feat: limit prompt

83d755ad · archer · ec9852fc · 83d755ad · 83d755ad · 83d755ad
Commit 83d755ad authored Jun 24, 2023 by archer
10 changed files
--- a/client/src/api/response/chat.d.ts
+++ b/client/src/api/response/chat.d.ts
@@ -5,6 +5,7 @@ export interface InitChatResponse {
  chatId: string;
  modelId: string;
  systemPrompt?: string;
+  limitPrompt?: string;
  model: {
    name: string;
    avatar: string;

--- a/client/src/components/Select/index.tsx
+++ b/client/src/components/Select/index.tsx
@@ -26,7 +26,7 @@ const MySelect = ({ placeholder, value, width = 'auto', list, onchange, ...props
  return (
    <Menu autoSelect={false} onOpen={onOpen} onClose={onClose}>
-      <MenuButton as={'span'}>
+      <MenuButton style={{ width: '100%' }} as={'span'}>
        <Button
          width={width}
          px={3}

--- a/client/src/constants/model.ts
+++ b/client/src/constants/model.ts
@@ -82,6 +82,7 @@ export const defaultModel: ModelSchema = {
    searchLimit: 5,
    searchEmptyText: '',
    systemPrompt: '',
+    limitPrompt: '',
    temperature: 0,
    maxToken: 4000,
    chatModel: OpenAiChatEnum.GPT35

--- a/client/src/pages/api/chat/init.ts
+++ b/client/src/pages/api/chat/init.ts
@@ -101,6 +101,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
        },
        chatModel: model.chat.chatModel,
        systemPrompt: isOwner ? model.chat.systemPrompt : '',
+        limitPrompt: isOwner ? model.chat.limitPrompt : '',
        history
      }
    });

--- a/client/src/pages/api/openapi/kb/appKbSearch.ts
+++ b/client/src/pages/api/openapi/kb/appKbSearch.ts
@@ -28,7 +28,11 @@ type Response = {
  userSystemPrompt: {
    obj: ChatRoleEnum;
    value: string;
-  };
+  }[];
+  userLimitPrompt: {
+    obj: ChatRoleEnum;
+    value: string;
+  }[];
  quotePrompt: {
    obj: ChatRoleEnum;
    value: string;
@@ -130,17 +134,24 @@ export async function appKbSearch({
  // 计算固定提示词的 token 数量
  const userSystemPrompt = model.chat.systemPrompt // user system prompt
-    ? {
+    ? [
-        obj: ChatRoleEnum.Human,
+        {
-        value: model.chat.systemPrompt
+          obj: ChatRoleEnum.System,
-      }
+          value: model.chat.systemPrompt
-    : {
+        }
-        obj: ChatRoleEnum.Human,
+      ]
-        value: `知识库是关于 ${model.name} 的内容，参考知识库回答问题。与 "${model.name}" 无关内容，直接回复: "我不知道"。`
+    : [];
-      };
+  const userLimitPrompt = [
+    {
+      obj: ChatRoleEnum.Human,
+      value: model.chat.limitPrompt
+        ? model.chat.limitPrompt
+        : `知识库是关于 ${model.name} 的内容，参考知识库回答问题。与 "${model.name}" 无关内容，直接回复: "我不知道"。`
+    }
+  ];
  const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
-    messages: [userSystemPrompt]
+    messages: [...userSystemPrompt, ...userLimitPrompt]
  });
  // filter part quote by maxToken
@@ -164,6 +175,7 @@ export async function appKbSearch({
  return {
    rawSearch,
    userSystemPrompt,
+    userLimitPrompt,
    quotePrompt: {
      obj: ChatRoleEnum.System,
      value: quoteText

--- a/client/src/pages/api/openapi/v1/chat/completions.ts
+++ b/client/src/pages/api/openapi/v1/chat/completions.ts
@@ -108,11 +108,12 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
    const {
      rawSearch = [],
      userSystemPrompt = [],
+      userLimitPrompt = [],
      quotePrompt = []
    } = await (async () => {
      // 使用了知识库搜索
      if (model.chat.relatedKbs?.length > 0) {
-        const { rawSearch, userSystemPrompt, quotePrompt } = await appKbSearch({
+        const { rawSearch, quotePrompt, userSystemPrompt, userLimitPrompt } = await appKbSearch({
          model,
          userId,
          fixedQuote: history[history.length - 1]?.quote,
@@ -123,21 +124,29 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
        return {
          rawSearch,
-          userSystemPrompt: userSystemPrompt ? [userSystemPrompt] : [],
+          userSystemPrompt,
+          userLimitPrompt,
          quotePrompt: [quotePrompt]
        };
      }
-      if (model.chat.systemPrompt) {
+      return {
-        return {
+        userSystemPrompt: model.chat.systemPrompt
-          userSystemPrompt: [
+          ? [
-            {
+              {
-              obj: ChatRoleEnum.System,
+                obj: ChatRoleEnum.System,
-              value: model.chat.systemPrompt
+                value: model.chat.systemPrompt
-            }
+              }
-          ]
+            ]
-        };
+          : [],
-      }
+        userLimitPrompt: model.chat.limitPrompt
-      return {};
+          ? [
+              {
+                obj: ChatRoleEnum.Human,
+                value: model.chat.limitPrompt
+              }
+            ]
+          : []
+      };
    })();
    // search result is empty
@@ -167,7 +176,13 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
    }
    // api messages. [quote,context,systemPrompt,question]
-    const completePrompts = [...quotePrompt, ...prompts.slice(0, -1), ...userSystemPrompt, prompt];
+    const completePrompts = [
+      ...quotePrompt,
+      ...userSystemPrompt,
+      ...prompts.slice(0, -1),
+      ...userLimitPrompt,
+      prompt
+    ];
    // chat temperature
    const modelConstantsData = ChatModelMap[model.chat.chatModel];
    // FastGpt temperature range: 1~10
@@ -176,7 +191,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
    );
    await sensitiveCheck({
-      input: `${prompt.value}`
+      input: `${userSystemPrompt[0]?.value}\n${userLimitPrompt[0]?.value}\n${prompt.value}`
    });
    // start model api. responseText and totalTokens: valid only if stream = false
@@ -259,7 +274,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
            ...(showAppDetail
              ? {
                  quote: rawSearch,
-                  systemPrompt: userSystemPrompt?.[0]?.value
+                  systemPrompt: `${userSystemPrompt[0]?.value}\n\n${userLimitPrompt[0]?.value}`
                }
              : {})
          }

--- a/client/src/pages/chat/index.tsx
+++ b/client/src/pages/chat/index.tsx
@@ -219,7 +219,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
            ...item,
            status: 'finish',
            quoteLen,
-            systemPrompt: chatData.systemPrompt
+            systemPrompt: `${chatData.systemPrompt}\n\n${chatData.limitPrompt}`
          };
        })
      }));
@@ -234,13 +234,14 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
    [
      chatId,
      modelId,
-      chatData.systemPrompt,
      setChatData,
-      loadHistory,
-      loadMyModels,
      generatingMessage,
      setForbidLoadChatData,
-      router
+      router,
+      chatData.systemPrompt,
+      chatData.limitPrompt,
+      loadHistory,
+      loadMyModels
    ]
  );
@@ -749,7 +750,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
                                px={[2, 4]}
                                onClick={() => setShowSystemPrompt(item.systemPrompt || '')}
                              >
-                                提示词
+                                提示词 & 限定词
                              </Button>
                            )}
                            {!!item.quoteLen && (

--- a/client/src/pages/model/components/detail/components/Settings.tsx
+++ b/client/src/pages/model/components/detail/components/Settings.tsx
 import React, { useCallback, useState, useMemo } from 'react';
-import { Box, Flex, Button, FormControl, Input, Textarea, Divider } from '@chakra-ui/react';
+import {
+  Box,
+  Flex,
+  Button,
+  FormControl,
+  Input,
+  Textarea,
+  Divider,
+  Tooltip
+} from '@chakra-ui/react';
+import { QuestionOutlineIcon } from '@chakra-ui/icons';
 import { useQuery } from '@tanstack/react-query';
 import { useForm } from 'react-hook-form';
 import { useRouter } from 'next/router';
@@ -20,6 +30,11 @@ import Avatar from '@/components/Avatar';
 import MySelect from '@/components/Select';
 import MySlider from '@/components/Slider';
+const systemPromptTip =
+  '模型固定的引导词，通过调整该内容，可以引导模型聊天方向。该内容会被固定在上下文的开头。';
+const limitPromptTip =
+  '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。例如:\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"';
 const Settings = ({ modelId }: { modelId: string }) => {
  const { toast } = useToast();
  const router = useRouter();
@@ -60,7 +75,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
    }
    return max;
-  }, [getValues, setValue, refresh]);
+  }, [getValues, setValue]);
  // 提交保存模型修改
  const saveSubmitSuccess = useCallback(
@@ -211,7 +226,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
          介绍
        </Box>
        <Textarea
-          rows={5}
+          rows={4}
          maxLength={500}
          placeholder={'给你的 AI 应用一个介绍'}
          {...register('intro')}
@@ -225,11 +240,14 @@ const Settings = ({ modelId }: { modelId: string }) => {
          对话模型
        </Box>
        <MySelect
-          width={['200px', '240px']}
+          width={['100%', '280px']}
          value={getValues('chat.chatModel')}
          list={chatModelList.map((item) => ({
            id: item.chatModel,
-            label: item.name
+            label: `${item.name} (${formatPrice(
+              ChatModelMap[getValues('chat.chatModel')]?.price,
+              1000
+            )} 元/1k tokens)`
          }))}
          onchange={(val: any) => {
            setValue('chat.chatModel', val);
@@ -237,15 +255,6 @@ const Settings = ({ modelId }: { modelId: string }) => {
          }}
        />
      </Flex>
-      <Flex alignItems={'center'} mt={5}>
-        <Box w={['60px', '100px', '140px']} flexShrink={0}>
-          价格
-        </Box>
-        <Box fontSize={['sm', 'md']}>
-          {formatPrice(ChatModelMap[getValues('chat.chatModel')]?.price, 1000)}
-          元/1K tokens(包括上下文和回答)
-        </Box>
-      </Flex>
      <Flex alignItems={'center'} my={10}>
        <Box w={['60px', '100px', '140px']} flexShrink={0}>
          温度
@@ -269,7 +278,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
      </Flex>
      <Flex alignItems={'center'} mt={12} mb={10}>
        <Box w={['60px', '100px', '140px']} flexShrink={0}>
-          最大长度
+          回复上限
        </Box>
        <Box flex={1} ml={'10px'}>
          <MySlider
@@ -292,15 +301,29 @@ const Settings = ({ modelId }: { modelId: string }) => {
      <Flex mt={10} alignItems={'flex-start'}>
        <Box w={['60px', '100px', '140px']} flexShrink={0}>
          提示词
+          <Tooltip label={systemPromptTip}>
+            <QuestionOutlineIcon display={['none', 'inline']} ml={1} />
+          </Tooltip>
        </Box>
        <Textarea
          rows={8}
-          placeholder={
+          placeholder={systemPromptTip}
-            '模型默认的 prompt 词，通过调整该内容，可以引导模型聊天方向。\n\n如果使用了知识库搜索，没有填写该内容时，系统会自动补充提示词；如果填写了内容，则以填写的内容为准。'
-          }
          {...register('chat.systemPrompt')}
        ></Textarea>
      </Flex>
+      <Flex mt={5} alignItems={'flex-start'}>
+        <Box w={['60px', '100px', '140px']} flexShrink={0}>
+          限定词
+          <Tooltip label={limitPromptTip}>
+            <QuestionOutlineIcon display={['none', 'inline']} ml={1} />
+          </Tooltip>
+        </Box>
+        <Textarea
+          rows={5}
+          placeholder={limitPromptTip}
+          {...register('chat.limitPrompt')}
+        ></Textarea>
+      </Flex>
      <Flex mt={5} alignItems={'center'}>
        <Box w={['60px', '100px', '140px']} flexShrink={0}></Box>

--- a/client/src/service/models/model.ts
+++ b/client/src/service/models/model.ts
@@ -43,7 +43,10 @@ const ModelSchema = new Schema({
      default: ''
    },
    systemPrompt: {
-      // 系统提示词
+      type: String,
+      default: ''
+    },
+    limitPrompt: {
      type: String,
      default: ''
    },

--- a/client/src/types/mongoSchema.d.ts
+++ b/client/src/types/mongoSchema.d.ts
@@ -43,6 +43,7 @@ export interface ModelSchema {
    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