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Commit 5fcdf28c by Archer Committed by GitHub
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user feedback and admin mark (#228) 

* fix: csv empty data

* feat: user feedback and mark answer

* version intro

* perf: chat logs sort
parent 2556c19a
Showing with 648 additions and 54 deletions
client/public/docs/chatProblem.md
### 常见问题
- [**Git 地址**,点击查看项目地址](https://github.com/labring/FastGPT)
- [**Git 地址**，点击查看项目地址](https://github.com/labring/FastGPT)
- [本地部署 FastGPT](https://doc.fastgpt.run/docs/installation)
- [API 文档](https://kjqvjse66l.feishu.cn/docx/DmLedTWtUoNGX8xui9ocdUEjnNh?pre_pathname=%2Fdrive%2Fhome%2F)
- **反馈问卷**: 如果你遇到任何使用问题或有期望的功能，可以[填写该问卷](https://www.wjx.cn/vm/rLIw1uD.aspx#)
- **问题文档**: [先看文档，再提问](https://kjqvjse66l.feishu.cn/docx/HtrgdT0pkonP4kxGx8qcu6XDnGh)
- [点击查看商业版文档](https://fael3z0zfze.feishu.cn/docx/F155dbirfo8vDDx2WgWc6extnwf)
**价格表**
| 计费项 | 价格: 元/ 1K tokens（包含上下文）|
......
client/public/docs/versionIntro.md
### Fast GPT V4.2
### Fast GPT V4.2.2
1. 新增 - 应用日志初版，可观测到所有对话记录
2. 新增 - 好友邀请链接，[点击查看](/account?currentTab=promotion)
3. 新增 - Iframe 嵌入页面图标可拖拽
4. 优化 - 知识库搜索提示词
5. 优化 - [使用文档](https://doc.fastgpt.run/docs/intro/)
6. [点击查看高级编排介绍文档](https://doc.fastgpt.run/docs/workflow)
1. **新增 - 用户反馈和管理员标注预期答案，以不断提高模型回复准确率。** 该功能为测试版，未来交互可能会有变化，欢迎大家提出宝贵意见。
2. 优化 - 知识库搜索提示词，更适配问答场景。
3. 新增 - 好友邀请链接，[点击查看](/account?currentTab=promotion)
4. 优化 - [使用文档](https://doc.fastgpt.run/docs/intro/)
5. [点击查看高级编排介绍文档](https://doc.fastgpt.run/docs/workflow)
client/public/locales/en/common.json
......@@ -3,6 +3,7 @@
"Cancel": "No",
"Confirm": "Yes",
"Running": "Running",
"Select value is empty": "Select value is empty",
"UnKnow": "UnKnow",
"Warning": "Warning",
"app": {
......@@ -17,6 +18,7 @@
"Copy Module Config": "Copy config",
"Export Config Successful": "The configuration has been copied. Please check for important data",
"Export Configs": "Export Configs",
"Feedback Count": "User Feedback",
"Import Config": "Import Config",
"Import Config Failed": "Failed to import the configuration, please ensure that the configuration is normal!",
"Import Configs": "Import Configs",
......@@ -26,16 +28,33 @@
"Logs Source": "Source",
"Logs Time": "Time",
"Logs Title": "Title",
"Mark Count": "Mark Count",
"My Apps": "My Apps",
"Output Field Settings": "Output Field Settings",
"Paste Config": "Paste Config"
},
"chat": {
"Admin Mark Content": "Corrected response",
"Complete Response": "Complete Response",
"Confirm to clear history": "Confirm to clear history?",
"Exit Chat": "Exit",
"Feedback Failed": "Feedback Failed",
"Feedback Mark": "Mark",
"Feedback Modal": "Feedback",
"Feedback Modal Tip": "Enter what you find unsatisfactory",
"Feedback Close": "Close Feedback",
"Feedback Submit": "Submit",
"Feedback Success": "Feedback Success",
"Feedback Update Failed": "Feedback Update Failed",
"History": "History",
"Mark": "Mark",
"Mark Description": "The annotation feature is currently in beta. \n\n After clicking Add annotation, you need to select a knowledge base in order to store annotation data. You can use this feature to quickly annotate questions and expected answers to guide the model to the next answer. At present, the annotation function, like other data in the knowledge base, is affected by the model, which does not mean that the annotation meets 100% expectations. The \n\n annotation data is only unidirectional synchronization with the knowledge base. If the knowledge base modifies the annotation data, the annotation data displayed in the log cannot be synchronized",
"Mark Description Title": "Mark Description",
"New Chat": "New Chat",
"Read Mark Description": "Read mark description",
"Read User Feedback": "Read user feedback",
"Select Mark Kb": "Select Dataset",
"Select Mark Kb Desc": "Select a dataset to store the expected answers",
"You need to a chat app": "You need to a chat app",
"logs": {
"api": "API",
......
client/public/locales/zh/common.json
......@@ -3,8 +3,9 @@
"Cancel": "取消",
"Confirm": "确认",
"Running": "运行中",
"Warning": "提示",
"Select value is empty": "选择的内容为空",
"UnKnow": "未知",
"Warning": "提示",
"app": {
"Advance App TestTip": "当前应用为高级编排模式\n如需切换为【简易模式】请点击左侧保存按键",
"App Detail": "应用详情",
......@@ -17,6 +18,7 @@
"Copy Module Config": "复制配置",
"Export Config Successful": "已复制配置，请注意检查是否有重要数据",
"Export Configs": "导出配置",
"Feedback Count": "用户反馈",
"Import Config": "导入配置",
"Import Config Failed": "导入配置失败，请确保配置正常！",
"Import Configs": "导入配置",
......@@ -26,16 +28,33 @@
"Logs Source": "来源",
"Logs Time": "时间",
"Logs Title": "标题",
"Mark Count": "标注答案数量",
"My Apps": "我的应用",
"Output Field Settings": "输出字段编辑",
"Paste Config": "粘贴配置"
},
"chat": {
"Admin Mark Content": "纠正后的回复",
"Complete Response": "完整响应",
"Confirm to clear history": "确认清空该应用的聊天记录？",
"Exit Chat": "退出聊天",
"Feedback Failed": "提交反馈异常",
"Feedback Mark": "标注",
"Feedback Modal": "结果反馈",
"Feedback Modal Tip": "输入你觉得回答不满意的地方",
"Feedback Close": "关闭反馈",
"Feedback Submit": "提交反馈",
"Feedback Success": "反馈成功!",
"Feedback Update Failed": "更新反馈状态失败",
"History": "记录",
"Mark": "标注预期回答",
"Mark Description": "当前标注功能为测试版。\n\n点击添加标注后，需要选择一个知识库，以便存储标注数据。你可以通过该功能快速的标注问题和预期回答，以便引导模型下次的回答。\n\n目前，标注功能同知识库其他数据一样，受模型的影响，不代表标注后 100% 符合预期。\n\n标注数据仅单向与知识库同步，如果知识库修改了该标注数据，日志展示的标注数据无法同步",
"Mark Description Title": "标注功能介绍",
"New Chat": "新对话",
"Read Mark Description": "查看标注功能介绍",
"Read User Feedback": "查看用户反馈",
"Select Mark Kb": "选择知识库",
"Select Mark Kb Desc": "选择一个知识库存储预期答案",
"You need to a chat app": "你需要创建一个应用",
"logs": {
"api": "API 调用",
......
client/src/api/chat.ts
......@@ -5,6 +5,7 @@ import { RequestPaging } from '../types/index';
import type { OutLinkSchema } from '@/types/mongoSchema';
import type { ShareChatEditType } from '@/types/app';
import type { Props as UpdateHistoryProps } from '@/pages/api/chat/history/updateChatHistory';
import { AdminUpdateFeedbackParams } from './request/chat';
/**
* 获取初始化聊天内容
......@@ -64,3 +65,9 @@ export const getShareChatList = (appId: string) =>
* delete a shareChat
*/
export const delShareChatById = (id: string) => DELETE(`/chat/shareChat/delete?id=${id}`);
export const userUpdateChatFeedback = (data: { chatItemId: string; userFeedback?: string }) =>
POST('/chat/feedback/userUpdate', data);
export const adminUpdateChatFeedback = (data: AdminUpdateFeedbackParams) =>
POST('/chat/feedback/adminUpdate', data);
client/src/api/plugins/kb.ts
......@@ -67,6 +67,14 @@ export const postKbDataFromList = (data: PushDataProps) =>
POST<PushDateResponse>(`/openapi/kb/pushData`, data);
/**
* insert one data to dataset
*/
export const insertData2Kb = (data: {
kbId: string;
data: { a: string; q: string; source?: string };
}) => POST<string>(`/plugins/kb/data/insertData`, data);
/**
* 更新一条数据
*/
export const putKbDataById = (data: UpdateDataProps) => PUT('/openapi/kb/updateData', data);
......
client/src/api/request/chat.d.ts 0 → 100644
export type AdminUpdateFeedbackParams = {
chatItemId: string;
kbId: string;
dataId: string;
content: string;
};
client/src/components/ChatBox/FeedbackModal.tsx 0 → 100644
import React, { useRef } from 'react';
import { ModalBody, Textarea, ModalFooter, Button } from '@chakra-ui/react';
import MyModal from '../MyModal';
import { useRequest } from '@/hooks/useRequest';
import { useTranslation } from 'next-i18next';
import { userUpdateChatFeedback } from '@/api/chat';
const FeedbackModal = ({
chatItemId,
onSuccess,
onClose
}: {
chatItemId: string;
onSuccess: (e: string) => void;
onClose: () => void;
}) => {
const ref = useRef<HTMLTextAreaElement>(null);
const { t } = useTranslation();
const { mutate, isLoading } = useRequest({
mutationFn: async () => {
const val = ref.current?.value || 'N/A';
return userUpdateChatFeedback({
chatItemId,
userFeedback: val
});
},
onSuccess() {
onSuccess(ref.current?.value || 'N/A');
},
successToast: t('chat.Feedback Success'),
errorToast: t('chat.Feedback Failed')
});
return (
<MyModal isOpen={true} onClose={onClose} title={t('chat.Feedback Modal')}>
<ModalBody>
<Textarea
ref={ref}
rows={10}
placeholder={t('chat.Feedback Modal Tip') || 'chat.Feedback Modal Tip'}
/>
</ModalBody>
<ModalFooter>
<Button variant={'base'} mr={2} onClick={onClose}>
{t('Cancel')}
</Button>
<Button isLoading={isLoading} onClick={mutate}>
{t('chat.Feedback Submit')}
</Button>
</ModalFooter>
</MyModal>
);
};
export default FeedbackModal;
client/src/components/ChatBox/ReadFeedbackModal.tsx 0 → 100644
import React from 'react';
import { ModalBody, ModalFooter, Button } from '@chakra-ui/react';
import MyModal from '../MyModal';
import { useRequest } from '@/hooks/useRequest';
import { useTranslation } from 'next-i18next';
import { userUpdateChatFeedback } from '@/api/chat';
const ReadFeedbackModal = ({
chatItemId,
content,
isMarked,
onMark,
onSuccess,
onClose
}: {
chatItemId: string;
content: string;
isMarked: boolean;
onMark: () => void;
onSuccess: () => void;
onClose: () => void;
}) => {
const { t } = useTranslation();
const { mutate, isLoading } = useRequest({
mutationFn: async () => {
return userUpdateChatFeedback({
chatItemId,
userFeedback: undefined
});
},
onSuccess() {
onSuccess();
},
errorToast: t('chat.Feedback Update Failed')
});
return (
<MyModal isOpen={true} onClose={onClose} title={t('chat.Feedback Modal')}>
<ModalBody>{content}</ModalBody>
<ModalFooter>
{!isMarked && (
<Button variant={'base'} mr={2} onClick={onMark}>
{t('chat.Feedback Mark')}
</Button>
)}
<Button isLoading={isLoading} onClick={mutate}>
{t('chat.Feedback Close')}
</Button>
</ModalFooter>
</MyModal>
);
};
export default React.memo(ReadFeedbackModal);
client/src/components/ChatBox/SelectDataset.tsx 0 → 100644
import React, { useRef, useState } from 'react';
import {
ModalBody,
useTheme,
ModalFooter,
Button,
ModalHeader,
Box,
Card,
Flex
} from '@chakra-ui/react';
import MyModal from '../MyModal';
import { useTranslation } from 'next-i18next';
import { useQuery } from '@tanstack/react-query';
import { useUserStore } from '@/store/user';
import { useToast } from '@/hooks/useToast';
import Avatar from '../Avatar';
import MyIcon from '@/components/Icon';
import { useGlobalStore } from '@/store/global';
const SelectDataset = ({
onSuccess,
onClose
}: {
onSuccess: (kbId: string) => void;
onClose: () => void;
}) => {
const { t } = useTranslation();
const theme = useTheme();
const { isPc } = useGlobalStore();
const { toast } = useToast();
const { myKbList, loadKbList } = useUserStore();
const [selectedId, setSelectedId] = useState<string>();
useQuery(['loadKbList'], loadKbList);
return (
<MyModal isOpen={true} onClose={onClose} w={'100%'} maxW={['90vw', '900px']} isCentered={!isPc}>
<Flex flexDirection={'column'} h={['90vh', 'auto']}>
<ModalHeader>
<Box>{t('chat.Select Mark Kb')}</Box>
<Box fontSize={'sm'} color={'myGray.500'} fontWeight={'normal'}>
{t('chat.Select Mark Kb Desc')}
</Box>
</ModalHeader>
<ModalBody
flex={['1 0 0', '0 0 auto']}
maxH={'80vh'}
overflowY={'auto'}
display={'grid'}
gridTemplateColumns={['repeat(1,1fr)', 'repeat(2,1fr)', 'repeat(3,1fr)']}
gridGap={3}
userSelect={'none'}
>
{myKbList.map((item) =>
(() => {
const selected = selectedId === item._id;
return (
<Card
key={item._id}
p={3}
border={theme.borders.base}
boxShadow={'sm'}
h={'80px'}
cursor={'pointer'}
_hover={{
boxShadow: 'md'
}}
{...(selected
? {
bg: 'myBlue.300'
}
: {})}
onClick={() => {
setSelectedId(item._id);
}}
>
<Flex alignItems={'center'} h={'38px'}>
<Avatar src={item.avatar} w={['24px', '28px', '32px']}></Avatar>
<Box ml={3} fontWeight={'bold'} fontSize={['md', 'lg', 'xl']}>
{item.name}
</Box>
</Flex>
<Flex justifyContent={'flex-end'} alignItems={'center'} fontSize={'sm'}>
<MyIcon mr={1} name="kbTest" w={'12px'} />
<Box color={'myGray.500'}>{item.vectorModel.name}</Box>
</Flex>
</Card>
);
})()
)}
</ModalBody>
<ModalFooter>
<Button variant={'base'} mr={2} onClick={onClose}>
{t('Cancel')}
</Button>
<Button
onClick={() => {
if (!selectedId) {
return toast({
status: 'warning',
title: t('Select value is empty')
});
}
onSuccess(selectedId);
}}
>
{t('Confirm')}
</Button>
</ModalFooter>
</Flex>
</MyModal>
);
};
export default SelectDataset;
client/src/components/Icon/icons/light/bad.svg 0 → 100644
<?xml version="1.0" standalone="no"?>
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1693117978437"
class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="5051"
xmlns:xlink="http://www.w3.org/1999/xlink" width="64" height="64">
<path
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15.9992-8.339583 3.989801-20.510974 8.989551-36.508175 15.00625-15.9992 6.014699-34.163292 11.176441-54.492275 15.486226-20.328984 4.309785-43.824809 8.136593-70.491475 11.486426l0 418.970051c111.329434 36.668167 210.661467 94.330283 297.9921 172.981351 83.320834 75.321234 134.313284 150.652467 152.977351 225.9977 18.0091-5.334733 31.338433-15.669217 39.998-31.00845 4.669767-9.339533 7.839608-20.508975 9.504525-33.498325 1.664917-12.99435 1.164942-30.658467-1.504925-52.987351-2.664867-22.338883-11.169442-50.507475-25.498725-84.505775-14.339283-34.0033-34.168292-72.0064-59.487026-114.0093-4.669767-8.659567-4.669767-17.334133 0-26.013699 2.0099-4.0098 5.00475-7.179641 8.989551-9.499525 3.989801-2.329884 8.319584-3.489826 12.99435-3.489826l178.99605 0c9.339533 0 16.679166-3.9998 22.0089-11.9994l2.019899-4.989751c1.339933-2.0099 2.344883-4.0098 3.00985-6.019699 0.659967-2.0049 1.159942-4.169792 1.499925-6.494675 0.339983-2.324884 0.839958-4.819759 1.504925-7.484626l0-7.9996c0.659967-2.669867 0.99495-5.334733 0.99495-7.9996 0-23.338833-4.674766-44.337783-14.019299-63.00385L938.986651 497.974101z"
p-id="5052"></path>
</svg>
\ No newline at end of file
client/src/components/Icon/icons/light/mark.svg 0 → 100644
<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1693123058703" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="16328" xmlns:xlink="http://www.w3.org/1999/xlink" width="64" height="64"><path d="M875.65 912h-380a36 36 0 0 1 0-72h380a36 36 0 1 1 0 72zM812.26 284.82L285.39 811.69l-88.11 15.1L212 738l526.72-526.72 73.54 73.54m90.51-11.31L750 120.77a16 16 0 0 0-22.62 0L152.5 695.68a34.11 34.11 0 0 0-9.5 18.56l-25.95 156.23a32 32 0 0 0 37 36.78l155.38-26.62a34.2 34.2 0 0 0 18.38-9.52l575-575a16 16 0 0 0 0-22.63z" p-id="16329"></path></svg>
\ No newline at end of file
client/src/components/Icon/index.tsx
......@@ -77,7 +77,9 @@ const map = {
playFill: require('./icons/fill/play.svg').default,
courseLight: require('./icons/light/course.svg').default,
promotionLight: require('./icons/light/promotion.svg').default,
logsLight: require('./icons/light/logs.svg').default
logsLight: require('./icons/light/logs.svg').default,
badLight: require('./icons/light/bad.svg').default,
markLight: require('./icons/light/mark.svg').default
};
export type IconName = keyof typeof map;
......
client/src/constants/kb.ts
......@@ -11,6 +11,6 @@ export const defaultKbDetail: KbItemType = {
name: 'Embedding-2',
price: 0.2,
defaultToken: 500,
maxToken: 8000
maxToken: 3000
}
};
client/src/pages/api/app/getChatLogs.ts
import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { Chat, ChatItem, connectToDatabase } from '@/service/mongo';
import { Chat, connectToDatabase } from '@/service/mongo';
import { authUser } from '@/service/utils/auth';
import type { PagingData } from '@/types';
import { AppLogsListItemType } from '@/types/app';
......@@ -30,25 +30,48 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const [data, total] = await Promise.all([
Chat.aggregate([
{ $match: where },
{ $sort: { updateTime: -1 } },
{ $skip: (pageNum - 1) * pageSize },
{ $limit: pageSize },
{
$lookup: {
from: 'chatitems',
localField: 'chatId',
foreignField: 'chatId',
as: 'messageCount'
as: 'chatitems'
}
},
{
$addFields: {
feedbackCount: {
$size: {
$filter: {
input: '$chatitems',
as: 'item',
cond: { $ifNull: ['$$item.userFeedback', false] }
}
}
},
markCount: {
$size: {
$filter: {
input: '$chatitems',
as: 'item',
cond: { $ifNull: ['$$item.adminFeedback', false] }
}
}
}
}
},
{ $sort: { feedbackCount: -1, updateTime: -1 } },
{ $skip: (pageNum - 1) * pageSize },
{ $limit: pageSize },
{
$project: {
id: '$chatId',
title: 1,
source: 1,
time: '$updateTime',
messageCount: { $size: '$messageCount' },
callbackCount: { $literal: 0 }
messageCount: { $size: '$chatitems' },
feedbackCount: 1,
markCount: 1
}
}
]),
......
client/src/pages/api/chat/feedback/adminUpdate.ts 0 → 100644
import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { connectToDatabase, ChatItem } from '@/service/mongo';
import { AdminUpdateFeedbackParams } from '@/api/request/chat';
import { authUser } from '@/service/utils/auth';
/* 初始化我的聊天框，需要身份验证 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
try {
await connectToDatabase();
const { chatItemId, kbId, dataId, content = undefined } = req.body as AdminUpdateFeedbackParams;
if (!chatItemId || !kbId || !dataId || !content) {
throw new Error('missing parameter');
}
const { userId } = await authUser({ req, authToken: true });
await ChatItem.findOneAndUpdate(
{
userId,
dataId: chatItemId
},
{
adminFeedback: {
kbId,
dataId,
content
}
}
);
jsonRes(res);
} catch (err) {
jsonRes(res, {
code: 500,
error: err
});
}
}
client/src/pages/api/chat/feedback/userUpdate.ts 0 → 100644
import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { connectToDatabase, ChatItem } from '@/service/mongo';
/* 初始化我的聊天框，需要身份验证 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
try {
await connectToDatabase();
const { chatItemId, userFeedback = undefined } = req.body as {
chatItemId: string;
userFeedback?: string;
};
if (!chatItemId) {
throw new Error('chatItemId is required');
}
await ChatItem.findOneAndUpdate(
{
dataId: chatItemId
},
{
...(userFeedback ? { userFeedback } : { $unset: { userFeedback: '' } })
}
);
jsonRes(res);
} catch (err) {
jsonRes(res, {
code: 500,
error: err
});
}
}
client/src/pages/api/chat/init.ts
......@@ -54,7 +54,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
chatId,
userId
},
`dataId obj value ${TaskResponseKeyEnum.responseData}`
`dataId obj value adminFeedback userFeedback ${TaskResponseKeyEnum.responseData}`
)
.sort({ _id: -1 })
.limit(30)
......
client/src/pages/api/openapi/kb/updateData.ts
......@@ -25,7 +25,10 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
await connectToDatabase();
// auth user and get kb
const [{ userId }, kb] = await Promise.all([authUser({ req }), KB.findById(kbId, 'model')]);
const [{ userId }, kb] = await Promise.all([
authUser({ req }),
KB.findById(kbId, 'vectorModel')
]);
if (!kb) {
throw new Error("Can't find database");
......
client/src/pages/api/plugins/kb/data/insertData.ts 0 → 100644
import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { connectToDatabase, KB } from '@/service/mongo';
import { authKb, authUser } from '@/service/utils/auth';
import { withNextCors } from '@/service/utils/tools';
import { PgTrainingTableName } from '@/constants/plugin';
import { insertKbItem, PgClient } from '@/service/pg';
import { modelToolMap } from '@/utils/plugin';
import { getVectorModel } from '@/service/utils/data';
import { getVector } from '@/pages/api/openapi/plugin/vector';
export type Props = {
kbId: string;
data: { a: string; q: string; source?: string };
};
export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
try {
await connectToDatabase();
const { kbId, data = { q: '', a: '' } } = req.body as Props;
if (!kbId || !data?.q) {
throw new Error('缺少参数');
}
// 凭证校验
const { userId } = await authUser({ req });
// auth kb
const kb = await authKb({ kbId, userId });
const q = data?.q?.replace(/\\n/g, '\n').trim().replace(/'/g, '"');
const a = data?.a?.replace(/\\n/g, '\n').trim().replace(/'/g, '"');
// token check
const token = modelToolMap.countTokens({
model: 'gpt-3.5-turbo',
messages: [{ obj: 'System', value: q }]
});
if (token > getVectorModel(kb.vectorModel).maxToken) {
throw new Error('Over Tokens');
}
const { rows: existsRows } = await PgClient.query(`
SELECT COUNT(*) > 0 AS exists
FROM ${PgTrainingTableName}
WHERE md5(q)=md5('${q}') AND md5(a)=md5('${a}') AND user_id='${userId}' AND kb_id='${kbId}'
`);
const exists = existsRows[0]?.exists || false;
if (exists) {
throw new Error('已经存在完全一致的数据');
}
const { vectors } = await getVector({
model: kb.vectorModel,
input: [q],
userId
});
const response = await insertKbItem({
userId,
kbId,
data: [
{
q,
a,
source: data.source,
vector: vectors[0]
}
]
});
// @ts-ignore
const id = response?.rows?.[0]?.id || '';
jsonRes(res, {
data: id
});
} catch (err) {
jsonRes(res, {
code: 500,
error: err
});
}
});
client/src/pages/app/detail/components/Logs.tsx
......@@ -9,7 +9,9 @@ import {
Th,
Td,
Tbody,
useTheme
useTheme,
useDisclosure,
ModalBody
} from '@chakra-ui/react';
import MyIcon from '@/components/Icon';
import { useTranslation } from 'next-i18next';
......@@ -24,12 +26,19 @@ import ChatBox, { type ComponentRef } from '@/components/ChatBox';
import { useQuery } from '@tanstack/react-query';
import { getInitChatSiteInfo } from '@/api/chat';
import Tag from '@/components/Tag';
import MyModal from '@/components/MyModal';
const Logs = ({ appId }: { appId: string }) => {
const { t } = useTranslation();
const { isPc } = useGlobalStore();
const {
isOpen: isOpenMarkDesc,
onOpen: onOpenMarkDesc,
onClose: onCloseMarkDesc
} = useDisclosure();
const {
data: logs,
isLoading,
Pagination,
......@@ -54,7 +63,16 @@ const Logs = ({ appId }: { appId: string }) => {
{t('app.Chat logs')}
</Box>
<Box color={'myGray.500'} fontSize={'sm'}>
{t('app.Chat Logs Tips')}
{t('app.Chat Logs Tips')},{' '}
<Box
as={'span'}
mr={2}
textDecoration={'underline'}
cursor={'pointer'}
onClick={onOpenMarkDesc}
>
{t('chat.Read Mark Description')}
</Box>
</Box>
</>
)}
......@@ -69,6 +87,8 @@ const Logs = ({ appId }: { appId: string }) => {
<Th>{t('app.Logs Time')}</Th>
<Th>{t('app.Logs Title')}</Th>
<Th>{t('app.Logs Message Total')}</Th>
<Th>{t('app.Feedback Count')}</Th>
<Th>{t('app.Mark Count')}</Th>
</Tr>
</Thead>
<Tbody>
......@@ -86,6 +106,27 @@ const Logs = ({ appId }: { appId: string }) => {
{item.title}
</Td>
<Td>{item.messageCount}</Td>
<Td w={'100px'}>
{!!item?.feedbackCount ? (
<Box display={'inline-block'}>
<Flex
bg={'#FFF2EC'}
color={'#C96330'}
px={3}
py={1}
alignItems={'center'}
borderRadius={'lg'}
fontWeight={'bold'}
>
<MyIcon mr={1} name={'badLight'} color={'#C96330'} w={'14px'} />
{item.feedbackCount}
</Flex>
</Box>
) : (
<>-</>
)}
</Td>
<Td>{item.markCount}</Td>
</Tr>
))}
</Tbody>
......@@ -109,6 +150,13 @@ const Logs = ({ appId }: { appId: string }) => {
onClose={() => setDetailLogsId(undefined)}
/>
)}
<MyModal
isOpen={isOpenMarkDesc}
onClose={onCloseMarkDesc}
title={t('chat.Mark Description Title')}
>
<ModalBody whiteSpace={'pre-wrap'}>{t('chat.Mark Description')}</ModalBody>
</MyModal>
</Flex>
);
};
......@@ -222,6 +270,7 @@ function DetailLogsModal({
<Box pt={2} flex={'1 0 0'}>
<ChatBox
ref={ChatBoxRef}
isLogs
chatId={chatId}
appAvatar={chat?.app.avatar}
userAvatar={HUMAN_ICON}
......
client/src/pages/kb/detail/components/Import/Csv.tsx
......@@ -38,7 +38,10 @@ const CsvImport = ({ kbId }: { kbId: string }) => {
const { mutate: onclickUpload, isLoading: uploading } = useMutation({
mutationFn: async () => {
const chunks = files.map((file) => file.chunks).flat();
const chunks = files
.map((file) => file.chunks)
.flat()
.filter((item) => item?.q);
const filterChunks = chunks.filter((item) => item.q.length < maxToken);
......
client/src/pages/kb/detail/components/Import/Manual.tsx
import React, { useState } from 'react';
import { Box, Textarea, Button } from '@chakra-ui/react';
import { Box, Textarea, Button, Flex } from '@chakra-ui/react';
import { useForm } from 'react-hook-form';
import { useToast } from '@/hooks/useToast';
import { useRequest } from '@/hooks/useRequest';
......@@ -7,6 +7,8 @@ import { getErrText } from '@/utils/tools';
import { postKbDataFromList } from '@/api/plugins/kb';
import { TrainingModeEnum } from '@/constants/plugin';
import { useUserStore } from '@/store/user';
import MyTooltip from '@/components/MyTooltip';
import { QuestionOutlineIcon } from '@chakra-ui/icons';
type ManualFormType = { q: string; a: string };
......@@ -70,7 +72,12 @@ const ManualImport = ({ kbId }: { kbId: string }) => {
<Box p={[4, 8]} h={'100%'} overflow={'overlay'}>
<Box display={'flex'} flexDirection={['column', 'row']}>
<Box flex={1} mr={[0, 4]} mb={[4, 0]} h={['50%', '100%']} position={'relative'}>
<Flex>
<Box h={'30px'}>{'匹配的知识点'}</Box>
<MyTooltip label={'被向量化的部分，通常是问题，也可以是一段陈述描述'}>
<QuestionOutlineIcon ml={1} />
</MyTooltip>
</Flex>
<Textarea
placeholder={`匹配的知识点。这部分内容会被搜索，请把控内容的质量。最多 ${maxToken} 字。`}
maxLength={maxToken}
......@@ -87,7 +94,14 @@ const ManualImport = ({ kbId }: { kbId: string }) => {
</Box>
</Box>
<Box flex={1} h={['50%', '100%']}>
<Box h={'30px'}>补充知识</Box>
<Flex>
<Box h={'30px'}>{'补充知识'}</Box>
<MyTooltip
label={'匹配的知识点被命中后，这部分内容会随匹配知识点一起注入模型，引导模型回答'}
>
<QuestionOutlineIcon ml={1} />
</MyTooltip>
</Flex>
<Textarea
placeholder={
'补充知识。这部分内容不会被搜索，但会作为"匹配的知识点"的内容补充，你可以讲一些细节的内容填写在这里。总和最多 3000 字。'
......
client/src/pages/kb/detail/components/InputDataModal.tsx
import React, { useState, useCallback } from 'react';
import { Box, Flex, Button, Textarea, IconButton } from '@chakra-ui/react';
import { useForm } from 'react-hook-form';
import { postKbDataFromList, putKbDataById, delOneKbDataByDataId } from '@/api/plugins/kb';
import { insertData2Kb, putKbDataById, delOneKbDataByDataId } from '@/api/plugins/kb';
import { useToast } from '@/hooks/useToast';
import { TrainingModeEnum } from '@/constants/plugin';
import { getErrText } from '@/utils/tools';
import { vectorModelList } from '@/store/static';
import MyIcon from '@/components/Icon';
import MyModal from '@/components/MyModal';
import MyTooltip from '@/components/MyTooltip';
import { QuestionOutlineIcon } from '@chakra-ui/icons';
import { useUserStore } from '@/store/user';
import { useQuery } from '@tanstack/react-query';
export type FormData = { dataId?: string; a: string; q: string };
export type FormData = { dataId?: string; a: string; q: string; source?: string };
const InputDataModal = ({
onClose,
......@@ -30,16 +32,20 @@ const InputDataModal = ({
const [loading, setLoading] = useState(false);
const { toast } = useToast();
const { kbDetail, getKbDetail } = useUserStore();
const { register, handleSubmit, reset } = useForm<FormData>({
defaultValues
});
const maxToken = kbDetail.vectorModel?.maxToken || 2000;
/**
* 确认导入新数据
*/
const sureImportData = useCallback(
async (e: FormData) => {
if (e.a.length + e.q.length >= 3000) {
if (e.q.length >= maxToken) {
toast({
title: '总长度超长了',
status: 'warning'
......@@ -50,22 +56,16 @@ const InputDataModal = ({
try {
const data = {
dataId: '',
a: e.a,
q: e.q,
source: '手动录入'
};
const { insertLen } = await postKbDataFromList({
data.dataId = await insertData2Kb({
kbId,
mode: TrainingModeEnum.index,
data: [data]
data
});
if (insertLen === 0) {
toast({
title: '已存在完全一致的数据',
status: 'warning'
});
} else {
toast({
title: '导入数据成功,需要一段时间训练',
status: 'success'
......@@ -74,7 +74,6 @@ const InputDataModal = ({
a: '',
q: ''
});
}
onSuccess(data);
} catch (err: any) {
......@@ -85,7 +84,7 @@ const InputDataModal = ({
}
setLoading(false);
},
[kbId, onSuccess, reset, toast]
[kbId, maxToken, onSuccess, reset, toast]
);
const updateData = useCallback(
......@@ -121,6 +120,11 @@ const InputDataModal = ({
[defaultValues.a, defaultValues.q, kbId, onClose, onSuccess, toast]
);
useQuery(['getKbDetail'], () => {
if (kbDetail._id === kbId) return null;
return getKbDetail(kbId);
});
return (
<MyModal
isOpen={true}
......@@ -142,10 +146,15 @@ const InputDataModal = ({
pb={2}
>
<Box flex={1} mr={[0, 4]} mb={[4, 0]} h={['50%', '100%']}>
<Flex>
<Box h={'30px'}>{'匹配的知识点'}</Box>
<MyTooltip label={'被向量化的部分，通常是问题，也可以是一段陈述描述'}>
<QuestionOutlineIcon ml={1} />
</MyTooltip>
</Flex>
<Textarea
placeholder={'匹配的知识点。这部分内容会被搜索，请把控内容的质量。总和最多 3000 字。'}
maxLength={3000}
placeholder={`匹配的知识点。这部分内容会被搜索，请把控内容的质量，最多 ${maxToken} 字。`}
maxLength={maxToken}
resize={'none'}
h={'calc(100% - 30px)'}
{...register(`q`, {
......@@ -154,7 +163,14 @@ const InputDataModal = ({
/>
</Box>
<Box flex={1} h={['50%', '100%']}>
<Box h={'30px'}>补充知识</Box>
<Flex>
<Box h={'30px'}>{'补充知识'}</Box>
<MyTooltip
label={'匹配的知识点被命中后，这部分内容会随匹配知识点一起注入模型，引导模型回答'}
>
<QuestionOutlineIcon ml={1} />
</MyTooltip>
</Flex>
<Textarea
placeholder={
'补充知识。这部分内容不会被搜索，但会作为"匹配的知识点"的内容补充，你可以讲一些细节的内容填写在这里。总和最多 3000 字。'
......
client/src/service/models/chatItem.ts
......@@ -41,7 +41,11 @@ const ChatItemSchema = new Schema({
type: String
},
adminFeedback: {
type: String
type: {
kbId: String,
dataId: String,
content: String
}
},
[TaskResponseKeyEnum.responseData]: {
type: [
......
client/src/service/moduleDispatch/chat/oneapi.ts
......@@ -211,8 +211,10 @@ function filterQuote({
const quotePrompt =
filterQuoteQA.length > 0
? `"""${filterQuoteQA
.map((item) => (item.a ? `[${item.q}\n${item.a}]` : `${item.q}`))
.join('\n\n')}"""`
.map((item) =>
item.a ? `{instruction:"${item.q}",output:"${item.a}"}` : `{instruction:"${item.q}"}`
)
.join('\n')}"""`
: '';
return {
......@@ -240,11 +242,11 @@ function getChatMessages({
return limitPrompt;
}
const defaultPrompt =
'三引号引用的内容是你的补充知识，它们是最新的，根据引用内容来回答我的问题。';
'三引号是我提供给你的专属知识，它们拥有最高优先级。instruction 是相关介绍，output 是预期回答，使用引用内容来回答我下面的问题。';
if (limitPrompt) {
return `${defaultPrompt}${limitPrompt}`;
}
return `${defaultPrompt}你仅回答引用包含的内容，如果问题不包含在引用中，你直接回复: "你的问题没有在知识库中体现"`;
return `${defaultPrompt}\n回答内容限制：你仅回答三引号中提及的内容，下面我提出的问题与引用内容无关时，你可以直接回复: "你的问题没有在知识库中体现"`;
})();
const messages: ChatItemType[] = [
......
client/src/service/pg.ts
......@@ -142,7 +142,9 @@ class Pg {
}
const fields = props.values[0].map((item) => item.key).join(',');
const sql = `INSERT INTO ${table} (${fields}) VALUES ${this.getInsertValStr(props.values)} `;
const sql = `INSERT INTO ${table} (${fields}) VALUES ${this.getInsertValStr(
props.values
)} RETURNING id`;
const pg = await connectPg();
return pg.query(sql);
}
......
client/src/service/utils/data.ts
......@@ -2,7 +2,15 @@ export const getChatModel = (model?: string) => {
return global.chatModels.find((item) => item.model === model);
};
export const getVectorModel = (model?: string) => {
return global.vectorModels.find((item) => item.model === model) || global.vectorModels[0];
return (
global.vectorModels.find((item) => item.model === model) || {
model: 'UnKnow',
name: 'UnKnow',
defaultToken: 500,
price: 0,
maxToken: 3000
}
);
};
export const getModel = (model?: string) => {
......
client/src/types/app.d.ts
......@@ -114,5 +114,6 @@ export type AppLogsListItemType = {
time: Date;
title: string;
messageCount: number;
callbackCount: number;
feedbackCount: number;
markCount: number;
};
client/src/types/chat.d.ts
......@@ -2,6 +2,7 @@ import { ChatRoleEnum } from '@/constants/chat';
import type { InitChatResponse, InitShareChatResponse } from '@/api/response/chat';
import { TaskResponseKeyEnum } from '@/constants/chat';
import { ClassifyQuestionAgentItemType } from './app';
import { ChatItemSchema } from './mongoSchema';
export type ExportChatType = 'md' | 'pdf' | 'html';
......@@ -9,6 +10,8 @@ export type ChatItemType = {
dataId?: string;
obj: `${ChatRoleEnum}`;
value: string;
userFeedback?: string;
adminFeedback?: ChatItemSchema['adminFeedback'];
[TaskResponseKeyEnum.responseData]?: ChatHistoryItemResType[];
};
......
client/src/types/mongoSchema.d.ts
......@@ -103,7 +103,11 @@ export interface ChatItemSchema extends ChatItemType {
appId: string;
time: Date;
userFeedback?: string;
adminFeedback?: string;
adminFeedback?: {
kbId: string;
dataId: string;
content: string;
};
}
export type BillListItemType = {
......@@ -137,7 +141,7 @@ export interface OpenApiSchema {
userId: string;
createTime: Date;
lastUsedTime?: Date;
apiKey: String;
apiKey: string;
}
export interface PromotionRecordSchema {
......
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