perf: search prompt

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archer 2023-05-09 16:32:02 +08:00
parent f52f514f5f
commit 4dc541e0a6
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GPG Key ID: 569A5660D2379E28
13 changed files with 82 additions and 59 deletions

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@ -35,7 +35,7 @@ const Layout = ({ children, isPcDevice }: { children: JSX.Element; isPcDevice: b
return ( return (
<> <>
<Box h={'100%'} overflow={'overlay'} bg={'gray.100'}> <Box h={'100%'} overflowY={'auto'} bg={'gray.100'}>
{isPc ? ( {isPc ? (
pcUnShowLayoutRoute[router.pathname] ? ( pcUnShowLayoutRoute[router.pathname] ? (
<Auth>{children}</Auth> <Auth>{children}</Auth>

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@ -102,9 +102,7 @@ const Navbar = () => {
justifyContent={'center'} justifyContent={'center'}
onClick={() => { onClick={() => {
if (item.link === router.asPath) return; if (item.link === router.asPath) return;
router.push(item.link, undefined, { router.push(item.link);
shallow: true
});
}} }}
cursor={'pointer'} cursor={'pointer'}
w={'60px'} w={'60px'}

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@ -55,7 +55,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// 使用了知识库搜索 // 使用了知识库搜索
if (model.chat.useKb) { if (model.chat.useKb) {
const { code, searchPrompt } = await searchKb({ const { code, searchPrompts } = await searchKb({
userOpenAiKey, userOpenAiKey,
prompts, prompts,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity, similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
@ -65,10 +65,10 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// search result is empty // search result is empty
if (code === 201) { if (code === 201) {
return res.send(searchPrompt?.value); return res.send(searchPrompts[0]?.value);
} }
searchPrompt && prompts.unshift(searchPrompt); prompts.splice(prompts.length - 1, 0, ...searchPrompts);
} else { } else {
// 没有用知识库搜索,仅用系统提示词 // 没有用知识库搜索,仅用系统提示词
model.chat.systemPrompt && model.chat.systemPrompt &&
@ -103,8 +103,12 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
stream, stream,
chatResponse: streamResponse, chatResponse: streamResponse,
prompts, prompts,
systemPrompt: systemPrompt: showModelDetail
showModelDetail && prompts[0].obj === ChatRoleEnum.System ? prompts[0].value : '' ? prompts
.filter((item) => item.obj === ChatRoleEnum.System)
.map((item) => item.value)
.join('\n')
: ''
}); });
// 只有使用平台的 key 才计费 // 只有使用平台的 key 才计费

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@ -73,7 +73,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
if (model.chat.useKb) { if (model.chat.useKb) {
const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22; const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22;
const { code, searchPrompt } = await searchKb({ const { code, searchPrompts } = await searchKb({
prompts, prompts,
similarity, similarity,
model, model,
@ -82,10 +82,9 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// search result is empty // search result is empty
if (code === 201) { if (code === 201) {
return res.send(searchPrompt?.value); return res.send(searchPrompts[0]?.value);
} }
prompts.splice(prompts.length - 1, 0, ...searchPrompts);
searchPrompt && prompts.unshift(searchPrompt);
} else { } else {
// 没有用知识库搜索,仅用系统提示词 // 没有用知识库搜索,仅用系统提示词
if (model.chat.systemPrompt) { if (model.chat.systemPrompt) {

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@ -122,14 +122,14 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const prompts = [prompt]; const prompts = [prompt];
// 获取向量匹配到的提示词 // 获取向量匹配到的提示词
const { searchPrompt } = await searchKb({ const { searchPrompts } = await searchKb({
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity, similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
prompts, prompts,
model, model,
userId userId
}); });
searchPrompt && prompts.unshift(searchPrompt); prompts.splice(prompts.length - 1, 0, ...searchPrompts);
// 计算温度 // 计算温度
const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed( const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(

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@ -508,7 +508,7 @@ const Chat = ({
isLeavePage.current = true; isLeavePage.current = true;
controller.current?.abort(); controller.current?.abort();
}; };
}, []); }, [modelId, chatId]);
return ( return (
<Flex <Flex

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@ -279,9 +279,9 @@ const ModelDataCard = ({ modelId, isOwner }: { modelId: string; isOwner: boolean
</Tbody> </Tbody>
</Table> </Table>
</TableContainer> </TableContainer>
<Box mt={2} textAlign={'end'}> <Flex mt={2} justifyContent={'flex-end'}>
<Pagination /> <Pagination />
</Box> </Flex>
</Box> </Box>
<Loading loading={isLoading} fixed={false} /> <Loading loading={isLoading} fixed={false} />

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@ -61,13 +61,7 @@ const SelectFileModal = ({
const { openConfirm, ConfirmChild } = useConfirm({ const { openConfirm, ConfirmChild } = useConfirm({
content: `确认导入该文件,需要一定时间进行拆解,该任务无法终止!如果余额不足,未完成的任务会被直接清除。一共 ${ content: `确认导入该文件,需要一定时间进行拆解,该任务无法终止!如果余额不足,未完成的任务会被直接清除。一共 ${
splitRes.chunks.length splitRes.chunks.length
} ${ } ${splitRes.tokens ? `大约 ${splitRes.tokens} 个tokens。` : ''}`
splitRes.tokens
? `大约 ${splitRes.tokens} 个tokens, 约 ${formatPrice(
splitRes.tokens * modeMap[mode].price
)} `
: ''
}`
}); });
const onSelectFile = useCallback( const onSelectFile = useCallback(

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@ -101,9 +101,9 @@ const modelList = () => {
<Grid templateColumns={['1fr', '1fr 1fr', '1fr 1fr 1fr']} gridGap={4} mt={4}> <Grid templateColumns={['1fr', '1fr 1fr', '1fr 1fr 1fr']} gridGap={4} mt={4}>
<ShareModelList models={models} onclickCollection={onclickCollection} /> <ShareModelList models={models} onclickCollection={onclickCollection} />
</Grid> </Grid>
<Box mt={4}> <Flex mt={4} justifyContent={'flex-end'}>
<Pagination /> <Pagination />
</Box> </Flex>
</Card> </Card>
<Loading loading={isLoading} /> <Loading loading={isLoading} />

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@ -1,5 +1,5 @@
import React from 'react'; import React from 'react';
import { Card, Box, Table, Thead, Tbody, Tr, Th, Td, TableContainer } from '@chakra-ui/react'; import { Card, Box, Table, Thead, Tbody, Tr, Th, Td, TableContainer, Flex } from '@chakra-ui/react';
import { BillTypeMap } from '@/constants/user'; import { BillTypeMap } from '@/constants/user';
import { getUserBills } from '@/api/user'; import { getUserBills } from '@/api/user';
import type { UserBillType } from '@/types/user'; import type { UserBillType } from '@/types/user';
@ -48,9 +48,9 @@ const BillTable = () => {
<Loading loading={isLoading} fixed={false} /> <Loading loading={isLoading} fixed={false} />
</TableContainer> </TableContainer>
<Box mt={4} mr={4} textAlign={'end'}> <Flex mt={4} px={4} justifyContent={'flex-end'}>
<Pagination /> <Pagination />
</Box> </Flex>
</Card> </Card>
); );
}; };

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@ -139,9 +139,9 @@ const OpenApi = () => {
<Loading loading={isLoading} fixed={false} /> <Loading loading={isLoading} fixed={false} />
</TableContainer> </TableContainer>
<Box mt={4} mr={4} textAlign={'end'}> <Flex mt={4} px={4} justifyContent={'flex-end'}>
<Pagination /> <Pagination />
</Box> </Flex>
</Card> </Card>
<Modal isOpen={isOpenWithdraw} onClose={onCloseWithdraw}> <Modal isOpen={isOpenWithdraw} onClose={onCloseWithdraw}>
<ModalOverlay /> <ModalOverlay />

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@ -23,10 +23,10 @@ export const searchKb = async ({
similarity?: number; similarity?: number;
}): Promise<{ }): Promise<{
code: 200 | 201; code: 200 | 201;
searchPrompt?: { searchPrompts: {
obj: `${ChatRoleEnum}`; obj: ChatRoleEnum;
value: string; value: string;
}; }[];
}> => { }> => {
async function search(textArr: string[] = []) { async function search(textArr: string[] = []) {
// 获取提示词的向量 // 获取提示词的向量
@ -85,17 +85,38 @@ export const searchKb = async ({
}; };
const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0]; const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0];
// count fixed system prompt // 计算固定提示词的 token 数量
const fixedSystemPrompt = ` const fixedPrompts = [
${model.chat.systemPrompt} ...(model.chat.systemPrompt
${ ? [
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity ? '不回答知识库外的内容.' : '' {
} obj: ChatRoleEnum.System,
:`; value: model.chat.systemPrompt
}
]
: []),
...(model.chat.searchMode === ModelVectorSearchModeEnum.noContext
? [
{
obj: ChatRoleEnum.System,
value: `知识库是关于"${model.name}"的内容,根据知识库内容回答问题.`
}
]
: [
{
obj: ChatRoleEnum.System,
value: `我们来玩问答游戏,规则为:
1.
2."${model.name}"
3.
4.,"我不知道。"
`
}
])
];
const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({ const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
messages: [{ obj: 'System', value: fixedSystemPrompt }] messages: fixedPrompts
}); });
const maxTokens = modelConstantsData.systemMaxToken - fixedSystemTokens; const maxTokens = modelConstantsData.systemMaxToken - fixedSystemTokens;
const filterSystemPrompt = filterRate const filterSystemPrompt = filterRate
@ -111,31 +132,38 @@ ${
if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) { if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
return { return {
code: 201, code: 201,
searchPrompt: { searchPrompts: [
obj: ChatRoleEnum.AI, {
value: '对不起,你的问题不在知识库中。' obj: ChatRoleEnum.System,
} value: '对不起,你的问题不在知识库中。'
}
]
}; };
} }
/* 高相似度+无上下文,不添加额外知识,仅用系统提示词 */ /* 高相似度+无上下文,不添加额外知识,仅用系统提示词 */
if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) { if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
return { return {
code: 200, code: 200,
searchPrompt: model.chat.systemPrompt searchPrompts: model.chat.systemPrompt
? { ? [
obj: ChatRoleEnum.System, {
value: model.chat.systemPrompt obj: ChatRoleEnum.System,
} value: model.chat.systemPrompt
: undefined }
]
: []
}; };
} }
/* 有匹配 */ /* 有匹配 */
return { return {
code: 200, code: 200,
searchPrompt: { searchPrompts: [
obj: ChatRoleEnum.System, {
value: `${fixedSystemPrompt}'${filterSystemPrompt}'` obj: ChatRoleEnum.System,
} value: `知识库:'${filterSystemPrompt}'`
},
...fixedPrompts
]
}; };
}; };

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@ -27,7 +27,7 @@ export const lafClaudChat = async ({
.join('\n'); .join('\n');
const systemPromptText = systemPrompt ? `\n知识库内容:'${systemPrompt}'\n` : ''; const systemPromptText = systemPrompt ? `\n知识库内容:'${systemPrompt}'\n` : '';
const prompt = `${systemPromptText}我的问题:'${messages[messages.length - 1].value}'`; const prompt = `${systemPromptText}\n我的问题:'${messages[messages.length - 1].value}'`;
const lafResponse = await axios.post( const lafResponse = await axios.post(
'https://hnvacz.laf.run/claude-gpt', 'https://hnvacz.laf.run/claude-gpt',