name

client/src/pages/api/admin/initv4.ts

@@ -2,22 +2,665 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { authUser } from '@/service/utils/auth';
-import { connectToDatabase, TrainingData, User, promotionRecord } from '@/service/mongo';
-import { TrainingModeEnum } from '@/constants/plugin';
-import mongoose from 'mongoose';
+import { connectToDatabase, App } from '@/service/mongo';
+import { appTemplates } from '@/constants/app';
+import { rawSearchKey } from '@/constants/chat';
+
+const chatTemplate = ({
+  model,
+  temperature,
+  maxToken,
+  systemPrompt,
+  limitPrompt
+}: {
+  model: string;
+  temperature: number;
+  maxToken: number;
+  systemPrompt: string;
+  limitPrompt: string;
+}) => {
+  return [
+    {
+      logo: '/imgs/module/userChatInput.png',
+      name: '用户问题',
+      intro: '用户输入的内容。该模块通常作为应用的入口，用户在发送消息后会首先执行该模块。',
+      type: 'initInput',
+      flowType: 'questionInput',
+      url: '/app/modules/init/userChatInput',
+      inputs: [
+        {
+          key: 'userChatInput',
+          type: 'systemInput',
+          label: '用户问题',
+          connected: false
+        }
+      ],
+      outputs: [
+        {
+          key: 'userChatInput',
+          label: '用户问题',
+          type: 'source',
+          targets: [
+            {
+              moduleId: '7pacf0',
+              key: 'userChatInput'
+            }
+          ]
+        }
+      ],
+      position: {
+        x: 477.9074315528994,
+        y: 1604.2106242223683
+      },
+      moduleId: '7z5g5h'
+    },
+    {
+      logo: '/imgs/module/AI.png',
+      name: 'AI 对话',
+      intro: 'AI 大模型对话',
+      flowType: 'chatNode',
+      type: 'http',
+      url: '/app/modules/chat/gpt',
+      inputs: [
+        {
+          key: 'model',
+          type: 'custom',
+          label: '对话模型',
+          value: model,
+          list: [
+            {
+              label: 'Gpt35-4k',
+              value: 'gpt-3.5-turbo'
+            },
+            {
+              label: 'Gpt35-16k',
+              value: 'gpt-3.5-turbo-16k'
+            },
+            {
+              label: 'Gpt4',
+              value: 'gpt-4'
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'temperature',
+          type: 'slider',
+          label: '温度',
+          value: temperature,
+          min: 0,
+          max: 10,
+          step: 1,
+          markList: [
+            {
+              label: '严谨',
+              value: 0
+            },
+            {
+              label: '发散',
+              value: 10
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'maxToken',
+          type: 'slider',
+          label: '回复上限',
+          value: maxToken,
+          min: 0,
+          max: 16000,
+          step: 50,
+          markList: [
+            {
+              label: '0',
+              value: 0
+            },
+            {
+              label: '16000',
+              value: 16000
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'systemPrompt',
+          type: 'textarea',
+          label: '系统提示词',
+          description:
+            '模型固定的引导词，通过调整该内容，可以引导模型聊天方向。该内容会被固定在上下文的开头。',
+          placeholder:
+            '模型固定的引导词，通过调整该内容，可以引导模型聊天方向。该内容会被固定在上下文的开头。',
+          value: systemPrompt,
+          connected: false
+        },
+        {
+          key: 'limitPrompt',
+          type: 'textarea',
+          label: '限定词',
+          description:
+            '限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。例如:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
+          placeholder:
+            '限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。例如:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
+          value: limitPrompt,
+          connected: false
+        },
+        {
+          key: 'switch',
+          type: 'target',
+          label: '触发器',
+          connected: false
+        },
+        {
+          key: 'quotePrompt',
+          type: 'target',
+          label: '引用内容',
+          connected: false
+        },
+        {
+          key: 'history',
+          type: 'target',
+          label: '聊天记录',
+          connected: true
+        },
+        {
+          key: 'userChatInput',
+          type: 'target',
+          label: '用户问题',
+          connected: true
+        }
+      ],
+      outputs: [
+        {
+          key: 'answerText',
+          label: '模型回复',
+          description: '直接响应，无需配置',
+          type: 'hidden',
+          targets: []
+        }
+      ],
+      position: {
+        x: 981.9682828103937,
+        y: 890.014595014464
+      },
+      moduleId: '7pacf0'
+    },
+    {
+      logo: '/imgs/module/history.png',
+      name: '聊天记录',
+      intro: '用户输入的内容。该模块通常作为应用的入口，用户在发送消息后会首先执行该模块。',
+      type: 'initInput',
+      flowType: 'historyNode',
+      url: '/app/modules/init/history',
+      inputs: [
+        {
+          key: 'maxContext',
+          type: 'numberInput',
+          label: '最长记录数',
+          value: 4,
+          min: 0,
+          max: 50,
+          connected: false
+        },
+        {
+          key: 'history',
+          type: 'hidden',
+          label: '聊天记录',
+          connected: false
+        }
+      ],
+      outputs: [
+        {
+          key: 'history',
+          label: '聊天记录',
+          type: 'source',
+          targets: [
+            {
+              moduleId: '7pacf0',
+              key: 'history'
+            }
+          ]
+        }
+      ],
+      position: {
+        x: 452.5466249541586,
+        y: 1276.3930310334215
+      },
+      moduleId: 'xj0c9p'
+    }
+  ];
+};
+const kbTemplate = ({
+  model,
+  temperature,
+  maxToken,
+  systemPrompt,
+  limitPrompt,
+  kbs = [],
+  searchSimilarity,
+  searchLimit,
+  searchEmptyText
+}: {
+  model: string;
+  temperature: number;
+  maxToken: number;
+  systemPrompt: string;
+  limitPrompt: string;
+  kbs: string[];
+  searchSimilarity: number;
+  searchLimit: number;
+  searchEmptyText: string;
+}) => {
+  return [
+    {
+      logo: '/imgs/module/userChatInput.png',
+      name: '用户问题',
+      intro: '用户输入的内容。该模块通常作为应用的入口，用户在发送消息后会首先执行该模块。',
+      type: 'initInput',
+      flowType: 'questionInput',
+      url: '/app/modules/init/userChatInput',
+      inputs: [
+        {
+          key: 'userChatInput',
+          type: 'systemInput',
+          label: '用户问题',
+          connected: false
+        }
+      ],
+      outputs: [
+        {
+          key: 'userChatInput',
+          label: '用户问题',
+          type: 'source',
+          targets: [
+            {
+              moduleId: 'q9v14m',
+              key: 'userChatInput'
+            },
+            {
+              moduleId: 'qbf8td',
+              key: 'userChatInput'
+            }
+          ]
+        }
+      ],
+      position: {
+        x: -210.24817109253843,
+        y: 665.7922967022607
+      },
+      moduleId: 'v0nc1s'
+    },
+    {
+      logo: '/imgs/module/history.png',
+      name: '聊天记录',
+      intro: '用户输入的内容。该模块通常作为应用的入口，用户在发送消息后会首先执行该模块。',
+      type: 'initInput',
+      flowType: 'historyNode',
+      url: '/app/modules/init/history',
+      inputs: [
+        {
+          key: 'maxContext',
+          type: 'numberInput',
+          label: '最长记录数',
+          value: 4,
+          min: 0,
+          max: 50,
+          connected: false
+        },
+        {
+          key: 'history',
+          type: 'hidden',
+          label: '聊天记录',
+          connected: false
+        }
+      ],
+      outputs: [
+        {
+          key: 'history',
+          label: '聊天记录',
+          type: 'source',
+          targets: [
+            {
+              moduleId: 'qbf8td',
+              key: 'history'
+            }
+          ]
+        }
+      ],
+      position: {
+        x: 211.58250540918442,
+        y: 611.8700401034965
+      },
+      moduleId: 'k9y3jm'
+    },
+    {
+      logo: '/imgs/module/AI.png',
+      name: 'AI 对话',
+      intro: 'AI 大模型对话',
+      flowType: 'chatNode',
+      type: 'http',
+      url: '/app/modules/chat/gpt',
+      inputs: [
+        {
+          key: 'model',
+          type: 'custom',
+          label: '对话模型',
+          value: model,
+          list: [
+            {
+              label: 'Gpt35-4k',
+              value: 'gpt-3.5-turbo'
+            },
+            {
+              label: 'Gpt35-16k',
+              value: 'gpt-3.5-turbo-16k'
+            },
+            {
+              label: 'Gpt4',
+              value: 'gpt-4'
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'temperature',
+          type: 'slider',
+          label: '温度',
+          value: temperature,
+          min: 0,
+          max: 10,
+          step: 1,
+          markList: [
+            {
+              label: '严谨',
+              value: 0
+            },
+            {
+              label: '发散',
+              value: 10
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'maxToken',
+          type: 'slider',
+          label: '回复上限',
+          value: maxToken,
+          min: 0,
+          max: 16000,
+          step: 50,
+          markList: [
+            {
+              label: '0',
+              value: 0
+            },
+            {
+              label: '16000',
+              value: 16000
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'systemPrompt',
+          type: 'textarea',
+          label: '系统提示词',
+          description:
+            '模型固定的引导词，通过调整该内容，可以引导模型聊天方向。该内容会被固定在上下文的开头。',
+          placeholder:
+            '模型固定的引导词，通过调整该内容，可以引导模型聊天方向。该内容会被固定在上下文的开头。',
+          value: systemPrompt,
+          connected: false
+        },
+        {
+          key: 'limitPrompt',
+          type: 'textarea',
+          label: '限定词',
+          description:
+            '限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。例如:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
+          placeholder:
+            '限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。例如:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
+          value: limitPrompt,
+          connected: false
+        },
+        {
+          key: 'switch',
+          type: 'target',
+          label: '触发器',
+          connected: true
+        },
+        {
+          key: 'quotePrompt',
+          type: 'target',
+          label: '引用内容',
+          connected: true
+        },
+        {
+          key: 'history',
+          type: 'target',
+          label: '聊天记录',
+          connected: true
+        },
+        {
+          key: 'userChatInput',
+          type: 'target',
+          label: '用户问题',
+          connected: true
+        }
+      ],
+      outputs: [
+        {
+          key: 'answerText',
+          label: '模型回复',
+          description: '直接响应，无需配置',
+          type: 'hidden',
+          targets: []
+        }
+      ],
+      position: {
+        x: 830.725790038998,
+        y: 201.0790739617387
+      },
+      moduleId: 'qbf8td'
+    },
+    {
+      logo: '/imgs/module/db.png',
+      name: '知识库搜索',
+      intro: '去知识库中搜索对应的答案。可作为 AI 对话引用参考。',
+      flowType: 'kbSearchNode',
+      type: 'http',
+      url: '/app/modules/kb/search',
+      inputs: [
+        {
+          key: 'kb_ids',
+          type: 'custom',
+          label: '关联的知识库',
+          value: kbs,
+          list: [],
+          connected: false
+        },
+        {
+          key: 'similarity',
+          type: 'slider',
+          label: '相似度',
+          value: searchSimilarity,
+          min: 0,
+          max: 1,
+          step: 0.01,
+          markList: [
+            {
+              label: '0',
+              value: 0
+            },
+            {
+              label: '1',
+              value: 1
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'limit',
+          type: 'slider',
+          label: '单次搜索上限',
+          value: searchLimit,
+          min: 1,
+          max: 20,
+          step: 1,
+          markList: [
+            {
+              label: '1',
+              value: 1
+            },
+            {
+              label: '20',
+              value: 20
+            }
+          ],
+          connected: false
+        },
+        {
+          key: 'switch',
+          type: 'target',
+          label: '触发器',
+          connected: true
+        },
+        {
+          key: 'userChatInput',
+          type: 'target',
+          label: '用户问题',
+          connected: true
+        }
+      ],
+      outputs: [
+        {
+          key: rawSearchKey,
+          label: '源搜索数据',
+          type: 'hidden',
+          response: true,
+          targets: []
+        },
+        {
+          key: 'isEmpty',
+          label: '搜索结果为空',
+          type: 'source',
+          targets: [
+            ...(searchEmptyText
+              ? [
+                  {
+                    moduleId: 'w8av9y',
+                    key: 'switch'
+                  }
+                ]
+              : [])
+          ]
+        },
+        {
+          key: 'quotePrompt',
+          label: '引用内容',
+          description: '搜索结果为空时不返回',
+          type: 'source',
+          targets: [
+            {
+              moduleId: 'qbf8td',
+              key: 'quotePrompt'
+            }
+          ]
+        }
+      ],
+      position: {
+        x: 101.2612930583856,
+        y: -31.342317423453437
+      },
+      moduleId: 'q9v14m'
+    },
+    searchEmptyText
+      ? [
+          {
+            logo: '/imgs/module/reply.png',
+            name: '指定回复',
+            intro: '该模块可以直接回复一段指定的内容。常用于引导、提示。',
+            type: 'answer',
+            flowType: 'answerNode',
+            inputs: [
+              {
+                key: 'switch',
+                type: 'target',
+                label: '触发器',
+                connected: true
+              },
+              {
+                key: 'answerText',
+                value: searchEmptyText,
+                type: 'input',
+                label: '回复的内容',
+                connected: false
+              }
+            ],
+            outputs: [],
+            position: {
+              x: 827.8570503787319,
+              y: -63.837994077710675
+            },
+            moduleId: 'w8av9y'
+          }
+        ]
+      : []
+  ];
+};
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
     await authUser({ req, authRoot: true });
-    const { amount, userId, type } = req.body as {
-      amount: number;
-      userId: number;
-      type: 'withdraw';
-    };
     await connectToDatabase();
 
+    // 遍历所有的 app
+    const apps = await App.find(
+      {
+        chat: { $ne: null },
+        modules: { $ne: null }
+      },
+      '_id chat'
+    ).limit(2);
+
+    const result = await Promise.all(
+      apps.map(async (app) => {
+        const modules = (() => {
+          if (app.chat.relatedKbs.length === 0) {
+            return chatTemplate({
+              model: app.chat.chatModel,
+              temperature: app.chat.temperature,
+              maxToken: app.chat.maxToken,
+              systemPrompt: app.chat.systemPrompt,
+              limitPrompt: app.chat.limitPrompt
+            });
+          } else {
+            return kbTemplate({
+              model: app.chat.chatModel,
+              temperature: app.chat.temperature,
+              maxToken: app.chat.maxToken,
+              systemPrompt: app.chat.systemPrompt,
+              limitPrompt: app.chat.limitPrompt,
+              kbs: app.chat.relatedKbs,
+              searchEmptyText: app.chat.searchEmptyText,
+              searchLimit: app.chat.searchLimit,
+              searchSimilarity: app.chat.searchSimilarity
+            });
+          }
+        })();
+
+        return modules;
+      })
+    );
+
+    console.log(apps);
+
     jsonRes(res, {
-      data: ''
+      data: {
+        apps,
+        result
+      }
     });
   } catch (error) {
     jsonRes(res, {

client/src/pages/api/app/modules/agent/classifyQuestion.ts

@@ -6,15 +6,16 @@ import { ChatContextFilter } from '@/service/utils/chat/index';
 import type { ChatItemType } from '@/types/chat';
 import { ChatRoleEnum } from '@/constants/chat';
 import { getOpenAIApi, axiosConfig } from '@/service/ai/openai';
-import type { RecognizeIntentionAgentItemType } from '@/types/app';
+import type { ClassifyQuestionAgentItemType } from '@/types/app';
 import { countModelPrice, pushTaskBillListItem } from '@/service/events/pushBill';
 import { getModel } from '@/service/utils/data';
+import { authUser } from '@/service/utils/auth';
 
 export type Props = {
   systemPrompt?: string;
   history?: ChatItemType[];
   userChatInput: string;
-  agents: RecognizeIntentionAgentItemType[];
+  agents: ClassifyQuestionAgentItemType[];
   billId?: string;
 };
 export type Response = { history: ChatItemType[] };
@@ -24,6 +25,7 @@ const agentFunName = 'agent_user_question';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
+    await authUser({ req, authRoot: true });
     let { userChatInput } = req.body as Props;
 
     if (!userChatInput) {
@@ -114,7 +116,7 @@ export async function classifyQuestion({
 
   await pushTaskBillListItem({
     billId,
-    moduleName: 'Recognize Intention',
+    moduleName: 'Classify Question',
     amount: countModelPrice({ model: agentModel, tokens: totalTokens }),
     model: getModel(agentModel)?.name,
     tokenLen: totalTokens

client/src/pages/api/app/modules/agent/extract.ts

@@ -6,12 +6,13 @@ import { ChatContextFilter } from '@/service/utils/chat/index';
 import type { ChatItemType } from '@/types/chat';
 import { ChatRoleEnum } from '@/constants/chat';
 import { getOpenAIApi, axiosConfig } from '@/service/ai/openai';
-import type { RecognizeIntentionAgentItemType } from '@/types/app';
+import type { ClassifyQuestionAgentItemType } from '@/types/app';
+import { authUser } from '@/service/utils/auth';
 
 export type Props = {
   history?: ChatItemType[];
   userChatInput: string;
-  agents: RecognizeIntentionAgentItemType[];
+  agents: ClassifyQuestionAgentItemType[];
   description: string;
 };
 export type Response = { history: ChatItemType[] };
@@ -21,6 +22,8 @@ const agentFunName = 'agent_extract_data';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
+    await authUser({ req, authRoot: true });
+
     const response = await extract(req.body);
 
     jsonRes(res, {

client/src/pages/api/app/modules/chat/gpt.ts

@@ -13,6 +13,7 @@ import { getOpenAIApi, axiosConfig } from '@/service/ai/openai';
 import { SpecificInputEnum } from '@/constants/app';
 import { getChatModel } from '@/service/utils/data';
 import { countModelPrice, pushTaskBillListItem } from '@/service/events/pushBill';
+import { authUser } from '@/service/utils/auth';
 
 export type Props = {
   model: `${OpenAiChatEnum}`;
@@ -31,6 +32,8 @@ export type Response = { [SpecificInputEnum.answerText]: string; totalTokens: nu
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   let { model, temperature = 0, stream } = req.body as Props;
   try {
+    await authUser({ req, authRoot: true });
+
     const response = await chatCompletion({
       ...req.body,
       res,

client/src/pages/api/app/modules/kb/search.ts

@@ -5,9 +5,10 @@ import { withNextCors } from '@/service/utils/tools';
 import type { ChatItemType } from '@/types/chat';
 import { ChatRoleEnum, rawSearchKey } from '@/constants/chat';
 import { modelToolMap } from '@/utils/plugin';
-import { getVector } from '../../plugin/vector';
+import { getVector } from '@/pages/api/openapi/plugin/vector';
 import { countModelPrice, pushTaskBillListItem } from '@/service/events/pushBill';
 import { getModel } from '@/service/utils/data';
+import { authUser } from '@/service/utils/auth';
 
 export type QuoteItemType = {
   kb_id: string;
@@ -34,6 +35,8 @@ type Response = {
 
 export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
+    await authUser({ req, authRoot: true });
+
     const { kb_ids = [], userChatInput } = req.body as Props;
 
     if (!userChatInput || !Array.isArray(kb_ids)) {