mirror of
https://github.com/Wei-Shaw/claude-relay-service.git
synced 2026-01-23 00:53:33 +00:00
feat: 新增支持Azure OpenAI账户
This commit is contained in:
shaw
529
src/services/azureOpenaiRelayService.js
Normal file
529
src/services/azureOpenaiRelayService.js
Normal file
@@ -0,0 +1,529 @@
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const axios = require('axios')
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const ProxyHelper = require('../utils/proxyHelper')
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const logger = require('../utils/logger')
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// 转换模型名称（去掉 azure/ 前缀）
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function normalizeModelName(model) {
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if (model && model.startsWith('azure/')) {
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return model.replace('azure/', '')
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}
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return model
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}
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// 处理 Azure OpenAI 请求
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async function handleAzureOpenAIRequest({
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account,
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requestBody,
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headers: _headers = {}, // 前缀下划线表示未使用
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isStream = false,
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endpoint = 'chat/completions'
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}) {
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// 声明变量在函数顶部，确保在 catch 块中也能访问
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let requestUrl = ''
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let proxyAgent = null
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let deploymentName = ''
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try {
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// 构建 Azure OpenAI 请求 URL
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const baseUrl = account.azureEndpoint
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deploymentName = account.deploymentName || 'default'
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// Azure Responses API requires preview versions; fall back appropriately
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const apiVersion =
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account.apiVersion || (endpoint === 'responses' ? '2024-10-01-preview' : '2024-02-01')
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if (endpoint === 'chat/completions') {
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requestUrl = `${baseUrl}/openai/deployments/${deploymentName}/chat/completions?api-version=${apiVersion}`
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} else if (endpoint === 'responses') {
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requestUrl = `${baseUrl}/openai/responses?api-version=${apiVersion}`
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} else {
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requestUrl = `${baseUrl}/openai/deployments/${deploymentName}/${endpoint}?api-version=${apiVersion}`
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}
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// 准备请求头
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const requestHeaders = {
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'Content-Type': 'application/json',
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'api-key': account.apiKey
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}
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// 移除不需要的头部
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delete requestHeaders['anthropic-version']
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delete requestHeaders['x-api-key']
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delete requestHeaders['host']
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// 处理请求体
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const processedBody = { ...requestBody }
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// 标准化模型名称
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if (processedBody.model) {
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processedBody.model = normalizeModelName(processedBody.model)
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} else {
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processedBody.model = 'gpt-4'
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}
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// 使用统一的代理创建工具
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proxyAgent = ProxyHelper.createProxyAgent(account.proxy)
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// 配置请求选项
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const axiosConfig = {
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method: 'POST',
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url: requestUrl,
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headers: requestHeaders,
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data: processedBody,
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timeout: 600000, // 10 minutes for Azure OpenAI
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validateStatus: () => true,
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// 添加连接保活选项
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keepAlive: true,
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maxRedirects: 5,
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// 防止socket hang up
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socketKeepAlive: true
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}
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// 如果有代理，添加代理配置
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if (proxyAgent) {
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axiosConfig.httpsAgent = proxyAgent
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// 为代理添加额外的keep-alive设置
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if (proxyAgent.options) {
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proxyAgent.options.keepAlive = true
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proxyAgent.options.keepAliveMsecs = 1000
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}
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logger.debug(
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`Using proxy for Azure OpenAI request: ${ProxyHelper.getProxyDescription(account.proxy)}`
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)
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}
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// 流式请求特殊处理
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if (isStream) {
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axiosConfig.responseType = 'stream'
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requestHeaders.accept = 'text/event-stream'
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} else {
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requestHeaders.accept = 'application/json'
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}
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logger.debug(`Making Azure OpenAI request`, {
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requestUrl,
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method: 'POST',
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endpoint,
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deploymentName,
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apiVersion,
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hasProxy: !!proxyAgent,
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proxyInfo: ProxyHelper.maskProxyInfo(account.proxy),
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isStream,
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requestBodySize: JSON.stringify(processedBody).length
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})
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logger.debug('Azure OpenAI request headers', {
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'content-type': requestHeaders['Content-Type'],
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'user-agent': requestHeaders['user-agent'] || 'not-set',
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customHeaders: Object.keys(requestHeaders).filter(
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(key) => !['Content-Type', 'user-agent'].includes(key)
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)
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})
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logger.debug('Azure OpenAI request body', {
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model: processedBody.model,
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messages: processedBody.messages?.length || 0,
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otherParams: Object.keys(processedBody).filter((key) => !['model', 'messages'].includes(key))
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})
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const requestStartTime = Date.now()
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logger.debug(`🔄 Starting Azure OpenAI HTTP request at ${new Date().toISOString()}`)
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// 发送请求
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const response = await axios(axiosConfig)
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const requestDuration = Date.now() - requestStartTime
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logger.debug(`✅ Azure OpenAI HTTP request completed at ${new Date().toISOString()}`)
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logger.debug(`Azure OpenAI response received`, {
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status: response.status,
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statusText: response.statusText,
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duration: `${requestDuration}ms`,
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responseHeaders: Object.keys(response.headers || {}),
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hasData: !!response.data,
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contentType: response.headers?.['content-type'] || 'unknown'
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})
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return response
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} catch (error) {
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const errorDetails = {
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message: error.message,
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code: error.code,
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status: error.response?.status,
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statusText: error.response?.statusText,
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responseData: error.response?.data,
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requestUrl: requestUrl || 'unknown',
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endpoint,
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deploymentName: deploymentName || account?.deploymentName || 'unknown',
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hasProxy: !!proxyAgent,
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proxyType: account?.proxy?.type || 'none',
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isTimeout: error.code === 'ECONNABORTED',
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isNetworkError: !error.response,
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stack: error.stack
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}
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// 特殊错误类型的详细日志
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if (error.code === 'ENOTFOUND') {
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logger.error('DNS Resolution Failed for Azure OpenAI', {
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...errorDetails,
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hostname: requestUrl && requestUrl !== 'unknown' ? new URL(requestUrl).hostname : 'unknown',
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suggestion: 'Check if Azure endpoint URL is correct and accessible'
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})
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} else if (error.code === 'ECONNREFUSED') {
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logger.error('Connection Refused by Azure OpenAI', {
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...errorDetails,
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suggestion: 'Check if proxy settings are correct or Azure service is accessible'
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})
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} else if (error.code === 'ECONNRESET' || error.message.includes('socket hang up')) {
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logger.error('🚨 Azure OpenAI Connection Reset / Socket Hang Up', {
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...errorDetails,
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suggestion:
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'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.'
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})
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} else if (error.code === 'ECONNABORTED' || error.code === 'ETIMEDOUT') {
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logger.error('🚨 Azure OpenAI Request Timeout', {
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...errorDetails,
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timeoutMs: 600000,
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suggestion:
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'Request exceeded 10-minute timeout. Consider reducing model complexity or check if Azure service is responding slowly.'
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})
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} else if (
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error.code === 'CERT_AUTHORITY_INVALID' ||
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error.code === 'UNABLE_TO_VERIFY_LEAF_SIGNATURE'
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) {
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logger.error('SSL Certificate Error for Azure OpenAI', {
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...errorDetails,
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suggestion: 'SSL certificate validation failed - check proxy SSL settings'
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})
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} else if (error.response?.status === 401) {
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logger.error('Azure OpenAI Authentication Failed', {
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...errorDetails,
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suggestion: 'Check if Azure OpenAI API key is valid and not expired'
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})
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} else if (error.response?.status === 404) {
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logger.error('Azure OpenAI Deployment Not Found', {
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...errorDetails,
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suggestion: 'Check if deployment name and Azure endpoint are correct'
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})
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} else {
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logger.error('Azure OpenAI Request Failed', errorDetails)
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}
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throw error
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}
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}
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// 安全的流管理器
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class StreamManager {
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constructor() {
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this.activeStreams = new Set()
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this.cleanupCallbacks = new Map()
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}
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registerStream(streamId, cleanup) {
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this.activeStreams.add(streamId)
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this.cleanupCallbacks.set(streamId, cleanup)
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}
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cleanup(streamId) {
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if (this.activeStreams.has(streamId)) {
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try {
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const cleanup = this.cleanupCallbacks.get(streamId)
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if (cleanup) {
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cleanup()
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}
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} catch (error) {
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logger.warn(`Stream cleanup error for ${streamId}:`, error.message)
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} finally {
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this.activeStreams.delete(streamId)
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this.cleanupCallbacks.delete(streamId)
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}
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}
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}
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getActiveStreamCount() {
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return this.activeStreams.size
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}
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}
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const streamManager = new StreamManager()
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// SSE 缓冲区大小限制
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const MAX_BUFFER_SIZE = 64 * 1024 // 64KB
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const MAX_EVENT_SIZE = 16 * 1024 // 16KB 单个事件最大大小
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// 处理流式响应
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function handleStreamResponse(upstreamResponse, clientResponse, options = {}) {
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const { onData, onEnd, onError } = options
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const streamId = `stream_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`
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logger.info(`Starting Azure OpenAI stream handling`, {
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streamId,
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upstreamStatus: upstreamResponse.status,
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upstreamHeaders: Object.keys(upstreamResponse.headers || {}),
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clientRemoteAddress: clientResponse.req?.connection?.remoteAddress,
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hasOnData: !!onData,
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hasOnEnd: !!onEnd,
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hasOnError: !!onError
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})
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return new Promise((resolve, reject) => {
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let buffer = ''
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let usageData = null
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let actualModel = null
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let hasEnded = false
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let eventCount = 0
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const maxEvents = 10000 // 最大事件数量限制
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// 设置响应头
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clientResponse.setHeader('Content-Type', 'text/event-stream')
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clientResponse.setHeader('Cache-Control', 'no-cache')
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clientResponse.setHeader('Connection', 'keep-alive')
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clientResponse.setHeader('X-Accel-Buffering', 'no')
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// 透传某些头部
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const passThroughHeaders = [
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'x-request-id',
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'x-ratelimit-remaining-requests',
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'x-ratelimit-remaining-tokens'
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]
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passThroughHeaders.forEach((header) => {
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const value = upstreamResponse.headers[header]
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if (value) {
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clientResponse.setHeader(header, value)
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}
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})
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// 立即刷新响应头
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if (typeof clientResponse.flushHeaders === 'function') {
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clientResponse.flushHeaders()
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}
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// 解析 SSE 事件以捕获 usage 数据
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const parseSSEForUsage = (data) => {
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const lines = data.split('\n')
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for (const line of lines) {
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if (line.startsWith('data: ')) {
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try {
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const jsonStr = line.slice(6) // 移除 'data: ' 前缀
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if (jsonStr.trim() === '[DONE]') {
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continue
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}
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const eventData = JSON.parse(jsonStr)
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// 获取模型信息
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if (eventData.model) {
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actualModel = eventData.model
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}
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// 获取使用统计（Responses API: response.completed -> response.usage）
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if (eventData.type === 'response.completed' && eventData.response) {
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if (eventData.response.model) {
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actualModel = eventData.response.model
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}
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if (eventData.response.usage) {
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usageData = eventData.response.usage
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logger.debug('Captured Azure OpenAI nested usage (response.usage):', usageData)
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}
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}
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// 兼容 Chat Completions 风格（顶层 usage）
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if (!usageData && eventData.usage) {
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usageData = eventData.usage
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logger.debug('Captured Azure OpenAI usage (top-level):', usageData)
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}
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// 检查是否是完成事件
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if (eventData.choices && eventData.choices[0] && eventData.choices[0].finish_reason) {
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// 这是最后一个 chunk
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}
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} catch (e) {
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// 忽略解析错误
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}
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}
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}
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}
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// 注册流清理
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const cleanup = () => {
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if (!hasEnded) {
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hasEnded = true
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try {
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upstreamResponse.data?.removeAllListeners?.()
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upstreamResponse.data?.destroy?.()
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if (!clientResponse.headersSent) {
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clientResponse.status(502).end()
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} else if (!clientResponse.destroyed) {
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clientResponse.end()
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}
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} catch (error) {
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logger.warn('Stream cleanup error:', error.message)
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}
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}
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}
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streamManager.registerStream(streamId, cleanup)
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upstreamResponse.data.on('data', (chunk) => {
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try {
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if (hasEnded || clientResponse.destroyed) {
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return
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}
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eventCount++
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if (eventCount > maxEvents) {
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logger.warn(`Stream ${streamId} exceeded max events limit`)
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cleanup()
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return
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}
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const chunkStr = chunk.toString()
|
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// 转发数据给客户端
|
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if (!clientResponse.destroyed) {
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clientResponse.write(chunk)
|
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}
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// 同时解析数据以捕获 usage 信息，带缓冲区大小限制
|
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buffer += chunkStr
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// 防止缓冲区过大
|
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if (buffer.length > MAX_BUFFER_SIZE) {
|
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logger.warn(`Stream ${streamId} buffer exceeded limit, truncating`)
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buffer = buffer.slice(-MAX_BUFFER_SIZE / 2) // 保留后一半
|
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}
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// 处理完整的 SSE 事件
|
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if (buffer.includes('\n\n')) {
|
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const events = buffer.split('\n\n')
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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) {
|
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parseSSEForUsage(event)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (onData) {
|
||||
onData(chunk, { usageData, actualModel })
|
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}
|
||||
} catch (error) {
|
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logger.error('Error processing Azure OpenAI stream chunk:', error)
|
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if (!hasEnded) {
|
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cleanup()
|
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reject(error)
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
upstreamResponse.data.on('end', () => {
|
||||
if (hasEnded) {
|
||||
return
|
||||
}
|
||||
|
||||
streamManager.cleanup(streamId)
|
||||
hasEnded = true
|
||||
|
||||
try {
|
||||
// 处理剩余的 buffer
|
||||
if (buffer.trim() && buffer.length <= MAX_EVENT_SIZE) {
|
||||
parseSSEForUsage(buffer)
|
||||
}
|
||||
|
||||
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)
|
||||
})
|
||||
}
|
||||
|
||||
// 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)
|
||||
|
||||
// 提取 usage 数据
|
||||
const usageData = responseData.usage
|
||||
const actualModel = responseData.model
|
||||
|
||||
return { usageData, actualModel, responseData }
|
||||
} catch (error) {
|
||||
logger.error('Error handling Azure OpenAI non-stream response:', error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
handleAzureOpenAIRequest,
|
||||
handleStreamResponse,
|
||||
handleNonStreamResponse,
|
||||
normalizeModelName
|
||||
}
|
||||
Reference in New Issue
Block a user