Upload 14 files

src/routes/chat.js

@@ -1,430 +1,434 @@
-const express = require('express')
-const axios = require('axios')
-const WebSocket = require('ws')
-const router = express.Router()
-const { v4: uuidv4 } = require('uuid')
-const { uploadFileBuffer } = require('../lib/upload')
-const verify = require('./verify')
-const modelMap = require('../lib/model-map')
-
-
-async function parseMessages(req, res, next) {
-  const messages = req.body.messages
-  if (!Array.isArray(messages)) {
-    req.processedMessages = []
-    return next()
-  }
-
-  try {
-    const transformedMessages = await Promise.all(messages.map(async (msg) => {
-      const message = {
-        role: msg.role,
-        tool_calls: [],
-        template_format: "f-string"
-      }
-
-      if (Array.isArray(msg.content)) {
-        const contentItems = await Promise.all(msg.content.map(async (item) => {
-          if (item.type === "text") {
-            return {
-              type: "text",
-              text: item.text
-            }
-          }
-          else if (item.type === "image_url") {
-            try {
-              const base64Match = item.image_url.url.match(/^data:image\/\w+;base64,(.+)$/)
-              if (base64Match) {
-                const base64 = base64Match[1]
-                const data = Buffer.from(base64, 'base64')
-                const uploadResult = await uploadFileBuffer(data)
-
-                return {
-                  type: "media",
-                  media: {
-                    "type": "image",
-                    "url": uploadResult.file_url,
-                    "title": `image_${Date.now()}.png`
-                  }
-                }
-              } else {
-                return {
-                  type: "media",
-                  media: {
-                    "type": "image",
-                    "url": item.image_url.url,
-                    "title": "external_image"
-                  }
-                }
-              }
-            } catch (error) {
-              console.error("处理图像时出错:", error)
-              return {
-                type: "text",
-                text: "[图像处理失败]"
-              }
-            }
-          } else {
-            return {
-              type: "text",
-              text: JSON.stringify(item)
-            }
-          }
-        }))
-
-        message.content = contentItems
-      } else {
-        message.content = [
-          {
-            type: "text",
-            text: msg.content || ""
-          }
-        ]
-      }
-
-      return message
-    }))
-
-    req.body.messages = transformedMessages
-    return next()
-  } catch (error) {
-    console.error("处理消息时出错:", error.status)
-    req.body.messages = []
-    return next(error)
-  }
-}
-
-async function getChatID(req, res) {
-  try {
-    const url = 'https://api.promptlayer.com/api/dashboard/v2/workspaces/' + req.account.workspaceId + '/playground_sessions'
-    const headers = { Authorization: "Bearer " + req.account.token }
-    const model_data = modelMap[req.body.model] ? modelMap[req.body.model] : modelMap["claude-3-7-sonnet-20250219"]
-    let data = {
-      "id": uuidv4(),
-      "name": "Not implemented",
-      "prompt_blueprint": {
-        "inference_client_name": null,
-        "metadata": {
-          "model": model_data
-        },
-        "prompt_template": {
-          "type": "chat",
-          "messages": req.body.messages,
-          "tools": req.body.tools || [],
-          "tool_choice": req.body.tool_choice || "none",
-          "input_variables": [],
-          "functions": [],
-          "function_call": null
-        },
-        "provider_base_url_name": null
-      },
-      "input_variables": []
-    }
-
-    for (const item in req.body) {
-      if (item === "messages" || item === "model" || item === "stream") {
-        continue
-      }  else if (model_data.parameters[item]) {
-        model_data.parameters[item] = req.body[item]
-      }
-    }
-    data.prompt_blueprint.metadata.model = model_data
-    console.log(`模型参数: ${data.prompt_blueprint.metadata.model}`)
-
-    const response = await axios.put(url, data, { headers })
-    if (response.data.success) {
-      console.log(`生成会话ID成功: ${response.data.playground_session.id}`)
-      req.chatID = response.data.playground_session.id
-      return response.data.playground_session.id
-    } else {
-      return false
-    }
-  } catch (error) {
-    // console.error("错误:", error.response?.data)
-    res.status(500).json({
-      "error": {
-        "message": error.message || "服务器内部错误",
-        "type": "server_error",
-        "param": null,
-        "code": "server_error"
-      }
-    })
-    return false
-  }
-}
-
-async function sentRequest(req, res) {
-  try {
-    const url = 'https://api.promptlayer.com/api/dashboard/v2/workspaces/' + req.account.workspaceId + '/run_groups'
-    const headers = { Authorization: "Bearer " + req.account.token }
-    const model_data = modelMap[req.body.model] ? modelMap[req.body.model] : modelMap["claude-3-7-sonnet-20250219"]
-    let data = {
-      "id": uuidv4(),
-      "playground_session_id": req.chatID,
-      "shared_prompt_blueprint": {
-        "inference_client_name": null,
-        "metadata": {
-          "model": model_data
-        },
-        "prompt_template": {
-          "type": "chat",
-          "messages": req.body.messages,
-          "tools": req.body.tools || [],
-          "tool_choice": req.body.tool_choice || "none",
-          "input_variables": [],
-          "functions": [],
-          "function_call": null
-        },
-        "provider_base_url_name": null
-      },
-      "individual_run_requests": [
-        {
-          "input_variables": {},
-          "run_group_position": 1
-        }
-      ]
-    }
-
-    for (const item in req.body) {
-      if (item === "messages" || item === "model" || item === "stream") {
-        continue
-      } else if (model_data.parameters[item]) {
-        model_data.parameters[item] = req.body[item]
-      }
-    }
-    data.shared_prompt_blueprint.metadata.model = model_data
-
-    const response = await axios.post(url, data, { headers })
-    if (response.data.success) {
-      return response.data.run_group.individual_run_requests[0].id
-    } else {
-      return false
-    }
-  } catch (error) {
-    // console.error("错误:", error.response?.data)
-    res.status(500).json({
-      "error": {
-        "message": error.message || "服务器内部错误",
-        "type": "server_error",
-        "param": null,
-        "code": "server_error"
-      }
-    })
-  }
-}
-
-// 聊天完成路由
-router.post('/v1/chat/completions', verify, parseMessages, async (req, res) => {
-  // console.log(JSON.stringify(req.body))
-
-  try {
-
-    const setHeader = () => {
-      try {
-        if (req.body.stream === true) {
-          res.setHeader('Content-Type', 'text/event-stream')
-          res.setHeader('Cache-Control', 'no-cache')
-          res.setHeader('Connection', 'keep-alive')
-        } else {
-          res.setHeader('Content-Type', 'application/json')
-        }
-      } catch (error) {
-        // console.error("设置响应头时出错:", error)
-      }
-    }
-
-    const { access_token, clientId } = req.account
-    // 生成会话ID
-    await getChatID(req, res)
-
-    // 发送的数据
-    const sendAction = `{"action":10,"channel":"user:${clientId}","params":{"agent":"react-hooks/2.0.2"}}`
-    // 构建 WebSocket URL
-    const wsUrl = `wss://realtime.ably.io/?access_token=${encodeURIComponent(access_token)}&clientId=${clientId}&format=json&heartbeats=true&v=3&agent=ably-js%2F2.0.2%20browser`
-    // 创建 WebSocket 连接
-    const ws = new WebSocket(wsUrl)
-
-    // 状态详细
-    let ThinkingLastContent = ""
-    let TextLastContent = ""
-    let ThinkingStart = false
-    let ThinkingEnd = false
-    let RequestID = ""
-    let MessageID = "chatcmpl-" + uuidv4()
-    let streamChunk = {
-      "id": MessageID,
-      "object": "chat.completion.chunk",
-      "system_fingerprint": "fp_44709d6fcb",
-      "created": Math.floor(Date.now() / 1000),
-      "model": req.body.model,
-      "choices": [
-        {
-          "index": 0,
-          "delta": {
-            "content": null
-          },
-          "finish_reason": null
-        }
-      ]
-    }
-
-    ws.on('open', async () => {
-      ws.send(sendAction)
-      RequestID = await sentRequest(req, res)
-      setHeader()
-    })
-
-    ws.on('message', async (data) => {
-      try {
-        data = data.toString()
-        // 在此记录原始 WebSocket 消息
-        console.log("Raw WebSocket message from PromptLayer:", data);
-        // console.log(JSON.parse(data))
-        let ContentText = JSON.parse(data)?.messages?.[0]
-        let ContentData = JSON.parse(ContentText?.data)
-        const isRequestID = ContentData?.individual_run_request_id
-        if (isRequestID != RequestID || !isRequestID) return
-
-        let output = ""
-
-        if (ContentText?.name === "UPDATE_LAST_MESSAGE") {
-          const MessageArray = ContentData?.payload?.message?.content
-          for (const item of MessageArray) {
-
-            if (item.type === "text") {
-              output = item.text.replace(TextLastContent, "")
-              if (ThinkingStart && !ThinkingEnd) {
-                ThinkingEnd = true
-                output = `${output}\n\n</think>`
-              }
-              TextLastContent = item.text
-            }
-            else if (item.type === "thinking" && MessageArray.length === 1) {
-              output = item.thinking.replace(ThinkingLastContent, "")
-              if (!ThinkingStart) {
-                ThinkingStart = true
-                output = `<think>\n\n${output}`
-              }
-              ThinkingLastContent = item.thinking
-            }
-
-          }
-
-          if (req.body.stream === true) {
-            streamChunk.choices[0].delta.content = output
-            res.write(`data: ${JSON.stringify(streamChunk)}\n\n`)
-          }
-
-        }
-        else if (ContentText?.name === "INDIVIDUAL_RUN_COMPLETE") {
-
-          if (req.body.stream !== true) {
-            output = ThinkingLastContent ? `<think>\n\n${ThinkingLastContent}\n\n</think>\n\n${TextLastContent}` : TextLastContent
-          }
-
-          if (ThinkingLastContent === "" && TextLastContent === "") {
-            output = "该模型在发送请求时遇到错误: \n1. 请检查请求参数,模型支持参数和默认参数可在/v1/models下查看\n2. 参数设置大小是否超过模型限制\n3. 模型当前官网此模型可能负载过高,可以切换别的模型尝试,这属于正常现象\n4. Anthropic系列模型的temperature的取值为0-1,请勿设置超过1的值\n5. 交流与支持群: https://t.me/nodejs_project"
-            streamChunk.choices[0].delta.content = output
-            res.write(`data: ${JSON.stringify(streamChunk)}\n\n`)
-          }
-
-          if (!req.body.stream || req.body.stream !== true) {
-            let responseJson = {
-              "id": MessageID,
-              "object": "chat.completion",
-              "created": Math.floor(Date.now() / 1000),
-              "system_fingerprint": "fp_44709d6fcb",
-              "model": req.body.model,
-              "choices": [
-                {
-                  "index": 0,
-                  "message": {
-                    "role": "assistant",
-                    "content": output
-                  },
-                  "finish_reason": "stop"
-                }
-              ],
-              "usage": {
-                "prompt_tokens": 0,
-                "completion_tokens": 0,
-                "total_tokens": 0
-              }
-            }
-
-            res.json(responseJson)
-            ws.close()
-            return
-          } else {
-            // 流式响应：发送结束标记
-            let finalChunk = {
-              "id": MessageID,
-              "object": "chat.completion.chunk",
-              "system_fingerprint": "fp_44709d6fcb",
-              "created": Math.floor(Date.now() / 1000),
-              "model": req.body.model,
-              "choices": [
-                {
-                  "index": 0,
-                  "delta": {},
-                  "finish_reason": "stop"
-                }
-              ]
-            }
-
-            res.write(`data: ${JSON.stringify(finalChunk)}\n\n`)
-            res.write(`data: [DONE]\n\n`)
-            res.end()
-          }
-          ws.close()
-        }
-
-      } catch (err) {
-        // console.error("处理WebSocket消息出错:", err)
-      }
-    })
-
-    ws.on('error', (err) => {
-      // 标准OpenAI错误响应格式
-      res.status(500).json({
-        "error": {
-          "message": err.message,
-          "type": "server_error",
-          "param": null,
-          "code": "server_error"
-        }
-      })
-    })
-
-    setTimeout(() => {
-      if (ws.readyState === WebSocket.OPEN) {
-        ws.close()
-        if (!res.headersSent) {
-          // 标准OpenAI超时错误响应格式
-          res.status(504).json({
-            "error": {
-              "message": "请求超时",
-              "type": "timeout",
-              "param": null,
-              "code": "timeout_error"
-            }
-          })
-        }
-      }
-    }, 300 * 1000)
-
-  } catch (error) {
-    console.error("错误:", error)
-    // 标准OpenAI通用错误响应格式
-    res.status(500).json({
-      "error": {
-        "message": error.message || "服务器内部错误",
-        "type": "server_error",
-        "param": null,
-        "code": "server_error"
-      }
-    })
-  }
-})
-
-module.exports = router
+const express = require('express')
+const axios = require('axios')
+const WebSocket = require('ws')
+const router = express.Router()
+const { v4: uuidv4 } = require('uuid')
+const { uploadFileBuffer } = require('../lib/upload')
+const verify = require('./verify')
+const modelMap = require('../lib/model-map')
+
+
+async function parseMessages(req, res, next) {
+  const messages = req.body.messages
+  if (!Array.isArray(messages)) {
+    req.processedMessages = []
+    return next()
+  }
+
+  try {
+    const transformedMessages = await Promise.all(messages.map(async (msg) => {
+      const message = {
+        role: msg.role,
+        tool_calls: [],
+        template_format: "f-string"
+      }
+
+      if (Array.isArray(msg.content)) {
+        const contentItems = await Promise.all(msg.content.map(async (item) => {
+          if (item.type === "text") {
+            return {
+              type: "text",
+              text: item.text
+            }
+          }
+          else if (item.type === "image_url") {
+            try {
+              const base64Match = item.image_url.url.match(/^data:image\/\w+;base64,(.+)$/)
+              if (base64Match) {
+                const base64 = base64Match[1]
+                const data = Buffer.from(base64, 'base64')
+                const uploadResult = await uploadFileBuffer(data)
+
+                return {
+                  type: "media",
+                  media: {
+                    "type": "image",
+                    "url": uploadResult.file_url,
+                    "title": `image_${Date.now()}.png`
+                  }
+                }
+              } else {
+                return {
+                  type: "media",
+                  media: {
+                    "type": "image",
+                    "url": item.image_url.url,
+                    "title": "external_image"
+                  }
+                }
+              }
+            } catch (error) {
+              console.error("处理图像时出错:", error)
+              return {
+                type: "text",
+                text: "[图像处理失败]"
+              }
+            }
+          } else {
+            return {
+              type: "text",
+              text: JSON.stringify(item)
+            }
+          }
+        }))
+
+        message.content = contentItems
+      } else {
+        message.content = [
+          {
+            type: "text",
+            text: msg.content || ""
+          }
+        ]
+      }
+
+      return message
+    }))
+
+    req.body.messages = transformedMessages
+    return next()
+  } catch (error) {
+    console.error("处理消息时出错:", error.status)
+    req.body.messages = []
+    return next(error)
+  }
+}
+
+async function getChatID(req, res) {
+  try {
+    const url = 'https://api.promptlayer.com/api/dashboard/v2/workspaces/' + req.account.workspaceId + '/playground_sessions'
+    const headers = { Authorization: "Bearer " + req.account.token }
+    const model_data = modelMap[req.body.model] ? modelMap[req.body.model] : modelMap["claude-3-7-sonnet-20250219"]
+    let data = {
+      "id": uuidv4(),
+      "name": "Not implemented",
+      "prompt_blueprint": {
+        "inference_client_name": null,
+        "metadata": {
+          "model": model_data
+        },
+        "prompt_template": {
+          "type": "chat",
+          "messages": req.body.messages,
+          "tools": req.body.tools || [],
+          "tool_choice": req.body.tool_choice || "none",
+          "input_variables": [],
+          "functions": [],
+          "function_call": null
+        },
+        "provider_base_url_name": null
+      },
+      "input_variables": []
+    }
+
+    for (const item in req.body) {
+      if (item === "messages" || item === "model" || item === "stream") {
+        continue
+      }  else if (model_data.parameters[item]) {
+        model_data.parameters[item] = req.body[item]
+      }
+    }
+    data.prompt_blueprint.metadata.model = model_data
+    console.log(`模型参数: ${data.prompt_blueprint.metadata.model}`)
+
+    // Log raw JSON being sent to PromptLayer for getChatID
+    console.log('Raw JSON sent to PromptLayer (getChatID):\n', JSON.stringify(data, null, 2));
+
+    const response = await axios.put(url, data, { headers })
+    if (response.data.success) {
+      console.log(`生成会话ID成功: ${response.data.playground_session.id}`)
+      req.chatID = response.data.playground_session.id
+      return response.data.playground_session.id
+    } else {
+      return false
+    }
+  } catch (error) {
+    // console.error("错误:", error.response?.data)
+    res.status(500).json({
+      "error": {
+        "message": error.message || "服务器内部错误",
+        "type": "server_error",
+        "param": null,
+        "code": "server_error"
+      }
+    })
+    return false
+  }
+}
+
+async function sentRequest(req, res) {
+  try {
+    const url = 'https://api.promptlayer.com/api/dashboard/v2/workspaces/' + req.account.workspaceId + '/run_groups'
+    const headers = { Authorization: "Bearer " + req.account.token }
+    const model_data = modelMap[req.body.model] ? modelMap[req.body.model] : modelMap["claude-3-7-sonnet-20250219"]
+    let data = {
+      "id": uuidv4(),
+      "playground_session_id": req.chatID,
+      "shared_prompt_blueprint": {
+        "inference_client_name": null,
+        "metadata": {
+          "model": model_data
+        },
+        "prompt_template": {
+          "type": "chat",
+          "messages": req.body.messages,
+          "tools": req.body.tools || [],
+          "tool_choice": req.body.tool_choice || "none",
+          "input_variables": [],
+          "functions": [],
+          "function_call": null
+        },
+        "provider_base_url_name": null
+      },
+      "individual_run_requests": [
+        {
+          "input_variables": {},
+          "run_group_position": 1
+        }
+      ]
+    }
+
+    for (const item in req.body) {
+      if (item === "messages" || item === "model" || item === "stream") {
+        continue
+      } else if (model_data.parameters[item]) {
+        model_data.parameters[item] = req.body[item]
+      }
+    }
+    data.shared_prompt_blueprint.metadata.model = model_data
+
+    // Log raw JSON being sent to PromptLayer for sentRequest
+    console.log('Raw JSON sent to PromptLayer (sentRequest):\n', JSON.stringify(data, null, 2));
+
+    const response = await axios.post(url, data, { headers })
+    if (response.data.success) {
+      return response.data.run_group.individual_run_requests[0].id
+    } else {
+      return false
+    }
+  } catch (error) {
+    // console.error("错误:", error.response?.data)
+    res.status(500).json({
+      "error": {
+        "message": error.message || "服务器内部错误",
+        "type": "server_error",
+        "param": null,
+        "code": "server_error"
+      }
+    })
+  }
+}
+
+// 聊天完成路由
+router.post('/v1/chat/completions', verify, parseMessages, async (req, res) => {
+  // console.log(JSON.stringify(req.body))
+
+  try {
+
+    const setHeader = () => {
+      try {
+        if (req.body.stream === true) {
+          res.setHeader('Content-Type', 'text/event-stream')
+          res.setHeader('Cache-Control', 'no-cache')
+          res.setHeader('Connection', 'keep-alive')
+        } else {
+          res.setHeader('Content-Type', 'application/json')
+        }
+      } catch (error) {
+        // console.error("设置响应头时出错:", error)
+      }
+    }
+
+    const { access_token, clientId } = req.account
+    // 生成会话ID
+    await getChatID(req, res)
+
+    // 发送的数据
+    const sendAction = `{"action":10,"channel":"user:${clientId}","params":{"agent":"react-hooks/2.0.2"}}`
+    // 构建 WebSocket URL
+    const wsUrl = `wss://realtime.ably.io/?access_token=${encodeURIComponent(access_token)}&clientId=${clientId}&format=json&heartbeats=true&v=3&agent=ably-js%2F2.0.2%20browser`
+    // 创建 WebSocket 连接
+    const ws = new WebSocket(wsUrl)
+
+    // 状态详细
+    let ThinkingLastContent = ""
+    let TextLastContent = ""
+    let ThinkingStart = false
+    let ThinkingEnd = false
+    let RequestID = ""
+    let MessageID = "chatcmpl-" + uuidv4()
+    let streamChunk = {
+      "id": MessageID,
+      "object": "chat.completion.chunk",
+      "system_fingerprint": "fp_44709d6fcb",
+      "created": Math.floor(Date.now() / 1000),
+      "model": req.body.model,
+      "choices": [
+        {
+          "index": 0,
+          "delta": {
+            "content": null
+          },
+          "finish_reason": null
+        }
+      ]
+    }
+
+    ws.on('open', async () => {
+      ws.send(sendAction)
+      RequestID = await sentRequest(req, res)
+      setHeader()
+    })
+
+    ws.on('message', async (data) => {
+      try {
+        data = data.toString()
+        // console.log(JSON.parse(data))
+        let ContentText = JSON.parse(data)?.messages?.[0]
+        let ContentData = JSON.parse(ContentText?.data)
+        const isRequestID = ContentData?.individual_run_request_id
+        if (isRequestID != RequestID || !isRequestID) return
+
+        let output = ""
+
+        if (ContentText?.name === "UPDATE_LAST_MESSAGE") {
+          const MessageArray = ContentData?.payload?.message?.content
+          for (const item of MessageArray) {
+
+            if (item.type === "text") {
+              output = item.text.replace(TextLastContent, "")
+              if (ThinkingStart && !ThinkingEnd) {
+                ThinkingEnd = true
+                output = `${output}\n\n</think>`
+              }
+              TextLastContent = item.text
+            }
+            else if (item.type === "thinking" && MessageArray.length === 1) {
+              output = item.thinking.replace(ThinkingLastContent, "")
+              if (!ThinkingStart) {
+                ThinkingStart = true
+                output = `<think>\n\n${output}`
+              }
+              ThinkingLastContent = item.thinking
+            }
+
+          }
+
+          if (req.body.stream === true) {
+            streamChunk.choices[0].delta.content = output
+            res.write(`data: ${JSON.stringify(streamChunk)}\n\n`)
+          }
+
+        }
+        else if (ContentText?.name === "INDIVIDUAL_RUN_COMPLETE") {
+
+          if (req.body.stream !== true) {
+            output = ThinkingLastContent ? `<think>\n\n${ThinkingLastContent}\n\n</think>\n\n${TextLastContent}` : TextLastContent
+          }
+
+          if (ThinkingLastContent === "" && TextLastContent === "") {
+            output = "该模型在发送请求时遇到错误: \n1. 请检查请求参数,模型支持参数和默认参数可在/v1/models下查看\n2. 参数设置大小是否超过模型限制\n3. 模型当前官网此模型可能负载过高,可以切换别的模型尝试,这属于正常现象\n4. Anthropic系列模型的temperature的取值为0-1,请勿设置超过1的值\n5. 交流与支持群: https://t.me/nodejs_project"
+            streamChunk.choices[0].delta.content = output
+            res.write(`data: ${JSON.stringify(streamChunk)}\n\n`)
+          }
+
+          if (!req.body.stream || req.body.stream !== true) {
+            let responseJson = {
+              "id": MessageID,
+              "object": "chat.completion",
+              "created": Math.floor(Date.now() / 1000),
+              "system_fingerprint": "fp_44709d6fcb",
+              "model": req.body.model,
+              "choices": [
+                {
+                  "index": 0,
+                  "message": {
+                    "role": "assistant",
+                    "content": output
+                  },
+                  "finish_reason": "stop"
+                }
+              ],
+              "usage": {
+                "prompt_tokens": 0,
+                "completion_tokens": 0,
+                "total_tokens": 0
+              }
+            }
+
+            res.json(responseJson)
+            ws.close()
+            return
+          } else {
+            // 流式响应：发送结束标记
+            let finalChunk = {
+              "id": MessageID,
+              "object": "chat.completion.chunk",
+              "system_fingerprint": "fp_44709d6fcb",
+              "created": Math.floor(Date.now() / 1000),
+              "model": req.body.model,
+              "choices": [
+                {
+                  "index": 0,
+                  "delta": {},
+                  "finish_reason": "stop"
+                }
+              ]
+            }
+
+            res.write(`data: ${JSON.stringify(finalChunk)}\n\n`)
+            res.write(`data: [DONE]\n\n`)
+            res.end()
+          }
+          ws.close()
+        }
+
+      } catch (err) {
+        // console.error("处理WebSocket消息出错:", err)
+      }
+    })
+
+    ws.on('error', (err) => {
+      // 标准OpenAI错误响应格式
+      res.status(500).json({
+        "error": {
+          "message": err.message,
+          "type": "server_error",
+          "param": null,
+          "code": "server_error"
+        }
+      })
+    })
+
+    setTimeout(() => {
+      if (ws.readyState === WebSocket.OPEN) {
+        ws.close()
+        if (!res.headersSent) {
+          // 标准OpenAI超时错误响应格式
+          res.status(504).json({
+            "error": {
+              "message": "请求超时",
+              "type": "timeout",
+              "param": null,
+              "code": "timeout_error"
+            }
+          })
+        }
+      }
+    }, 300 * 1000)
+
+  } catch (error) {
+    console.error("错误:", error)
+    // 标准OpenAI通用错误响应格式
+    res.status(500).json({
+      "error": {
+        "message": error.message || "服务器内部错误",
+        "type": "server_error",
+        "param": null,
+        "code": "server_error"
+      }
+    })
+  }
+})
+
+module.exports = router