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perf: chat上下文截断;QA提示词

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This commit is contained in:
archer
2023-04-21 23:30:26 +08:00
parent 4397a0ad6b
commit 3ea2cf1dcb
10 changed files with 63 additions and 34 deletions
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2
src/constants/model.ts
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@@ -35,7 +35,7 @@ export const modelList: ModelConstantsData[] = [
model: ChatModelNameEnum.GPT35,
trainName: '',
maxToken: 4000,
contextMaxToken: 7500,
contextMaxToken: 7000,
maxTemperature: 1.5,
price: 3
},

25
src/pages/api/chat/chatGpt.ts
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@@ -61,7 +61,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}
// 控制在 tokens 数量，防止超出
// const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
// 格式化文本内容成 chatgpt 格式
const map = {
@@ -69,14 +69,25 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
AI: ChatCompletionRequestMessageRoleEnum.Assistant,
SYSTEM: ChatCompletionRequestMessageRoleEnum.System
};
const formatPrompts: ChatCompletionRequestMessage[] = prompts.map((item: ChatItemType) => ({
role: map[item.obj],
content: item.value
}));
// console.log(formatPrompts);
const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
(item: ChatItemType) => ({
role: map[item.obj],
content: item.value
})
);
// 计算温度
const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
// console.log({
// model: model.service.chatModel,
// temperature: temperature,
// // max_tokens: modelConstantsData.maxToken,
// messages: formatPrompts,
// frequency_penalty: 0.5, // 越大，重复内容越少
// presence_penalty: -0.5, // 越大，越容易出现新内容
// stream: true,
// stop: ['.!?。']
// });
// 获取 chatAPI
const chatAPI = getOpenAIApi(userApiKey || systemKey);
// 发出请求

16
src/pages/api/chat/vectorGpt.ts
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@@ -1,7 +1,7 @@
import type { NextApiRequest, NextApiResponse } from 'next';
import { connectToDatabase } from '@/service/mongo';
import { authChat } from '@/service/utils/chat';
import { httpsAgent, systemPromptFilter } from '@/service/utils/tools';
import { httpsAgent, systemPromptFilter, openaiChatFilter } from '@/service/utils/tools';
import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
import { ChatItemType } from '@/types/chat';
import { jsonRes } from '@/service/response';
@@ -79,7 +79,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
`vector <=> '[${promptVector}]' < ${similarity}`
],
order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
limit: 30
limit: 20
});
const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
@@ -116,7 +116,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}
// 控制在 tokens 数量，防止超出
// const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
// 格式化文本内容成 chatgpt 格式
const map = {
@@ -124,10 +124,12 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
AI: ChatCompletionRequestMessageRoleEnum.Assistant,
SYSTEM: ChatCompletionRequestMessageRoleEnum.System
};
const formatPrompts: ChatCompletionRequestMessage[] = prompts.map((item: ChatItemType) => ({
role: map[item.obj],
content: item.value
}));
const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
(item: ChatItemType) => ({
role: map[item.obj],
content: item.value
})
);
// console.log(formatPrompts);
// 计算温度
const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);

4
src/pages/api/model/data/splitData.ts
View File

@@ -41,11 +41,11 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const tokens = encode(splitText + chunk).length;
if (tokens >= 4000) {
// 超过 4000，不要这块内容
textList.push(splitText);
splitText && textList.push(splitText);
splitText = chunk;
} else if (tokens >= 3000) {
// 超过 3000，取内容
textList.push(splitText + chunk);
splitText && textList.push(splitText + chunk);
splitText = '';
} else {
//没超过 3000，继续添加

13
src/pages/api/openapi/chat/chatGpt.ts
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@@ -74,16 +74,21 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
});
}
// 控制在 tokens 数量，防止超出
const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
// 格式化文本内容成 chatgpt 格式
const map = {
Human: ChatCompletionRequestMessageRoleEnum.User,
AI: ChatCompletionRequestMessageRoleEnum.Assistant,
SYSTEM: ChatCompletionRequestMessageRoleEnum.System
};
const formatPrompts: ChatCompletionRequestMessage[] = prompts.map((item: ChatItemType) => ({
role: map[item.obj],
content: item.value
}));
const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
(item: ChatItemType) => ({
role: map[item.obj],
content: item.value
})
);
// console.log(formatPrompts);
// 计算温度
const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);

22
src/pages/api/openapi/chat/vectorGpt.ts
View File

@@ -1,6 +1,11 @@
import type { NextApiRequest, NextApiResponse } from 'next';
import { connectToDatabase, Model } from '@/service/mongo';
import { httpsAgent, systemPromptFilter, authOpenApiKey } from '@/service/utils/tools';
import {
httpsAgent,
systemPromptFilter,
authOpenApiKey,
openaiChatFilter
} from '@/service/utils/tools';
import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
import { ChatItemType } from '@/types/chat';
import { jsonRes } from '@/service/response';
@@ -93,7 +98,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
`vector <=> '[${promptVector}]' < ${similarity}`
],
order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
limit: 30
limit: 20
});
const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
@@ -134,16 +139,21 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
});
}
// 控制在 tokens 数量，防止超出
const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);
// 格式化文本内容成 chatgpt 格式
const map = {
Human: ChatCompletionRequestMessageRoleEnum.User,
AI: ChatCompletionRequestMessageRoleEnum.Assistant,
SYSTEM: ChatCompletionRequestMessageRoleEnum.System
};
const formatPrompts: ChatCompletionRequestMessage[] = prompts.map((item: ChatItemType) => ({
role: map[item.obj],
content: item.value
}));
const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
(item: ChatItemType) => ({
role: map[item.obj],
content: item.value
})
);
// console.log(formatPrompts);
// 计算温度
const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);

2
src/pages/chat/index.tsx
View File

@@ -88,7 +88,7 @@ const Chat = ({ chatId }: { chatId: string }) => {
throttle(() => {
if (!ChatBox.current) return;
const isBottom =
ChatBox.current.scrollTop + ChatBox.current.clientHeight + 80 >=
ChatBox.current.scrollTop + ChatBox.current.clientHeight + 150 >=
ChatBox.current.scrollHeight;
isBottom && scrollToBottom('auto');

2
src/pages/model/detail/components/SelectFileModal.tsx
View File

@@ -86,7 +86,7 @@ const SelectFileModal = ({
await postModelDataSplitData({
modelId,
text: fileText.replace(/\\n/g, '\n').replace(/\n+/g, '\n'),
prompt: `下面是${prompt || '一段长文本'}`
prompt: `下面是"${prompt || '一段长文本'}"`
});
toast({
title: '导入数据成功,需要一段拆解和训练',

2
src/pages/model/detail/components/SelectUrlModal.tsx
View File

@@ -45,7 +45,7 @@ const SelectUrlModal = ({
await postModelDataSplitData({
modelId,
text: webText,
prompt: `下面是${prompt || '一段长文本'}`
prompt: `下面是"${prompt || '一段长文本'}"`
});
toast({
title: '导入数据成功,需要一段拆解和训练',

9
src/service/events/generateQA.ts
View File

@@ -69,9 +69,9 @@ export async function generateQA(next = false): Promise<any> {
const chatAPI = getOpenAIApi(userApiKey || systemKey);
const systemPrompt: ChatCompletionRequestMessage = {
role: 'system',
content: `${
dataItem.prompt || '下面是一段长文本'
},请从中提取出5至30个问题和答案,并按以下格式返回: Q1:\nA1:\nQ2:\nA2:\n`
content: `你是出题官.${
dataItem.prompt || '下面是"一段长文本"'
},从中选出5至20个题目和答案,题目包含问答题,计算题,代码题等.答案要详细.按格式返回: Q1:\nA1:\nQ2:\nA2:\n`
};
// 请求 chatgpt 获取回答
@@ -114,7 +114,8 @@ export async function generateQA(next = false): Promise<any> {
};
})
.catch((err) => {
console.log('QA 拆分错误', err);
console.log('QA拆分错误');
console.log(err.response?.status, err.response?.statusText, err.response?.data);
return Promise.reject(err);
})
)