perf: search prompt

4dc541e0 · archer · f52f514f · 4dc541e0 · 4dc541e0 · 4dc541e0
Commit 4dc541e0 authored May 09, 2023 by archer
13 changed files
--- a/src/components/Layout/index.tsx
+++ b/src/components/Layout/index.tsx
@@ -35,7 +35,7 @@ const Layout = ({ children, isPcDevice }: { children: JSX.Element; isPcDevice: b
  return (
    <>
-      <Box h={'100%'} overflow={'overlay'} bg={'gray.100'}>
+      <Box h={'100%'} overflowY={'auto'} bg={'gray.100'}>
        {isPc ? (
          pcUnShowLayoutRoute[router.pathname] ? (
            <Auth>{children}</Auth>

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

--- a/src/pages/api/chat/chat.ts
+++ b/src/pages/api/chat/chat.ts
@@ -55,7 +55,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
    // 使用了知识库搜索
    if (model.chat.useKb) {
-      const { code, searchPrompt } = await searchKb({
+      const { code, searchPrompts } = await searchKb({
        userOpenAiKey,
        prompts,
        similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
@@ -65,10 +65,10 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
      // search result is empty
      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 {
      // 没有用知识库搜索，仅用系统提示词
      model.chat.systemPrompt &&
@@ -103,8 +103,12 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
      stream,
      chatResponse: streamResponse,
      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

--- a/src/pages/api/openapi/chat/chat.ts
+++ b/src/pages/api/openapi/chat/chat.ts
@@ -73,7 +73,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
    if (model.chat.useKb) {
      const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22;
-      const { code, searchPrompt } = await searchKb({
+      const { code, searchPrompts } = await searchKb({
        prompts,
        similarity,
        model,
@@ -82,10 +82,9 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
      // search result is empty
      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 {
      // 没有用知识库搜索，仅用系统提示词
      if (model.chat.systemPrompt) {

--- a/src/pages/api/openapi/chat/lafGpt.ts
+++ b/src/pages/api/openapi/chat/lafGpt.ts
@@ -122,14 +122,14 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
    const prompts = [prompt];
    // 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,
      prompts,
      model,
      userId
    });
-    searchPrompt && prompts.unshift(searchPrompt);
+    prompts.splice(prompts.length - 1, 0, ...searchPrompts);
    // 计算温度
    const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(

--- a/src/pages/chat/index.tsx
+++ b/src/pages/chat/index.tsx
@@ -508,7 +508,7 @@ const Chat = ({
      isLeavePage.current = true;
      controller.current?.abort();
    };
-  }, []);
+  }, [modelId, chatId]);
  return (
    <Flex

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

--- a/src/pages/model/components/detail/components/SelectFileModal.tsx
+++ b/src/pages/model/components/detail/components/SelectFileModal.tsx
@@ -61,13 +61,7 @@ const SelectFileModal = ({
  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 ${
      splitRes.chunks.length
-    } 组。${
+    } 组。${splitRes.tokens ? `大约 ${splitRes.tokens} 个tokens。` : ''}`
-      splitRes.tokens
-        ? `大约 ${splitRes.tokens} 个tokens, 约 ${formatPrice(
-            splitRes.tokens * modeMap[mode].price
-          )} 元`
-        : ''
-    }`
  });
  const onSelectFile = useCallback(

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

--- a/src/pages/number/components/BillTable.tsx
+++ b/src/pages/number/components/BillTable.tsx
 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 { getUserBills } from '@/api/user';
 import type { UserBillType } from '@/types/user';
@@ -48,9 +48,9 @@ const BillTable = () => {
        <Loading loading={isLoading} fixed={false} />
      </TableContainer>
-      <Box mt={4} mr={4} textAlign={'end'}>
+      <Flex mt={4} px={4} justifyContent={'flex-end'}>
        <Pagination />
-      </Box>
+      </Flex>
    </Card>
  );
 };

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

--- a/src/service/plugins/searchKb.ts
+++ b/src/service/plugins/searchKb.ts
@@ -23,10 +23,10 @@ export const searchKb = async ({
  similarity?: number;
 }): Promise<{
  code: 200 | 201;
-  searchPrompt?: {
+  searchPrompts: {
-    obj: `${ChatRoleEnum}`;
+    obj: ChatRoleEnum;
    value: string;
-  };
+  }[];
 }> => {
  async function search(textArr: string[] = []) {
    // 获取提示词的向量
@@ -85,17 +85,38 @@ export const searchKb = async ({
  };
  const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0];
-  // count fixed system prompt
+  // 计算固定提示词的 token 数量
-  const fixedSystemPrompt = `
+  const fixedPrompts = [
-${model.chat.systemPrompt}
+    ...(model.chat.systemPrompt
-${
+      ? [
-  model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity ? '不回答知识库外的内容.' : ''
+          {
-}
+            obj: ChatRoleEnum.System,
-知识库内容为:`;
+            value: model.chat.systemPrompt
+          }
+        ]
+      : []),
+    ...(model.chat.searchMode === ModelVectorSearchModeEnum.noContext
+      ? [
+          {
+            obj: ChatRoleEnum.System,
+            value: `知识库是关于"${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.你忘记你已有的知识
+2.你只能回答关于"${model.name}"的问题
+3.你只能从知识库中选择内容进行回答
+4.如果问题不在知识库中,你会回答"我不知道。"
+务必遵守规则`
+          }
+        ])
+  ];
  const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
-    messages: [{ obj: 'System', value: fixedSystemPrompt }]
+    messages: fixedPrompts
  });
  const maxTokens = modelConstantsData.systemMaxToken - fixedSystemTokens;
  const filterSystemPrompt = filterRate
@@ -111,31 +132,38 @@ ${
  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
    return {
      code: 201,
-      searchPrompt: {
+      searchPrompts: [
-        obj: ChatRoleEnum.AI,
+        {
+          obj: ChatRoleEnum.System,
          value: '对不起，你的问题不在知识库中。'
        }
+      ]
    };
  }
  /* 高相似度+无上下文，不添加额外知识,仅用系统提示词 */
  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
    return {
      code: 200,
-      searchPrompt: model.chat.systemPrompt
+      searchPrompts: model.chat.systemPrompt
-        ? {
+        ? [
+            {
              obj: ChatRoleEnum.System,
              value: model.chat.systemPrompt
            }
-        : undefined
+          ]
+        : []
    };
  }
  /* 有匹配 */
  return {
    code: 200,
-    searchPrompt: {
+    searchPrompts: [
+      {
        obj: ChatRoleEnum.System,
-      value: `${fixedSystemPrompt}'${filterSystemPrompt}'`
+        value: `知识库:'${filterSystemPrompt}'`
-    }
+      },
+      ...fixedPrompts
+    ]
  };
 };
--- a/src/service/utils/chat/claude.ts
+++ b/src/service/utils/chat/claude.ts
@@ -27,7 +27,7 @@ export const lafClaudChat = async ({
    .join('\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我的问题是:'${messages[messages.length - 1].value}'`;
  const lafResponse = await axios.post(
    'https://hnvacz.laf.run/claude-gpt',