model

.github/workflows/admin-image.yml

@@ -0,0 +1,79 @@
+name: Build fastgpt-admin images and copy image to docker hub
+on:
+  workflow_dispatch:
+  push:
+    paths:
+      - 'admin/**'
+    branches:
+      - 'main'
+    tags:
+      - 'v*.*.*'
+jobs:
+  build-admin-images:
+    runs-on: ubuntu-20.04
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 1
+      - name: Install Dependencies
+        run: |
+          sudo apt update && sudo apt install -y nodejs npm
+      - name: Set up QEMU (optional)
+        uses: docker/setup-qemu-action@v2
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+        with:
+          driver-opts: network=host
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ghcr.io
+          username: ${{ github.repository_owner }}
+          password: ${{ secrets.GH_PAT }}
+      - name: Set DOCKER_REPO_TAGGED based on branch or tag
+        run: |
+          if [[ "${{ github.ref_name }}" == "main" ]]; then
+            echo "DOCKER_REPO_TAGGED=ghcr.io/${{ github.repository_owner }}/fastgpt-admin:latest" >> $GITHUB_ENV
+          else
+            echo "DOCKER_REPO_TAGGED=ghcr.io/${{ github.repository_owner }}/fastgpt-admin:${{ github.ref_name }}" >> $GITHUB_ENV
+          fi
+
+      - name: Build and publish image for main branch or tag push event
+        env:
+          DOCKER_REPO_TAGGED: ${{ env.DOCKER_REPO_TAGGED }}
+        run: |
+          cd client && \
+          docker buildx build \
+          --platform linux/amd64,linux/arm64 \
+          --label "org.opencontainers.image.source=  https://github.com/  ${{ github.repository_owner }}/FastGPT" \
+          --label "org.opencontainers.image.description=fastgpt-admin image" \
+          --label "org.opencontainers.image.licenses=MIT" \
+          --push \
+          -t ${DOCKER_REPO_TAGGED} \
+          -f Dockerfile \
+          .
+  push-to-docker-hub:
+    needs: build-admin-images
+    runs-on: ubuntu-20.04
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+      - name: Login to Docker Hub
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKER_HUB_NAME }}
+          password: ${{ secrets.DOCKER_HUB_PASSWORD }}
+      - name: Set DOCKER_REPO_TAGGED based on branch or tag
+        run: |
+          if [[ "${{ github.ref_name }}" == "main" ]]; then
+            echo "IMAGE_TAG=latest" >> $GITHUB_ENV
+          else
+            echo "IMAGE_TAG=${{ github.ref_name }}" >> $GITHUB_ENV
+          fi
+      - name: Pull image from GitHub Container Registry
+        run: docker pull ghcr.io/${{ github.repository_owner }}/fastgpt-admin:${{env.IMAGE_TAG}}
+      - name: Tag image with Docker Hub repository name and version tag
+        run: docker tag ghcr.io/${{ github.repository_owner }}/fastgpt-admin:${{env.IMAGE_TAG}} ${{ secrets.DOCKER_IMAGE_NAME }}:${{env.IMAGE_TAG}}
+      - name: Push image to Docker Hub
+        run: docker push ${{ secrets.DOCKER_IMAGE_NAME }}:${{env.IMAGE_TAG}}

.github/workflows/fastgpt-image.yml

@@ -1,13 +1,15 @@
-name: Build images and copy image to docker
+name: Build fastgpt images and copy image to docker hub
 on:
   workflow_dispatch:
   push:
+    paths:
+      - 'client/**'
     branches:
       - 'main'
     tags:
       - 'v*.*.*'
 jobs:
-  build-images:
+  build-fastgpt-images:
     runs-on: ubuntu-20.04
     steps:
       - name: Checkout
@@ -52,7 +54,7 @@ jobs:
           -f Dockerfile \
           .
   push-to-docker-hub:
-    needs: build-images
+    needs: build-fastgpt-images
     runs-on: ubuntu-20.04
     steps:
       - name: Checkout code

README.md

@@ -23,7 +23,7 @@ Fast GPT 允许你使用自己的 openai API KEY 来快速的调用 openai 接
 
 - [Sealos 部署](https://sealos.io/docs/examples/ai-applications/install-fastgpt-on-desktop) 无需服务器，代理和域名。
 - [docker-compose 部署](docs/deploy/docker.md)
-- [由社区贡献的宝塔部署和本地运行教程](https://space.bilibili.com/431177525/channel/collectiondetail?sid=1370663)
+- [由社区贡献的宝塔部署和本地运行教程](https://www.bilibili.com/video/BV1tV4y1y7Mj/?vd_source=92041a1a395f852f9d89158eaa3f61b4)
 
 ## :point_right: RoadMap
 
@@ -34,14 +34,6 @@ Fast GPT 允许你使用自己的 openai API KEY 来快速的调用 openai 接
 添加 wx 进入：  
 ![Demo](https://otnvvf-imgs.oss.laf.run/wx300.jpg)
 
-## 👀 其他
-
-- [FastGpt 常见问题](https://kjqvjse66l.feishu.cn/docx/HtrgdT0pkonP4kxGx8qcu6XDnGh)
-- [docker 部署教程](https://www.bilibili.com/video/BV1jo4y147fT/)
-- [公众号接入](https://www.bilibili.com/video/BV1xh4y1t7fy/)
-- [FastGpt V3.4 更新集合](https://www.bilibili.com/video/BV1Lo4y147Qh/?vd_source=92041a1a395f852f9d89158eaa3f61b4)
-- [FastGpt 知识库演示](https://www.bilibili.com/video/BV1Wo4y1p7i1/)
-
 ## Powered by
 
 - [TuShan: 5 分钟搭建后台管理系统](https://github.com/msgbyte/tushan)
@@ -49,6 +41,17 @@ Fast GPT 允许你使用自己的 openai API KEY 来快速的调用 openai 接
 - [Sealos: 快速部署集群应用](https://github.com/labring/sealos)
 - [One API: 令牌管理 & 二次分发，支持 Azure](https://github.com/songquanpeng/one-api)
 
+## 👀 其他
+
+- [FastGpt 常见问题](https://kjqvjse66l.feishu.cn/docx/HtrgdT0pkonP4kxGx8qcu6XDnGh)
+- [docker 部署教程视频](https://www.bilibili.com/video/BV1jo4y147fT/)
+- [公众号接入视频教程](https://www.bilibili.com/video/BV1xh4y1t7fy/)
+- [FastGpt 知识库演示](https://www.bilibili.com/video/BV1Wo4y1p7i1/)
+
+## 第三方生态
+
+- [luolinAI: 企微机器人，开箱即用](https://github.com/luolin-ai/FastGPT-Enterprise-WeChatbot)
+
 ## 🌟 Star History
 
 [![Star History Chart](https://api.star-history.com/svg?repos=c121914yu/FastGPT&type=Date)](https://star-history.com/#c121914yu/FastGPT&Date)

admin/service/route/kb.js

@@ -24,7 +24,6 @@ export const useKbRoute = (app) => {
             }
           : {})
       };
-      console.log(where);
 
       const kbsRaw = await Kb.find(where)
         .skip(start)

admin/service/route/user.js

@@ -8,11 +8,12 @@ const hashPassword = (psw) => {
   return crypto.createHash('sha256').update(psw).digest('hex');
 };
 
+const day = 60;
+
 export const useUserRoute = (app) => {
   // 统计近 30 天注册用户数量
   app.get('/users/data', auth(), async (req, res) => {
     try {
-      const day = 60;
       let startCount = await User.countDocuments({
         createTime: { $lt: new Date(Date.now() - day * 24 * 60 * 60 * 1000) }
       });
@@ -92,7 +93,6 @@ export const useUserRoute = (app) => {
       res.status(500).json({ error: 'Error fetching users' });
     }
   });
-
   // 创建用户
   app.post('/users', auth(), async (req, res) => {
     try {
@@ -134,7 +134,6 @@ export const useUserRoute = (app) => {
       res.status(500).json({ error: 'Error updating user' });
     }
   });
-
   // 新增: 获取 pays 列表
   app.get('/pays', auth(), async (req, res) => {
     try {
@@ -179,4 +178,58 @@ export const useUserRoute = (app) => {
       res.status(500).json({ error: 'Error fetching pays', details: err.message });
     }
   });
+  // 获取本月账单
+  app.get('/pays/data', auth(), async (req, res) => {
+    try {
+      let startCount = 0;
+
+      const paysRaw = await Pay.aggregate([
+        {
+          $match: {
+            status: 'SUCCESS',
+            createTime: {
+              $gte: new Date(Date.now() - day * 24 * 60 * 60 * 1000 + 8 * 60 * 60 * 1000) // 补时差
+            }
+          }
+        },
+        {
+          $addFields: {
+            adjustedCreateTime: { $add: ['$createTime', 8 * 60 * 60 * 1000] }
+          }
+        },
+        {
+          $group: {
+            _id: {
+              year: { $year: '$adjustedCreateTime' },
+              month: { $month: '$adjustedCreateTime' },
+              day: { $dayOfMonth: '$adjustedCreateTime' }
+            },
+            count: { $sum: '$price' }
+          }
+        },
+        {
+          $project: {
+            _id: 0,
+            date: { $dateFromParts: { year: '$_id.year', month: '$_id.month', day: '$_id.day' } },
+            count: 1
+          }
+        },
+        { $sort: { date: 1 } }
+      ]);
+
+      const countResult = paysRaw.map((item) => {
+        startCount += item.count;
+        return {
+          date: item.date,
+          total: startCount,
+          count: item.count
+        };
+      });
+
+      res.json(countResult);
+    } catch (err) {
+      console.log(`Error fetching users: ${err}`);
+      res.status(500).json({ error: 'Error fetching users' });
+    }
+  });
 };

admin/src/Dashboard.tsx

@@ -14,14 +14,31 @@ import {
 import dayjs from 'dayjs';
 
 const authStorageKey = 'tushan:auth';
+const PRICE_SCALE = 100000;
 
-type UsersChartDataType = { count: number; date: string; increase: number; increaseRate: string };
+type fetchChatData = {
+  count: number;
+  total?: number;
+  date: string;
+  increase?: number;
+  increaseRate?: string;
+};
+
+type chatDataType = {
+  date: string;
+  userCount: number;
+  userIncrease?: number;
+  userIncreaseRate?: string;
+  payTotal: number;
+  payCount: number;
+};
 
 export const Dashboard: React.FC = React.memo(() => {
   const [userCount, setUserCount] = useState(0); //用户数量
   const [kbCount, setkbCount] = useState(0);
   const [modelCount, setmodelCount] = useState(0);
-  const [usersData, setUsersData] = useState<UsersChartDataType[]>([]);
+
+  const [chatData, setChatData] = useState<chatDataType[]>([]);
 
   useEffect(() => {
     const baseUrl = import.meta.env.VITE_PUBLIC_SERVER_URL;
@@ -56,20 +73,33 @@ export const Dashboard: React.FC = React.memo(() => {
         setmodelCount(Number(modelTotalCount));
       }
     };
-    const fetchUserData = async () => {
-      const userResponse: UsersChartDataType[] = await fetch(`${baseUrl}/users/data`, {
-        headers
-      }).then((res) => res.json());
-      setUsersData(
-        userResponse.map((item) => ({
-          ...item,
-          date: dayjs(item.date).format('MM/DD')
-        }))
-      );
+
+    const fetchChatData = async () => {
+      const [userResponse, payResponse]: fetchChatData[][] = await Promise.all([
+        fetch(`${baseUrl}/users/data`, {
+          headers
+        }).then((res) => res.json()),
+        fetch(`${baseUrl}/pays/data`, {
+          headers
+        }).then((res) => res.json())
+      ]);
+
+      const data = userResponse.map((item, i) => {
+        const pay = payResponse.find((pay) => item.date === pay.date);
+        return {
+          date: dayjs(item.date).format('MM/DD'),
+          userCount: item.count,
+          userIncrease: item.increase,
+          userIncreaseRate: item.increaseRate,
+          payCount: pay ? pay.count / PRICE_SCALE : 0,
+          payTotal: pay?.total ? pay.total / PRICE_SCALE : 0
+        };
+      });
+      setChatData(data);
     };
 
     fetchCounts();
-    fetchUserData();
+    fetchChatData();
   }, []);
 
   return (
@@ -101,7 +131,13 @@ export const Dashboard: React.FC = React.memo(() => {
             </Grid.Row>
 
             <Divider />
-            <UserChart data={usersData} />
+
+            <div>
+              <strong>用户数量 & 支付情况</strong>
+              <UserChart data={chatData} />
+            </div>
+
+            <Divider />
           </Card>
         </Space>
       </div>
@@ -162,7 +198,7 @@ const DataItem = React.memo((props: { icon: React.ReactElement; title: string; c
 DataItem.displayName = 'DataItem';
 
 const CustomTooltip = ({ active, payload }: any) => {
-  const data = payload?.[0]?.payload as UsersChartDataType;
+  const data = payload?.[0]?.payload as chatDataType;
   if (active && data) {
     return (
       <div
@@ -174,13 +210,19 @@ const CustomTooltip = ({ active, payload }: any) => {
         }}
       >
         <p className="label">
-          count: <strong>{data.count}</strong>
+          日期: <strong>{data.date}</strong>
         </p>
         <p className="label">
-          increase: <strong>{data.increase}</strong>
+          用户总数: <strong>{data.userCount}</strong>
         </p>
         <p className="label">
-          increaseRate: <strong>{data.increaseRate}</strong>
+          用户今日增长数量: <strong>{data.userIncrease}</strong>
+        </p>
+        <p className="label">
+          今日支付: <strong>{data.payCount}</strong>元
+        </p>
+        <p className="label">
+          60天累计支付: <strong>{data.payTotal}</strong>元
         </p>
       </div>
     );
@@ -188,7 +230,7 @@ const CustomTooltip = ({ active, payload }: any) => {
   return null;
 };
 
-const UserChart = ({ data }: { data: UsersChartDataType[] }) => {
+const UserChart = ({ data }: { data: chatDataType[] }) => {
   return (
     <ResponsiveContainer width="100%" height={320}>
       <AreaChart
@@ -198,14 +240,14 @@ const UserChart = ({ data }: { data: UsersChartDataType[] }) => {
         margin={{ top: 10, right: 30, left: 0, bottom: 0 }}
       >
         <defs>
-          <linearGradient id="colorUv" x1="0" y1="0" x2="0" y2="1">
-            <stop offset="5%" stopColor="#8884d8" stopOpacity={0.8} />
-            <stop offset="95%" stopColor="#8884d8" stopOpacity={0} />
-          </linearGradient>
-          <linearGradient id="colorPv" x1="0" y1="0" x2="0" y2="1">
+          <linearGradient id="userCount" x1="0" y1="0" x2="0" y2="1">
             <stop offset="5%" stopColor="#82ca9d" stopOpacity={0.8} />
             <stop offset="95%" stopColor="#82ca9d" stopOpacity={0} />
           </linearGradient>
+          <linearGradient id="payTotal" x1="0" y1="0" x2="0" y2="1">
+            <stop offset="5%" stopColor="#8884d8" stopOpacity={0.8} />
+            <stop offset="95%" stopColor="#8884d8" stopOpacity={0} />
+          </linearGradient>
         </defs>
         <XAxis dataKey="date" />
         <YAxis />
@@ -213,10 +255,17 @@ const UserChart = ({ data }: { data: UsersChartDataType[] }) => {
         <Tooltip content={<CustomTooltip />} />
         <Area
           type="monotone"
-          dataKey="count"
+          dataKey="userCount"
           stroke="#82ca9d"
           fillOpacity={1}
-          fill="url(#colorPv)"
+          fill="url(#userCount)"
+        />
+        <Area
+          type="monotone"
+          dataKey="payTotal"
+          stroke="#8884d8"
+          fillOpacity={1}
+          fill="url(#payTotal)"
         />
       </AreaChart>
     </ResponsiveContainer>

client/.env.template

@@ -1,7 +1,7 @@
 # 运行端口，如果不是 3000 口运行，需要改成其他的。注意：不是改了这个变量就会变成其他端口，而是因为改成其他端口，才用这个变量。
 PORT=3000
 # database max link
-DB_MAX_LINK=15
+DB_MAX_LINK=5
 # 代理
 # AXIOS_PROXY_HOST=127.0.0.1
 # AXIOS_PROXY_PORT=7890

client/public/docs/chatProblem.md

@@ -8,9 +8,10 @@
 | --- | --- |
 | 知识库 - 索引 | 0.001 |
 | chatgpt - 对话 | 0.015 |
-| chatgpt16K - 对话 | 0.015 |
-| gpt4 - 对话 | 0.1 |
-| 文件拆分 | 0.015 |
+| chatgpt16K - 对话 | 0.03 |
+| 窝牛 GPT4 不稳定 - 对话 | 0.015 |
+| gpt4 - 对话 | 0.45 |
+| 文件拆分 | 0.03 |
 
 **其他问题**
 | 交流群 | 小助手 |

client/public/docs/intro.md

@@ -20,9 +20,9 @@ FastGpt 项目完全开源，可随意私有化部署，去除平台风险忧虑
 | --- | --- |
 | 知识库 - 索引 | 0.001 |
 | chatgpt - 对话 | 0.015 |
-| chatgpt16K - 对话 | 0.015 |
-| gpt4 - 对话 | 0.1 |
-| 文件拆分 | 0.015 |
+| chatgpt16K - 对话 | 0.03 |
+| gpt4 - 对话 | 0.45 |
+| 文件拆分 | 0.03 |
 
 ### 交流群/问题反馈
 

client/public/docs/versionIntro.md

@@ -1,7 +1,6 @@
 ### Fast GPT V3.9
 
-1. 限时优惠活动，更低价的 tokens。
-2. 新增 - 直接分段训练，可调节段落大小。
-3. 优化 - tokens 计算性能。
-4. 优化 - key 池管理，结合 one-api 项目，实现更方便的 key 池管理，具体参考[docker 部署 FastGpt](https://github.com/c121914yu/FastGPT/blob/main/docs/deploy/docker.md)
-5. 新增 - V2 版 OpenAPI，可以在任意第三方套壳 ChatGpt 项目中直接使用 FastGpt 的应用，注意！是直接，不需要改任何代码。具体参考[API 文档中《在第三方应用中使用 FastGpt》](https://kjqvjse66l.feishu.cn/docx/DmLedTWtUoNGX8xui9ocdUEjnNh)
+1. 新增 - 直接分段训练，可调节段落大小。
+2. 优化 - tokens 计算性能。
+3. 优化 - key 池管理，结合 one-api 项目，实现更方便的 key 池管理，具体参考[docker 部署 FastGpt](https://github.com/c121914yu/FastGPT/blob/main/docs/deploy/docker.md)
+4. 新增 - V2 版 OpenAPI，可以在任意第三方套壳 ChatGpt 项目中直接使用 FastGpt 的应用，注意！是直接，不需要改任何代码。具体参考[API 文档中《在第三方应用中使用 FastGpt》](https://kjqvjse66l.feishu.cn/docx/DmLedTWtUoNGX8xui9ocdUEjnNh)

client/src/components/Layout/index.tsx

@@ -51,7 +51,7 @@ const Layout = ({ children }: { children: JSX.Element }) => {
     return () => {
       window.removeEventListener('resize', resize);
     };
-  }, [setScreenWidth]);
+  }, []);
 
   const { data: unread = 0 } = useQuery(['getUnreadCount'], getUnreadCount, {
     enabled: !!userInfo,
@@ -64,8 +64,8 @@ const Layout = ({ children }: { children: JSX.Element }) => {
         h={'100%'}
         bgGradient={'linear(to-t,rgba(173, 206, 255, 0.05) 0%, rgba(173, 206, 255, 0.12) 100%)'}
       >
-        {isPc ? (
-          pcUnShowLayoutRoute[router.pathname] ? (
+        <Box h={'100%'} display={['none', 'block']}>
+          {pcUnShowLayoutRoute[router.pathname] ? (
             <Auth>{children}</Auth>
           ) : (
             <>
@@ -76,19 +76,22 @@ const Layout = ({ children }: { children: JSX.Element }) => {
                 <Auth>{children}</Auth>
               </Box>
             </>
-          )
-        ) : phoneUnShowLayoutRoute[router.pathname] || isChatPage ? (
-          <Auth>{children}</Auth>
-        ) : (
-          <Flex h={'100%'} flexDirection={'column'}>
-            <Box flex={'1 0 0'} h={0} overflow={'overlay'}>
-              <Auth>{children}</Auth>
-            </Box>
-            <Box h={'50px'} borderTop={'1px solid rgba(0,0,0,0.1)'}>
-              <NavbarPhone unread={unread} />
-            </Box>
-          </Flex>
-        )}
+          )}
+        </Box>
+        <Box h={'100%'} display={['block', 'none']}>
+          {phoneUnShowLayoutRoute[router.pathname] || isChatPage ? (
+            <Auth>{children}</Auth>
+          ) : (
+            <Flex h={'100%'} flexDirection={'column'}>
+              <Box flex={'1 0 0'} h={0} overflow={'overlay'}>
+                <Auth>{children}</Auth>
+              </Box>
+              <Box h={'50px'} borderTop={'1px solid rgba(0,0,0,0.1)'}>
+                <NavbarPhone unread={unread} />
+              </Box>
+            </Flex>
+          )}
+        </Box>
       </Box>
       <Loading loading={loading} />
     </>

client/src/components/Layout/navbarPhone.tsx

@@ -1,7 +1,7 @@
 import React, { useMemo } from 'react';
 import { useRouter } from 'next/router';
 import MyIcon from '../Icon';
-import { Flex } from '@chakra-ui/react';
+import { Flex, Box } from '@chakra-ui/react';
 import { useChatStore } from '@/store/chat';
 import Badge from '../Badge';
 
@@ -11,24 +11,28 @@ const NavbarPhone = ({ unread }: { unread: number }) => {
   const navbarList = useMemo(
     () => [
       {
+        label: '聊天',
         icon: 'tabbarChat',
         link: `/chat?modelId=${lastChatModelId}&chatId=${lastChatId}`,
         activeLink: ['/chat'],
         unread: 0
       },
       {
+        label: '应用',
         icon: 'tabbarModel',
         link: `/model`,
         activeLink: ['/model'],
         unread: 0
       },
       {
+        label: '工具',
         icon: 'tabbarMore',
         link: '/tools',
         activeLink: ['/tools'],
         unread: 0
       },
       {
+        label: '我的',
         icon: 'tabbarMe',
         link: '/number',
         activeLink: ['/number'],
@@ -57,7 +61,9 @@ const NavbarPhone = ({ unread }: { unread: number }) => {
             textAlign={'center'}
             alignItems={'center'}
             h={'100%'}
+            pt={1}
             px={3}
+            transform={'scale(0.9)'}
             {...(item.activeLink.includes(router.asPath)
               ? {
                   color: '#7089f1'
@@ -89,6 +95,7 @@ const NavbarPhone = ({ unread }: { unread: number }) => {
           >
             <Badge isDot count={item.unread}>
               <MyIcon name={item.icon as any} width={'20px'} height={'20px'} />
+              <Box fontSize={'12px'}>{item.label}</Box>
             </Badge>
           </Flex>
         ))}

client/src/components/Select/index.tsx

@@ -1,4 +1,4 @@
-import React from 'react';
+import React, { useRef } from 'react';
 import { Menu, MenuButton, MenuList, MenuItem, Button, useDisclosure } from '@chakra-ui/react';
 import type { ButtonProps } from '@chakra-ui/react';
 import { ChevronDownIcon } from '@chakra-ui/icons';
@@ -13,6 +13,7 @@ interface Props extends ButtonProps {
 }
 
 const MySelect = ({ placeholder, value, width = 'auto', list, onchange, ...props }: Props) => {
+  const ref = useRef<HTMLDivElement>(null);
   const menuItemStyles = {
     borderRadius: 'sm',
     py: 2,
@@ -26,8 +27,9 @@ const MySelect = ({ placeholder, value, width = 'auto', list, onchange, ...props
 
   return (
     <Menu autoSelect={false} onOpen={onOpen} onClose={onClose}>
-      <MenuButton style={{ width: '100%' }} as={'span'}>
+      <MenuButton style={{ width: '100%', position: 'relative' }} as={'span'}>
         <Button
+          ref={ref}
           width={width}
           px={3}
           variant={'base'}
@@ -47,9 +49,15 @@ const MySelect = ({ placeholder, value, width = 'auto', list, onchange, ...props
         </Button>
       </MenuButton>
       <MenuList
-        minW={
-          Array.isArray(width) ? width.map((item) => `${item} !important`) : `${width} !important`
-        }
+        minW={(() => {
+          const w = ref.current?.clientWidth;
+          if (w) {
+            return `${w}px !important`;
+          }
+          return Array.isArray(width)
+            ? width.map((item) => `${item} !important`)
+            : `${width} !important`;
+        })()}
         p={'6px'}
         border={'1px solid #fff'}
         boxShadow={'0px 2px 4px rgba(161, 167, 179, 0.25), 0px 0px 1px rgba(121, 141, 159, 0.25);'}
@@ -78,4 +86,4 @@ const MySelect = ({ placeholder, value, width = 'auto', list, onchange, ...props
   );
 };
 
-export default MySelect;
+export default React.memo(MySelect);

client/src/constants/model.ts

@@ -1,4 +1,3 @@
-import { getSystemModelList } from '@/api/system';
 import type { ShareChatEditType } from '@/types/model';
 import type { ModelSchema } from '@/types/mongoSchema';
 
@@ -10,7 +9,8 @@ export enum OpenAiChatEnum {
   'GPT35' = 'gpt-3.5-turbo',
   'GPT3516k' = 'gpt-3.5-turbo-16k',
   'GPT4' = 'gpt-4',
-  'GPT432k' = 'gpt-4-32k'
+  'GPT432k' = 'gpt-4-32k',
+  'GPT4LOW' = 'gpt-4-0314'
 }
 
 export type ChatModelType = `${OpenAiChatEnum}`;
@@ -25,6 +25,14 @@ export type ChatModelItemType = {
 };
 
 export const ChatModelMap = {
+  [OpenAiChatEnum.GPT4LOW]: {
+    chatModel: OpenAiChatEnum.GPT4LOW,
+    name: '窝牛Gpt4不稳定',
+    contextMaxToken: 4000,
+    systemMaxToken: 2400,
+    maxTemperature: 1.2,
+    price: 1.5
+  },
   [OpenAiChatEnum.GPT35]: {
     chatModel: OpenAiChatEnum.GPT35,
     name: 'Gpt35-4k',
@@ -39,7 +47,7 @@ export const ChatModelMap = {
     contextMaxToken: 16000,
     systemMaxToken: 8000,
     maxTemperature: 1.2,
-    price: 1.5
+    price: 3
   },
   [OpenAiChatEnum.GPT4]: {
     chatModel: OpenAiChatEnum.GPT4,
@@ -47,7 +55,7 @@ export const ChatModelMap = {
     contextMaxToken: 8000,
     systemMaxToken: 4000,
     maxTemperature: 1.2,
-    price: 10
+    price: 45
   },
   [OpenAiChatEnum.GPT432k]: {
     chatModel: OpenAiChatEnum.GPT432k,
@@ -59,15 +67,12 @@ export const ChatModelMap = {
   }
 };
 
-let chatModelList: ChatModelItemType[] = [];
-export const getChatModelList = async () => {
-  if (chatModelList.length > 0) {
-    return chatModelList;
-  }
-  const list = await getSystemModelList();
-  chatModelList = list;
-  return list;
-};
+export const chatModelList: ChatModelItemType[] = [
+  ChatModelMap[OpenAiChatEnum.GPT3516k],
+  ChatModelMap[OpenAiChatEnum.GPT35],
+  ChatModelMap[OpenAiChatEnum.GPT4LOW],
+  ChatModelMap[OpenAiChatEnum.GPT4]
+];
 
 export const defaultModel: ModelSchema = {
   _id: 'modelId',

client/src/hooks/useScreen.ts

@@ -8,7 +8,7 @@ interface Props {
 export function useScreen(data?: Props) {
   const { defaultIsPc = false } = data || {};
   const [isPc] = useMediaQuery('(min-width: 900px)', {
-    ssr: true,
+    ssr: false,
     fallback: defaultIsPc
   });
 

client/src/pages/_app.tsx

@@ -49,7 +49,7 @@ function App({ Component, pageProps }: AppProps) {
         />
         <link rel="icon" href="/favicon.ico" />
       </Head>
-      <Script src="/js/particles.js" strategy="lazyOnload"></Script>
+      <Script src="/js/particles.js"></Script>
       <Script src="/js/qrcode.min.js" strategy="afterInteractive"></Script>
       <Script src="/js/pdf.js" strategy="afterInteractive"></Script>
       <Script src="/js/html2pdf.bundle.min.js" strategy="afterInteractive"></Script>
@@ -60,10 +60,6 @@ function App({ Component, pageProps }: AppProps) {
             src={`https://www.recaptcha.net/recaptcha/api.js?render=${googleVerKey}`}
             strategy="afterInteractive"
           ></Script>
-          <Script
-            src={`https://www.google.com/recaptcha/api.js?render=${googleVerKey}`}
-            strategy="afterInteractive"
-          ></Script>
         </>
       )}
       <QueryClientProvider client={queryClient}>

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

@@ -1,37 +0,0 @@
-// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { jsonRes } from '@/service/response';
-import { authUser } from '@/service/utils/auth';
-import { connectToDatabase, TrainingData } from '@/service/mongo';
-import { TrainingModeEnum } from '@/constants/plugin';
-
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  try {
-    await authUser({ req, authRoot: true });
-
-    await connectToDatabase();
-
-    // split queue data
-    const result = await TrainingData.aggregate([
-      {
-        $group: {
-          _id: '$mode',
-          count: { $sum: 1 }
-        }
-      }
-    ]);
-
-    jsonRes(res, {
-      data: {
-        qaListLen: result.find((item) => item._id === TrainingModeEnum.qa)?.count || 0,
-        vectorListLen: result.find((item) => item._id === TrainingModeEnum.index)?.count || 0
-      }
-    });
-  } catch (error) {
-    console.log(error);
-    jsonRes(res, {
-      code: 500,
-      error
-    });
-  }
-}

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

@@ -0,0 +1,62 @@
+// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
+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';
+
+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();
+
+    if (!userId || !amount || type !== 'withdraw' || amount <= 0) {
+      throw new Error('params is error');
+    }
+
+    // check promotion balance
+    const countResidue: { totalAmount: number }[] = await promotionRecord.aggregate([
+      { $match: { userId: new mongoose.Types.ObjectId(userId) } },
+      {
+        $group: {
+          _id: null, // 分组条件，这里使用 null 表示不分组
+          totalAmount: { $sum: '$amount' } // 计算 amount 字段的总和
+        }
+      },
+      {
+        $project: {
+          _id: false, // 排除 _id 字段
+          totalAmount: true // 只返回 totalAmount 字段
+        }
+      }
+    ]);
+
+    const balance = countResidue[0].totalAmount;
+
+    if (balance < amount) {
+      throw new Error('可提现余额不足');
+    }
+
+    // add record
+    await promotionRecord.create({
+      userId,
+      type,
+      amount: -amount
+    });
+
+    jsonRes(res, {
+      data: balance
+    });
+  } catch (error) {
+    jsonRes(res, {
+      code: 500,
+      error
+    });
+  }
+}

client/src/pages/api/openapi/chat/chat.ts

@@ -129,7 +129,8 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
 
     // 发出请求
     const { streamResponse, responseMessages, responseText, totalTokens } =
-      await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+      await modelServiceToolMap.chatCompletion({
+        model: model.chat.chatModel,
         apiKey,
         temperature: +temperature,
         messages: completePrompts,

client/src/pages/api/openapi/kb/appKbSearch.ts

@@ -150,13 +150,15 @@ export async function appKbSearch({
     }
   ];
 
-  const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
+  const fixedSystemTokens = modelToolMap.countTokens({
+    model: model.chat.chatModel,
     messages: [...userSystemPrompt, ...userLimitPrompt]
   });
 
   // filter part quote by maxToken
-  const sliceResult = modelToolMap[model.chat.chatModel]
+  const sliceResult = modelToolMap
     .tokenSlice({
+      model: model.chat.chatModel,
       maxToken: modelConstantsData.systemMaxToken - fixedSystemTokens,
       messages: filterSearch.map((item, i) => ({
         obj: ChatRoleEnum.System,

client/src/pages/api/openapi/kb/pushData.ts

@@ -78,7 +78,8 @@ export async function pushDataToKb({
 
     if (mode === TrainingModeEnum.qa) {
       // count token
-      const token = modelToolMap[OpenAiChatEnum.GPT3516k].countTokens({
+      const token = modelToolMap.countTokens({
+        model: OpenAiChatEnum.GPT3516k,
         messages: [{ obj: 'System', value: item.q }]
       });
       if (token > modeMaxToken[TrainingModeEnum.qa]) {

client/src/pages/api/openapi/plugin/openaiEmbedding.ts

@@ -39,7 +39,12 @@ export async function openaiEmbedding({
   input,
   mustPay = false
 }: { userId: string; mustPay?: boolean } & Props) {
-  const apiKey = getSystemOpenAiKey();
+  const { userOpenAiKey, systemAuthKey } = await getApiKey({
+    model: 'gpt-3.5-turbo',
+    userId,
+    mustPay
+  });
+  const apiKey = userOpenAiKey || systemAuthKey;
 
   // 获取 chatAPI
   const chatAPI = getOpenAIApi(apiKey);
@@ -68,7 +73,7 @@ export async function openaiEmbedding({
     });
 
   pushGenerateVectorBill({
-    isPay: mustPay,
+    isPay: !userOpenAiKey,
     userId,
     text: input.join(''),
     tokenLen: result.tokenLen

client/src/pages/api/openapi/v1/chat/completions.ts

@@ -169,7 +169,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
           model: model.chat.chatModel,
           usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 },
           choices: [
-            { message: [{ role: 'assistant', content: response }], finish_reason: 'stop', index: 0 }
+            { message: { role: 'assistant', content: response }, finish_reason: 'stop', index: 0 }
           ]
         });
       }
@@ -196,7 +196,8 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
 
     // start model api. responseText and totalTokens: valid only if stream = false
     const { streamResponse, responseMessages, responseText, totalTokens } =
-      await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+      await modelServiceToolMap.chatCompletion({
+        model: model.chat.chatModel,
         apiKey: userOpenAiKey || apiKey,
         temperature: +temperature,
         maxToken: model.chat.maxToken,
@@ -298,7 +299,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
         model: model.chat.chatModel,
         usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: tokens },
         choices: [
-          { message: [{ role: 'assistant', content: answer }], finish_reason: 'stop', index: 0 }
+          { message: { role: 'assistant', content: answer }, finish_reason: 'stop', index: 0 }
         ]
       });
     }

client/src/pages/api/system/getModels.ts

@@ -9,6 +9,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
   chatModelList.push(ChatModelMap[OpenAiChatEnum.GPT3516k]);
   chatModelList.push(ChatModelMap[OpenAiChatEnum.GPT35]);
+  chatModelList.push(ChatModelMap[OpenAiChatEnum.GPT4LOW]);
   chatModelList.push(ChatModelMap[OpenAiChatEnum.GPT4]);
 
   jsonRes(res, {

client/src/pages/api/user/checkPayResult.ts

@@ -2,7 +2,7 @@ import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, User, Pay, TrainingData } from '@/service/mongo';
 import { authUser } from '@/service/utils/auth';
-import { PaySchema, UserModelSchema } from '@/types/mongoSchema';
+import { PaySchema } from '@/types/mongoSchema';
 import dayjs from 'dayjs';
 import { getPayResult } from '@/service/utils/wxpay';
 import { pushPromotionRecord } from '@/service/utils/promotion';

client/src/pages/api/user/inform/send.ts

@@ -4,6 +4,7 @@ import { jsonRes } from '@/service/response';
 import { connectToDatabase, Inform, User } from '@/service/mongo';
 import { authUser } from '@/service/utils/auth';
 import { InformTypeEnum } from '@/constants/user';
+import { startSendInform } from '@/service/events/sendInform';
 
 export type Props = {
   type: `${InformTypeEnum}`;
@@ -37,25 +38,26 @@ export async function sendInform({ type, title, content, userId }: Props) {
 
   try {
     if (userId) {
-      // skip it if have same inform within 5 minutes
-      const inform = await Inform.findOne({
-        type,
-        title,
-        content,
-        userId,
-        read: false,
-        time: { $lte: new Date(Date.now() + 5 * 60 * 1000) }
+      global.sendInformQueue.push(async () => {
+        // skip it if have same inform within 5 minutes
+        const inform = await Inform.findOne({
+          type,
+          title,
+          content,
+          userId,
+          time: { $gte: new Date(Date.now() - 5 * 60 * 1000) }
+        });
+
+        if (inform) return;
+
+        await Inform.create({
+          type,
+          title,
+          content,
+          userId
+        });
       });
-
-      if (inform) return;
-
-      await Inform.create({
-        type,
-        title,
-        content,
-        userId
-      });
-
+      startSendInform();
       return;
     }
 

client/src/pages/chat/index.tsx

@@ -63,8 +63,9 @@ import { adaptChatItem_openAI } from '@/utils/plugin/openai';
 
 const textareaMinH = '22px';
 
-const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
+const Chat = () => {
   const router = useRouter();
+  const { modelId = '', chatId = '' } = router.query as { modelId: string; chatId: string };
   const theme = useTheme();
 
   const ChatBox = useRef<HTMLDivElement>(null);
@@ -950,11 +951,4 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
   );
 };
 
-Chat.getInitialProps = ({ query, req }: any) => {
-  return {
-    modelId: query?.modelId || '',
-    chatId: query?.chatId || ''
-  };
-};
-
 export default Chat;

client/src/pages/chat/share.tsx

@@ -60,8 +60,9 @@ import { adaptChatItem_openAI } from '@/utils/plugin/openai';
 
 const textareaMinH = '22px';
 
-const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => {
+const Chat = () => {
   const router = useRouter();
+  const { shareId = '', historyId } = router.query as { shareId: string; historyId: string };
   const theme = useTheme();
 
   const ChatBox = useRef<HTMLDivElement>(null);
@@ -490,14 +491,13 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
   ]);
 
   // 初始化聊天框
-  useQuery(['init', historyId], () => {
+  useQuery(['init', shareId, historyId], () => {
     if (!shareId) {
       return null;
     }
 
     if (!historyId) {
-      router.replace(`/chat/share?shareId=${shareId}&historyId=${new Types.ObjectId()}`);
-      return null;
+      return router.replace(`/chat/share?shareId=${shareId}&historyId=${new Types.ObjectId()}`);
     }
 
     return loadChatInfo();
@@ -837,11 +837,4 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
   );
 };
 
-Chat.getInitialProps = ({ query, req }: any) => {
-  return {
-    shareId: query?.shareId || '',
-    historyId: query?.historyId || ''
-  };
-};
-
 export default Chat;

client/src/pages/index.tsx

@@ -140,8 +140,10 @@ const Home = () => {
 
   useEffect(() => {
     (async () => {
-      const { data: git } = await axios.get('https://api.github.com/repos/c121914yu/FastGPT');
-      setStar(git.stargazers_count);
+      try {
+        const { data: git } = await axios.get('https://api.github.com/repos/c121914yu/FastGPT');
+        setStar(git.stargazers_count);
+      } catch (error) {}
     })();
   }, []);
 

client/src/pages/kb/components/DataCard.tsx

@@ -154,7 +154,7 @@ const DataCard = ({ kbId }: { kbId: string }) => {
             mr={[2, 4]}
             size={'sm'}
             onClick={() => {
-              refetchData(pageNum);
+              getData(pageNum);
               getTrainingData({ kbId, init: true });
             }}
           />

client/src/pages/kb/index.tsx

@@ -7,8 +7,9 @@ import SideBar from '@/components/SideBar';
 import KbList from './components/KbList';
 import KbDetail from './components/Detail';
 
-const Kb = ({ kbId }: { kbId: string }) => {
+const Kb = () => {
   const router = useRouter();
+  const { kbId = '' } = router.query as { kbId: string };
   const { isPc } = useGlobalStore();
   const { lastKbId } = useUserStore();
 
@@ -35,9 +36,3 @@ const Kb = ({ kbId }: { kbId: string }) => {
 };
 
 export default Kb;
-
-Kb.getInitialProps = ({ query, req }: any) => {
-  return {
-    kbId: query?.kbId || ''
-  };
-};

client/src/pages/model/components/ModelList.tsx

@@ -12,10 +12,10 @@ import { MyModelsTypeEnum } from '@/constants/user';
 import dynamic from 'next/dynamic';
 
 const Avatar = dynamic(() => import('@/components/Avatar'), {
-  ssr: true
+  ssr: false
 });
 const Tabs = dynamic(() => import('@/components/Tabs'), {
-  ssr: true
+  ssr: false
 });
 
 const ModelList = ({ modelId }: { modelId: string }) => {

client/src/pages/model/components/detail/components/API.tsx

@@ -5,7 +5,7 @@ import dynamic from 'next/dynamic';
 import MyIcon from '@/components/Icon';
 
 const APIKeyModal = dynamic(() => import('@/components/APIKeyModal'), {
-  ssr: true
+  ssr: false
 });
 
 const API = ({ modelId }: { modelId: string }) => {

client/src/pages/model/components/detail/components/Settings.tsx

@@ -21,7 +21,7 @@ import { useSelectFile } from '@/hooks/useSelectFile';
 import { compressImg } from '@/utils/file';
 import { getErrText } from '@/utils/tools';
 import { useConfirm } from '@/hooks/useConfirm';
-import { ChatModelMap, getChatModelList } from '@/constants/model';
+import { ChatModelMap, chatModelList } from '@/constants/model';
 import { formatPrice } from '@/utils/user';
 
 import type { ModelSchema } from '@/types/mongoSchema';
@@ -75,7 +75,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
     }
 
     return max;
-  }, [getValues, setValue]);
+  }, [getValues, setValue, refresh]);
 
   // 提交保存模型修改
   const saveSubmitSuccess = useCallback(
@@ -185,8 +185,6 @@ const Settings = ({ modelId }: { modelId: string }) => {
     }
   });
 
-  const { data: chatModelList = [] } = useQuery(['initChatModelList'], getChatModelList);
-
   return (
     <Box
       pb={3}
@@ -240,12 +238,12 @@ const Settings = ({ modelId }: { modelId: string }) => {
           对话模型
         </Box>
         <MySelect
-          width={['100%', '280px']}
+          width={['100%', '300px']}
           value={getValues('chat.chatModel')}
           list={chatModelList.map((item) => ({
             id: item.chatModel,
             label: `${item.name} (${formatPrice(
-              ChatModelMap[getValues('chat.chatModel')]?.price,
+              ChatModelMap[item.chatModel]?.price,
               1000
             )} 元/1k tokens)`
           }))}
@@ -265,7 +263,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
               { label: '严谨', value: 0 },
               { label: '发散', value: 10 }
             ]}
-            width={['100%', '260px']}
+            width={['95%', '280px']}
             min={0}
             max={10}
             activeVal={getValues('chat.temperature')}
@@ -286,7 +284,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
               { label: '100', value: 100 },
               { label: `${tokenLimit}`, value: tokenLimit }
             ]}
-            width={['100%', '260px']}
+            width={['95%', '280px']}
             min={100}
             max={tokenLimit}
             step={50}

client/src/pages/model/index.tsx

@@ -13,8 +13,9 @@ const ModelDetail = dynamic(() => import('./components/detail/index'), {
   ssr: false
 });
 
-const Model = ({ modelId }: { modelId: string }) => {
+const Model = () => {
   const router = useRouter();
+  const { modelId = '' } = router.query as { modelId: string };
   const { isPc } = useGlobalStore();
   const { lastModelId } = useUserStore();
 
@@ -41,9 +42,3 @@ const Model = ({ modelId }: { modelId: string }) => {
 };
 
 export default Model;
-
-Model.getInitialProps = ({ query, req }: any) => {
-  return {
-    modelId: query?.modelId || ''
-  };
-};

client/src/pages/number/components/BillTable.tsx

@@ -40,7 +40,7 @@ const BillTable = () => {
             <Tr>
               <Th>时间</Th>
               <Th>类型</Th>
-              <Th>底层模型</Th>
+              <Th>模型</Th>
               <Th>内容长度</Th>
               <Th>Tokens 长度</Th>
               <Th>金额</Th>

client/src/pages/number/components/PayModal.tsx

@@ -115,9 +115,9 @@ const PayModal = ({ onClose }: { onClose: () => void }) => {
 | --- | --- |
 | 知识库 - 索引 | 0.001 |
 | chatgpt - 对话 | 0.015 |
-| chatgpt16K - 对话 | 0.015 |
-| gpt4 - 对话 | 0.1 |
-| 文件拆分 | 0.015 |`}
+| chatgpt16K - 对话 | 0.03 |
+| gpt4 - 对话 | 0.45 |
+| 文件拆分 | 0.03 |`}
                 />
               </>
             )}

client/src/pages/number/index.tsx

@@ -23,21 +23,21 @@ import Tabs from '@/components/Tabs';
 import BillTable from './components/BillTable';
 
 const PayRecordTable = dynamic(() => import('./components/PayRecordTable'), {
-  ssr: true
+  ssr: false
 });
 const PromotionTable = dynamic(() => import('./components/PromotionTable'), {
-  ssr: true
+  ssr: false
 });
 const InformTable = dynamic(() => import('./components/InformTable'), {
-  ssr: true
+  ssr: false
 });
 const PayModal = dynamic(() => import('./components/PayModal'), {
   loading: () => <Loading fixed={false} />,
-  ssr: true
+  ssr: false
 });
 const WxConcat = dynamic(() => import('@/components/WxConcat'), {
   loading: () => <Loading fixed={false} />,
-  ssr: true
+  ssr: false
 });
 
 enum TableEnum {
@@ -54,7 +54,6 @@ const NumberSetting = ({ tableType }: { tableType: `${TableEnum}` }) => {
     { label: '佣金', id: TableEnum.promotion, Component: <PromotionTable /> },
     { label: '通知', id: TableEnum.inform, Component: <InformTable /> }
   ]);
-  const [currentTab, setCurrentTab] = useState(tableType);
 
   const router = useRouter();
   const { copyData } = useCopyData();
@@ -84,7 +83,14 @@ const NumberSetting = ({ tableType }: { tableType: `${TableEnum}` }) => {
     async (data: UserUpdateParams) => {
       setLoading(true);
       try {
-        data.openaiKey && (await authOpenAiKey(data.openaiKey));
+        if (data.openaiKey) {
+          const text = await authOpenAiKey(data.openaiKey);
+          text &&
+            toast({
+              title: text,
+              status: 'warning'
+            });
+        }
         await putUserInfo({
           openaiKey: data.openaiKey,
           avatar: data.avatar
@@ -95,7 +101,7 @@ const NumberSetting = ({ tableType }: { tableType: `${TableEnum}` }) => {
         });
         reset(data);
         toast({
-          title: '更新成功',
+          title: '更新数据成功',
           status: 'success'
         });
       } catch (error) {
@@ -195,7 +201,7 @@ const NumberSetting = ({ tableType }: { tableType: `${TableEnum}` }) => {
             <Box flex={'0 0 85px'}>openaiKey:</Box>
             <Input
               {...register(`openaiKey`)}
-              maxW={'300px'}
+              maxW={'350px'}
               placeholder={'openai账号。回车或失去焦点保存'}
               size={'sm'}
               onBlur={handleSubmit(onclickSave)}
@@ -214,7 +220,8 @@ const NumberSetting = ({ tableType }: { tableType: `${TableEnum}` }) => {
           {[
             { label: '佣金比例', value: `${userInfo?.promotion.rate || 15}%` },
             { label: '已注册用户数', value: `${invitedAmount}人` },
-            { label: '累计佣金', value: `￥${historyAmount}` }
+            { label: '累计佣金', value: `￥${historyAmount}` },
+            { label: '可用佣金', value: `￥${residueAmount}` }
           ].map((item) => (
             <Flex key={item.label} alignItems={'center'} mt={4} justifyContent={'space-between'}>
               <Box w={'120px'}>{item.label}</Box>
@@ -251,13 +258,13 @@ const NumberSetting = ({ tableType }: { tableType: `${TableEnum}` }) => {
           m={'auto'}
           w={'200px'}
           list={tableList.current}
-          activeId={currentTab}
+          activeId={tableType}
           size={'sm'}
-          onChange={(id: any) => setCurrentTab(id)}
+          onChange={(id: any) => router.replace(`/number?type=${id}`)}
         />
         <Box minH={'300px'}>
           {(() => {
-            const item = tableList.current.find((item) => item.id === currentTab);
+            const item = tableList.current.find((item) => item.id === tableType);
 
             return item ? item.Component : null;
           })()}

client/src/service/events/generateQA.ts

@@ -63,8 +63,9 @@ export async function generateQA(): Promise<any> {
     // 请求 chatgpt 获取回答
     const response = await Promise.all(
       [data.q].map((text) =>
-        modelServiceToolMap[OpenAiChatEnum.GPT3516k]
+        modelServiceToolMap
           .chatCompletion({
+            model: OpenAiChatEnum.GPT3516k,
             apiKey: systemAuthKey,
             temperature: 0.8,
             messages: [
@@ -153,7 +154,8 @@ A2:
       sendInform({
         type: 'system',
         title: 'QA 任务中止',
-        content: '由于账号余额不足，QA 任务中止，重新充值后将会继续。',
+        content:
+          '由于账号余额不足，索引生成任务中止，重新充值后将会继续。暂停的任务将在 7 天后被删除。',
         userId
       });
       console.log('余额不足，暂停向量生成任务');

client/src/service/events/generateVector.ts

@@ -104,7 +104,8 @@ export async function generateVector(): Promise<any> {
       sendInform({
         type: 'system',
         title: '索引生成任务中止',
-        content: '由于账号余额不足，索引生成任务中止，重新充值后将会继续。',
+        content:
+          '由于账号余额不足，索引生成任务中止，重新充值后将会继续。暂停的任务将在 7 天后被删除。',
         userId
       });
       console.log('余额不足，暂停向量生成任务');

client/src/service/events/sendInform.ts

@@ -0,0 +1,16 @@
+export const startSendInform = async () => {
+  if (global.sendInformQueue.length === 0 || global.sendInformQueueLen > 0) return;
+  global.sendInformQueueLen++;
+
+  try {
+    const fn = global.sendInformQueue[global.sendInformQueue.length - 1];
+    await fn();
+    global.sendInformQueue.pop();
+    global.sendInformQueueLen--;
+
+    startSendInform();
+  } catch (error) {
+    global.sendInformQueueLen--;
+    startSendInform();
+  }
+};

client/src/service/models/trainingData.ts

@@ -15,6 +15,10 @@ const TrainingDataSchema = new Schema({
     ref: 'kb',
     required: true
   },
+  expireAt: {
+    type: Date,
+    default: () => new Date()
+  },
   lockTime: {
     type: Date,
     default: () => new Date('2000/1/1')
@@ -44,5 +48,13 @@ const TrainingDataSchema = new Schema({
   }
 });
 
+try {
+  TrainingDataSchema.index({ lockTime: 1 });
+  TrainingDataSchema.index({ userId: 1 });
+  TrainingDataSchema.index({ expireAt: 1 }, { expireAfterSeconds: 7 * 24 * 60 });
+} catch (error) {
+  console.log(error);
+}
+
 export const TrainingData: MongoModel<TrainingDateType> =
   models['trainingData'] || model('trainingData', TrainingDataSchema);

client/src/service/mongo.ts

@@ -20,6 +20,8 @@ export async function connectToDatabase(): Promise<void> {
     pgIvfflatProbe: 10,
     sensitiveCheck: false
   };
+  global.sendInformQueue = [];
+  global.sendInformQueueLen = 0;
   // proxy obj
   if (process.env.AXIOS_PROXY_HOST && process.env.AXIOS_PROXY_PORT) {
     global.httpsAgent = tunnel.httpsOverHttp({
@@ -36,9 +38,9 @@ export async function connectToDatabase(): Promise<void> {
     global.mongodb = await mongoose.connect(process.env.MONGODB_URI as string, {
       bufferCommands: true,
       dbName: process.env.MONGODB_NAME,
-      maxConnecting: Number(process.env.DB_MAX_LINK || 10),
-      maxPoolSize: Number(process.env.DB_MAX_LINK || 10),
-      minPoolSize: 5
+      maxConnecting: Number(process.env.DB_MAX_LINK || 5),
+      maxPoolSize: Number(process.env.DB_MAX_LINK || 5),
+      minPoolSize: 2
     });
     console.log('mongo connected');
   } catch (error) {

client/src/service/pg.ts

@@ -12,7 +12,7 @@ export const connectPg = async () => {
     user: process.env.PG_USER,
     password: process.env.PG_PASSWORD,
     database: process.env.PG_DB_NAME,
-    max: Number(process.env.DB_MAX_LINK || 10),
+    max: Number(process.env.DB_MAX_LINK || 5),
     idleTimeoutMillis: 30000,
     connectionTimeoutMillis: 5000
   });

client/src/service/utils/auth.ts

@@ -176,39 +176,18 @@ export const getApiKey = async ({
   userId: string;
   mustPay?: boolean;
 }) => {
-  const user = await User.findById(userId);
+  const user = await User.findById(userId, 'openaiKey balance');
   if (!user) {
     return Promise.reject(ERROR_ENUM.unAuthorization);
   }
 
-  const keyMap = {
-    [OpenAiChatEnum.GPT35]: {
-      userOpenAiKey: user.openaiKey || '',
-      systemAuthKey: getSystemOpenAiKey()
-    },
-    [OpenAiChatEnum.GPT3516k]: {
-      userOpenAiKey: user.openaiKey || '',
-      systemAuthKey: getSystemOpenAiKey()
-    },
-    [OpenAiChatEnum.GPT4]: {
-      userOpenAiKey: user.openaiKey || '',
-      systemAuthKey: getSystemOpenAiKey()
-    },
-    [OpenAiChatEnum.GPT432k]: {
-      userOpenAiKey: user.openaiKey || '',
-      systemAuthKey: getSystemOpenAiKey()
-    }
-  };
-
-  if (!keyMap[model]) {
-    return Promise.reject('App  model is exists');
-  }
+  const userOpenAiKey = user.openaiKey || '';
+  const systemAuthKey = getSystemOpenAiKey();
 
   // 有自己的key
-  if (!mustPay && keyMap[model].userOpenAiKey) {
+  if (!mustPay && userOpenAiKey) {
     return {
-      user,
-      userOpenAiKey: keyMap[model].userOpenAiKey,
+      userOpenAiKey,
       systemAuthKey: ''
     };
   }
@@ -219,9 +198,8 @@ export const getApiKey = async ({
   }
 
   return {
-    user,
     userOpenAiKey: '',
-    systemAuthKey: keyMap[model].systemAuthKey
+    systemAuthKey
   };
 };
 

client/src/service/utils/chat/index.ts

@@ -27,6 +27,7 @@ export type StreamResponseType = {
   chatResponse: any;
   prompts: ChatItemType[];
   res: NextApiResponse;
+  model: `${OpenAiChatEnum}`;
   [key: string]: any;
 };
 export type StreamResponseReturnType = {
@@ -35,49 +36,9 @@ export type StreamResponseReturnType = {
   finishMessages: ChatItemType[];
 };
 
-export const modelServiceToolMap: Record<
-  ChatModelType,
-  {
-    chatCompletion: (data: ChatCompletionType) => Promise<ChatCompletionResponseType>;
-    streamResponse: (data: StreamResponseType) => Promise<StreamResponseReturnType>;
-  }
-> = {
-  [OpenAiChatEnum.GPT35]: {
-    chatCompletion: (data: ChatCompletionType) =>
-      chatResponse({ model: OpenAiChatEnum.GPT35, ...data }),
-    streamResponse: (data: StreamResponseType) =>
-      openAiStreamResponse({
-        model: OpenAiChatEnum.GPT35,
-        ...data
-      })
-  },
-  [OpenAiChatEnum.GPT3516k]: {
-    chatCompletion: (data: ChatCompletionType) =>
-      chatResponse({ model: OpenAiChatEnum.GPT3516k, ...data }),
-    streamResponse: (data: StreamResponseType) =>
-      openAiStreamResponse({
-        model: OpenAiChatEnum.GPT3516k,
-        ...data
-      })
-  },
-  [OpenAiChatEnum.GPT4]: {
-    chatCompletion: (data: ChatCompletionType) =>
-      chatResponse({ model: OpenAiChatEnum.GPT4, ...data }),
-    streamResponse: (data: StreamResponseType) =>
-      openAiStreamResponse({
-        model: OpenAiChatEnum.GPT4,
-        ...data
-      })
-  },
-  [OpenAiChatEnum.GPT432k]: {
-    chatCompletion: (data: ChatCompletionType) =>
-      chatResponse({ model: OpenAiChatEnum.GPT432k, ...data }),
-    streamResponse: (data: StreamResponseType) =>
-      openAiStreamResponse({
-        model: OpenAiChatEnum.GPT432k,
-        ...data
-      })
-  }
+export const modelServiceToolMap = {
+  chatCompletion: chatResponse,
+  streamResponse: openAiStreamResponse
 };
 
 /* delete invalid symbol */
@@ -124,7 +85,8 @@ export const ChatContextFilter = ({
   }
 
   // 去掉 system 的 token
-  maxTokens -= modelToolMap[model].countTokens({
+  maxTokens -= modelToolMap.countTokens({
+    model,
     messages: systemPrompts
   });
 
@@ -135,7 +97,8 @@ export const ChatContextFilter = ({
   for (let i = chatPrompts.length - 1; i >= 0; i--) {
     chats.unshift(chatPrompts[i]);
 
-    const tokens = modelToolMap[model].countTokens({
+    const tokens = modelToolMap.countTokens({
+      model,
       messages: chats
     });
 
@@ -164,13 +127,14 @@ export const resStreamResponse = async ({
   res.setHeader('X-Accel-Buffering', 'no');
   res.setHeader('Cache-Control', 'no-cache, no-transform');
 
-  const { responseContent, totalTokens, finishMessages } = await modelServiceToolMap[
-    model
-  ].streamResponse({
-    chatResponse,
-    prompts,
-    res
-  });
+  const { responseContent, totalTokens, finishMessages } = await modelServiceToolMap.streamResponse(
+    {
+      chatResponse,
+      prompts,
+      res,
+      model
+    }
+  );
 
   return { responseContent, totalTokens, finishMessages };
 };
@@ -186,16 +150,27 @@ export const V2_StreamResponse = async ({
 }) => {
   let responseContent = '';
   let error: any = null;
-
+  let truncateData = '';
   const clientRes = async (data: string) => {
+    //部分代理会导致流式传输时的数据被截断，不为json格式，这里做一个兼容
     const { content = '' } = (() => {
       try {
+        if (truncateData) {
+          try {
+            //判断是否为json，如果是的话直接跳过后续拼装操作，注意极端情况下可能出现截断成3截以上情况也可以兼容
+            JSON.parse(data);
+          } catch (e) {
+            data = truncateData + data;
+          }
+          truncateData = '';
+        }
         const json = JSON.parse(data);
         const content: string = json?.choices?.[0].delta.content || '';
         error = json.error;
         responseContent += content;
         return { content };
       } catch (error) {
+        truncateData = data;
         return {};
       }
     })();
@@ -248,7 +223,8 @@ export const V2_StreamResponse = async ({
     value: responseContent
   });
 
-  const totalTokens = modelToolMap[model].countTokens({
+  const totalTokens = modelToolMap.countTokens({
+    model,
     messages: finishMessages
   });
 

client/src/service/utils/chat/openai.ts

@@ -35,7 +35,8 @@ export const chatResponse = async ({
   const adaptMessages = adaptChatItem_openAI({ messages: filterMessages, reserveId: false });
   const chatAPI = getOpenAIApi(apiKey);
 
-  const promptsToken = modelToolMap[model].countTokens({
+  const promptsToken = modelToolMap.countTokens({
+    model,
     messages: filterMessages
   });
 
@@ -116,7 +117,8 @@ export const openAiStreamResponse = async ({
       value: responseContent
     });
 
-    const totalTokens = modelToolMap[model].countTokens({
+    const totalTokens = modelToolMap.countTokens({
+      model,
       messages: finishMessages
     });
 

client/src/service/utils/wxpay.ts

@@ -1,8 +1,8 @@
 // @ts-ignore
 import Payment from 'wxpay-v3';
 
-export const getPayment = () => {
-  return new Payment({
+export const getPayment = () =>
+  new Payment({
     appid: process.env.WX_APPID,
     mchid: process.env.WX_MCHID,
     private_key: process.env.WX_PRIVATE_KEY?.replace(/\\n/g, '\n'),
@@ -10,22 +10,30 @@ export const getPayment = () => {
     apiv3_private_key: process.env.WX_V3_CODE,
     notify_url: process.env.WX_NOTIFY_URL
   });
-};
 
-export const nativePay = (amount: number, payId: string): Promise<string> =>
-  getPayment()
-    .native({
+export const nativePay = async (amount: number, payId: string) => {
+  try {
+    const res = await getPayment().native({
       description: 'Fast GPT 余额充值',
       out_trade_no: payId,
       amount: {
         total: amount
       }
-    })
-    .then((res: any) => JSON.parse(res.data).code_url);
+    });
+    return JSON.parse(res.data).code_url as string;
+  } catch (error) {
+    return Promise.reject(error);
+  }
+};
 
-export const getPayResult = (payId: string) =>
-  getPayment()
-    .getTransactionsByOutTradeNo({
+export const getPayResult = async (payId: string) => {
+  try {
+    const res = await getPayment().getTransactionsByOutTradeNo({
       out_trade_no: payId
-    })
-    .then((res: any) => JSON.parse(res.data));
+    });
+
+    return JSON.parse(res.data);
+  } catch (error) {
+    return Promise.reject(error);
+  }
+};

client/src/types/index.d.ts

@@ -21,7 +21,9 @@ declare global {
   var QRCode: any;
   var qaQueueLen: number;
   var vectorQueueLen: number;
-  var OpenAiEncMap: Record<string, Tiktoken>;
+  var OpenAiEncMap: Tiktoken;
+  var sendInformQueue: (() => Promise<void>)[];
+  var sendInformQueueLen: number;
   var systemEnv: {
     vectorMaxProcess: number;
     qaMaxProcess: number;

client/src/types/mongoSchema.d.ts

@@ -70,6 +70,7 @@ export interface TrainingDataSchema {
   _id: string;
   userId: string;
   kbId: string;
+  expireAt: Date;
   lockTime: Date;
   mode: `${TrainingModeEnum}`;
   prompt: string;

client/src/types/user.d.ts

@@ -19,7 +19,7 @@ export interface UserUpdateParams {
 export interface UserBillType {
   id: string;
   time: Date;
-  modelName: BillSchema['modelName'];
+  modelName: string;
   type: BillSchema['type'];
   textLen: number;
   tokenLen: number;

client/src/utils/adapt.ts

@@ -1,17 +1,17 @@
 import { formatPrice } from './user';
-import dayjs from 'dayjs';
 import type { BillSchema } from '../types/mongoSchema';
 import type { UserBillType } from '@/types/user';
 import { ChatItemType } from '@/types/chat';
 import { ChatCompletionRequestMessageRoleEnum } from 'openai';
 import { ChatRoleEnum } from '@/constants/chat';
 import type { MessageItemType } from '@/pages/api/openapi/v1/chat/completions';
+import { ChatModelMap, OpenAiChatEnum } from '@/constants/model';
 
 export const adaptBill = (bill: BillSchema): UserBillType => {
   return {
     id: bill._id,
     type: bill.type,
-    modelName: bill.modelName,
+    modelName: ChatModelMap[bill.modelName as `${OpenAiChatEnum}`]?.name || bill.modelName,
     time: bill.time,
     textLen: bill.textLen,
     tokenLen: bill.tokenLen,

client/src/utils/file.ts

@@ -152,7 +152,7 @@ export const splitText_token = ({ text, maxLen }: { text: string; maxLen: number
   const slideLen = Math.floor(maxLen * 0.3);
 
   try {
-    const enc = getOpenAiEncMap()[OpenAiChatEnum.GPT35];
+    const enc = getOpenAiEncMap();
     // filter empty text. encode sentence
     const encodeText = enc.encode(text);
 

client/src/utils/plugin/index.ts

@@ -4,32 +4,8 @@ import type { ChatItemType } from '@/types/chat';
 import { countOpenAIToken, openAiSliceTextByToken } from './openai';
 import { gpt_chatItemTokenSlice } from '@/pages/api/openapi/text/gptMessagesSlice';
 
-export const modelToolMap: Record<
-  ChatModelType,
-  {
-    countTokens: (data: { messages: ChatItemType[] }) => number;
-    sliceText: (data: { text: string; length: number }) => string;
-    tokenSlice: (data: { messages: ChatItemType[]; maxToken: number }) => ChatItemType[];
-  }
-> = {
-  [OpenAiChatEnum.GPT35]: {
-    countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }),
-    sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data }),
-    tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT35, ...data })
-  },
-  [OpenAiChatEnum.GPT3516k]: {
-    countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT3516k, messages }),
-    sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT3516k, ...data }),
-    tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT3516k, ...data })
-  },
-  [OpenAiChatEnum.GPT4]: {
-    countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT4, messages }),
-    sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT4, ...data }),
-    tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT4, ...data })
-  },
-  [OpenAiChatEnum.GPT432k]: {
-    countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT432k, messages }),
-    sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT432k, ...data }),
-    tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT432k, ...data })
-  }
+export const modelToolMap = {
+  countTokens: countOpenAIToken,
+  sliceText: openAiSliceTextByToken,
+  tokenSlice: gpt_chatItemTokenSlice
 };

client/src/utils/plugin/openai.ts

@@ -4,7 +4,6 @@ import { ChatRoleEnum } from '@/constants/chat';
 import { ChatCompletionRequestMessageRoleEnum } from 'openai';
 import { OpenAiChatEnum } from '@/constants/model';
 import axios from 'axios';
-import dayjs from 'dayjs';
 import type { MessageItemType } from '@/pages/api/openapi/v1/chat/completions';
 
 export const getOpenAiEncMap = () => {
@@ -14,28 +13,11 @@ export const getOpenAiEncMap = () => {
   if (typeof global !== 'undefined' && global.OpenAiEncMap) {
     return global.OpenAiEncMap;
   }
-  const enc = {
-    [OpenAiChatEnum.GPT35]: encoding_for_model('gpt-3.5-turbo', {
-      '<|im_start|>': 100264,
-      '<|im_end|>': 100265,
-      '<|im_sep|>': 100266
-    }),
-    [OpenAiChatEnum.GPT3516k]: encoding_for_model('gpt-3.5-turbo', {
-      '<|im_start|>': 100264,
-      '<|im_end|>': 100265,
-      '<|im_sep|>': 100266
-    }),
-    [OpenAiChatEnum.GPT4]: encoding_for_model('gpt-4', {
-      '<|im_start|>': 100264,
-      '<|im_end|>': 100265,
-      '<|im_sep|>': 100266
-    }),
-    [OpenAiChatEnum.GPT432k]: encoding_for_model('gpt-4-32k', {
-      '<|im_start|>': 100264,
-      '<|im_end|>': 100265,
-      '<|im_sep|>': 100266
-    })
-  };
+  const enc = encoding_for_model('gpt-3.5-turbo', {
+    '<|im_start|>': 100264,
+    '<|im_end|>': 100265,
+    '<|im_sep|>': 100266
+  });
 
   if (typeof window !== 'undefined') {
     window.OpenAiEncMap = enc;
@@ -78,7 +60,7 @@ export function countOpenAIToken({
   const adaptMessages = adaptChatItem_openAI({ messages, reserveId: true });
   const token = adaptMessages.reduce((sum, item) => {
     const text = `${item.role}\n${item.content}`;
-    const enc = getOpenAiEncMap()[model];
+    const enc = getOpenAiEncMap();
     const encodeText = enc.encode(text);
     const tokens = encodeText.length + diffVal;
     return sum + tokens;
@@ -96,7 +78,7 @@ export const openAiSliceTextByToken = ({
   text: string;
   length: number;
 }) => {
-  const enc = getOpenAiEncMap()[model];
+  const enc = getOpenAiEncMap();
   const encodeText = enc.encode(text);
   const decoder = new TextDecoder();
   return decoder.decode(enc.decode(encodeText.slice(0, length)));
@@ -111,16 +93,11 @@ export const authOpenAiKey = async (key: string) => {
     })
     .then((res) => {
       if (!res.data.access_until) {
-        return Promise.reject('OpenAI Key 无效，请重试或更换 key');
-      }
-      const keyExpiredTime = dayjs(res.data.access_until * 1000);
-      const currentTime = dayjs();
-      if (keyExpiredTime.isBefore(currentTime)) {
-        return Promise.reject('OpenAI Key 已过期');
+        return Promise.resolve('OpenAI Key 可能无效');
       }
     })
     .catch((err) => {
       console.log(err);
-      return Promise.reject(err?.response?.data?.error || 'OpenAI 账号无效，请重试或更换 key');
+      return Promise.reject(err?.response?.data?.error?.message || 'OpenAI Key 可能无效');
     });
 };

docs/deploy/fastgpt/docker-compose.yml

@@ -1,4 +1,4 @@
-# host 版本。
+# 非 host 版本, 不使用本机代理
 version: '3.3'
 services:
   pg:
@@ -6,8 +6,10 @@ services:
     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.4.2 # 阿里云
     container_name: pg
     restart: always
-    ports:
+    ports: # 生产环境建议不要暴露
       - 8100:5432
+    networks:
+      - fastgpt
     environment:
       # 这里的配置只有首次运行生效。修改后，重启镜像是不会生效的。需要把持久化数据删除再重启，才有效果
       - POSTGRES_USER=fastgpt
@@ -15,31 +17,40 @@ services:
       - POSTGRES_DB=fastgpt
     volumes:
       # 刚创建的文件
-      - /root/fastgpt/pg/init.sql:/docker-entrypoint-initdb.d/init.sh
-      - /root/fastgpt/pg/data:/var/lib/postgresql/data
-  mongodb:
+      - ./pg/init.sql:/docker-entrypoint-initdb.d/init.sh
+      - ./pg/data:/var/lib/postgresql/data
+  mongo:
     # image: mongo:5.0.18
     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/mongo:5.0.18 # 阿里云
     container_name: mongo
     restart: always
-    ports:
+    ports: # 生产环境建议不要暴露
       - 27017:27017
+    networks:
+      - fastgpt
     environment:
       # 这里的配置只有首次运行生效。修改后，重启镜像是不会生效的。需要把持久化数据删除再重启，才有效果
       - MONGO_INITDB_ROOT_USERNAME=username
       - MONGO_INITDB_ROOT_PASSWORD=password
     volumes:
-      - /root/fastgpt/mongo/data:/data/db
-      - /root/fastgpt/mongo/logs:/var/log/mongodb
+      - ./mongo/data:/data/db
+      - ./mongo/logs:/var/log/mongodb
   fastgpt:
+    container_name: fastgpt
     # image: c121914yu/fast-gpt:latest # docker hub
     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:latest # 阿里云
     # network_mode: host #
+    ports:
+      - 3000:3000
+    networks:
+      - fastgpt
+    depends_on:
+      - mongo
+      - pg
     restart: always
-    container_name: fastgpt
     environment: # 可选的变量，不需要的话需要去掉
       - PORT=3000 # 运行的端口地址，如果不是 3000，需要修改成实际地址。
-      - DB_MAX_LINK=15 # database max link
+      - DB_MAX_LINK=5 # database max link
       # proxy（可选）
       - AXIOS_PROXY_HOST=127.0.0.1
       - AXIOS_PROXY_PORT=7890
@@ -59,17 +70,17 @@ services:
       # root key, 最高权限，可以内部接口互相调用
       - ROOT_KEY=root_key
       # 和上方mongo镜像的username,password对应
-      - MONGODB_URI=mongodb://username:password@0.0.0.0:27017/?authSource=admin
+      - MONGODB_URI=mongodb://username:password@mongo:27017/?authSource=admin
       - MONGODB_NAME=fastgpt
-      - PG_HOST=0.0.0.0
-      - PG_PORT=8100
+      - PG_HOST=pg
+      - PG_PORT=5432
       # 和上方PG镜像对应.
       - PG_USER=fastgpt
       - PG_PASSWORD=1234
       - PG_DB_NAME=fastgpt
       # oneapi 配置 推荐使用 one-api 管理key
-      - ONEAPI_URL=https://kfcwurtbijvh.cloud.sealos.io/v1
-      - ONEAPI_KEY=sk-itJ9v8qthRiFDzfs62Ea21Aa9b004c8791937dCf4cC568Ff
+      - ONEAPI_URL=https://xxxxx.cloud.sealos.io/v1
+      - ONEAPI_KEY=sk-xxxxxx
       # openai 相关配置：使用了 oneapi 后，下面只需要填下 OPENAI_BASE_URL （国外可全忽略）
       - OPENAIKEY=sk-xxxxx
       - OPENAI_BASE_URL=https://api.openai.com/v1
@@ -80,16 +91,21 @@ services:
     restart: always
     ports:
       - 3001:3001
+    networks:
+      - fastgpt
+    depends_on:
+      - mongo
+      - fastgpt
     environment:
-      - MONGODB_URI=mongodb://username:password@0.0.0.0:27017/?authSource=admin
+      - MONGODB_URI=mongodb://username:password@mongo:27017/?authSource=admin
       - MONGODB_NAME=fastgpt
       - ADMIN_USER=username
       - ADMIN_PASS=password
       - ADMIN_SECRET=any
-      - PARENT_URL=http://0.0.0.0:3000
+      - PARENT_URL=http://fastgpt:3000
       - PARENT_ROOT_KEY=root_key
-  key-admin:
-    container_name: key-admin
+  keyadmin:
+    container_name: keyadmin
     image: justsong/one-api
     restart: always
     ports:
@@ -97,7 +113,7 @@ services:
     environment:
       - TZ=Asia/Shanghai
     volumes:
-      - /home/ubuntu/data/one-api:/data
+      - /keyadmin:/data
   nginx: # 宝塔不需要额外装 nginx
     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/nginx:alpine3.17
     # image: nginx:alpine3.17
@@ -106,8 +122,135 @@ services:
     network_mode: host
     volumes:
       # 刚创建的文件
-      - /root/fastgpt/nginx/nginx.conf:/etc/nginx/nginx.conf:ro
-      - /root/fastgpt/nginx/logs:/var/log/nginx
+      - ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro
+      - ./nginx/logs:/var/log/nginx
       # https证书，没有的话不填，对应的nginx.conf也要修改
-      - /root/fastgpt/nginx/ssl/docgpt.key:/ssl/docgpt.key
-      - /root/fastgpt/nginx/ssl/docgpt.pem:/ssl/docgpt.pem
+      - ./nginx/ssl/docgpt.key:/ssl/docgpt.key
+      - ./nginx/ssl/docgpt.pem:/ssl/docgpt.pem
+networks:
+  fastgpt:
+# host 版本, 不推荐，推荐直接用上面的，用个 BASE_URL 中转
+# version: '3.3'
+# services:
+#   pg:
+#     # image: ankane/pgvector:v0.4.2 # dockerhub
+#     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.4.2 # 阿里云
+#     container_name: pg
+#     restart: always
+#     ports: # 生产环境建议不要暴露
+#       - 8100:5432
+#     networks:
+#       - fastgpt
+#     environment:
+#       # 这里的配置只有首次运行生效。修改后，重启镜像是不会生效的。需要把持久化数据删除再重启，才有效果
+#       - POSTGRES_USER=fastgpt
+#       - POSTGRES_PASSWORD=1234
+#       - POSTGRES_DB=fastgpt
+#     volumes:
+#       # 刚创建的文件
+#       - ./pg/init.sql:/docker-entrypoint-initdb.d/init.sh
+#       - ./pg/data:/var/lib/postgresql/data
+#   mongo:
+#     # image: mongo:5.0.18
+#     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/mongo:5.0.18 # 阿里云
+#     container_name: mongo
+#     restart: always
+#     ports: # 生产环境建议不要暴露
+#       - 27017:27017
+#     networks:
+#       - fastgpt
+#     environment:
+#       # 这里的配置只有首次运行生效。修改后，重启镜像是不会生效的。需要把持久化数据删除再重启，才有效果
+#       - MONGO_INITDB_ROOT_USERNAME=username
+#       - MONGO_INITDB_ROOT_PASSWORD=password
+#     volumes:
+#       - ./mongo/data:/data/db
+#       - ./mongo/logs:/var/log/mongodb
+#   fastgpt:
+#     # image: ghcr.io/c121914yu/fastgpt:latest # github
+#     # image: c121914yu/fast-gpt:latest # docker hub
+#     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:latest # 阿里云
+#     network_mode: host
+#     restart: always
+#     container_name: fastgpt
+#     environment: # 可选的变量，不需要的话需要去掉
+#       - PORT=3000 # 运行的端口地址，如果不是 3000，需要修改成实际地址。
+#       - DB_MAX_LINK=15 # database max link
+#       # proxy（可选）
+#       - AXIOS_PROXY_HOST=127.0.0.1
+#       - AXIOS_PROXY_PORT=7890
+#       # 发送邮箱验证码配置。用的是QQ邮箱。参考 nodeMail 获取MAILE_CODE，自行百度。
+#       - MY_MAIL=54545@qq.com
+#       - MAILE_CODE=1234
+#       # 阿里短信服务（邮箱和短信至少二选一）
+#       - aliAccessKeyId=xxxx
+#       - aliAccessKeySecret=xxxx
+#       - aliSignName=xxxxx
+#       - aliTemplateCode=SMS_xxxx
+#       # google V3 安全校验（可选）
+#       - CLIENT_GOOGLE_VER_TOKEN=xxx
+#       - SERVICE_GOOGLE_VER_TOKEN=xx
+#       # token加密凭证（随便填，作为登录凭证）
+#       - TOKEN_KEY=xxxx
+#       # root key, 最高权限，可以内部接口互相调用
+#       - ROOT_KEY=xxx
+#       # 和上方mongo镜像的username,password对应
+#       - MONGODB_URI=mongodb://username:password@0.0.0.0:27017/?authSource=admin
+#       - MONGODB_NAME=fastgpt
+#       - PG_HOST=0.0.0.0
+#       - PG_PORT=8100
+#       # 和上方PG镜像对应.
+#       - PG_USER=fastgpt
+#       - PG_PASSWORD=1234
+#       - PG_DB_NAME=fastgpt
+#       # oneapi 配置 推荐使用 one-api 管理key
+#       - ONEAPI_URL=https://xxxxx.cloud.sealos.io/v1
+#       - ONEAPI_KEY=sk-xxxxx
+#       # openai 相关配置：使用了 oneapi 后，下面只需要填下 OPENAI_BASE_URL （国外可全忽略）
+#       - OPENAIKEY=sk-xxxxx
+#       - OPENAI_BASE_URL=https://api.openai.com/v1
+#       - OPENAI_BASE_URL_AUTH=可选的安全凭证，会放到 header.auth 里
+#   fastgpt-admin:
+#     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-admin:latest
+#     container_name: fastgpt-admin
+#     restart: always
+#     ports:
+#       - 3001:3001
+#     networks:
+#       - fastgpt
+#     depends_on:
+#       - mongo
+#       - fastgpt
+#     environment:
+#       - MONGODB_URI=mongodb://username:password@mongo:27017/?authSource=admin
+#       - MONGODB_NAME=fastgpt
+#       - ADMIN_USER=username
+#       - ADMIN_PASS=password
+#       - ADMIN_SECRET=any
+#       - PARENT_URL=http://fastgpt:3000
+#       - PARENT_ROOT_KEY=root_key
+#   key-admin:
+#     container_name: key-admin
+#     image: justsong/one-api
+#     restart: always
+#     ports:
+#       - 3002:3000
+#     environment:
+#       - TZ=Asia/Shanghai
+#     volumes:
+#       - /home/ubuntu/data/one-api:/data
+#   nginx: # 宝塔不需要额外装 nginx
+#     image: registry.cn-hangzhou.aliyuncs.com/fastgpt/nginx:alpine3.17
+#     # image: nginx:alpine3.17
+#     container_name: nginx
+#     restart: always
+#     network_mode: host
+#     volumes:
+#       # 刚创建的文件
+#       - ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro
+#       - ./nginx/logs:/var/log/nginx
+#       # https证书，没有的话不填，对应的nginx.conf也要修改
+#       - ./nginx/ssl/docgpt.key:/ssl/docgpt.key
+#       - ./nginx/ssl/docgpt.pem:/ssl/docgpt.pem
+# networks:
+#   fastgpt:

docs/deploy/one-api/sealos.md

@@ -30,7 +30,7 @@ https://cloud.sealos.io/
 
 ```
 # 下面的地址是 Sealos 提供的，务必写上 v1
-OPENAI_BASE_URL=https://xxxx.cloud.sealos.io/v1
+ONEAPI_URL=https://xxxx.cloud.sealos.io/v1
 # 下面的 key 由 one-api 提供
-OPENAIKEY=sk-xxxxxx
+ONEAPI_KEY=sk-xxxxxx
 ```