ChatGPT/FastGPT
1
0
Fork 0
mirror of https://github.com/labring/FastGPT.git synced 2025-08-03 21:48:02 +00:00
Code Issues Packages Projects Releases Wiki Activity

v4.4.3 (#316)

Browse Source
This commit is contained in:
Archer
2023-09-18 21:26:42 +08:00
committed by GitHub
parent 81e37a5736
commit 06be57815e
24 changed files with 459 additions and 707 deletions
Download Patch File Download Diff File Expand all files Collapse all files

5
client/src/components/ChatBox/index.tsx
View File

@@ -613,11 +613,6 @@ const ChatBox = (
flexDirection={'column'}
alignItems={item.obj === 'Human' ? 'flex-end' : 'flex-start'}
py={5}
_hover={{
'& .control': {
display: item.status === 'finish' ? 'flex' : 'none'
}
}}
>
{item.obj === 'Human' && (
<>

13
client/src/components/MyModal/index.tsx
View File

@@ -10,11 +10,10 @@ import {
} from '@chakra-ui/react';
interface Props extends ModalContentProps {
showCloseBtn?: boolean;
title?: any;
isCentered?: boolean;
isOpen: boolean;
onClose: () => void;
onClose?: () => void;
}
const MyModal = ({
@@ -22,14 +21,18 @@ const MyModal = ({
onClose,
title,
children,
showCloseBtn = true,
isCentered,
w = 'auto',
maxW = ['90vw', '600px'],
...props
}: Props) => {
return (
<Modal isOpen={isOpen} onClose={onClose} autoFocus={false} isCentered={isCentered}>
<Modal
isOpen={isOpen}
onClose={() => onClose && onClose()}
autoFocus={false}
isCentered={isCentered}
>
<ModalOverlay />
<ModalContent
display={'flex'}
@@ -43,7 +46,7 @@ const MyModal = ({
>
{!!title && <ModalHeader>{title}</ModalHeader>}
<Box overflow={'overlay'} h={'100%'}>
{showCloseBtn && <ModalCloseButton />}
{onClose && <ModalCloseButton />}
{children}
</Box>
</ModalContent>

68
client/src/constants/flow/ModuleTemplate.ts
View File

@@ -163,19 +163,23 @@ export const ChatModule: FlowModuleTemplateType = {
value: ''
},
{
key: 'limitPrompt',
type: FlowInputItemTypeEnum.textarea,
key: 'quoteTemplate',
type: FlowInputItemTypeEnum.hidden,
label: '引用内容模板',
valueType: FlowValueTypeEnum.string,
value: ''
},
{
key: 'quotePrompt',
type: FlowInputItemTypeEnum.hidden,
label: '引用内容提示词',
valueType: FlowValueTypeEnum.string,
label: '限定词',
max: 500,
description: ChatModelLimitTip,
placeholder: ChatModelLimitTip,
value: ''
},
Input_Template_TFSwitch,
{
key: 'quoteQA',
type: FlowInputItemTypeEnum.target,
type: FlowInputItemTypeEnum.custom,
label: '引用内容',
description: "对象数组格式，结构：\n [{q:'问题',a:'回答'}]",
valueType: FlowValueTypeEnum.kbQuote
@@ -664,19 +668,6 @@ export const appTemplates: (AppItemType & { avatar: string; intro: string })[] =
value: '',
connected: true
},
{
key: 'limitPrompt',
type: 'textarea',
valueType: 'string',
label: '限定词',
max: 500,
description:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
placeholder:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
value: '',
connected: true
},
{
key: 'switch',
type: 'target',
@@ -1013,18 +1004,6 @@ export const appTemplates: (AppItemType & { avatar: string; intro: string })[] =
value: '',
connected: true
},
{
key: 'limitPrompt',
type: 'textarea',
valueType: 'string',
label: '限定词',
description:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
placeholder:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
value: '',
connected: true
},
{
key: 'switch',
type: 'target',
@@ -1319,18 +1298,6 @@ export const appTemplates: (AppItemType & { avatar: string; intro: string })[] =
value: '',
connected: true
},
{
key: 'limitPrompt',
type: 'textarea',
valueType: 'string',
label: '限定词',
description:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
placeholder:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
value: '将我的问题直接翻译成英语{{language}}',
connected: true
},
{
key: 'switch',
type: 'target',
@@ -1703,19 +1670,6 @@ export const appTemplates: (AppItemType & { avatar: string; intro: string })[] =
value: '知识库是关于 laf 的内容。',
connected: true
},
{
key: 'limitPrompt',
type: 'textarea',
valueType: 'string',
label: '限定词',
description:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
placeholder:
'限定模型对话范围，会被放置在本次提问前，拥有强引导和限定性。可使用变量，例如 {{language}}。引导例子:\n1. 知识库是关于 Laf 的介绍，参考知识库回答问题，与 "Laf" 无关内容，直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题，其他问题回复: "xxxx"',
value:
'我的问题都是关于 laf 的。根据知识库回答我的问题，与 laf 无关问题，直接回复：“我不清楚，我仅能回答 laf 相关的问题。”。',
connected: true
},
{
key: 'switch',
type: 'target',

11
client/src/pages/account/components/PayModal.tsx
View File

@@ -64,16 +64,7 @@ const PayModal = ({ onClose }: { onClose: () => void }) => {
);
return (
<MyModal
isOpen={true}
onClose={() => {
if (payId) return;
onClose();
}}
title={t('user.Pay')}
isCentered
showCloseBtn={!payId}
>
<MyModal isOpen={true} onClose={payId ? onClose : undefined} title={t('user.Pay')} isCentered>
<ModalBody py={0}>
{!payId && (
<>

446
client/src/pages/api/admin/initv4.ts
View File

@@ -1,446 +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, App } from '@/service/mongo';
import { FlowModuleTypeEnum, SpecialInputKeyEnum } from '@/constants/flow';
import { TaskResponseKeyEnum } from '@/constants/chat';
import { FlowInputItemType } from '@/types/flow';
const chatModelInput = ({
model,
temperature,
maxToken,
systemPrompt,
limitPrompt,
kbList
}: {
model: string;
temperature: number;
maxToken: number;
systemPrompt: string;
limitPrompt: string;
kbList: { kbId: string }[];
}): FlowInputItemType[] => [
{
key: 'model',
value: model,
type: 'custom',
label: '对话模型',
connected: true
},
{
key: 'temperature',
value: temperature,
label: '温度',
type: 'slider',
connected: true
},
{
key: 'maxToken',
value: maxToken,
type: 'custom',
label: '回复上限',
connected: true
},
{
key: 'systemPrompt',
value: systemPrompt,
type: 'textarea',
label: '系统提示词',
connected: true
},
{
key: 'limitPrompt',
label: '限定词',
type: 'textarea',
value: limitPrompt,
connected: true
},
{
key: 'switch',
type: 'target',
label: '触发器',
connected: kbList.length > 0
},
{
key: 'quoteQA',
type: 'target',
label: '引用内容',
connected: kbList.length > 0
},
{
key: 'history',
type: 'target',
label: '聊天记录',
connected: true
},
{
key: 'userChatInput',
type: 'target',
label: '用户问题',
connected: true
}
];
const chatTemplate = ({
model,
temperature,
maxToken,
systemPrompt,
limitPrompt
}: {
model: string;
temperature: number;
maxToken: number;
systemPrompt: string;
limitPrompt: string;
}) => {
return [
{
flowType: FlowModuleTypeEnum.questionInput,
inputs: [
{
key: 'userChatInput',
connected: true
}
],
outputs: [
{
key: 'userChatInput',
targets: [
{
moduleId: 'chatModule',
key: 'userChatInput'
}
]
}
],
position: {
x: 464.32198615344566,
y: 1602.2698463081606
},
moduleId: 'userChatInput'
},
{
flowType: FlowModuleTypeEnum.historyNode,
inputs: [
{
key: 'maxContext',
value: 10,
connected: true
},
{
key: 'history',
connected: true
}
],
outputs: [
{
key: 'history',
targets: [
{
moduleId: 'chatModule',
key: 'history'
}
]
}
],
position: {
x: 452.5466249541586,
y: 1276.3930310334215
},
moduleId: 'history'
},
{
flowType: FlowModuleTypeEnum.chatNode,
inputs: chatModelInput({
model,
temperature,
maxToken,
systemPrompt,
limitPrompt,
kbList: []
}),
outputs: [
{
key: TaskResponseKeyEnum.answerText,
targets: []
}
],
position: {
x: 981.9682828103937,
y: 890.014595014464
},
moduleId: 'chatModule'
}
];
};
const kbTemplate = ({
model,
temperature,
maxToken,
systemPrompt,
limitPrompt,
kbList = [],
searchSimilarity,
searchLimit,
searchEmptyText
}: {
model: string;
temperature: number;
maxToken: number;
systemPrompt: string;
limitPrompt: string;
kbList: { kbId: string }[];
searchSimilarity: number;
searchLimit: number;
searchEmptyText: string;
}) => {
return [
{
flowType: FlowModuleTypeEnum.questionInput,
inputs: [
{
key: 'userChatInput',
connected: true
}
],
outputs: [
{
key: 'userChatInput',
targets: [
{
moduleId: 'chatModule',
key: 'userChatInput'
},
{
moduleId: 'kbSearch',
key: 'userChatInput'
}
]
}
],
position: {
x: 464.32198615344566,
y: 1602.2698463081606
},
moduleId: 'userChatInput'
},
{
flowType: FlowModuleTypeEnum.historyNode,
inputs: [
{
key: 'maxContext',
value: 10,
connected: true
},
{
key: 'history',
connected: true
}
],
outputs: [
{
key: 'history',
targets: [
{
moduleId: 'chatModule',
key: 'history'
}
]
}
],
position: {
x: 452.5466249541586,
y: 1276.3930310334215
},
moduleId: 'history'
},
{
flowType: FlowModuleTypeEnum.kbSearchNode,
inputs: [
{
key: 'kbList',
value: kbList,
connected: true
},
{
key: 'similarity',
value: searchSimilarity,
connected: true
},
{
key: 'limit',
value: searchLimit,
connected: true
},
{
key: 'switch',
connected: false
},
{
key: 'userChatInput',
connected: true
}
],
outputs: [
{
key: 'isEmpty',
targets: searchEmptyText
? [
{
moduleId: 'emptyText',
key: 'switch'
}
]
: [
{
moduleId: 'chatModule',
key: 'switch'
}
]
},
{
key: 'unEmpty',
targets: [
{
moduleId: 'chatModule',
key: 'switch'
}
]
},
{
key: 'quoteQA',
targets: [
{
moduleId: 'chatModule',
key: 'quoteQA'
}
]
}
],
position: {
x: 956.0838440206068,
y: 887.462827870246
},
moduleId: 'kbSearch'
},
...(searchEmptyText
? [
{
flowType: FlowModuleTypeEnum.answerNode,
inputs: [
{
key: 'switch',
connected: true
},
{
key: SpecialInputKeyEnum.answerText,
value: searchEmptyText,
connected: true
}
],
outputs: [],
position: {
x: 1553.5815811529146,
y: 637.8753731306779
},
moduleId: 'emptyText'
}
]
: []),
{
flowType: FlowModuleTypeEnum.chatNode,
inputs: chatModelInput({ model, temperature, maxToken, systemPrompt, limitPrompt, kbList }),
outputs: [
{
key: TaskResponseKeyEnum.answerText,
targets: []
}
],
position: {
x: 1551.71405495818,
y: 977.4911578918461
},
moduleId: 'chatModule'
}
];
};
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
try {
await authUser({ req, authRoot: true });
await connectToDatabase();
const { limit = 1000 } = req.body as { limit: number };
let skip = 0;
const total = await App.countDocuments();
let promise = Promise.resolve();
console.log(total);
for (let i = 0; i < total; i += limit) {
const skipVal = skip;
skip += limit;
promise = promise
.then(() => init(limit, skipVal))
.then(() => {
console.log(skipVal);
});
}
await promise;
jsonRes(res, {});
} catch (error) {
jsonRes(res, {
code: 500,
error
});
}
}
async function init(limit: number, skip: number) {
// 遍历 app
const apps = await App.find(
{
chat: { $ne: null },
modules: { $exists: false }
// userId: '63f9a14228d2a688d8dc9e1b'
},
'_id chat'
).limit(limit);
return Promise.all(
apps.map(async (app) => {
if (!app.chat) return app;
const modules = (() => {
if (app.chat.relatedKbs.length === 0) {
return chatTemplate({
model: app.chat.chatModel,
temperature: app.chat.temperature,
maxToken: app.chat.maxToken,
systemPrompt: app.chat.systemPrompt,
limitPrompt: app.chat.limitPrompt
});
} else {
return kbTemplate({
model: app.chat.chatModel,
temperature: app.chat.temperature,
maxToken: app.chat.maxToken,
systemPrompt: app.chat.systemPrompt,
limitPrompt: app.chat.limitPrompt,
kbList: app.chat.relatedKbs.map((id) => ({ kbId: id })),
searchEmptyText: app.chat.searchEmptyText,
searchLimit: app.chat.searchLimit,
searchSimilarity: app.chat.searchSimilarity
});
}
})();
await App.findByIdAndUpdate(app.id, {
modules
});
return modules;
})
);
}

6
client/src/pages/api/openapi/v1/chat/completions.ts
View File

@@ -31,6 +31,7 @@ import { SystemInputEnum } from '@/constants/app';
import { getSystemTime } from '@/utils/user';
import { authOutLinkChat } from '@/service/support/outLink/auth';
import requestIp from 'request-ip';
import { replaceVariable } from '@/utils/common/tools/text';
export type MessageItemType = ChatCompletionRequestMessage & { dataId?: string };
type FastGptWebChatProps = {
@@ -424,10 +425,7 @@ function loadModules(
}
// variables replace
const replacedVal = item.value.replace(
/{{(.*?)}}/g,
(match, key) => variables[key.trim()] || match
);
const replacedVal = replaceVariable(item.value, variables);
return {
key: item.key,

112
client/src/pages/app/detail/components/AIChatSettingsModal.tsx Normal file
View File

@@ -0,0 +1,112 @@
import React from 'react';
import MyModal from '@/components/MyModal';
import { useTranslation } from 'react-i18next';
import { EditFormType } from '@/utils/app';
import { useForm } from 'react-hook-form';
import {
Box,
BoxProps,
Button,
Flex,
Link,
ModalBody,
ModalFooter,
Textarea
} from '@chakra-ui/react';
import MyTooltip from '@/components/MyTooltip';
import { QuestionOutlineIcon } from '@chakra-ui/icons';
import { defaultQuotePrompt, defaultQuoteTemplate } from '@/prompts/core/AIChat';
import { feConfigs } from '@/store/static';
const AIChatSettingsModal = ({
onClose,
onSuccess,
defaultData
}: {
onClose: () => void;
onSuccess: (e: EditFormType['chatModel']) => void;
defaultData: EditFormType['chatModel'];
}) => {
const { t } = useTranslation();
const { register, handleSubmit } = useForm({
defaultValues: defaultData
});
const LabelStyles: BoxProps = {
fontWeight: 'bold',
mb: 1,
fontSize: ['sm', 'md']
};
return (
<MyModal
isOpen
title={
<Flex alignItems={'flex-end'}>
{t('app.Quote Prompt Settings')}
{feConfigs?.show_doc && (
<Link
href={'https://doc.fastgpt.run/docs/use-cases/prompt/'}
target={'_blank'}
ml={1}
textDecoration={'underline'}
fontWeight={'normal'}
fontSize={'md'}
>
查看说明
</Link>
)}
</Flex>
}
w={'700px'}
>
<ModalBody>
<Box>
<Box {...LabelStyles}>
引用内容模板
<MyTooltip
label={t('template.Quote Content Tip', { default: defaultQuoteTemplate })}
forceShow
>
<QuestionOutlineIcon display={['none', 'inline']} ml={1} />
</MyTooltip>
</Box>
<Textarea
rows={4}
placeholder={t('template.Quote Content Tip', { default: defaultQuoteTemplate }) || ''}
borderColor={'myGray.100'}
{...register('quoteTemplate')}
/>
</Box>
<Box mt={4}>
<Box {...LabelStyles}>
引用内容提示词
<MyTooltip
label={t('template.Quote Prompt Tip', { default: defaultQuotePrompt })}
forceShow
>
<QuestionOutlineIcon display={['none', 'inline']} ml={1} />
</MyTooltip>
</Box>
<Textarea
rows={6}
placeholder={t('template.Quote Prompt Tip', { default: defaultQuotePrompt }) || ''}
borderColor={'myGray.100'}
{...register('quotePrompt')}
/>
</Box>
</ModalBody>
<ModalFooter>
<Button variant={'base'} onClick={onClose}>
{t('Cancel')}
</Button>
<Button ml={4} onClick={handleSubmit(onSuccess)}>
{t('Confirm')}
</Button>
</ModalFooter>
</MyModal>
);
};
export default AIChatSettingsModal;

76
client/src/pages/app/detail/components/AdEdit/components/Nodes/NodeChat.tsx
View File

@@ -4,21 +4,36 @@ import NodeCard from '../modules/NodeCard';
import { FlowModuleItemType } from '@/types/flow';
import Divider from '../modules/Divider';
import Container from '../modules/Container';
import RenderInput from '../render/RenderInput';
import RenderInput, { Label } from '../render/RenderInput';
import RenderOutput from '../render/RenderOutput';
import { FlowOutputItemTypeEnum } from '@/constants/flow';
import MySelect from '@/components/Select';
import { chatModelList } from '@/store/static';
import MySlider from '@/components/Slider';
import { Box } from '@chakra-ui/react';
import { Box, Button, Flex, useDisclosure } from '@chakra-ui/react';
import { formatPrice } from '@/utils/user';
import MyIcon from '@/components/Icon';
import dynamic from 'next/dynamic';
import { AIChatProps } from '@/types/core/aiChat';
const AIChatSettingsModal = dynamic(() => import('../../../AIChatSettingsModal'));
const NodeChat = ({ data }: NodeProps<FlowModuleItemType>) => {
const { moduleId, inputs, outputs, onChangeNode } = data;
const outputsLen = useMemo(
() => outputs.filter((item) => item.type !== FlowOutputItemTypeEnum.hidden).length,
[outputs]
);
const chatModulesData = useMemo(() => {
const obj: Record<string, any> = {};
inputs.forEach((item) => {
obj[item.key] = item.value;
});
return obj as AIChatProps;
}, [inputs]);
const {
isOpen: isOpenAIChatSetting,
onOpen: onOpenAIChatSetting,
onClose: onCloseAIChatSetting
} = useDisclosure();
return (
<NodeCard minW={'400px'} {...data}>
@@ -109,21 +124,48 @@ const NodeChat = ({ data }: NodeProps<FlowModuleItemType>) => {
/>
</Box>
);
},
quoteQA: (inputItem) => {
return (
<Button
variant={'base'}
leftIcon={<MyIcon name={'settingLight'} w={'14px'} />}
onClick={onOpenAIChatSetting}
>
引用提示词设置
</Button>
);
}
}}
/>
</Container>
{outputsLen > 0 && (
<>
<Divider text="Output" />
<Container>
<RenderOutput
onChangeNode={onChangeNode}
moduleId={moduleId}
flowOutputList={outputs}
/>
</Container>
</>
<Divider text="Output" />
<Container>
<RenderOutput onChangeNode={onChangeNode} moduleId={moduleId} flowOutputList={outputs} />
</Container>
{isOpenAIChatSetting && (
<AIChatSettingsModal
onClose={onCloseAIChatSetting}
onSuccess={(e) => {
for (let key in e) {
const item = inputs.find((input) => input.key === key);
if (!item) continue;
onChangeNode({
moduleId,
type: 'inputs',
key,
value: {
...item,
// @ts-ignore
value: e[key]
}
});
}
onCloseAIChatSetting();
}}
defaultData={chatModulesData}
/>
)}
</NodeCard>
);

120
client/src/pages/app/detail/components/BasicEdit/index.tsx
View File

@@ -63,6 +63,7 @@ import { useDatasetStore } from '@/store/dataset';
const VariableEditModal = dynamic(() => import('../VariableEditModal'));
const InfoModal = dynamic(() => import('../InfoModal'));
const KBSelectModal = dynamic(() => import('../KBSelectModal'));
const AIChatSettingsModal = dynamic(() => import('../AIChatSettingsModal'));
const Settings = ({ appId }: { appId: string }) => {
const theme = useTheme();
@@ -101,6 +102,11 @@ const Settings = ({ appId }: { appId: string }) => {
name: 'kb.list'
});
const {
isOpen: isOpenAIChatSetting,
onOpen: onOpenAIChatSetting,
onClose: onCloseAIChatSetting
} = useDisclosure();
const {
isOpen: isOpenKbSelect,
onOpen: onOpenKbSelect,
@@ -335,51 +341,61 @@ const Settings = ({ appId }: { appId: string }) => {
+&ensp;新增
</Flex>
</Flex>
<Box mt={2} borderRadius={'lg'} overflow={'hidden'} borderWidth={'1px'} borderBottom="none">
<TableContainer>
<Table bg={'white'}>
<Thead>
<Tr>
<Th>变量名</Th>
<Th>变量 key</Th>
<Th>必填</Th>
<Th></Th>
</Tr>
</Thead>
<Tbody>
{variables.map((item, index) => (
<Tr key={item.id}>
<Td>{item.label} </Td>
<Td>{item.key}</Td>
<Td>{item.required ? '✔' : ''}</Td>
<Td>
<MyIcon
mr={3}
name={'settingLight'}
w={'16px'}
cursor={'pointer'}
onClick={() => setEditVariable(item)}
/>
<MyIcon
name={'delete'}
w={'16px'}
cursor={'pointer'}
onClick={() => removeVariable(index)}
/>
</Td>
{variables.length > 0 && (
<Box
mt={2}
borderRadius={'lg'}
overflow={'hidden'}
borderWidth={'1px'}
borderBottom="none"
>
<TableContainer>
<Table bg={'white'}>
<Thead>
<Tr>
<Th>变量名</Th>
<Th>变量 key</Th>
<Th>必填</Th>
<Th></Th>
</Tr>
))}
</Tbody>
</Table>
</TableContainer>
</Box>
</Thead>
<Tbody>
{variables.map((item, index) => (
<Tr key={item.id}>
<Td>{item.label} </Td>
<Td>{item.key}</Td>
<Td>{item.required ? '✔' : ''}</Td>
<Td>
<MyIcon
mr={3}
name={'settingLight'}
w={'16px'}
cursor={'pointer'}
onClick={() => setEditVariable(item)}
/>
<MyIcon
name={'delete'}
w={'16px'}
cursor={'pointer'}
onClick={() => removeVariable(index)}
/>
</Td>
</Tr>
))}
</Tbody>
</Table>
</TableContainer>
</Box>
)}
</Box>
{/* model */}
<Box mt={5} {...BoxStyles}>
<Flex alignItems={'center'}>
<Avatar src={'/imgs/module/AI.png'} w={'18px'} />
<Box ml={2}>AI 配置</Box>
<Box ml={2} flex={1}>
AI 配置
</Box>
</Flex>
<Flex alignItems={'center'} mt={5}>
@@ -452,20 +468,6 @@ const Settings = ({ appId }: { appId: string }) => {
{...register('chatModel.systemPrompt')}
></Textarea>
</Flex>
<Flex mt={5} alignItems={'flex-start'}>
<Box {...LabelStyles}>
限定词
<MyTooltip label={ChatModelLimitTip} forceShow>
<QuestionOutlineIcon display={['none', 'inline']} ml={1} />
</MyTooltip>
</Box>
<Textarea
rows={5}
placeholder={ChatModelLimitTip}
borderColor={'myGray.100'}
{...register('chatModel.limitPrompt')}
></Textarea>
</Flex>
</Box>
{/* kb */}
@@ -483,6 +485,10 @@ const Settings = ({ appId }: { appId: string }) => {
<MyIcon name={'edit'} w={'14px'} mr={1} />
参数
</Flex>
<Flex {...BoxBtnStyles} onClick={onOpenAIChatSetting}>
<MyIcon mr={1} name={'settingLight'} w={'14px'} />
提示词
</Flex>
</Flex>
<Flex mt={1} color={'myGray.600'} fontSize={['sm', 'md']}>
相似度: {getValues('kb.searchSimilarity')}, 单次搜索数量: {getValues('kb.searchLimit')},
@@ -548,6 +554,16 @@ const Settings = ({ appId }: { appId: string }) => {
}}
/>
)}
{isOpenAIChatSetting && (
<AIChatSettingsModal
onClose={onCloseAIChatSetting}
onSuccess={(e) => {
setValue('chatModel', e);
onCloseAIChatSetting();
}}
defaultData={getValues('chatModel')}
/>
)}
{isOpenKbSelect && (
<KBSelectModal
activeKbs={selectedKbList.map((item) => ({

1
client/src/pages/app/detail/components/InfoModal.tsx
View File

@@ -55,7 +55,6 @@ const InfoModal = ({
name: data.name,
avatar: data.avatar,
intro: data.intro,
chat: data.chat,
share: data.share
});
},

2
client/src/pages/app/detail/components/OutLink.tsx
View File

@@ -282,8 +282,6 @@ export function EditLinkModal({
return (
<MyModal
isOpen={true}
showCloseBtn={false}
onClose={() => {}}
title={isEdit ? titleMap.current.edit[type] : titleMap.current.create[type]}
>
<ModalBody>

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

@@ -168,7 +168,7 @@ const InputDataModal = ({
</Box>
<Box flex={1} h={['50%', '100%']}>
<Flex>
<Box h={'30px'}>{'预期答案'}</Box>
<Box h={'30px'}>{'补充内容'}</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'}
>
@@ -177,9 +177,8 @@ const InputDataModal = ({
</Flex>
<Textarea
placeholder={
'预期答案。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，通常是问题的答案。总和最多 3000 字。'
'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，通常是问题的答案。'
}
maxLength={3000}
resize={'none'}
h={'calc(100% - 30px)'}
{...register('a')}

10
client/src/prompts/core/AIChat.ts Normal file
View File

@@ -0,0 +1,10 @@
export const defaultQuoteTemplate = `{instruction:"{{q}}",output:"{{a}}"}`;
export const defaultQuotePrompt = `你的背景知识:
"""
{{quote}}
"""
对话要求：
1. 背景知识是最新的，其中 instruction 是相关介绍，output 是预期回答或补充。
2. 使用背景知识回答问题。
3. 背景知识无法满足问题时，你需严谨的回答问题。
我的问题是:"{{question}}"`;

76
client/src/service/moduleDispatch/chat/oneapi.ts
View File

@@ -17,12 +17,12 @@ import { ChatCompletionRequestMessageRoleEnum } from 'openai';
import { AppModuleItemType } from '@/types/app';
import { countMessagesTokens, sliceMessagesTB } from '@/utils/common/tiktoken';
import { adaptChat2GptMessages } from '@/utils/common/adapt/message';
import { defaultQuotePrompt, defaultQuoteTemplate } from '@/prompts/core/AIChat';
import type { AIChatProps } from '@/types/core/aiChat';
import { replaceVariable } from '@/utils/common/tools/text';
export type ChatProps = {
export type ChatProps = AIChatProps & {
res: NextApiResponse;
model: string;
temperature?: number;
maxToken?: number;
history?: ChatItemType[];
userChatInput: string;
stream?: boolean;
@@ -52,7 +52,9 @@ export const dispatchChatCompletion = async (props: Record<string, any>): Promis
quoteQA = [],
userChatInput,
systemPrompt = '',
limitPrompt = '',
limitPrompt,
quoteTemplate,
quotePrompt,
userOpenaiAccount,
outputs
} = props as ChatProps;
@@ -67,16 +69,16 @@ export const dispatchChatCompletion = async (props: Record<string, any>): Promis
return Promise.reject('The chat model is undefined, you need to select a chat model.');
}
const { filterQuoteQA, quotePrompt, hasQuoteOutput } = filterQuote({
const { filterQuoteQA, quoteText, hasQuoteOutput } = filterQuote({
quoteQA,
model: modelConstantsData
model: modelConstantsData,
quoteTemplate
});
if (modelConstantsData.censor) {
await textCensor({
text: `${systemPrompt}
${quotePrompt}
${limitPrompt}
${quoteText}
${userChatInput}
`
});
@@ -85,6 +87,7 @@ export const dispatchChatCompletion = async (props: Record<string, any>): Promis
const { messages, filterMessages } = getChatMessages({
model: modelConstantsData,
history,
quoteText,
quotePrompt,
userChatInput,
systemPrompt,
@@ -189,39 +192,40 @@ export const dispatchChatCompletion = async (props: Record<string, any>): Promis
function filterQuote({
quoteQA = [],
model
model,
quoteTemplate
}: {
quoteQA: ChatProps['quoteQA'];
model: ChatModelItemType;
quoteTemplate?: string;
}) {
const sliceResult = sliceMessagesTB({
maxTokens: model.quoteMaxToken,
messages: quoteQA.map((item) => ({
obj: ChatRoleEnum.System,
value: item.a ? `${item.q}\n${item.a}` : item.q
value: replaceVariable(quoteTemplate || defaultQuoteTemplate, item)
}))
});
// slice filterSearch
const filterQuoteQA = quoteQA.slice(0, sliceResult.length);
const quotePrompt =
const quoteText =
filterQuoteQA.length > 0
? `"""${filterQuoteQA
.map((item) =>
item.a ? `{instruction:"${item.q}",output:"${item.a}"}` : `{instruction:"${item.q}"}`
)
.join('\n')}"""`
? `${filterQuoteQA
.map((item) => replaceVariable(quoteTemplate || defaultQuoteTemplate, item))
.join('\n')}`
: '';
return {
filterQuoteQA,
quotePrompt,
quoteText,
hasQuoteOutput: !!filterQuoteQA.find((item) => item.a)
};
}
function getChatMessages({
quotePrompt,
quoteText,
history = [],
systemPrompt,
limitPrompt,
@@ -229,32 +233,28 @@ function getChatMessages({
model,
hasQuoteOutput
}: {
quotePrompt: string;
quotePrompt?: string;
quoteText: string;
history: ChatProps['history'];
systemPrompt: string;
limitPrompt: string;
limitPrompt?: string;
userChatInput: string;
model: ChatModelItemType;
hasQuoteOutput: boolean;
}) {
const { quoteGuidePrompt } = getDefaultPrompt({ hasQuoteOutput });
const systemText = `${quotePrompt ? `${quoteGuidePrompt}\n\n` : ''}${systemPrompt}`;
const question = hasQuoteOutput
? replaceVariable(quotePrompt || defaultQuotePrompt, {
quote: quoteText,
question: userChatInput
})
: userChatInput;
const messages: ChatItemType[] = [
...(systemText
...(systemPrompt
? [
{
obj: ChatRoleEnum.System,
value: systemText
}
]
: []),
...(quotePrompt
? [
{
obj: ChatRoleEnum.System,
value: quotePrompt
value: systemPrompt
}
]
: []),
@@ -269,7 +269,7 @@ function getChatMessages({
: []),
{
obj: ChatRoleEnum.Human,
value: userChatInput
value: question
}
];
@@ -375,11 +375,3 @@ async function streamResponse({
answer
};
}
function getDefaultPrompt({ hasQuoteOutput }: { hasQuoteOutput?: boolean }) {
return {
quoteGuidePrompt: `三引号引用的内容是我提供给你的知识库，它们拥有最高优先级。instruction 是相关介绍${
hasQuoteOutput ? '，output 是预期回答或补充。' : '。'
}`
};
}

10
client/src/types/core/aiChat.d.ts vendored Normal file
View File

@@ -0,0 +1,10 @@
export type AIChatProps = {
model: string;
systemPrompt: string;
temperature: number;
maxToken: number;
quoteTemplate?: string;
quotePrompt?: string;
frequency: number;
presence: number;
};

11
client/src/types/mongoSchema.d.ts vendored
View File

@@ -50,17 +50,6 @@ export interface AppSchema {
collection: number;
};
modules: AppModuleItemType[];
chat?: {
relatedKbs: string[];
searchSimilarity: number;
searchLimit: number;
searchEmptyText: string;
systemPrompt: string;
limitPrompt: string;
temperature: number;
maxToken: number;
chatModel: ChatModelType; // 聊天时用的模型，训练后就是训练的模型
};
}
export interface CollectionSchema {

43
client/src/utils/app.ts
View File

@@ -1,5 +1,5 @@
import type { AppModuleItemType, VariableItemType } from '@/types/app';
import { chatModelList, vectorModelList } from '@/store/static';
import { chatModelList } from '@/store/static';
import {
FlowInputItemTypeEnum,
FlowModuleTypeEnum,
@@ -7,20 +7,12 @@ import {
SpecialInputKeyEnum
} from '@/constants/flow';
import { SystemInputEnum } from '@/constants/app';
import { TaskResponseKeyEnum } from '@/constants/chat';
import type { SelectedKbType } from '@/types/plugin';
import { FlowInputItemType } from '@/types/flow';
import type { AIChatProps } from '@/types/core/aiChat';
export type EditFormType = {
chatModel: {
model: string;
systemPrompt: string;
limitPrompt: string;
temperature: number;
maxToken: number;
frequency: number;
presence: number;
};
chatModel: AIChatProps;
kb: {
list: SelectedKbType;
searchSimilarity: number;
@@ -41,8 +33,9 @@ export const getDefaultAppForm = (): EditFormType => {
chatModel: {
model: defaultChatModel.model,
systemPrompt: '',
limitPrompt: '',
temperature: 0,
quotePrompt: '',
quoteTemplate: '',
maxToken: defaultChatModel.contextMaxToken / 2,
frequency: 0.5,
presence: -0.5
@@ -109,9 +102,14 @@ export const appModules2Form = (modules: AppModuleItemType[]) => {
key: 'systemPrompt'
});
updateVal({
formKey: 'chatModel.limitPrompt',
formKey: 'chatModel.quoteTemplate',
inputs: module.inputs,
key: 'limitPrompt'
key: 'quoteTemplate'
});
updateVal({
formKey: 'chatModel.quotePrompt',
inputs: module.inputs,
key: 'quotePrompt'
});
} else if (module.flowType === FlowModuleTypeEnum.kbSearchNode) {
updateVal({
@@ -178,16 +176,23 @@ const chatModelInput = (formData: EditFormType): FlowInputItemType[] => [
},
{
key: 'systemPrompt',
value: formData.chatModel.systemPrompt,
value: formData.chatModel.systemPrompt || '',
type: 'textarea',
label: '系统提示词',
connected: true
},
{
key: 'limitPrompt',
type: 'textarea',
value: formData.chatModel.limitPrompt,
label: '限定词',
key: 'quoteTemplate',
value: formData.chatModel.quoteTemplate || '',
type: 'hidden',
label: '引用内容模板',
connected: true
},
{
key: 'quotePrompt',
value: formData.chatModel.quotePrompt || '',
type: 'hidden',
label: '引用内容提示词',
connected: true
},
{

2
client/src/utils/common/tiktoken/index.ts
View File

@@ -81,7 +81,7 @@ export function sliceMessagesTB({
const tokens = countPromptTokens(item.content, item.role);
reduceTokens -= tokens;
if (tokens > 0) {
if (reduceTokens > 0) {
result.push(messages[i]);
} else {
break;

12
client/src/utils/common/tools/text.ts Normal file
View File

@@ -0,0 +1,12 @@
/*
replace {{variable}} to value
*/
export function replaceVariable(text: string, obj: Record<string, string>) {
for (const key in obj) {
const val = obj[key];
if (typeof val !== 'string') continue;
text = text.replace(new RegExp(`{{(${key})}}`, 'g'), val);
}
return text || '';
}