src/services/azureOpenaiRelayService.js

const axios = require('axios')
const ProxyHelper = require('../utils/proxyHelper')
const logger = require('../utils/logger')
const config = require('../../config/config')

// 转换模型名称（去掉 azure/ 前缀）
function normalizeModelName(model) {
  if (model && model.startsWith('azure/')) {
    return model.replace('azure/', '')
  }
  return model
}

// 处理 Azure OpenAI 请求
async function handleAzureOpenAIRequest({
  account,
  requestBody,
  headers: _headers = {}, // 前缀下划线表示未使用
  isStream = false,
  endpoint = 'chat/completions'
}) {
  // 声明变量在函数顶部，确保在 catch 块中也能访问
  let requestUrl = ''
  let proxyAgent = null
  let deploymentName = ''

  try {
    // 构建 Azure OpenAI 请求 URL
    const baseUrl = account.azureEndpoint
    deploymentName = account.deploymentName || 'default'
    // Azure Responses API requires preview versions; fall back appropriately
    const apiVersion =
      account.apiVersion || (endpoint === 'responses' ? '2025-04-01-preview' : '2024-02-01')
    if (endpoint === 'chat/completions') {
      requestUrl = `${baseUrl}/openai/deployments/${deploymentName}/chat/completions?api-version=${apiVersion}`
    } else if (endpoint === 'responses') {
      requestUrl = `${baseUrl}/openai/responses?api-version=${apiVersion}`
    } else {
      requestUrl = `${baseUrl}/openai/deployments/${deploymentName}/${endpoint}?api-version=${apiVersion}`
    }

    // 准备请求头
    const requestHeaders = {
      'Content-Type': 'application/json',
      'api-key': account.apiKey
    }

    // 移除不需要的头部
    delete requestHeaders['anthropic-version']
    delete requestHeaders['x-api-key']
    delete requestHeaders['host']

    // 处理请求体
    const processedBody = { ...requestBody }

    // 标准化模型名称
    if (endpoint === 'responses') {
      processedBody.model = deploymentName
    } else if (processedBody.model) {
      processedBody.model = normalizeModelName(processedBody.model)
    } else {
      processedBody.model = 'gpt-4'
    }

    // 使用统一的代理创建工具
    proxyAgent = ProxyHelper.createProxyAgent(account.proxy)

    // 配置请求选项
    const axiosConfig = {
      method: 'POST',
      url: requestUrl,
      headers: requestHeaders,
      data: processedBody,
      timeout: config.requestTimeout || 600000,
      validateStatus: () => true,
      // 添加连接保活选项
      keepAlive: true,
      maxRedirects: 5,
      // 防止socket hang up
      socketKeepAlive: true
    }

    // 如果有代理，添加代理配置
    if (proxyAgent) {
      axiosConfig.httpAgent = proxyAgent
      axiosConfig.httpsAgent = proxyAgent
      axiosConfig.proxy = false
      // 为代理添加额外的keep-alive设置
      if (proxyAgent.options) {
        proxyAgent.options.keepAlive = true
        proxyAgent.options.keepAliveMsecs = 1000
      }
      logger.debug(
        `Using proxy for Azure OpenAI request: ${ProxyHelper.getProxyDescription(account.proxy)}`
      )
    }

    // 流式请求特殊处理
    if (isStream) {
      axiosConfig.responseType = 'stream'
      requestHeaders.accept = 'text/event-stream'
    } else {
      requestHeaders.accept = 'application/json'
    }

    logger.debug(`Making Azure OpenAI request`, {
      requestUrl,
      method: 'POST',
      endpoint,
      deploymentName,
      apiVersion,
      hasProxy: !!proxyAgent,
      proxyInfo: ProxyHelper.maskProxyInfo(account.proxy),
      isStream,
      requestBodySize: JSON.stringify(processedBody).length
    })

    logger.debug('Azure OpenAI request headers', {
      'content-type': requestHeaders['Content-Type'],
      'user-agent': requestHeaders['user-agent'] || 'not-set',
      customHeaders: Object.keys(requestHeaders).filter(
        (key) => !['Content-Type', 'user-agent'].includes(key)
      )
    })

    logger.debug('Azure OpenAI request body', {
      model: processedBody.model,
      messages: processedBody.messages?.length || 0,
      otherParams: Object.keys(processedBody).filter((key) => !['model', 'messages'].includes(key))
    })

    const requestStartTime = Date.now()
    logger.debug(`🔄 Starting Azure OpenAI HTTP request at ${new Date().toISOString()}`)

    // 发送请求
    const response = await axios(axiosConfig)

    const requestDuration = Date.now() - requestStartTime
    logger.debug(`✅ Azure OpenAI HTTP request completed at ${new Date().toISOString()}`)

    logger.debug(`Azure OpenAI response received`, {
      status: response.status,
      statusText: response.statusText,
      duration: `${requestDuration}ms`,
      responseHeaders: Object.keys(response.headers || {}),
      hasData: !!response.data,
      contentType: response.headers?.['content-type'] || 'unknown'
    })

    return response
  } catch (error) {
    const errorDetails = {
      message: error.message,
      code: error.code,
      status: error.response?.status,
      statusText: error.response?.statusText,
      responseData: error.response?.data,
      requestUrl: requestUrl || 'unknown',
      endpoint,
      deploymentName: deploymentName || account?.deploymentName || 'unknown',
      hasProxy: !!proxyAgent,
      proxyType: account?.proxy?.type || 'none',
      isTimeout: error.code === 'ECONNABORTED',
      isNetworkError: !error.response,
      stack: error.stack
    }

    // 特殊错误类型的详细日志
    if (error.code === 'ENOTFOUND') {
      logger.error('DNS Resolution Failed for Azure OpenAI', {
        ...errorDetails,
        hostname: requestUrl && requestUrl !== 'unknown' ? new URL(requestUrl).hostname : 'unknown',
        suggestion: 'Check if Azure endpoint URL is correct and accessible'
      })
    } else if (error.code === 'ECONNREFUSED') {
      logger.error('Connection Refused by Azure OpenAI', {
        ...errorDetails,
        suggestion: 'Check if proxy settings are correct or Azure service is accessible'
      })
    } else if (error.code === 'ECONNRESET' || error.message.includes('socket hang up')) {
      logger.error('🚨 Azure OpenAI Connection Reset / Socket Hang Up', {
        ...errorDetails,
        suggestion:
          'Connection was dropped by Azure OpenAI or proxy. This might be due to long request processing time, proxy timeout, or network instability. Try reducing request complexity or check proxy settings.'
      })
    } else if (error.code === 'ECONNABORTED' || error.code === 'ETIMEDOUT') {
      logger.error('🚨 Azure OpenAI Request Timeout', {
        ...errorDetails,
        timeoutMs: 600000,
        suggestion:
          'Request exceeded 10-minute timeout. Consider reducing model complexity or check if Azure service is responding slowly.'
      })
    } else if (
      error.code === 'CERT_AUTHORITY_INVALID' ||
      error.code === 'UNABLE_TO_VERIFY_LEAF_SIGNATURE'
    ) {
      logger.error('SSL Certificate Error for Azure OpenAI', {
        ...errorDetails,
        suggestion: 'SSL certificate validation failed - check proxy SSL settings'
      })
    } else if (error.response?.status === 401) {
      logger.error('Azure OpenAI Authentication Failed', {
        ...errorDetails,
        suggestion: 'Check if Azure OpenAI API key is valid and not expired'
      })
    } else if (error.response?.status === 404) {
      logger.error('Azure OpenAI Deployment Not Found', {
        ...errorDetails,
        suggestion: 'Check if deployment name and Azure endpoint are correct'
      })
    } else {
      logger.error('Azure OpenAI Request Failed', errorDetails)
    }

    throw error
  }
}

// 安全的流管理器
class StreamManager {
  constructor() {
    this.activeStreams = new Set()
    this.cleanupCallbacks = new Map()
  }

  registerStream(streamId, cleanup) {
    this.activeStreams.add(streamId)
    this.cleanupCallbacks.set(streamId, cleanup)
  }

  cleanup(streamId) {
    if (this.activeStreams.has(streamId)) {
      try {
        const cleanup = this.cleanupCallbacks.get(streamId)
        if (cleanup) {
          cleanup()
        }
      } catch (error) {
        logger.warn(`Stream cleanup error for ${streamId}:`, error.message)
      } finally {
        this.activeStreams.delete(streamId)
        this.cleanupCallbacks.delete(streamId)
      }
    }
  }

  getActiveStreamCount() {
    return this.activeStreams.size
  }
}

const streamManager = new StreamManager()

// SSE 缓冲区大小限制
const MAX_BUFFER_SIZE = 64 * 1024 // 64KB
const MAX_EVENT_SIZE = 16 * 1024 // 16KB 单个事件最大大小

// 处理流式响应
function handleStreamResponse(upstreamResponse, clientResponse, options = {}) {
  const { onData, onEnd, onError } = options
  const streamId = `stream_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`

  logger.info(`Starting Azure OpenAI stream handling`, {
    streamId,
    upstreamStatus: upstreamResponse.status,
    upstreamHeaders: Object.keys(upstreamResponse.headers || {}),
    clientRemoteAddress: clientResponse.req?.connection?.remoteAddress,
    hasOnData: !!onData,
    hasOnEnd: !!onEnd,
    hasOnError: !!onError
  })

  return new Promise((resolve, reject) => {
    let buffer = ''
    let usageData = null
    let actualModel = null
    let hasEnded = false
    let eventCount = 0
    const maxEvents = 10000 // 最大事件数量限制

    // 专门用于保存最后几个chunks以提取usage数据
    let finalChunksBuffer = ''
    const FINAL_CHUNKS_SIZE = 32 * 1024 // 32KB保留最终chunks
    const allParsedEvents = [] // 存储所有解析的事件用于最终usage提取

    // 设置响应头
    clientResponse.setHeader('Content-Type', 'text/event-stream')
    clientResponse.setHeader('Cache-Control', 'no-cache')
    clientResponse.setHeader('Connection', 'keep-alive')
    clientResponse.setHeader('X-Accel-Buffering', 'no')

    // 透传某些头部
    const passThroughHeaders = [
      'x-request-id',
      'x-ratelimit-remaining-requests',
      'x-ratelimit-remaining-tokens'
    ]
    passThroughHeaders.forEach((header) => {
      const value = upstreamResponse.headers[header]
      if (value) {
        clientResponse.setHeader(header, value)
      }
    })

    // 立即刷新响应头
    if (typeof clientResponse.flushHeaders === 'function') {
      clientResponse.flushHeaders()
    }

    // 强化的SSE事件解析，保存所有事件用于最终处理
    const parseSSEForUsage = (data, isFromFinalBuffer = false) => {
      const lines = data.split('\n')

      for (const line of lines) {
        if (line.startsWith('data: ')) {
          try {
            const jsonStr = line.slice(6) // 移除 'data: ' 前缀
            if (jsonStr.trim() === '[DONE]') {
              continue
            }
            const eventData = JSON.parse(jsonStr)

            // 保存所有成功解析的事件
            allParsedEvents.push(eventData)

            // 获取模型信息
            if (eventData.model) {
              actualModel = eventData.model
            }

            // 使用强化的usage提取函数
            const { usageData: extractedUsage, actualModel: extractedModel } =
              extractUsageDataRobust(
                eventData,
                `stream-event-${isFromFinalBuffer ? 'final' : 'normal'}`
              )

            if (extractedUsage && !usageData) {
              usageData = extractedUsage
              if (extractedModel) {
                actualModel = extractedModel
              }
              logger.debug(`🎯 Stream usage captured via robust extraction`, {
                isFromFinalBuffer,
                usageData,
                actualModel
              })
            }

            // 原有的简单提取作为备用
            if (!usageData) {
              // 获取使用统计（Responses API: response.completed -> response.usage）
              if (eventData.type === 'response.completed' && eventData.response) {
                if (eventData.response.model) {
                  actualModel = eventData.response.model
                }
                if (eventData.response.usage) {
                  usageData = eventData.response.usage
                  logger.debug('🎯 Stream usage (backup method - response.usage):', usageData)
                }
              }

              // 兼容 Chat Completions 风格（顶层 usage）
              if (!usageData && eventData.usage) {
                usageData = eventData.usage
                logger.debug('🎯 Stream usage (backup method - top-level):', usageData)
              }
            }
          } catch (e) {
            logger.debug('SSE parsing error (expected for incomplete chunks):', e.message)
          }
        }
      }
    }

    // 注册流清理
    const cleanup = () => {
      if (!hasEnded) {
        hasEnded = true
        try {
          upstreamResponse.data?.removeAllListeners?.()
          upstreamResponse.data?.destroy?.()

          if (!clientResponse.headersSent) {
            clientResponse.status(502).end()
          } else if (!clientResponse.destroyed) {
            clientResponse.end()
          }
        } catch (error) {
          logger.warn('Stream cleanup error:', error.message)
        }
      }
    }

    streamManager.registerStream(streamId, cleanup)

    upstreamResponse.data.on('data', (chunk) => {
      try {
        if (hasEnded || clientResponse.destroyed) {
          return
        }

        eventCount++
        if (eventCount > maxEvents) {
          logger.warn(`Stream ${streamId} exceeded max events limit`)
          cleanup()
          return
        }

        const chunkStr = chunk.toString()

        // 转发数据给客户端
        if (!clientResponse.destroyed) {
          clientResponse.write(chunk)
        }

        // 同时解析数据以捕获 usage 信息，带缓冲区大小限制
        buffer += chunkStr

        // 保留最后的chunks用于最终usage提取（不被truncate影响）
        finalChunksBuffer += chunkStr
        if (finalChunksBuffer.length > FINAL_CHUNKS_SIZE) {
          finalChunksBuffer = finalChunksBuffer.slice(-FINAL_CHUNKS_SIZE)
        }

        // 防止主缓冲区过大 - 但保持最后部分用于usage解析
        if (buffer.length > MAX_BUFFER_SIZE) {
          logger.warn(
            `Stream ${streamId} buffer exceeded limit, truncating main buffer but preserving final chunks`
          )
          // 保留最后1/4而不是1/2，为usage数据留更多空间
          buffer = buffer.slice(-MAX_BUFFER_SIZE / 4)
        }

        // 处理完整的 SSE 事件
        if (buffer.includes('\n\n')) {
          const events = buffer.split('\n\n')
          buffer = events.pop() || '' // 保留最后一个可能不完整的事件

          for (const event of events) {
            if (event.trim() && event.length <= MAX_EVENT_SIZE) {
              parseSSEForUsage(event)
            }
          }
        }

        if (onData) {
          onData(chunk, { usageData, actualModel })
        }
      } catch (error) {
        logger.error('Error processing Azure OpenAI stream chunk:', error)
        if (!hasEnded) {
          cleanup()
          reject(error)
        }
      }
    })

    upstreamResponse.data.on('end', () => {
      if (hasEnded) {
        return
      }

      streamManager.cleanup(streamId)
      hasEnded = true

      try {
        logger.debug(`🔚 Stream ended, performing comprehensive usage extraction for ${streamId}`, {
          mainBufferSize: buffer.length,
          finalChunksBufferSize: finalChunksBuffer.length,
          parsedEventsCount: allParsedEvents.length,
          hasUsageData: !!usageData
        })

        // 多层次的最终usage提取策略
        if (!usageData) {
          logger.debug('🔍 No usage found during stream, trying final extraction methods...')

          // 方法1: 解析剩余的主buffer
          if (buffer.trim() && buffer.length <= MAX_EVENT_SIZE) {
            parseSSEForUsage(buffer, false)
          }

          // 方法2: 解析保留的final chunks buffer
          if (!usageData && finalChunksBuffer.trim()) {
            logger.debug('🔍 Trying final chunks buffer for usage extraction...')
            parseSSEForUsage(finalChunksBuffer, true)
          }

          // 方法3: 从所有解析的事件中重新搜索usage
          if (!usageData && allParsedEvents.length > 0) {
            logger.debug('🔍 Searching through all parsed events for usage...')

            // 倒序查找，因为usage通常在最后
            for (let i = allParsedEvents.length - 1; i >= 0; i--) {
              const { usageData: foundUsage, actualModel: foundModel } = extractUsageDataRobust(
                allParsedEvents[i],
                `final-event-scan-${i}`
              )
              if (foundUsage) {
                usageData = foundUsage
                if (foundModel) {
                  actualModel = foundModel
                }
                logger.debug(`🎯 Usage found in event ${i} during final scan!`)
                break
              }
            }
          }

          // 方法4: 尝试合并所有事件并搜索
          if (!usageData && allParsedEvents.length > 0) {
            logger.debug('🔍 Trying combined events analysis...')
            const combinedData = {
              events: allParsedEvents,
              lastEvent: allParsedEvents[allParsedEvents.length - 1],
              eventCount: allParsedEvents.length
            }

            const { usageData: combinedUsage } = extractUsageDataRobust(
              combinedData,
              'combined-events'
            )
            if (combinedUsage) {
              usageData = combinedUsage
              logger.debug('🎯 Usage found via combined events analysis!')
            }
          }
        }

        // 最终usage状态报告
        if (usageData) {
          logger.debug('✅ Final stream usage extraction SUCCESS', {
            streamId,
            usageData,
            actualModel,
            totalEvents: allParsedEvents.length,
            finalBufferSize: finalChunksBuffer.length
          })
        } else {
          logger.warn('❌ Final stream usage extraction FAILED', {
            streamId,
            totalEvents: allParsedEvents.length,
            finalBufferSize: finalChunksBuffer.length,
            mainBufferSize: buffer.length,
            lastFewEvents: allParsedEvents.slice(-3).map((e) => ({
              type: e.type,
              hasUsage: !!e.usage,
              hasResponse: !!e.response,
              keys: Object.keys(e)
            }))
          })
        }

        if (onEnd) {
          onEnd({ usageData, actualModel })
        }

        if (!clientResponse.destroyed) {
          clientResponse.end()
        }

        resolve({ usageData, actualModel })
      } catch (error) {
        logger.error('Stream end handling error:', error)
        reject(error)
      }
    })

    upstreamResponse.data.on('error', (error) => {
      if (hasEnded) {
        return
      }

      streamManager.cleanup(streamId)
      hasEnded = true

      logger.error('Upstream stream error:', error)

      try {
        if (onError) {
          onError(error)
        }

        if (!clientResponse.headersSent) {
          clientResponse.status(502).json({ error: { message: 'Upstream stream error' } })
        } else if (!clientResponse.destroyed) {
          clientResponse.end()
        }
      } catch (cleanupError) {
        logger.warn('Error during stream error cleanup:', cleanupError.message)
      }

      reject(error)
    })

    // 客户端断开时清理
    const clientCleanup = () => {
      streamManager.cleanup(streamId)
    }

    clientResponse.on('close', clientCleanup)
    clientResponse.on('aborted', clientCleanup)
    clientResponse.on('error', clientCleanup)
  })
}

// 强化的用量数据提取函数
function extractUsageDataRobust(responseData, context = 'unknown') {
  logger.debug(`🔍 Attempting usage extraction for ${context}`, {
    responseDataKeys: Object.keys(responseData || {}),
    responseDataType: typeof responseData,
    hasUsage: !!responseData?.usage,
    hasResponse: !!responseData?.response
  })

  let usageData = null
  let actualModel = null

  try {
    // 策略 1: 顶层 usage (标准 Chat Completions)
    if (responseData?.usage) {
      usageData = responseData.usage
      actualModel = responseData.model
      logger.debug('✅ Usage extracted via Strategy 1 (top-level)', { usageData, actualModel })
    }

    // 策略 2: response.usage (Responses API)
    else if (responseData?.response?.usage) {
      usageData = responseData.response.usage
      actualModel = responseData.response.model || responseData.model
      logger.debug('✅ Usage extracted via Strategy 2 (response.usage)', { usageData, actualModel })
    }

    // 策略 3: 嵌套搜索 - 深度查找 usage 字段
    else {
      const findUsageRecursive = (obj, path = '') => {
        if (!obj || typeof obj !== 'object') {
          return null
        }

        for (const [key, value] of Object.entries(obj)) {
          const currentPath = path ? `${path}.${key}` : key

          if (key === 'usage' && value && typeof value === 'object') {
            logger.debug(`✅ Usage found at path: ${currentPath}`, value)
            return { usage: value, path: currentPath }
          }

          if (typeof value === 'object' && value !== null) {
            const nested = findUsageRecursive(value, currentPath)
            if (nested) {
              return nested
            }
          }
        }
        return null
      }

      const found = findUsageRecursive(responseData)
      if (found) {
        usageData = found.usage
        // Try to find model in the same parent object
        const pathParts = found.path.split('.')
        pathParts.pop() // remove 'usage'
        let modelParent = responseData
        for (const part of pathParts) {
          modelParent = modelParent?.[part]
        }
        actualModel = modelParent?.model || responseData?.model
        logger.debug('✅ Usage extracted via Strategy 3 (recursive)', {
          usageData,
          actualModel,
          foundPath: found.path
        })
      }
    }

    // 策略 4: 特殊响应格式处理
    if (!usageData) {
      // 检查是否有 choices 数组，usage 可能在最后一个 choice 中
      if (responseData?.choices?.length > 0) {
        const lastChoice = responseData.choices[responseData.choices.length - 1]
        if (lastChoice?.usage) {
          usageData = lastChoice.usage
          actualModel = responseData.model || lastChoice.model
          logger.debug('✅ Usage extracted via Strategy 4 (choices)', { usageData, actualModel })
        }
      }
    }

    // 最终验证和记录
    if (usageData) {
      logger.debug('🎯 Final usage extraction result', {
        context,
        usageData,
        actualModel,
        inputTokens: usageData.prompt_tokens || usageData.input_tokens || 0,
        outputTokens: usageData.completion_tokens || usageData.output_tokens || 0,
        totalTokens: usageData.total_tokens || 0
      })
    } else {
      logger.warn('❌ Failed to extract usage data', {
        context,
        responseDataStructure: `${JSON.stringify(responseData, null, 2).substring(0, 1000)}...`,
        availableKeys: Object.keys(responseData || {}),
        responseSize: JSON.stringify(responseData || {}).length
      })
    }
  } catch (extractionError) {
    logger.error('🚨 Error during usage extraction', {
      context,
      error: extractionError.message,
      stack: extractionError.stack,
      responseDataType: typeof responseData
    })
  }

  return { usageData, actualModel }
}

// 处理非流式响应
function handleNonStreamResponse(upstreamResponse, clientResponse) {
  try {
    // 设置状态码
    clientResponse.status(upstreamResponse.status)

    // 设置响应头
    clientResponse.setHeader('Content-Type', 'application/json')

    // 透传某些头部
    const passThroughHeaders = [
      'x-request-id',
      'x-ratelimit-remaining-requests',
      'x-ratelimit-remaining-tokens'
    ]
    passThroughHeaders.forEach((header) => {
      const value = upstreamResponse.headers[header]
      if (value) {
        clientResponse.setHeader(header, value)
      }
    })

    // 返回响应数据
    const responseData = upstreamResponse.data
    clientResponse.json(responseData)

    // 使用强化的用量提取
    const { usageData, actualModel } = extractUsageDataRobust(responseData, 'non-stream')

    return { usageData, actualModel, responseData }
  } catch (error) {
    logger.error('Error handling Azure OpenAI non-stream response:', error)
    throw error
  }
}

module.exports = {
  handleAzureOpenAIRequest,
  handleStreamResponse,
  handleNonStreamResponse,
  normalizeModelName
}