/**
 * @license
 * Copyright 2025 QWEN
 * SPDX-License-Identifier: Apache-2.0
 */
import type { CountTokensResponse, GenerateContentParameters, CountTokensParameters, EmbedContentResponse, EmbedContentParameters } from '@google/genai';
import { GenerateContentResponse } from '@google/genai';
import type { ContentGenerator } from './contentGenerator.js';
import OpenAI from 'openai';
import type { LlmRole } from '../telemetry/llmRole.js';
import type { Config } from '../config/config.js';
export declare class OpenAIContentGenerator implements ContentGenerator {
    protected client: OpenAI;
    private model;
    private config;
    protected readonly isOpenRouter: boolean;
    private streamingToolCalls;
    private streamingReasoningDetails;
    private streamingReasoningContent;
    private reasoningContentHistory;
    constructor(apiKey: string, model: string, config: Config);
    /**
     * Hook for subclasses to customize error handling behavior
     * @param error The error that occurred
     * @param request The original request
     * @returns true if error logging should be suppressed, false otherwise
     */
    protected shouldSuppressErrorLogging(_error: unknown, _request: GenerateContentParameters): boolean;
    /**
     * Check if metadata should be included in the request
     * Only include metadata for specific providers that support it
     */
    private shouldIncludeMetadata;
    /**
     * Build metadata object conditionally
     * @param userPromptId The prompt ID for this request
     * @returns metadata object if should be included, undefined otherwise
     */
    private buildMetadata;
    /**
     * Check if an error is a timeout error
     */
    private isTimeoutError;
    generateContent(request: GenerateContentParameters, userPromptId: string, _role?: LlmRole): Promise<GenerateContentResponse>;
    generateContentStream(request: GenerateContentParameters, userPromptId: string, _role?: LlmRole): Promise<AsyncGenerator<GenerateContentResponse>>;
    private streamGenerator;
    /**
     * Combine streaming responses for logging purposes
     */
    private combineStreamResponsesForLogging;
    countTokens(request: CountTokensParameters): Promise<CountTokensResponse>;
    embedContent(request: EmbedContentParameters): Promise<EmbedContentResponse>;
    private convertGeminiParametersToOpenAI;
    private convertGeminiToolsToOpenAI;
    private convertToOpenAIFormat;
    /**
     * Check if the current model is a Gemini reasoning model (Gemini 3, 2.5 series)
     * These models require reasoning_details/thought_signature for tool calls
     */
    private isGeminiReasoningModel;
    /**
     * Validate thoughtSignature to prevent "Corrupted thought signature" errors.
     * Valid thoughtSignature should have properly encrypted data (long base64 strings).
     * Invalid ones may contain short UUIDs or corrupted data.
     *
     * 验证 thoughtSignature 以防止 "Corrupted thought signature" 错误。
     * 有效的 thoughtSignature 应该包含正确加密的数据（长 base64 字符串）。
     * 无效的可能包含短 UUID 或损坏的数据。
     */
    private isValidThoughtSignature;
    /**
     * Add reasoning_content field to assistant messages for thinking-enabled models.
     * Models like Kimi K2.5 require the actual reasoning content to be echoed back;
     * models like DeepSeek accept an empty string.
     * We use the stored history when available, falling back to empty string.
     */
    private addReasoningContentToAssistantMessages;
    /**
     * Filter out REASONING_DETAILS_MARKER from text to prevent it from leaking
     * into messages sent to the model. This can happen when AionUI includes
     * conversation history that contains the marker.
     *
     * 过滤文本中的 REASONING_DETAILS_MARKER，防止其泄露到发送给模型的消息中。
     * 这种情况可能发生在 AionUI 包含含有 marker 的对话历史时。
     */
    private filterReasoningDetailsMarker;
    /**
     * 清理消息历史中的孤立工具调用，防止 OpenAI API 报错。
     * 同时对相同 tool_call_id 的工具响应进行去重，防止不接受重复响应的 API 返回 400 错误。
     *
     * Clean up orphaned tool calls from message history to prevent OpenAI API errors.
     * Also deduplicates tool responses with the same tool_call_id to prevent 400 errors
     * from providers that don't accept duplicate responses for the same tool call.
     */
    private cleanOrphanedToolCalls;
    /**
     * Reorders tool response messages so each one immediately follows the
     * assistant message whose tool_calls it answers.
     *
     * The Gemini history may interleave user Content entries (e.g. system-prompt
     * injections) between a model's functionCall and the corresponding
     * functionResponse.  In Gemini-native format that is fine (matching is by id),
     * but the OpenAI chat-completions API requires every assistant message with
     * tool_calls to be followed immediately by tool messages for each call id.
     */
    private ensureToolResponseOrdering;
    /**
     * Merge consecutive assistant messages to combine split text and tool calls
     */
    private mergeConsecutiveAssistantMessages;
    private convertToGeminiFormat;
    private convertStreamChunkToGeminiFormat;
    /**
     * Build sampling parameters with clear priority:
     * 1. Config-level sampling parameters (highest priority)
     * 2. Request-level parameters (medium priority)
     * 3. Default values (lowest priority)
     */
    private buildSamplingParameters;
    private mapFinishReason;
    /**
     * Convert Gemini request format to OpenAI chat completion format for logging
     */
    private convertGeminiRequestToOpenAI;
    /**
     * Clean up orphaned tool calls for logging purposes
     */
    private cleanOrphanedToolCallsForLogging;
    /**
     * Logging variant of ensureToolResponseOrdering for the OpenAIMessage type.
     */
    private ensureToolResponseOrderingForLogging;
    /**
     * Merge consecutive assistant messages to combine split text and tool calls for logging
     */
    private mergeConsecutiveAssistantMessagesForLogging;
    /**
     * Convert Gemini response format to OpenAI chat completion format for logging
     */
    private convertGeminiResponseToOpenAI;
    /**
     * Map Gemini finish reasons to OpenAI finish reasons
     */
    private mapGeminiFinishReasonToOpenAI;
}