockModels, DeepSeekModels, GoogleAIModels, LlamaCppModels, LMStudioModels, NvidiaNimModels, OpenAIModels, VertexModels } from "../constants/enums.js";
import type { Tool } from "ai";
import type { ValidationSchema } from "./aliases.js";
import type { EnhancedGenerateResult, GenerateResult, TextGenerationOptions } from "./generate.js";
import type { StreamOptions, StreamResult } from "./stream.js";
import type { ExternalMCPToolInfo } from "./externalMcp.js";
import type { ClaudeSubscriptionTier, AnthropicAuthMethod, AnthropicAuthConfig, SubscriptionInfo, OAuthToken } from "./subscription.js";
export type { ClaudeSubscriptionTier, AnthropicAuthMethod, AnthropicAuthConfig, SubscriptionInfo, } from "./subscription.js";
/**
 * Generic AI SDK model interface
 */
export type AISDKModel = {
    [key: string]: unknown;
};
/**
 * Union type of all supported model names
 */
export type SupportedModelName = BedrockModels | DeepSeekModels | OpenAIModels | VertexModels | GoogleAIModels | AnthropicModels | NvidiaNimModels | LMStudioModels | LlamaCppModels;
/**
 * Extract provider names from enum
 */
export type ProviderName = (typeof AIProviderName)[keyof typeof AIProviderName];
/**
 * Provider status information
 */
export type ProviderStatus = {
    provider: string;
    status: "working" | "failed" | "not-configured";
    configured: boolean;
    authenticated: boolean;
    error?: string;
    responseTime?: number;
    model?: string;
    /**
     * Subscription information for providers that support subscription tiers
     * (e.g., Anthropic Claude with Pro/Max/Team/Enterprise subscriptions)
     */
    subscription?: SubscriptionInfo;
    /**
     * The authentication method currently in use for this provider
     */
    authMethod?: AnthropicAuthMethod;
};
/**
 * Structural type for provider errors from external sources.
 * For throwing errors, use the ProviderError class from errors.ts.
 */
export type ProviderErrorLike = Error & {
    code?: string | number;
    statusCode?: number;
    provider?: string;
    originalError?: unknown;
};
/**
 * AWS Credential Configuration for Bedrock provider
 */
export type AWSCredentialConfig = {
    region?: string;
    profile?: string;
    roleArn?: string;
    roleSessionName?: string;
    timeout?: number;
    /** @deprecated Prefer maxAttempts to match AWS SDK v3 config */
    maxRetries?: number;
    /** Number of attempts as per AWS SDK v3 ("retry-mode") */
    maxAttempts?: number;
    enableDebugLogging?: boolean;
    /** Optional service endpoint override (e.g., VPC/Gov endpoints) */
    endpoint?: string;
};
/**
 * Per-provider credential overrides for generate() / stream() calls.
 *
 * When set on `NeurolinkConstructorConfig.credentials`, applies as the default
 * for all calls from that NeuroLink instance. When set on
 * `GenerateOptions.credentials` or `StreamOptions.credentials`, overrides the
 * instance default for that single call.
 *
 * Unset providers fall through to environment variables (existing behaviour).
 */
export type NeurolinkCredentials = {
    openai?: {
        apiKey?: string;
        baseURL?: string;
    };
    anthropic?: {
        apiKey?: string;
        oauthToken?: string;
    };
    googleAiStudio?: {
        apiKey?: string;
    };
    vertex?: {
        projectId?: string;
        location?: string;
        /** Vertex Express Mode — simplified API-key auth */
        apiKey?: string;
        /** Full service-account JSON string */
        serviceAccountKey?: string;
        /** Inline service-account fields (alternative to serviceAccountKey) */
        clientEmail?: string;
        privateKey?: string;
    };
    bedrock?: {
        accessKeyId?: string;
        secretAccessKey?: string;
        sessionToken?: string;
        region?: string;
    };
    sagemaker?: {
        accessKeyId?: string;
        secretAccessKey?: string;
        sessionToken?: string;
        region?: string;
        endpoint?: string;
    };
    azure?: {
        apiKey?: string;
        resourceName?: string;
        deploymentName?: string;
        apiVersion?: string;
    };
    mistral?: {
        apiKey?: string;
    };
    huggingFace?: {
        apiKey?: string;
        baseURL?: string;
    };
    openrouter?: {
        apiKey?: string;
        baseURL?: string;
    };
    litellm?: {
        apiKey?: string;
        baseURL?: string;
    };
    openaiCompatible?: {
        apiKey?: string;
        baseURL?: string;
    };
    ollama?: {
        baseURL?: string;
    };
    deepseek?: {
        apiKey?: string;
        baseURL?: string;
    };
    nvidiaNim?: {
        apiKey?: string;
        baseURL?: string;
    };
    lmStudio?: {
        apiKey?: string;
        baseURL?: string;
    };
    llamacpp?: {
        apiKey?: string;
        baseURL?: string;
    };
    xai?: {
        apiKey?: string;
        baseURL?: string;
    };
    groq?: {
        apiKey?: string;
        baseURL?: string;
    };
    cohere?: {
        apiKey?: string;
        baseURL?: string;
    };
    together?: {
        apiKey?: string;
        baseURL?: string;
    };
    fireworks?: {
        apiKey?: string;
        baseURL?: string;
    };
    perplexity?: {
        apiKey?: string;
        baseURL?: string;
    };
    cloudflare?: {
        apiKey?: string;
        accountId?: string;
        baseURL?: string;
    };
    replicate?: {
        apiToken?: string;
        baseUrl?: string;
    };
    voyage?: {
        apiKey?: string;
        baseURL?: string;
    };
    jina?: {
        apiKey?: string;
        baseURL?: string;
    };
    stability?: {
        apiKey?: string;
        baseURL?: string;
    };
    ideogram?: {
        apiKey?: string;
        baseURL?: string;
    };
    recraft?: {
        apiKey?: string;
        baseURL?: string;
    };
};
/**
 * Voyage AI /embeddings response shape.
 */
export type VoyageEmbeddingsResponse = {
    object: "list";
    data: {
        object: "embedding";
        embedding: number[];
        index: number;
    }[];
    model: string;
    usage?: {
        total_tokens?: number;
    };
};
/**
 * Jina AI /embeddings response shape (compatible with OpenAI's shape).
 */
export type JinaEmbeddingsResponse = {
    object?: string;
    data: {
        object?: string;
        embedding: number[];
        index: number;
    }[];
    model?: string;
    usage?: {
        total_tokens?: number;
        prompt_tokens?: number;
    };
};
/**
 * Jina AI /rerank response shape.
 */
export type JinaRerankResponse = {
    model?: string;
    results: {
        index: number;
        relevance_score: number;
        document?: {
            text?: string;
        };
    }[];
    usage?: {
        total_tokens?: number;
    };
};
/**
 * Stability AI /v2beta/stable-image/generate/{model} response shape
 * (returns either binary directly, or JSON with base64 when Accept is set
 * to application/json). We always request JSON for uniformity.
 */
export type StabilityImageResponse = {
    image?: string;
    finish_reason?: "SUCCESS" | "ERROR" | "CONTENT_FILTERED";
    seed?: number;
};
/**
 * Ideogram /api/v1/ideogram-v3/generate response shape.
 */
export type IdeogramImageResponse = {
    created?: string;
    data: {
        prompt?: string;
        resolution?: string;
        is_image_safe?: boolean;
        seed?: number;
        url?: string;
        style_type?: string;
    }[];
};
/**
 * Recraft /v1/images/generations response shape.
 */
export type RecraftImageResponse = {
    created?: number;
    data: {
        url?: string;
        b64_json?: string;
        image_id?: string;
    }[];
};
/**
 * NVIDIA NIM extra request body parameters passed via `providerOptions.openai.body`.
 * Lives here (not in providers/nvidiaNim.ts) per CLAUDE.md rule 2.
 */
export type NvidiaNimExtraBody = {
    top_k?: number;
    min_p?: number;
    repetition_penalty?: number;
    min_tokens?: number;
    chat_template?: string;
    request_id?: string;
    ignore_eos?: boolean;
    chat_template_kwargs?: {
        thinking?: boolean;
        enable_thinking?: boolean;
        reasoning_budget?: number;
    };
};
/**
 * AWS Credential Validation Result
 */
export type CredentialValidationResult = {
    isValid: boolean;
    credentialSource: string;
    region: string;
    hasExpiration: boolean;
    expirationTime?: Date;
    error?: string;
    debugInfo: {
        accessKeyId: string;
        hasSessionToken: boolean;
        providerConfig: Readonly<Required<AWSCredentialConfig>>;
    };
};
/**
 * Service Connectivity Test Result
 */
export type ServiceConnectivityResult = {
    bedrockAccessible: boolean;
    availableModels: number;
    responseTimeMs: number;
    error?: string;
    sampleModels: string[];
};
/**
 * Model Capabilities - Maximally Reusable
 */
export type ModelCapability = "text" | "vision" | "function-calling" | "embedding" | "audio" | "video" | "code" | "reasoning" | "multimodal";
/**
 * Model Use Cases - High Reusability
 */
export type ModelUseCase = "chat" | "completion" | "analysis" | "coding" | "creative" | "reasoning" | "translation" | "summarization" | "classification";
/**
 * Provider health status
 */
export type ProviderHealthStatus = "healthy" | "degraded" | "unhealthy" | "unknown";
/**
 * Stream processing phases
 */
export type StreamPhase = "initializing" | "streaming" | "processing" | "complete" | "error";
/**
 * Model Filter Configuration - High Reusability
 */
export type ModelFilter = {
    provider?: string;
    capability?: ModelCapability;
    useCase?: ModelUseCase;
    requireVision?: boolean;
    requireFunctionCalling?: boolean;
    maxTokens?: number;
    costLimit?: number;
};
/**
 * Model Resolution Context - High Reusability
 */
export type ModelResolutionContext = {
    requireCapabilities?: ModelCapability[];
    preferredProviders?: string[];
    useCase?: ModelUseCase;
    budgetConstraints?: {
        maxCostPerRequest?: number;
        maxTokens?: number;
    };
    performance?: {
        maxLatency?: number;
        minQuality?: number;
    };
};
/**
 * Model Statistics Object - High Reusability
 */
export type ModelStats = {
    name: string;
    provider: string;
    capabilities: ModelCapability[];
    useCases: ModelUseCase[];
    performance: {
        avgLatency?: number;
        avgTokensPerSecond?: number;
        reliability?: number;
    };
    pricing?: ModelPricing;
    metadata: {
        [key: string]: JsonValue;
    } & {
        version?: string;
        lastUpdated?: Date;
    };
};
/**
 * Model Pricing Information - High Reusability
 */
export type ModelPricing = {
    inputTokens?: {
        price: number;
        currency: string;
        per: number;
    };
    outputTokens?: {
        price: number;
        currency: string;
        per: number;
    };
    requestPrice?: {
        price: number;
        currency: string;
    };
    tier?: "free" | "basic" | "premium" | "enterprise";
    average?: number;
    min?: number;
    max?: number;
    free?: boolean;
};
/**
 * Provider capabilities
 */
export type ProviderCapabilities = {
    supportsStreaming: boolean;
    supportsTools: boolean;
    supportsImages: boolean;
    supportsAudio: boolean;
    maxTokens?: number;
    supportedModels: string[];
    /**
     * Whether the provider supports subscription-based features and tier management
     * When true, the provider can adapt behavior based on subscription tier
     */
    subscriptionAware?: boolean;
    /**
     * List of authentication methods supported by this provider
     * e.g., ["api_key", "oauth", "session_token", "environment"]
     */
    supportedAuthMethods?: string[];
};
/**
 * Provider configuration specifying provider and its available models (from core types)
 */
export type AIModelProviderConfig = {
    provider: AIProviderName;
    models: SupportedModelName[];
};
/**
 * Provider configuration for individual providers
 */
export type IndividualProviderConfig = {
    apiKey?: string;
    baseURL?: string;
    timeout?: number;
    retries?: number;
    model?: string;
    /**
     * The subscription tier for the provider (e.g., Claude Pro, Max, Team, Enterprise)
     * Used to determine rate limits, available features, and pricing
     */
    subscriptionTier?: ClaudeSubscriptionTier;
    /**
     * The authentication method to use for the provider
     * Supports API key, OAuth, session token, or environment variable
     */
    authMethod?: AnthropicAuthMethod;
    /**
     * Detailed authentication configuration including credentials and options
     */
    authConfig?: AnthropicAuthConfig;
    /**
     * Whether to enable beta features for the provider
     * Beta features may be unstable or subject to change
     */
    enableBetaFeatures?: boolean;
    [key: string]: unknown;
};
/**
 * Anthropic-specific provider configuration
 *
 * @description Extends the base provider configuration with Anthropic-specific
 * options for OAuth, subscription management, and beta features.
 */
export type AnthropicProviderConfig = IndividualProviderConfig & {
    /**
     * The subscription tier for Claude access
     */
    subscriptionTier?: ClaudeSubscriptionTier;
    /**
     * The authentication method to use
     */
    authMethod?: AnthropicAuthMethod;
    /**
     * Whether to enable beta features
     */
    enableBetaFeatures?: boolean;
    /**
     * OAuth token for OAuth authentication.
     * Required when authMethod is "oauth".
     */
    oauthToken?: OAuthToken;
    /**
     * OAuth configuration for OAuth-based authentication
     */
    oauthConfig?: {
        /**
         * OAuth client ID for the application
         */
        clientId?: string;
        /**
         * OAuth redirect URI for the callback
         */
        redirectUri?: string;
        /**
         * OAuth scopes to request
         */
        scopes?: string[];
        /**
         * OAuth authorization endpoint URL
         */
        authorizationEndpoint?: string;
        /**
         * OAuth token endpoint URL
         */
        tokenEndpoint?: string;
    };
};
/**
 * Type guard to check if a configuration is an AnthropicProviderConfig
 *
 * @param config - The configuration object to check
 * @returns True if the configuration is an AnthropicProviderConfig
 *
 * @example
 * ```typescript
 * const config = getProviderConfig();
 * if (isAnthropicConfig(config)) {
 *   // TypeScript knows config is AnthropicProviderConfig here
 *   console.log(config.subscriptionTier);
 *   console.log(config.oauthConfig?.clientId);
 * }
 * ```
 */
export declare function isAnthropicConfig(config: unknown): config is AnthropicProviderConfig;
/**
 * Configuration options for provider validation
 */
export type ProviderConfigOptions = {
    providerName: string;
    envVarName: string;
    setupUrl: string;
    description: string;
    instructions: string[];
    fallbackEnvVars?: string[];
    optional?: boolean;
};
/**
 * AI Provider type with flexible parameter support
 */
export type AIProvider = {
    stream(optionsOrPrompt: StreamOptions | string, analysisSchema?: ValidationSchema): Promise<StreamResult>;
    generate(optionsOrPrompt: TextGenerationOptions | string, analysisSchema?: ValidationSchema): Promise<EnhancedGenerateResult | null>;
    gen(optionsOrPrompt: TextGenerationOptions | string, analysisSchema?: ValidationSchema): Promise<EnhancedGenerateResult | null>;
    embed(text: string, modelName?: string): Promise<number[]>;
    embedMany(texts: string[], modelName?: string): Promise<number[][]>;
    setupToolExecutor(sdk: {
        customTools: Map<string, unknown>;
        executeTool: (toolName: string, params: unknown) => Promise<unknown>;
    }, functionTag: string): void;
    /**
     * Propagate trace context from NeuroLink SDK for parent-child span hierarchy.
     * Use this method instead of accessing `_traceContext` directly.
     */
    setTraceContext(ctx: {
        traceId: string;
        parentSpanId: string;
    } | null): void;
};
/**
 * Provider attempt result for iteration tracking (converted from interface)
 */
export type ProviderAttempt = {
    provider: AIProviderName;
    model: SupportedModelName;
    success: boolean;
    error?: string;
    stack?: string;
};
/**
 * Error types for provider creation
 */
export type ProviderCreationError = {
    code: "INVALID_PROVIDER" | "CONFIGURATION_ERROR" | "INSTANTIATION_ERROR";
    message: string;
    provider: string;
    details?: Record<string, unknown>;
};
/**
 * Provider factory function type
 */
export type ProviderFactory = (modelName?: string, providerName?: string, sdk?: unknown) => Promise<unknown>;
/**
 * Configuration options for the provider registry
 */
export type ProviderRegistryOptions = {
    /**
     * Enable loading of manual MCP configurations from .mcp-config.json
     * Should only be true for CLI mode, false for SDK mode
     */
    enableManualMCP?: boolean;
};
/**
 * Provider metadata type
 */
export type ProviderMetadata = {
    name: string;
    version: string;
    capabilities: ProviderCapability[];
    models: string[];
    healthStatus: ProviderHealthStatus;
};
/**
 * Provider capability type
 */
export type ProviderCapability = "text-generation" | "streaming" | "tool-calling" | "image-generation" | "embeddings";
/**
 * Extended tool type that combines AI SDK tools with external MCP tool info
 */
export type ExtendedTool = Tool & Partial<ExternalMCPToolInfo>;
/**
 * AI SDK generate result with steps support (extends GenerateResult)
 */
export type AISDKGenerateResult = GenerateResult & {
    steps?: Array<{
        toolCalls?: Array<{
            toolName?: string;
            name?: string;
            [key: string]: unknown;
        }>;
        [key: string]: unknown;
    }>;
    [key: string]: unknown;
};
/**
 * Bedrock tool usage structure
 */
export type BedrockToolUse = {
    toolUseId: string;
    name: string;
    input: Record<string, unknown>;
};
/**
 * Bedrock tool result structure
 */
export type BedrockToolResult = {
    toolUseId: string;
    content: Array<{
        text: string;
    }>;
    status: string;
};
/**
 * Bedrock content block structure
 */
export type BedrockContentBlock = {
    text?: string;
    image?: {
        format: "png" | "jpeg" | "gif" | "webp";
        source: {
            bytes?: Uint8Array | Buffer;
        };
    };
    document?: {
        format: "pdf" | "csv" | "doc" | "docx" | "xls" | "xlsx" | "html" | "txt" | "md";
        name: string;
        source: {
            bytes?: Uint8Array | Buffer;
        };
    };
    toolUse?: BedrockToolUse;
    toolResult?: BedrockToolResult;
};
/**
 * Bedrock message structure
 */
export type BedrockMessage = {
    role: "user" | "assistant";
    content: BedrockContentBlock[];
};
/**
 * Google AI Live media configuration
 */
export type GenAILiveMedia = {
    data: string;
    mimeType: string;
};
/**
 * Live server message inline data
 */
export type LiveServerMessagePartInlineData = {
    data?: string;
};
/**
 * Live server message model turn
 */
export type LiveServerMessageModelTurn = {
    parts?: Array<{
        inlineData?: LiveServerMessagePartInlineData;
    }>;
};
/**
 * Live server content structure
 */
export type LiveServerContent = {
    modelTurn?: LiveServerMessageModelTurn;
    interrupted?: boolean;
};
/**
 * Live server message structure
 */
export type LiveServerMessage = {
    serverContent?: LiveServerContent;
};
/**
 * Live connection callbacks
 */
export type LiveConnectCallbacks = {
    onopen?: () => void;
    onmessage?: (message: LiveServerMessage) => void;
    onerror?: (e: {
        message?: string;
    }) => void;
    onclose?: (e: {
        code?: number;
        reason?: string;
    }) => void;
};
/**
 * Live connection configuration
 */
export type LiveConnectConfig = {
    model: string;
    callbacks: LiveConnectCallbacks;
    config: {
        responseModalities: ("TEXT" | "IMAGE" | "AUDIO")[];
        speechConfig: {
            voiceConfig: {
                prebuiltVoiceConfig: {
                    voiceName: string;
                };
            };
        };
    };
};
/**
 * Google AI Live session interface
 */
export type GenAILiveSession = {
    sendRealtimeInput?: (payload: {
        media?: GenAILiveMedia;
        event?: string;
    }) => Promise<void> | void;
    sendInput?: (payload: {
        event?: string;
        media?: GenAILiveMedia;
    }) => Promise<void> | void;
    close?: (code?: number, reason?: string) => Promise<void> | void;
};
/**
 * Google AI generateContentStream response chunk
 */
export type GenAIStreamChunk = {
    text?: string;
    functionCalls?: Array<{
        name: string;
        args: Record<string, unknown>;
    }>;
    candidates?: Array<{
        content?: {
            parts?: Array<{
                text?: string;
                inlineData?: {
                    data?: string;
                    mimeType?: string;
                };
            }>;
        };
    }>;
};
/**
 * Google AI generate content response
 */
export type GenAIGenerateContentResponse = {
    candidates?: Array<{
        content?: {
            parts?: Array<{
                text?: string;
                inlineData?: {
                    data?: string;
                    mimeType?: string;
                };
            }>;
        };
    }>;
};
/**
 * Google AI models API interface
 */
export type GenAIModelsAPI = {
    generateContentStream: (params: {
        model: string;
        contents: Array<{
            role: string;
            parts: unknown[];
        }>;
        config?: Record<string, unknown>;
    }) => Promise<AsyncIterable<GenAIStreamChunk>>;
    generateContent: (params: {
        model: string;
        contents: Array<{
            role: string;
            parts: unknown[];
        }>;
        config?: Record<string, unknown>;
    }) => Promise<GenAIGenerateContentResponse>;
    embedContent: (params: {
        model: string;
        contents: string | string[];
        config?: Record<string, unknown>;
    }) => Promise<{
        embeddings?: Array<{
            values?: number[];
        }>;
    }>;
};
/**
 * Google AI client interface
 */
export type GenAIClient = {
    live: {
        connect: (config: LiveConnectConfig) => Promise<GenAILiveSession>;
    };
    models: GenAIModelsAPI;
};
/**
 * HTTP options for Google GenAI SDK
 * Allows custom fetch implementation for proxy support
 */
export type GoogleGenAIHttpOptions = {
    /** Custom fetch implementation for proxy support */
    fetch?: typeof fetch;
};
/**
 * Google GenAI constructor type
 * Supports both API key (Google AI Studio) and Vertex AI configurations
 */
export type GoogleGenAIClass = new (cfg: {
    apiKey: string;
    httpOptions?: GoogleGenAIHttpOptions;
} | {
    vertexai: boolean;
    project: string;
    location: string;
    httpOptions?: GoogleGenAIHttpOptions;
}) => GenAIClient;
/**
 * Google Vertex AI provider settings for native SDK configuration
 * Used with @google/genai SDK in vertexai mode
 *
 * Note: Authentication is handled via environment variables (GOOGLE_APPLICATION_CREDENTIALS)
 * or the temporary credentials file approach, not through these settings fields.
 */
export type GoogleVertexProviderSettings = {
    /** Google Cloud project ID */
    project: string;
    /** Google Cloud region/location (e.g., 'us-central1') */
    location: string;
    /** Optional custom fetch implementation */
    fetch?: typeof fetch;
};
/**
 * Anthropic Vertex AI settings for Claude models on Vertex
 * Used with @anthropic-ai/vertex-sdk
 */
export type AnthropicVertexSettings = {
    /** Google Cloud project ID */
    projectId: string;
    /** Google Cloud region for Anthropic models (e.g., 'us-east5') */
    region: string;
};
/**
 * OpenAI-compatible models endpoint response structure
 */
export type ModelsResponse = {
    data: Array<{
        id: string;
        object: string;
        created?: number;
        owned_by?: string;
    }>;
};
/**
 * Ollama tool call structure
 */
export type OllamaToolCall = {
    id: string;
    type: "function";
    function: {
        name: string;
        arguments: string;
    };
};
/**
 * Ollama tool result structure
 */
export type OllamaToolResult = {
    tool_call_id: string;
    content: string;
};
/**
 * Ollama message structure for conversation and tool execution
 */
export type OllamaMessage = {
    role: "system" | "user" | "assistant" | "tool";
    content: string | Array<{
        type: string;
        text?: string;
        [key: string]: unknown;
    }>;
    tool_calls?: OllamaToolCall[];
    images?: string[];
};
/**
 * Default model aliases for easy reference
 */
export declare const DEFAULT_MODEL_ALIASES: {
    readonly LATEST_OPENAI: OpenAIModels.GPT_4O;
    readonly FASTEST_OPENAI: OpenAIModels.GPT_4O_MINI;
    readonly LATEST_ANTHROPIC: AnthropicModels.CLAUDE_3_5_SONNET;
    readonly FASTEST_ANTHROPIC: AnthropicModels.CLAUDE_3_5_HAIKU;
    readonly LATEST_GOOGLE: GoogleAIModels.GEMINI_2_5_PRO;
    readonly FASTEST_GOOGLE: GoogleAIModels.GEMINI_2_5_FLASH;
    readonly BEST_CODING: AnthropicModels.CLAUDE_3_5_SONNET;
    readonly BEST_ANALYSIS: GoogleAIModels.GEMINI_2_5_PRO;
    readonly BEST_CREATIVE: AnthropicModels.CLAUDE_3_5_SONNET;
    readonly BEST_VALUE: GoogleAIModels.GEMINI_2_5_FLASH;
};
/**
 * @deprecated Use DEFAULT_MODEL_ALIASES instead. Will be removed in future version.
 */
export declare const ModelAliases: {
    readonly LATEST_OPENAI: OpenAIModels.GPT_4O;
    readonly FASTEST_OPENAI: OpenAIModels.GPT_4O_MINI;
    readonly LATEST_ANTHROPIC: AnthropicModels.CLAUDE_3_5_SONNET;
    readonly FASTEST_ANTHROPIC: AnthropicModels.CLAUDE_3_5_HAIKU;
    readonly LATEST_GOOGLE: GoogleAIModels.GEMINI_2_5_PRO;
    readonly FASTEST_GOOGLE: GoogleAIModels.GEMINI_2_5_FLASH;
    readonly BEST_CODING: AnthropicModels.CLAUDE_3_5_SONNET;
    readonly BEST_ANALYSIS: GoogleAIModels.GEMINI_2_5_PRO;
    readonly BEST_CREATIVE: AnthropicModels.CLAUDE_3_5_SONNET;
    readonly BEST_VALUE: GoogleAIModels.GEMINI_2_5_FLASH;
};
/**
 * Default provider configurations
 */
export declare const DEFAULT_PROVIDER_CONFIGS: AIModelProviderConfig[];
/**
 * Adaptive semaphore configuration for concurrency management
 */
export type AdaptiveSemaphoreConfig = {
    initialConcurrency: number;
    maxConcurrency: number;
    minConcurrency: number;
};
/**
 * Metrics for adaptive semaphore performance tracking
 */
export type AdaptiveSemaphoreMetrics = {
    activeRequests: number;
    currentConcurrency: number;
    completedCount: number;
    errorCount: number;
    averageResponseTime: number;
    waitingCount: number;
};
/**
 * AWS configuration options for SageMaker client
 */
export type SageMakerConfig = {
    /** AWS region for SageMaker service */
    region: string;
    /** AWS access key ID */
    accessKeyId: string;
    /** AWS secret access key */
    secretAccessKey: string;
    /** AWS session token (optional, for temporary credentials) */
    sessionToken?: string;
    /** Request timeout in milliseconds */
    timeout?: number;
    /** Maximum number of retry attempts */
    maxRetries?: number;
    /** Custom SageMaker endpoint URL (optional) */
    endpoint?: string;
};
/**
 * Model-specific configuration for SageMaker endpoints
 */
export type SageMakerModelConfig = {
    /** SageMaker endpoint name */
    endpointName: string;
    /** Model type for request/response formatting */
    modelType?: "llama" | "mistral" | "claude" | "huggingface" | "jumpstart" | "custom";
    /** Content type for requests */
    contentType?: string;
    /** Accept header for responses */
    accept?: string;
    /** Custom attributes for the endpoint */
    customAttributes?: string;
    /** Input format specification */
    inputFormat?: "huggingface" | "jumpstart" | "custom";
    /** Output format specification */
    outputFormat?: "huggingface" | "jumpstart" | "custom";
    /** Maximum tokens for generation */
    maxTokens?: number;
    /** Temperature parameter */
    temperature?: number;
    /** Top-p parameter */
    topP?: number;
    /** Stop sequences */
    stopSequences?: string[];
    /** Initial concurrency for batch processing */
    initialConcurrency?: number;
    /** Maximum concurrency for batch processing */
    maxConcurrency?: number;
    /** Minimum concurrency for batch processing */
    minConcurrency?: number;
    /** Maximum concurrent detection tests */
    maxConcurrentDetectionTests?: number;
};
/**
 * SageMaker endpoint information and metadata
 */
export type SageMakerEndpointInfo = {
    /** Endpoint name */
    endpointName: string;
    /** Endpoint ARN */
    endpointArn: string;
    /** Associated model name */
    modelName: string;
    /** EC2 instance type */
    instanceType: string;
    /** Endpoint creation timestamp */
    creationTime: string;
    /** Last modification timestamp */
    lastModifiedTime: string;
    /** Current endpoint status */
    endpointStatus: "InService" | "Creating" | "Updating" | "SystemUpdating" | "RollingBack" | "Deleting" | "Failed";
    /** Current instance count */
    currentInstanceCount?: number;
    /** Variant weights for A/B testing */
    productionVariants?: Array<{
        variantName: string;
        modelName: string;
        initialInstanceCount: number;
        instanceType: string;
        currentWeight?: number;
    }>;
};
/**
 * Token usage and billing information
 */
export type SageMakerUsage = {
    /** Number of prompt tokens */
    promptTokens: number;
    /** Number of completion tokens */
    completionTokens: number;
    /** Total tokens used */
    total: number;
    /** Request processing time in milliseconds */
    requestTime?: number;
    /** Model inference time in milliseconds */
    inferenceTime?: number;
    /** Estimated cost in USD */
    estimatedCost?: number;
};
/**
 * Parameters for SageMaker endpoint invocation
 */
export type InvokeEndpointParams = {
    /** Endpoint name to invoke */
    EndpointName: string;
    /** Request body as string or Uint8Array */
    Body: string | Uint8Array;
    /** Content type of the request */
    ContentType?: string;
    /** Accept header for response format */
    Accept?: string;
    /** Custom attributes for the request */
    CustomAttributes?: string;
    /** Target model for multi-model endpoints */
    TargetModel?: string;
    /** Target variant for A/B testing */
    TargetVariant?: string;
    /** Inference ID for request tracking */
    InferenceId?: string;
};
/**
 * Response from SageMaker endpoint invocation
 */
export type InvokeEndpointResponse = {
    /** Response body */
    Body?: Uint8Array;
    /** Content type of the response */
    ContentType?: string;
    /** Invoked production variant */
    InvokedProductionVariant?: string;
    /** Custom attributes in the response */
    CustomAttributes?: string;
};
/**
 * Streaming response chunk from SageMaker
 */
export type SageMakerStreamChunk = {
    /** Text content in the chunk */
    content?: string;
    /** Indicates if this is the final chunk */
    done?: boolean;
    /** Usage information (only in final chunk) */
    usage?: SageMakerUsage;
    /** Error information if chunk contains error */
    error?: string;
    /** Finish reason for generation */
    finishReason?: "stop" | "length" | "tool-calls" | "content-filter" | "unknown";
    /** Tool call in progress (Phase 2.3) */
    toolCall?: SageMakerStreamingToolCall;
    /** Tool result chunk (Phase 2.3) */
    toolResult?: SageMakerStreamingToolResult;
    /** Structured output streaming (Phase 2.3) */
    structuredOutput?: SageMakerStructuredOutput;
};
/**
 * Tool call information for function calling
 */
export type SageMakerToolCall = {
    /** Tool call identifier */
    id: string;
    /** Tool/function name */
    name: string;
    /** Tool arguments as JSON object */
    arguments: Record<string, unknown>;
    /** Tool call type */
    type: "function";
};
/**
 * Tool result information
 */
export type SageMakerToolResult = {
    /** Tool call identifier */
    toolCallId: string;
    /** Tool name */
    toolName: string;
    /** Tool result data */
    result: unknown;
    /** Execution status */
    status: "success" | "error";
    /** Error message if status is error */
    error?: string;
};
/**
 * Streaming tool call information (Phase 2.3)
 */
export type SageMakerStreamingToolCall = {
    /** Tool call identifier */
    id: string;
    /** Tool/function name */
    name?: string;
    /** Partial or complete arguments as JSON string */
    arguments?: string;
    /** Tool call type */
    type: "function";
    /** Indicates if this tool call is complete */
    complete?: boolean;
    /** Delta text for incremental argument building */
    argumentsDelta?: string;
};
/**
 * Streaming tool result information (Phase 2.3)
 */
export type SageMakerStreamingToolResult = {
    /** Tool call identifier */
    toolCallId: string;
    /** Tool name */
    toolName: string;
    /** Partial or complete result data */
    result?: unknown;
    /** Result delta for incremental responses */
    resultDelta?: string;
    /** Execution status */
    status: "pending" | "running" | "success" | "error";
    /** Error message if status is error */
    error?: string;
    /** Indicates if this result is complete */
    complete?: boolean;
};
/**
 * Structured output streaming information (Phase 2.3)
 */
export type SageMakerStructuredOutput = {
    /** Partial JSON object being built */
    partialObject?: Record<string, unknown>;
    /** JSON delta text */
    jsonDelta?: string;
    /** Current parsing path (e.g., "user.name") */
    currentPath?: string;
    /** Schema validation errors */
    validationErrors?: string[];
    /** Indicates if JSON is complete and valid */
    complete?: boolean;
    /** JSON schema being validated against */
    schema?: Record<string, unknown>;
};
/**
 * Enhanced generation request options
 */
export type SageMakerGenerationOptions = {
    /** Input prompt text */
    prompt: string;
    /** System prompt for context */
    systemPrompt?: string;
    /** Maximum tokens to generate */
    maxTokens?: number;
    /** Temperature for randomness (0-1) */
    temperature?: number;
    /** Top-p nucleus sampling (0-1) */
    topP?: number;
    /** Top-k sampling */
    topK?: number;
    /** Stop sequences to end generation */
    stopSequences?: string[];
    /** Enable streaming response */
    stream?: boolean;
    /** Tools available for function calling */
    tools?: Array<{
        name: string;
        description: string;
        parameters: Record<string, unknown>;
    }>;
    /** Tool choice mode */
    toolChoice?: "auto" | "none" | {
        type: "tool";
        name: string;
    };
};
/**
 * Generation response from SageMaker
 */
export type SageMakerGenerationResponse = {
    /** Generated text content */
    text: string;
    /** Token usage information */
    usage: SageMakerUsage;
    /** Finish reason for generation */
    finishReason: "stop" | "length" | "tool-calls" | "content-filter" | "unknown";
    /** Tool calls made during generation */
    toolCalls?: SageMakerToolCall[];
    /** Tool results if tools were executed */
    toolResults?: SageMakerToolResult[];
    /** Additional metadata */
    metadata?: Record<string, unknown>;
    /** Model version or identifier */
    modelVersion?: string;
};
/**
 * Error codes specific to SageMaker operations
 */
export type SageMakerErrorCode = "VALIDATION_ERROR" | "MODEL_ERROR" | "INTERNAL_ERROR" | "SERVICE_UNAVAILABLE" | "CREDENTIALS_ERROR" | "NETWORK_ERROR" | "ENDPOINT_NOT_FOUND" | "THROTTLING_ERROR" | "UNKNOWN_ERROR";
/**
 * SageMaker-specific error information
 */
export type SageMakerErrorInfo = {
    /** Error code */
    code: SageMakerErrorCode;
    /** Human-readable error message */
    message: string;
    /** HTTP status code if applicable */
    statusCode?: number;
    /** Original error from AWS SDK */
    cause?: Error;
    /** Endpoint name where error occurred */
    endpoint?: string;
    /** Request ID for debugging */
    requestId?: string;
    /** Retry suggestion */
    retryable?: boolean;
};
/**
 * Batch inference job configuration
 */
export type BatchInferenceConfig = {
    /** Input S3 location */
    inputS3Uri: string;
    /** Output S3 location */
    outputS3Uri: string;
    /** SageMaker model name */
    modelName: string;
    /** Instance type for batch job */
    instanceType: string;
    /** Instance count for batch job */
    instanceCount: number;
    /** Maximum payload size in MB */
    maxPayloadInMB?: number;
    /** Batch strategy */
    batchStrategy?: "MultiRecord" | "SingleRecord";
};
/**
 * Model deployment configuration
 */
export type ModelDeploymentConfig = {
    /** Model name */
    modelName: string;
    /** Endpoint name */
    endpointName: string;
    /** EC2 instance type */
    instanceType: string;
    /** Initial instance count */
    initialInstanceCount: number;
    /** Model data S3 location */
    modelDataUrl: string;
    /** Container image URI */
    image: string;
    /** IAM execution role ARN */
    executionRoleArn: string;
    /** Resource tags */
    tags?: Record<string, string>;
    /** Auto scaling configuration */
    autoScaling?: {
        minCapacity: number;
        maxCapacity: number;
        targetValue: number;
        scaleUpCooldown: number;
        scaleDownCooldown: number;
    };
};
/**
 * Endpoint metrics and monitoring data
 */
export type EndpointMetrics = {
    /** Endpoint name */
    endpointName: string;
    /** Total invocations */
    invocations: number;
    /** Average latency in milliseconds */
    averageLatency: number;
    /** Error rate percentage */
    errorRate: number;
    /** CPU utilization percentage */
    cpuUtilization?: number;
    /** Memory utilization percentage */
    memoryUtilization?: number;
    /** Instance count */
    instanceCount: number;
    /** Timestamp of metrics as ISO 8601 date string */
    timestamp: string;
};
/**
 * Cost estimation data
 */
export type CostEstimate = {
    /** Estimated cost in USD */
    estimatedCost: number;
    /** Currency code */
    currency: string;
    /** Cost breakdown */
    breakdown: {
        /** Instance hours cost */
        instanceCost: number;
        /** Request-based cost */
        requestCost: number;
        /** Total processing hours */
        totalHours: number;
    };
    /** Time period for estimate */
    period?: {
        start: string;
        end: string;
    };
};
/**
 * SageMaker generation result type for better type safety
 */
export type SageMakerGenerateResult = {
    text?: string;
    reasoning?: string | Array<{
        type: "text";
        text: string;
        signature?: string;
    } | {
        type: "redacted";
        data: string;
    }>;
    files?: Array<{
        data: string | Uint8Array;
        mimeType: string;
    }>;
    logprobs?: Array<{
        token: string;
        logprob: number;
        topLogprobs: Array<{
            token: string;
            logprob: number;
        }>;
    }>;
    usage: {
        promptTokens: number;
        completionTokens: number;
        totalTokens?: number;
    };
    finishReason: "stop" | "length" | "content-filter" | "tool-calls" | "error" | "unknown";
    warnings?: Array<{
        type: "other";
        message: string;
    }>;
    rawCall: {
        rawPrompt: unknown;
        rawSettings: Record<string, unknown>;
    };
    rawResponse?: {
        headers?: Record<string, string>;
    };
    request?: {
        body?: string;
    };
    toolCalls?: SageMakerToolCall[];
    object?: unknown;
};
export type ProviderHealthStatusOptions = {
    provider: AIProviderName;
    isHealthy: boolean;
    isConfigured: boolean;
    hasApiKey: boolean;
    lastChecked: Date;
    error?: string;
    warning?: string;
    responseTime?: number;
    configurationIssues: string[];
    recommendations: string[];
};
/**
 * Structural adapter type capturing what AI SDK's `streamText` / `generateText`
 * actually invoke at runtime on a model object.
 *
 * `OllamaLanguageModel` satisfies this type. The provider can cast
 * `new OllamaLanguageModel(...)` to `LanguageModel` via this
 * intermediate type, avoiding `as unknown as LanguageModel`.
 */
export type OllamaAsLanguageModel = {
    readonly specificationVersion: string;
    readonly provider: string;
    readonly modelId: string;
    readonly supportedUrls: Record<string, RegExp[]>;
    doGenerate(options: Record<string, unknown>): Promise<unknown>;
    doStream(options: Record<string, unknown>): Promise<unknown>;
};
/**
 * Structural type that captures what AI SDK's `streamText` / `generateText`
 * actually invoke at runtime on a model object.
 *
 * `SageMakerLanguageModel` satisfies this type. Consumers can cast
 * `new SageMakerLanguageModel(...)` to `LanguageModel` via this
 * intermediate type, avoiding `as unknown as LanguageModel`.
 */
export type SageMakerAsLanguageModel = {
    readonly specificationVersion: string;
    readonly provider: string;
    readonly modelId: string;
    readonly supportedUrls: Record<string, RegExp[]>;
    doGenerate(options: Record<string, unknown>): Promise<unknown>;
    doStream(options: Record<string, unknown>): Promise<unknown>;
};
export type ProviderHealthCheckOptions = {
    timeout?: number;
    includeConnectivityTest?: boolean;
    includeModelValidation?: boolean;
    cacheResults?: boolean;
    maxCacheAge?: number;
};
/**
 * Amazon Bedrock specific types
 */
export declare namespace BedrockTypes {
    type Client = {
        send(command: unknown): Promise<unknown>;
        config: {
            region?: string;
            credentials?: unknown;
        };
    };
    type InvokeModelCommand = {
        input: {
            modelId: string;
            body: string;
            contentType?: string;
        };
    };
}
/**
 * Mistral specific types
 */
export declare namespace MistralTypes {
    type Client = {
        chat?: {
            complete?: (options: unknown) => Promise<unknown>;
            stream?: (options: unknown) => AsyncIterable<unknown>;
        };
    };
}
/**
 * OpenTelemetry specific types (for telemetry service)
 */
export declare namespace TelemetryTypes {
    type Meter = {
        createCounter(name: string, options?: unknown): Counter;
        createHistogram(name: string, options?: unknown): Histogram;
    };
    type Tracer = {
        startSpan(name: string, options?: unknown): Span;
    };
    type Counter = {
        add(value: number, attributes?: UnknownRecord): void;
    };
    type Histogram = {
        record(value: number, attributes?: UnknownRecord): void;
    };
    type Span = {
        end(): void;
        setStatus(status: unknown): void;
        recordException(exception: unknown): void;
    };
}
/**
 * OpenRouter provider configuration
 */
export type OpenRouterConfig = {
    /** OpenRouter API key */
    apiKey: string;
    /** HTTP Referer header for attribution on openrouter.ai/activity */
    referer?: string;
    /** App name for X-Title header attribution */
    appName?: string;
};
/**
 * OpenRouter model information from /api/v1/models endpoint
 */
export type OpenRouterModelInfo = {
    /** Model ID in format 'provider/model-name' */
    id: string;
    /** Supported parameters (e.g., 'tools', 'temperature') */
    supported_parameters?: string[];
    /** Model name */
    name?: string;
    /** Model description */
    description?: string;
    /** Pricing information */
    pricing?: {
        prompt?: string;
        completion?: string;
    };
    /** Context length */
    context_length?: number;
};
/**
 * OpenRouter models API response
 */
export type OpenRouterModelsResponse = {
    data: OpenRouterModelInfo[];
};
/**
 * OpenRouter provider static cache properties (for testing/internal use)
 */
export type OpenRouterProviderCache = {
    modelsCache: string[];
    modelsCacheTime: number;
    toolCapableModels: Set<string>;
    capabilitiesCached: boolean;
};
/** A single function declaration for the Gemini native SDK. */
export type NativeFunctionDeclaration = {
    name: string;
    description: string;
    parametersJsonSchema?: Record<string, unknown>;
};
/** The tools config array expected by the @google/genai SDK. */
export type NativeToolsConfig = Array<{
    functionDeclarations: NativeFunctionDeclaration[];
}>;
/**
 * Return value of buildNativeToolDeclarations.
 *
 * `originalNameMap` lets callers translate a Google-safe (sanitized,
 * suffix-disambiguated) tool name back to the original identifier the
 * SDK consumer registered. Sanitized names are transport-only — they
 * MUST be hidden from tool-call metadata exposed to consumers.
 */
export type NativeToolDeclarationsResult = {
    toolsConfig: NativeToolsConfig;
    executeMap: Map<string, Tool["execute"]>;
    originalNameMap: Map<string, string>;
};
/** A single function call returned by the Gemini model. */
export type NativeFunctionCall = {
    name: string;
    args: Record<string, unknown>;
};
/** A single function response to feed back into the conversation. */
export type NativeFunctionResponse = {
    functionResponse: {
        name: string;
        response: unknown;
    };
};
/** Result from collectStreamChunks. */
export type CollectedChunkResult = {
    rawResponseParts: unknown[];
    stepFunctionCalls: NativeFunctionCall[];
    inputTokens: number;
    outputTokens: number;
};
/** Push-based text channel for incremental streaming. */
export type TextChannel = {
    /** Push a text chunk to the consumer. */
    push: (text: string) => void;
    /** Signal that no more chunks will arrive. */
    close: () => void;
    /** Signal that the producer encountered a fatal error. */
    error: (err: unknown) => void;
    /** Async iterable consumed by the StreamResult. */
    iterable: AsyncIterable<{
        content: string;
    }>;
};
/** Language model object shape (LanguageModelV2/V3). */
export type LanguageModelObject = {
    readonly modelId: string;
    readonly provider: string;
};
/** Step finish event shape for multi-step generation. */
export type StepFinishEvent = {
    readonly toolCalls: ReadonlyArray<unknown>;
    readonly toolResults: ReadonlyArray<unknown>;
    readonly text: string;
    readonly finishReason: string;
    readonly usage: {
        inputTokens?: number;
        outputTokens?: number;
    };
    [key: string]: unknown;
};
/**
 * Represents an AI SDK Tool that may carry a legacy `parameters` field
 * (from AI SDK v3/v4) in addition to the current `inputSchema`.
 */
export type ToolWithLegacyParams = {
    description?: string;
    inputSchema?: unknown;
    execute?: (...args: unknown[]) => unknown;
    /** Legacy field from AI SDK v3/v4 */
    parameters?: unknown;
};
/**
 * Provider constructor interface - supports both sync constructors and async
 * factory functions.
 */
export type ProviderConstructor = {
    new (modelName?: string, providerName?: string, sdk?: UnknownRecord, region?: string, credentials?: UnknownRecord): AIProvider;
} | ((modelName?: string, providerName?: string, sdk?: UnknownRecord, region?: string, credentials?: UnknownRecord) => Promise<AIProvider>);
/** Provider registration entry held by ProviderFactory. */
export type ProviderRegistration = {
    constructor: ProviderConstructor;
    defaultModel?: string;
    aliases?: string[];
};
/** Minimal NeuroLink-like instance accepted by the image generation service. */
export type NeuroLinkInstance = {
    generate: (options: Record<string, unknown>) => Promise<unknown>;
};
/** ProviderError enriched with HTTP response fields from Ollama. */
export type OllamaHttpError = ProviderError & {
    statusCode: number;
    statusText: string;
    responseBody: string;
};
/** Model type detection result. */
export type ModelDetectionResult = {
    type: StreamingCapability["modelType"];
    confidence: number;
    evidence: string[];
    suggestedConfig?: Partial<SageMakerModelConfig>;
};
/** Endpoint health and metadata information. */
export type EndpointHealth = {
    status: "healthy" | "unhealthy" | "unknown";
    responseTime: number;
    metadata?: Record<string, unknown>;
    modelInfo?: {
        name?: string;
        version?: string;
        framework?: string;
        architecture?: string;
    };
};
/** Configuration object for a detection test wrapper. */
export type DetectionTestConfig = {
    test: () => Promise<void>;
    index: number;
    testName: string;
    endpointName: string;
    semaphore: {
        acquire(): Promise<void>;
        release(): void;
    };
    incrementRateLimit: () => void;
    maxRateLimitRetries: number;
    rateLimitState: {
        count: number;
    };
};
/** Configuration object for parallel detection test execution. */
export type ParallelDetectionConfig = {
    maxConcurrentTests: number;
    maxRateLimitRetries: number;
    initialRateLimitCount: number;
};
/** Individual SageMaker diagnostic result. */
export type DiagnosticResult = {
    name: string;
    category: "configuration" | "connectivity" | "streaming";
    status: "pass" | "fail" | "warning";
    message: string;
    details?: string;
    recommendation?: string;
};
/** Aggregated SageMaker diagnostic report. */
export type DiagnosticReport = {
    overallStatus: "healthy" | "issues" | "critical";
    results: DiagnosticResult[];
    summary: {
        total: number;
        passed: number;
        failed: number;
        warnings: number;
    };
};
/** SageMaker tool_call item in the OpenAI-compatible payload shape. */
export type SageMakerOpenAIToolCall = {
    type: "function";
    id: string;
    function: {
        name: string;
        arguments: string;
    };
};
/**
 * Event pushed through the Google AI Studio voice session's internal queue
 * while audio chunks stream back from the Gemini Live API.
 */
export type GoogleLiveAudioQueueItem = {
    type: "audio";
    audio: import("./stream.js").AudioChunk;
} | {
    type: "end";
} | {
    type: "error";
    error: unknown;
};
/**
 * Single part inside a Google Vertex "native" (non-AI-SDK) generateContent
 * payload — either inline text or an inline base64 data blob.
 *
 * Despite the "Vertex" prefix, the shape is identical for the Google AI
 * Studio native path (`@google/genai` SDK), so AI Studio re-uses this type.
 */
export type VertexNativePart = {
    text: string;
} | {
    inlineData: {
        mimeType: string;
        data: string;
    };
};
/**
 * Subset of `GenerateOptions["input"]` consumed by the shared Gemini-native
 * multimodal-parts builder. Kept narrow so the helper doesn't depend on the
 * full `GenerateOptions` shape. The `images` field mirrors the public
 * `GenerateOptions["input"].images` shape so the helper accepts the same
 * value SDK callers pass in (plain Buffer/string or `ImageWithAltText`).
 */
export type GeminiMultimodalInput = {
    text?: string;
    pdfFiles?: Array<Buffer | string>;
    images?: Array<Buffer | string | {
        data: Buffer | string;
        altText?: string;
    }>;
};
/**
 * Internal helpers used by the conversation-history builder in
 * providers/googleVertex.ts to merge interleaved tool call / result turns.
 */
export type VertexToolStep = {
    type: "tool_step";
    callParts: unknown[];
    resultParts: unknown[];
};
export type VertexRegularSegment = {
    type: "regular";
    role: string;
    parts: unknown[];
};
export type VertexSegment = VertexToolStep | VertexRegularSegment;
/**
 * Function declaration shape accepted by the @google/genai SDK when tools are
 * attached to a Vertex generateContent call.
 */
export type VertexGenaiFunctionDeclaration = {
    name: string;
    description: string;
    parametersJsonSchema?: Record<string, unknown>;
};
/**
 * Message payload passed to the Anthropic Vertex SDK — mirrors the Anthropic
 * Messages API shape (role + structured content blocks).
 */
export type VertexAnthropicMessage = {
    role: "user" | "assistant";
    content: string | Array<{
        type: "text";
        text: string;
    } | {
        type: "image";
        source: {
            type: "base64";
            media_type: string;
            data: string;
        };
    } | {
        type: "document";
        source: {
            type: "base64";
            media_type: string;
            data: string;
        };
    } | {
        type: "tool_use";
        id: string;
        name: string;
        input: unknown;
    } | {
        type: "tool_result";
        tool_use_id: string;
        content: string;
    } | {
        type: "thinking";
        thinking: string;
    } | {
        type: "redacted_thinking";
        data: string;
    }>;
};
/** Tool definition accepted by the Anthropic Vertex SDK. */
export type VertexAnthropicTool = {
    name: string;
    description: string;
    input_schema: {
        type: "object";
        properties?: Record<string, unknown>;
        required?: string[];
    };
};
/**
 * Content block variants returned by the Anthropic Vertex SDK during streaming
 * and generation — used to narrow responses before handing tool calls back.
 */
export type VertexAnthropicContentBlock = {
    type: "text";
    text: string;
} | {
    type: "tool_use";
    id: string;
    name: string;
    input: Record<string, unknown>;
} | {
    type: "tool_result";
    tool_use_id: string;
    content: string;
};