/**
 * Type-safe LLM (Large Language Model) vendor classes.
 */
import { type OpenAIPresetModel } from "../presets.js";
import type { LlmConfig } from "../types.js";
import { BaseLLM, type BaseLlmOptions } from "./base.js";
/**
 * Constructor options for OpenAI LLM.
 */
type OpenAICommonOptions = BaseLlmOptions & {
    /** OpenAI API key. Optional only for AgentKit-supported Agora-managed models. */
    apiKey?: string;
    /** Model name (e.g., 'gpt-4o-mini', 'gpt-4', 'gpt-3.5-turbo') */
    model: string;
    /** API endpoint URL */
    url?: string;
    /** Maximum number of conversation history messages to cache */
    maxHistory?: number;
    /** Sampling temperature (0.0–2.0) */
    temperature?: number;
    /** Nucleus sampling (0.0–1.0) */
    topP?: number;
    /** Maximum tokens to generate */
    maxTokens?: number;
    /** System messages for the LLM */
    systemMessages?: Record<string, unknown>[];
    /** Greeting message for the agent */
    greetingMessage?: string;
    /** Failure message when LLM call fails */
    failureMessage?: string;
    /** Input modalities (defaults to ["text"]) */
    inputModalities?: string[];
    /** Additional LLM parameters */
    params?: Record<string, unknown>;
    /** Custom headers forwarded to the LLM provider */
    headers?: Record<string, string>;
};
export type OpenAIOptions = (OpenAICommonOptions & {
    apiKey: string;
    url: string;
}) | (Omit<OpenAICommonOptions, "model" | "url" | "vendor"> & {
    apiKey?: undefined;
    model: OpenAIPresetModel;
    url?: undefined;
    vendor?: undefined;
});
/**
 * OpenAI LLM vendor (and OpenAI-compatible APIs).
 *
 * @example
 * ```typescript
 * const llm = new OpenAI({
 *   apiKey: process.env.OPENAI_API_KEY,
 *   model: 'gpt-4o',
 *   url: 'https://api.openai.com/v1/chat/completions',
 * });
 * ```
 */
export declare class OpenAI extends BaseLLM {
    private readonly options;
    constructor(options: OpenAIOptions);
    toConfig(): LlmConfig;
}
/**
 * Constructor options for Azure OpenAI LLM.
 */
export interface AzureOpenAIOptions extends BaseLlmOptions {
    /** Azure OpenAI API key */
    apiKey: string;
    /** Model/deployment name */
    model: string;
    /** Azure resource name (e.g., 'my-resource'). Required when endpoint is not set. */
    resourceName?: string;
    /** Full Azure base URL (e.g., for sovereign clouds or private endpoints). Takes precedence over resourceName. */
    endpoint?: string;
    /** Deployment name in Azure */
    deploymentName: string;
    /** Azure API version (defaults to '2024-08-01-preview') */
    apiVersion?: string;
    /** Maximum number of conversation history messages to cache */
    maxHistory?: number;
    /** Sampling temperature (0.0–2.0) */
    temperature?: number;
    /** Nucleus sampling (0.0–1.0) */
    topP?: number;
    /** Maximum tokens to generate */
    maxTokens?: number;
    /** System messages for the LLM */
    systemMessages?: Record<string, unknown>[];
    /** Greeting message for the agent */
    greetingMessage?: string;
    /** Failure message when LLM call fails */
    failureMessage?: string;
    /** Input modalities (defaults to ["text"]) */
    inputModalities?: string[];
    /** Additional LLM parameters */
    params?: Record<string, unknown>;
    /** Custom headers forwarded to the LLM provider */
    headers?: Record<string, string>;
}
/**
 * Azure OpenAI LLM vendor.
 *
 * @example
 * ```typescript
 * const llm = new AzureOpenAI({
 *   apiKey: process.env.AZURE_OPENAI_API_KEY,
 *   model: 'gpt-4',
 *   resourceName: 'my-azure-resource',
 *   deploymentName: 'gpt-4-deployment',
 * });
 * ```
 */
export declare class AzureOpenAI extends BaseLLM {
    private readonly options;
    constructor(options: AzureOpenAIOptions);
    toConfig(): LlmConfig;
}
/**
 * Constructor options for Anthropic Claude LLM.
 */
export interface AnthropicOptions extends BaseLlmOptions {
    /** Anthropic API key */
    apiKey: string;
    /** Model name (e.g., 'claude-3-5-sonnet-20241022', 'claude-3-opus-20240229') */
    model: string;
    /** API endpoint URL */
    url: string;
    /** Maximum number of conversation history messages to cache */
    maxHistory?: number;
    /** Maximum tokens to generate */
    maxTokens: number;
    /** Sampling temperature (0.0–1.0) */
    temperature?: number;
    /** Nucleus sampling (0.0–1.0) */
    topP?: number;
    /** System messages for the LLM */
    systemMessages?: Record<string, unknown>[];
    /** Greeting message for the agent */
    greetingMessage?: string;
    /** Failure message when LLM call fails */
    failureMessage?: string;
    /** Input modalities (defaults to ["text"]) */
    inputModalities?: string[];
    /** Additional LLM parameters */
    params?: Record<string, unknown>;
    /** Custom headers forwarded to the LLM provider */
    headers?: Record<string, string>;
}
/**
 * Anthropic Claude LLM vendor.
 *
 * @example
 * ```typescript
 * const llm = new Anthropic({
 *   apiKey: process.env.ANTHROPIC_API_KEY,
 *   model: 'claude-3-5-sonnet-20241022',
 *   url: 'https://api.anthropic.com/v1/messages',
 *   headers: { 'anthropic-version': '2023-06-01' },
 *   maxTokens: 1024,
 * });
 * ```
 */
export declare class Anthropic extends BaseLLM {
    private readonly options;
    constructor(options: AnthropicOptions);
    toConfig(): LlmConfig;
}
/**
 * Constructor options for Google Gemini LLM.
 */
export interface GeminiOptions extends BaseLlmOptions {
    /** Google API key */
    apiKey: string;
    /** Model name (e.g., 'gemini-pro', 'gemini-pro-vision') */
    model: string;
    /** Optional full API endpoint URL override. When omitted, AgentKit builds the official Gemini stream URL. */
    url?: string;
    /** Maximum number of conversation history messages to cache */
    maxHistory?: number;
    /** Sampling temperature (0.0–2.0) */
    temperature?: number;
    /** Nucleus sampling (0.0–1.0) */
    topP?: number;
    /** Top-k sampling */
    topK?: number;
    /** Maximum output tokens to generate */
    maxOutputTokens?: number;
    /** System messages for the LLM */
    systemMessages?: Record<string, unknown>[];
    /** Greeting message for the agent */
    greetingMessage?: string;
    /** Failure message when LLM call fails */
    failureMessage?: string;
    /** Input modalities (defaults to ["text"]) */
    inputModalities?: string[];
    /** Additional LLM parameters */
    params?: Record<string, unknown>;
    /** Custom headers forwarded to the LLM provider */
    headers?: Record<string, string>;
}
/**
 * Google Gemini LLM vendor.
 *
 * @example
 * ```typescript
 * const llm = new Gemini({
 *   apiKey: process.env.GOOGLE_API_KEY,
 *   model: 'gemini-pro',
 * });
 * ```
 */
export declare class Gemini extends BaseLLM {
    private readonly options;
    constructor(options: GeminiOptions);
    toConfig(): LlmConfig;
}
type OpenAIStyleOptions = BaseLlmOptions & {
    apiKey: string;
    model: string;
    url: string;
    maxHistory?: number;
    temperature?: number;
    topP?: number;
    maxTokens?: number;
    systemMessages?: Record<string, unknown>[];
    greetingMessage?: string;
    failureMessage?: string;
    inputModalities?: string[];
    params?: Record<string, unknown>;
    headers?: Record<string, string>;
};
export type GroqOptions = OpenAIStyleOptions;
export declare class Groq extends BaseLLM {
    private readonly options;
    constructor(options: GroqOptions);
    toConfig(): LlmConfig;
}
export type CustomLLMOptions = OpenAIStyleOptions;
export declare class CustomLLM extends BaseLLM {
    private readonly options;
    constructor(options: CustomLLMOptions);
    toConfig(): LlmConfig;
}
export interface VertexAILLMOptions extends BaseLlmOptions {
    apiKey: string;
    model: string;
    projectId: string;
    location: string;
    url?: string;
    maxHistory?: number;
    temperature?: number;
    topP?: number;
    topK?: number;
    maxOutputTokens?: number;
    systemMessages?: Record<string, unknown>[];
    greetingMessage?: string;
    failureMessage?: string;
    inputModalities?: string[];
    params?: Record<string, unknown>;
    headers?: Record<string, string>;
}
export declare class VertexAILLM extends BaseLLM {
    private readonly options;
    constructor(options: VertexAILLMOptions);
    toConfig(): LlmConfig;
}
export interface AmazonBedrockOptions extends BaseLlmOptions {
    /** AWS access key ID. */
    accessKey: string;
    /** AWS secret access key. */
    secretKey: string;
    /** AWS region. */
    region: string;
    model: string;
    maxHistory?: number;
    maxTokens?: number;
    temperature?: number;
    topP?: number;
    topK?: number;
    systemMessages?: Record<string, unknown>[];
    greetingMessage?: string;
    failureMessage?: string;
    inputModalities?: string[];
    params?: Record<string, unknown>;
    headers?: Record<string, string>;
}
export declare class AmazonBedrock extends BaseLLM {
    private readonly options;
    constructor(options: AmazonBedrockOptions);
    toConfig(): LlmConfig;
}
export interface DifyOptions extends BaseLlmOptions {
    apiKey: string;
    url: string;
    model: string;
    user?: string;
    conversationId?: string;
    maxHistory?: number;
    systemMessages?: Record<string, unknown>[];
    greetingMessage?: string;
    failureMessage?: string;
    inputModalities?: string[];
    params?: Record<string, unknown>;
    headers?: Record<string, string>;
}
export declare class Dify extends BaseLLM {
    private readonly options;
    constructor(options: DifyOptions);
    toConfig(): LlmConfig;
}
export {};