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user feedback and admin mark (#228)

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* fix: csv empty data

* feat: user feedback and mark answer

* version intro

* perf: chat logs sort
This commit is contained in:
Archer
2023-08-27 23:12:06 +08:00
committed by GitHub
parent 2556c19a9a
commit 5fcdf28c5c
32 changed files with 886 additions and 67 deletions
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37
client/src/pages/api/app/getChatLogs.ts
View File

@@ -1,6 +1,6 @@
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
}
}
]),

40
client/src/pages/api/chat/feedback/adminUpdate.ts Normal file
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@@ -0,0 +1,40 @@
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
});
}
}

34
client/src/pages/api/chat/feedback/userUpdate.ts Normal file
View File

@@ -0,0 +1,34 @@
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
});
}
}

2
client/src/pages/api/chat/init.ts
View File

@@ -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)

5
client/src/pages/api/openapi/kb/updateData.ts
View File

@@ -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");

88
client/src/pages/api/plugins/kb/data/insertData.ts Normal file
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@@ -0,0 +1,88 @@
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
});
}
});

53
client/src/pages/app/detail/components/Logs.tsx
View File

@@ -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';
@@ -24,11 +26,18 @@ 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,
@@ -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}

5
client/src/pages/kb/detail/components/Import/Csv.tsx
View File

@@ -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);

20
client/src/pages/kb/detail/components/Import/Manual.tsx
View File

@@ -1,5 +1,5 @@
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'}>
<Box h={'30px'}>{'匹配的知识点'}</Box>
<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。'

72
client/src/pages/kb/detail/components/InputDataModal.tsx
View File

@@ -1,15 +1,17 @@
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'
@@ -50,31 +56,24 @@ 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'
});
reset({
a: '',
q: ''
});
}
toast({
title: '导入数据成功,需要一段时间训练',
status: 'success'
});
reset({
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%']}>
<Box h={'30px'}>{'匹配的知识点'}</Box>
<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。'