v4.5 (#403)

projects/app/src/service/common/bill/push.ts

@@ -1,12 +1,12 @@
 import { Bill } from '@/service/mongo';
 import { MongoUser } from '@fastgpt/support/user/schema';
 import { BillSourceEnum } from '@/constants/user';
-import { getModel } from '@/service/utils/data';
+import { getModelMap, ModelTypeEnum } from '@/service/core/ai/model';
 import { ChatHistoryItemResType } from '@/types/chat';
 import { formatPrice } from '@fastgpt/common/bill/index';
 import { addLog } from '@/service/utils/tools';
 import type { CreateBillType } from '@/types/common/bill';
-import { defaultQGModel } from '@/pages/api/system/getInitData';
+import { defaultQGModels } from '@/constants/model';
 
 async function createBill(data: CreateBillType) {
   try {
@@ -106,7 +106,7 @@ export const pushQABill = async ({
   addLog.info('splitData generate success', { totalTokens });
 
   // 获取模型单价格, 都是用 gpt35 拆分
-  const unitPrice = global.qaModel.price || 3;
+  const unitPrice = global.qaModels?.[0]?.price || 3;
   // 计算价格
   const total = unitPrice * totalTokens;
 
@@ -158,7 +158,7 @@ export const pushGenerateVectorBill = async ({
         {
           moduleName: '索引生成',
           amount: total,
-          model: vectorModel.model,
+          model: vectorModel.name,
           tokenLen
         }
       ]
@@ -167,14 +167,22 @@ export const pushGenerateVectorBill = async ({
   return { total };
 };
 
-export const countModelPrice = ({ model, tokens }: { model: string; tokens: number }) => {
-  const modelData = getModel(model);
+export const countModelPrice = ({
+  model,
+  tokens,
+  type
+}: {
+  model: string;
+  tokens: number;
+  type: `${ModelTypeEnum}`;
+}) => {
+  const modelData = getModelMap?.[type]?.(model);
   if (!modelData) return 0;
   return modelData.price * tokens;
 };
 
 export const pushQuestionGuideBill = ({ tokens, userId }: { tokens: number; userId: string }) => {
-  const qgModel = global.qgModel || defaultQGModel;
+  const qgModel = global.qgModels?.[0] || defaultQGModels[0];
   const total = qgModel.price * tokens;
   createBill({
     userId,

projects/app/src/service/common/stream.ts

@@ -1,39 +0,0 @@
-import type { NextApiResponse } from 'next';
-
-export function responseWriteController({
-  res,
-  readStream
-}: {
-  res: NextApiResponse;
-  readStream: any;
-}) {
-  res.on('drain', () => {
-    readStream.resume();
-  });
-
-  return (text: string | Buffer) => {
-    const writeResult = res.write(text);
-    if (!writeResult) {
-      readStream.pause();
-    }
-  };
-}
-
-export function responseWrite({
-  res,
-  write,
-  event,
-  data
-}: {
-  res?: NextApiResponse;
-  write?: (text: string) => void;
-  event?: string;
-  data: string;
-}) {
-  const Write = write || res?.write;
-
-  if (!Write) return;
-
-  event && Write(`event: ${event}\n`);
-  Write(`data: ${data}\n\n`);
-}

projects/app/src/service/core/ai/model.ts

@@ -0,0 +1,68 @@
+import {
+  defaultChatModels,
+  defaultCQModels,
+  defaultExtractModels,
+  defaultQAModels,
+  defaultQGModels,
+  defaultVectorModels
+} from '@/constants/model';
+
+export const getChatModel = (model?: string) => {
+  return (
+    (global.chatModels || defaultChatModels).find((item) => item.model === model) ||
+    defaultChatModels[0]
+  );
+};
+export const getQAModel = (model?: string) => {
+  return (
+    (global.qaModels || defaultQAModels).find((item) => item.model === model) ||
+    global.qaModels?.[0] ||
+    defaultQAModels[0]
+  );
+};
+export const getCQModel = (model?: string) => {
+  return (
+    (global.cqModels || defaultCQModels).find((item) => item.model === model) ||
+    global.cqModels?.[0] ||
+    defaultCQModels[0]
+  );
+};
+export const getExtractModel = (model?: string) => {
+  return (
+    (global.extractModels || defaultExtractModels).find((item) => item.model === model) ||
+    global.extractModels?.[0] ||
+    defaultExtractModels[0]
+  );
+};
+export const getQGModel = (model?: string) => {
+  return (
+    (global.qgModels || defaultQGModels).find((item) => item.model === model) ||
+    global.qgModels?.[0] ||
+    defaultQGModels[0]
+  );
+};
+
+export const getVectorModel = (model?: string) => {
+  return (
+    global.vectorModels.find((item) => item.model === model) ||
+    global.vectorModels?.[0] ||
+    defaultVectorModels[0]
+  );
+};
+
+export enum ModelTypeEnum {
+  chat = 'chat',
+  qa = 'qa',
+  cq = 'cq',
+  extract = 'extract',
+  qg = 'qg',
+  vector = 'vector'
+}
+export const getModelMap = {
+  [ModelTypeEnum.chat]: getChatModel,
+  [ModelTypeEnum.qa]: getQAModel,
+  [ModelTypeEnum.cq]: getCQModel,
+  [ModelTypeEnum.extract]: getExtractModel,
+  [ModelTypeEnum.qg]: getQGModel,
+  [ModelTypeEnum.vector]: getVectorModel
+};

projects/app/src/service/core/app/module.ts

@@ -0,0 +1,12 @@
+import { FlowModuleTypeEnum } from '@/constants/flow';
+import { AppModuleItemType } from '@/types/app';
+
+export const getChatModelNameListByModules = (modules: AppModuleItemType[]): string[] => {
+  const chatModules = modules.filter((item) => item.flowType === FlowModuleTypeEnum.chatNode);
+  return chatModules
+    .map((item) => {
+      const model = item.inputs.find((input) => input.key === 'model')?.value;
+      return global.chatModels.find((item) => item.model === model)?.name || '';
+    })
+    .filter((item) => item);
+};

projects/app/src/service/events/generateQA.ts

@@ -73,7 +73,7 @@ export async function generateQA(): Promise<any> {
     ];
     const ai = getAIApi(undefined, 480000);
     const chatResponse = await ai.chat.completions.create({
-      model: global.qaModel.model,
+      model: global.qaModels[0].model,
       temperature: 0.01,
       messages,
       stream: false

projects/app/src/service/moduleDispatch/agent/classifyQuestion.ts

@@ -10,9 +10,11 @@ import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
 import { replaceVariable } from '@/utils/common/tools/text';
 import { Prompt_CQJson } from '@/global/core/prompt/agent';
-import { defaultCQModel } from '@/pages/api/system/getInitData';
+import { FunctionModelItemType } from '@/types/model';
+import { getCQModel } from '@/service/core/ai/model';
 
 type Props = ModuleDispatchProps<{
+  model: string;
   systemPrompt?: string;
   history?: ChatItemType[];
   [SystemInputEnum.userChatInput]: string;
@@ -30,20 +32,26 @@ export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse
   const {
     moduleName,
     user,
-    inputs: { agents, userChatInput }
+    inputs: { model, agents, userChatInput }
   } = props as Props;
 
   if (!userChatInput) {
     return Promise.reject('Input is empty');
   }
 
-  const cqModel = global.cqModel || defaultCQModel;
+  const cqModel = getCQModel(model);
 
   const { arg, tokens } = await (async () => {
     if (cqModel.functionCall) {
-      return functionCall(props);
+      return functionCall({
+        ...props,
+        cqModel
+      });
     }
-    return completions(props);
+    return completions({
+      ...props,
+      cqModel
+    });
   })();
 
   const result = agents.find((item) => item.key === arg?.type) || agents[agents.length - 1];
@@ -64,45 +72,45 @@ export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse
 
 async function functionCall({
   user,
+  cqModel,
   inputs: { agents, systemPrompt, history = [], userChatInput }
-}: Props) {
-  const cqModel = global.cqModel;
-
+}: Props & { cqModel: FunctionModelItemType }) {
   const messages: ChatItemType[] = [
-    ...(systemPrompt
-      ? [
-          {
-            obj: ChatRoleEnum.System,
-            value: systemPrompt
-          }
-        ]
-      : []),
     ...history,
     {
       obj: ChatRoleEnum.Human,
-      value: userChatInput
+      value: systemPrompt
+        ? `补充的背景知识:
+"""
+${systemPrompt}
+"""
+我的问题: ${userChatInput}
+      `
+        : userChatInput
     }
   ];
+
   const filterMessages = ChatContextFilter({
     messages,
     maxTokens: cqModel.maxToken
   });
   const adaptMessages = adaptChat2GptMessages({ messages: filterMessages, reserveId: false });
 
-  //   function body
+  // function body
   const agentFunction = {
     name: agentFunName,
-    description: '判断用户问题的类型属于哪方面，返回对应的字段',
+    description: '请根据对话记录及补充的背景知识，判断用户的问题类型，并返回对应的字段',
     parameters: {
       type: 'object',
       properties: {
         type: {
           type: 'string',
-          description: agents.map((item) => `${item.value}，返回：'${item.key}'`).join('；'),
+          description: `判断用户的问题类型，并返回对应的字段。下面是几种问题类型: ${agents
+            .map((item) => `${item.value}，返回：'${item.key}'`)
+            .join('；')}`,
           enum: agents.map((item) => item.key)
         }
-      },
-      required: ['type']
+      }
     }
   };
   const ai = getAIApi(user.openaiAccount, 48000);
@@ -133,15 +141,14 @@ async function functionCall({
 }
 
 async function completions({
+  cqModel,
   user,
   inputs: { agents, systemPrompt = '', history = [], userChatInput }
-}: Props) {
-  const extractModel = global.extractModel;
-
+}: Props & { cqModel: FunctionModelItemType }) {
   const messages: ChatItemType[] = [
     {
       obj: ChatRoleEnum.Human,
-      value: replaceVariable(extractModel.prompt || Prompt_CQJson, {
+      value: replaceVariable(cqModel.functionPrompt || Prompt_CQJson, {
         systemPrompt,
         typeList: agents.map((item) => `ID: "${item.key}", 问题类型:${item.value}`).join('\n'),
         text: `${history.map((item) => `${item.obj}:${item.value}`).join('\n')}
@@ -153,7 +160,7 @@ Human:${userChatInput}`
   const ai = getAIApi(user.openaiAccount, 480000);
 
   const data = await ai.chat.completions.create({
-    model: extractModel.model,
+    model: cqModel.model,
     temperature: 0.01,
     messages: adaptChat2GptMessages({ messages, reserveId: false }),
     stream: false

projects/app/src/service/moduleDispatch/agent/extract.ts

@@ -9,7 +9,7 @@ import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
 import { Prompt_ExtractJson } from '@/global/core/prompt/agent';
 import { replaceVariable } from '@/utils/common/tools/text';
-import { defaultExtractModel } from '@/pages/api/system/getInitData';
+import { FunctionModelItemType } from '@/types/model';
 
 type Props = ModuleDispatchProps<{
   history?: ChatItemType[];
@@ -37,13 +37,19 @@ export async function dispatchContentExtract(props: Props): Promise<Response> {
     return Promise.reject('Input is empty');
   }
 
-  const extractModel = global.extractModel || defaultExtractModel;
+  const extractModel = global.extractModels[0];
 
   const { arg, tokens } = await (async () => {
     if (extractModel.functionCall) {
-      return functionCall(props);
+      return functionCall({
+        ...props,
+        extractModel
+      });
     }
-    return completions(props);
+    return completions({
+      ...props,
+      extractModel
+    });
   })();
 
   // remove invalid key
@@ -83,11 +89,10 @@ export async function dispatchContentExtract(props: Props): Promise<Response> {
 }
 
 async function functionCall({
+  extractModel,
   user,
   inputs: { history = [], content, extractKeys, description }
-}: Props) {
-  const extractModel = global.extractModel;
-
+}: Props & { extractModel: FunctionModelItemType }) {
   const messages: ChatItemType[] = [
     ...history,
     {
@@ -152,15 +157,14 @@ async function functionCall({
 }
 
 async function completions({
+  extractModel,
   user,
   inputs: { history = [], content, extractKeys, description }
-}: Props) {
-  const extractModel = global.extractModel;
-
+}: Props & { extractModel: FunctionModelItemType }) {
   const messages: ChatItemType[] = [
     {
       obj: ChatRoleEnum.Human,
-      value: replaceVariable(extractModel.prompt || Prompt_ExtractJson, {
+      value: replaceVariable(extractModel.functionPrompt || Prompt_ExtractJson, {
         description,
         json: extractKeys
           .map(

projects/app/src/service/moduleDispatch/chat/oneapi.ts

@@ -7,7 +7,6 @@ import { textAdaptGptResponse } from '@/utils/adapt';
 import { getAIApi } from '@fastgpt/core/ai/config';
 import type { ChatCompletion, StreamChatType } from '@fastgpt/core/ai/type';
 import { TaskResponseKeyEnum } from '@/constants/chat';
-import { getChatModel } from '@/service/utils/data';
 import { countModelPrice } from '@/service/common/bill/push';
 import { ChatModelItemType } from '@/types/model';
 import { postTextCensor } from '@fastgpt/common/plusApi/censor';
@@ -15,12 +14,13 @@ import { ChatCompletionRequestMessageRoleEnum } from '@fastgpt/core/ai/constant'
 import { AppModuleItemType } from '@/types/app';
 import { countMessagesTokens, sliceMessagesTB } from '@/utils/common/tiktoken';
 import { adaptChat2GptMessages } from '@/utils/common/adapt/message';
-import { defaultQuotePrompt, defaultQuoteTemplate } from '@/global/core/prompt/AIChat';
+import { Prompt_QuotePromptList, Prompt_QuoteTemplateList } from '@/global/core/prompt/AIChat';
 import type { AIChatProps } from '@/types/core/aiChat';
 import { replaceVariable } from '@/utils/common/tools/text';
 import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
-import { responseWrite, responseWriteController } from '@/service/common/stream';
+import { responseWrite, responseWriteController } from '@fastgpt/common/tools/stream';
+import { getChatModel, ModelTypeEnum } from '@/service/core/ai/model';
 
 export type ChatProps = ModuleDispatchProps<
   AIChatProps & {
@@ -47,12 +47,13 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
     user,
     outputs,
     inputs: {
-      model = global.chatModels[0]?.model,
+      model,
       temperature = 0,
       maxToken = 4000,
       history = [],
       quoteQA = [],
       userChatInput,
+      isResponseAnswerText = true,
       systemPrompt = '',
       limitPrompt,
       quoteTemplate,
@@ -63,6 +64,8 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
     return Promise.reject('Question is empty');
   }
 
+  stream = stream && isResponseAnswerText;
+
   // temperature adapt
   const modelConstantsData = getChatModel(model);
 
@@ -110,18 +113,18 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
     model,
     temperature,
     max_tokens,
+    stream,
     messages: [
-      ...(modelConstantsData.defaultSystem
+      ...(modelConstantsData.defaultSystemChatPrompt
         ? [
             {
               role: ChatCompletionRequestMessageRoleEnum.System,
-              content: modelConstantsData.defaultSystem
+              content: modelConstantsData.defaultSystemChatPrompt
             }
           ]
         : []),
       ...messages
-    ],
-    stream
+    ]
   });
 
   const { answerText, totalTokens, completeMessages } = await (async () => {
@@ -172,7 +175,9 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
     [TaskResponseKeyEnum.responseData]: {
       moduleType: FlowModuleTypeEnum.chatNode,
       moduleName,
-      price: user.openaiAccount?.key ? 0 : countModelPrice({ model, tokens: totalTokens }),
+      price: user.openaiAccount?.key
+        ? 0
+        : countModelPrice({ model, tokens: totalTokens, type: ModelTypeEnum.chat }),
       model: modelConstantsData.name,
       tokens: totalTokens,
       question: userChatInput,
@@ -198,7 +203,7 @@ function filterQuote({
     maxTokens: model.quoteMaxToken,
     messages: quoteQA.map((item, index) => ({
       obj: ChatRoleEnum.System,
-      value: replaceVariable(quoteTemplate || defaultQuoteTemplate, {
+      value: replaceVariable(quoteTemplate || Prompt_QuoteTemplateList[0].value, {
         ...item,
         index: index + 1
       })
@@ -212,7 +217,7 @@ function filterQuote({
     filterQuoteQA.length > 0
       ? `${filterQuoteQA
           .map((item, index) =>
-            replaceVariable(quoteTemplate || defaultQuoteTemplate, {
+            replaceVariable(quoteTemplate || Prompt_QuoteTemplateList[0].value, {
               ...item,
               index: `${index + 1}`
             })
@@ -243,7 +248,7 @@ function getChatMessages({
   model: ChatModelItemType;
 }) {
   const question = quoteText
-    ? replaceVariable(quotePrompt || defaultQuotePrompt, {
+    ? replaceVariable(quotePrompt || Prompt_QuotePromptList[0].value, {
         quote: quoteText,
         question: userChatInput
       })
@@ -275,7 +280,7 @@ function getChatMessages({
 
   const filterMessages = ChatContextFilter({
     messages,
-    maxTokens: Math.ceil(model.contextMaxToken - 300) // filter token. not response maxToken
+    maxTokens: Math.ceil(model.maxToken - 300) // filter token. not response maxToken
   });
 
   const adaptMessages = adaptChat2GptMessages({ messages: filterMessages, reserveId: false });
@@ -294,7 +299,7 @@ function getMaxTokens({
   model: ChatModelItemType;
   filterMessages: ChatProps['inputs']['history'];
 }) {
-  const tokensLimit = model.contextMaxToken;
+  const tokensLimit = model.maxToken;
   /* count response max token */
 
   const promptsToken = countMessagesTokens({
@@ -349,7 +354,7 @@ async function streamResponse({
       stream.controller?.abort();
       break;
     }
-    const content = part.choices[0]?.delta?.content || '';
+    const content = part.choices?.[0]?.delta?.content || '';
     answer += content;
 
     responseWrite({

projects/app/src/service/moduleDispatch/kb/search.ts

@@ -8,6 +8,7 @@ import type { QuoteItemType } from '@/types/chat';
 import { PgDatasetTableName } from '@/constants/plugin';
 import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
+import { ModelTypeEnum } from '@/service/core/ai/model';
 type KBSearchProps = ModuleDispatchProps<{
   kbList: SelectedDatasetType;
   similarity: number;
@@ -66,7 +67,11 @@ export async function dispatchKBSearch(props: Record<string, any>): Promise<KBSe
     responseData: {
       moduleType: FlowModuleTypeEnum.kbSearchNode,
       moduleName,
-      price: countModelPrice({ model: vectorModel.model, tokens: tokenLen }),
+      price: countModelPrice({
+        model: vectorModel.model,
+        tokens: tokenLen,
+        type: ModelTypeEnum.vector
+      }),
       model: vectorModel.name,
       tokens: tokenLen,
       similarity,

projects/app/src/service/moduleDispatch/tools/answer.ts

@@ -1,5 +1,5 @@
 import { sseResponseEventEnum, TaskResponseKeyEnum } from '@/constants/chat';
-import { sseResponse } from '@/service/utils/tools';
+import { responseWrite } from '@fastgpt/common/tools/stream';
 import { textAdaptGptResponse } from '@/utils/adapt';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
 export type AnswerProps = ModuleDispatchProps<{
@@ -21,7 +21,7 @@ export const dispatchAnswer = (props: Record<string, any>): AnswerResponse => {
   const formatText = typeof text === 'string' ? text : JSON.stringify(text, null, 2);
 
   if (stream) {
-    sseResponse({
+    responseWrite({
       res,
       event: detail ? sseResponseEventEnum.answer : undefined,
       data: textAdaptGptResponse({

projects/app/src/service/moduleDispatch/tools/runApp.ts

@@ -3,7 +3,7 @@ import type { ModuleDispatchProps } from '@/types/core/chat/type';
 import { SelectAppItemType } from '@/types/core/app/flow';
 import { dispatchModules } from '@/pages/api/v1/chat/completions';
 import { App } from '@/service/mongo';
-import { responseWrite } from '@/service/common/stream';
+import { responseWrite } from '@fastgpt/common/tools/stream';
 import { ChatRoleEnum, TaskResponseKeyEnum, sseResponseEventEnum } from '@/constants/chat';
 import { textAdaptGptResponse } from '@/utils/adapt';
 

projects/app/src/service/pg.ts

@@ -232,6 +232,6 @@ export async function initPg() {
     `);
     console.log('init pg successful');
   } catch (error) {
-    addLog.error('init pg error', error);
+    console.log('init pg error', error);
   }
 }

projects/app/src/service/response.ts

@@ -1,7 +1,9 @@
 import { sseResponseEventEnum } from '@/constants/chat';
 import { NextApiResponse } from 'next';
 import { proxyError, ERROR_RESPONSE, ERROR_ENUM } from '@fastgpt/common/constant/errorCode';
-import { clearCookie, sseResponse, addLog } from './utils/tools';
+import { addLog } from './utils/tools';
+import { clearCookie } from '@fastgpt/support/user/auth';
+import { responseWrite } from '@fastgpt/common/tools/stream';
 
 export interface ResponseType<T = any> {
   code: number;
@@ -66,7 +68,7 @@ export const sseErrRes = (res: NextApiResponse, error: any) => {
       clearCookie(res);
     }
 
-    return sseResponse({
+    return responseWrite({
       res,
       event: sseResponseEventEnum.error,
       data: JSON.stringify(ERROR_RESPONSE[errResponseKey])
@@ -86,7 +88,7 @@ export const sseErrRes = (res: NextApiResponse, error: any) => {
 
   addLog.error(`sse error: ${msg}`, error);
 
-  sseResponse({
+  responseWrite({
     res,
     event: sseResponseEventEnum.error,
     data: JSON.stringify({ message: msg })

projects/app/src/service/utils/data.ts

@@ -1,24 +0,0 @@
-export const getChatModel = (model?: string) => {
-  return global.chatModels.find((item) => item.model === model);
-};
-export const getVectorModel = (model?: string) => {
-  return (
-    global.vectorModels.find((item) => item.model === model) || {
-      model: 'UnKnow',
-      name: 'UnKnow',
-      defaultToken: 500,
-      price: 0,
-      maxToken: 3000
-    }
-  );
-};
-
-export const getModel = (model?: string) => {
-  return [
-    ...global.chatModels,
-    ...global.vectorModels,
-    global.qaModel,
-    global.extractModel,
-    global.cqModel
-  ].find((item) => item.model === model);
-};

projects/app/src/service/utils/tools.ts

@@ -1,37 +1,7 @@
-import type { NextApiResponse, NextApiHandler, NextApiRequest } from 'next';
-import NextCors from 'nextjs-cors';
+import type { NextApiResponse } from 'next';
 import { generateQA } from '../events/generateQA';
 import { generateVector } from '../events/generateVector';
 
-/* set cookie */
-export const setCookie = (res: NextApiResponse, token: string) => {
-  res.setHeader(
-    'Set-Cookie',
-    `token=${token}; Path=/; HttpOnly; Max-Age=604800; Samesite=None; Secure;`
-  );
-};
-/* clear cookie */
-export const clearCookie = (res: NextApiResponse) => {
-  res.setHeader('Set-Cookie', 'token=; Path=/; Max-Age=0');
-};
-
-export function withNextCors(handler: NextApiHandler): NextApiHandler {
-  return async function nextApiHandlerWrappedWithNextCors(
-    req: NextApiRequest,
-    res: NextApiResponse
-  ) {
-    const methods = ['GET', 'eHEAD', 'PUT', 'PATCH', 'POST', 'DELETE'];
-    const origin = req.headers.origin;
-    await NextCors(req, res, {
-      methods,
-      origin: origin,
-      optionsSuccessStatus: 200
-    });
-
-    return handler(req, res);
-  };
-}
-
 /* start task */
 export const startQueue = () => {
   if (!global.systemEnv) return;
@@ -43,20 +13,6 @@ export const startQueue = () => {
   }
 };
 
-export const sseResponse = ({
-  res,
-  event,
-  data
-}: {
-  res: NextApiResponse;
-  event?: string;
-  data: string;
-}) => {
-  if (res.closed) return;
-  event && res.write(`event: ${event}\n`);
-  res.write(`data: ${data}\n\n`);
-};
-
 /* add logger */
 export const addLog = {
   info: (msg: string, obj?: Record<string, any>) => {