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Commit 944e876a by archer
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feat: chat quote

parent ee2c259c
Showing with 932 additions and 659 deletions
src/api/chat.ts
import { GET, POST, DELETE } from './request'; import { GET, POST, DELETE } from './request';
import type { ChatItemType, HistoryItemType } from '@/types/chat'; import type { HistoryItemType } from '@/types/chat';
import type { InitChatResponse, InitShareChatResponse } from './response/chat'; import type { InitChatResponse, InitShareChatResponse } from './response/chat';
import { RequestPaging } from '../types/index'; import { RequestPaging } from '../types/index';
import type { ShareChatSchema } from '@/types/mongoSchema'; import type { ShareChatSchema } from '@/types/mongoSchema';
import type { ShareChatEditType } from '@/types/model'; import type { ShareChatEditType } from '@/types/model';
import { Obj2Query } from '@/utils/tools'; import { Obj2Query } from '@/utils/tools';
import { Response as LastChatResultResponseType } from '@/pages/api/openapi/chat/lastChatResult';
/** /**
* 获取初始化聊天内容 * 获取初始化聊天内容
...@@ -24,15 +25,10 @@ export const getChatHistory = (data: RequestPaging) => ...@@ -24,15 +25,10 @@ export const getChatHistory = (data: RequestPaging) =>
export const delChatHistoryById = (id: string) => GET(`/chat/removeHistory?id=${id}`); export const delChatHistoryById = (id: string) => GET(`/chat/removeHistory?id=${id}`);
/** /**
* 存储一轮对话 * get latest chat result by chatId
*/ */
export const postSaveChat = (data: { export const getChatResult = (chatId: string) =>
modelId: string; GET<LastChatResultResponseType>('/openapi/chat/lastChatResult', { chatId });
newChatId: '' | string;
chatId: '' | string;
prompts: [ChatItemType, ChatItemType];
}) => POST<string>('/chat/saveChat', data);
/** /**
* 删除一句对话 * 删除一句对话
*/ */
......
src/api/fetch.ts
import { SYSTEM_PROMPT_HEADER, NEW_CHATID_HEADER } from '@/constants/chat'; import { NEW_CHATID_HEADER } from '@/constants/chat';
interface StreamFetchProps { interface StreamFetchProps {
url: string; url: string;
...@@ -7,55 +7,52 @@ interface StreamFetchProps { ...@@ -7,55 +7,52 @@ interface StreamFetchProps {
abortSignal: AbortController; abortSignal: AbortController;
} }
export const streamFetch = ({ url, data, onMessage, abortSignal }: StreamFetchProps) => export const streamFetch = ({ url, data, onMessage, abortSignal }: StreamFetchProps) =>
new Promise<{ responseText: string; systemPrompt: string; newChatId: string }>( new Promise<{ responseText: string; newChatId: string }>(async (resolve, reject) => {
async (resolve, reject) => { try {
try { const res = await fetch(url, {
const res = await fetch(url, { method: 'POST',
method: 'POST', headers: {
headers: { 'Content-Type': 'application/json'
'Content-Type': 'application/json' },
}, body: JSON.stringify(data),
body: JSON.stringify(data), signal: abortSignal.signal
signal: abortSignal.signal });
}); const reader = res.body?.getReader();
const reader = res.body?.getReader(); if (!reader) return;
if (!reader) return;
const decoder = new TextDecoder(); const decoder = new TextDecoder();
const systemPrompt = decodeURIComponent(res.headers.get(SYSTEM_PROMPT_HEADER) || '').trim(); const newChatId = decodeURIComponent(res.headers.get(NEW_CHATID_HEADER) || '');
const newChatId = decodeURIComponent(res.headers.get(NEW_CHATID_HEADER) || '');
let responseText = ''; let responseText = '';
const read = async () => { const read = async () => {
try { try {
const { done, value } = await reader?.read(); const { done, value } = await reader?.read();
if (done) { if (done) {
if (res.status === 200) { if (res.status === 200) {
resolve({ responseText, systemPrompt, newChatId }); resolve({ responseText, newChatId });
} else { } else {
const parseError = JSON.parse(responseText); const parseError = JSON.parse(responseText);
reject(parseError?.message || '请求异常'); reject(parseError?.message || '请求异常');
}
return;
}
const text = decoder.decode(value);
responseText += text;
onMessage(text);
read();
} catch (err: any) {
if (err?.message === 'The user aborted a request.') {
return resolve({ responseText, systemPrompt, newChatId });
} }
reject(typeof err === 'string' ? err : err?.message || '请求异常');
return;
}
const text = decoder.decode(value);
responseText += text;
onMessage(text);
read();
} catch (err: any) {
if (err?.message === 'The user aborted a request.') {
return resolve({ responseText, newChatId });
} }
}; reject(typeof err === 'string' ? err : err?.message || '请求异常');
read(); }
} catch (err: any) { };
console.log(err, '===='); read();
reject(typeof err === 'string' ? err : err?.message || '请求异常'); } catch (err: any) {
} console.log(err, '====');
reject(typeof err === 'string' ? err : err?.message || '请求异常');
} }
); });
src/constants/chat.ts
export const SYSTEM_PROMPT_HEADER = 'System-Prompt-Header'; export const NEW_CHATID_HEADER = 'response-new-chat-id';
export const NEW_CHATID_HEADER = 'Chat-Id-Header';
export enum ChatRoleEnum { export enum ChatRoleEnum {
System = 'System', System = 'System',
......
src/pages/_app.tsx
...@@ -55,7 +55,7 @@ export default function App({ Component, pageProps }: AppProps) { ...@@ -55,7 +55,7 @@ export default function App({ Component, pageProps }: AppProps) {
<Script src="/js/qrcode.min.js" strategy="lazyOnload"></Script> <Script src="/js/qrcode.min.js" strategy="lazyOnload"></Script>
<Script src="/js/pdf.js" strategy="lazyOnload"></Script> <Script src="/js/pdf.js" strategy="lazyOnload"></Script>
<Script src="/js/html2pdf.bundle.min.js" strategy="lazyOnload"></Script> <Script src="/js/html2pdf.bundle.min.js" strategy="lazyOnload"></Script>
<Script src="/js/particles.js" strategy="lazyOnload"></Script> <Script src="/js/particles.js"></Script>
<QueryClientProvider client={queryClient}> <QueryClientProvider client={queryClient}>
<ChakraProvider theme={theme}> <ChakraProvider theme={theme}>
<ColorModeScript initialColorMode={theme.config.initialColorMode} /> <ColorModeScript initialColorMode={theme.config.initialColorMode} />
......
src/pages/api/chat/chat.ts
...@@ -2,19 +2,24 @@ import type { NextApiRequest, NextApiResponse } from 'next'; ...@@ -2,19 +2,24 @@ import type { NextApiRequest, NextApiResponse } from 'next';
import { connectToDatabase } from '@/service/mongo'; import { connectToDatabase } from '@/service/mongo';
import { authChat } from '@/service/utils/auth'; import { authChat } from '@/service/utils/auth';
import { modelServiceToolMap } from '@/service/utils/chat'; import { modelServiceToolMap } from '@/service/utils/chat';
import { ChatItemSimpleType } from '@/types/chat'; import { ChatItemType } from '@/types/chat';
import { jsonRes } from '@/service/response'; import { jsonRes } from '@/service/response';
import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model'; import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
import { pushChatBill } from '@/service/events/pushBill'; import { pushChatBill } from '@/service/events/pushBill';
import { resStreamResponse } from '@/service/utils/chat'; import { resStreamResponse } from '@/service/utils/chat';
import { searchKb } from '@/service/plugins/searchKb'; import { appKbSearch } from '../openapi/kb/appKbSearch';
import { ChatRoleEnum } from '@/constants/chat'; import { ChatRoleEnum } from '@/constants/chat';
import { BillTypeEnum } from '@/constants/user'; import { BillTypeEnum } from '@/constants/user';
import { sensitiveCheck } from '@/service/api/text'; import { sensitiveCheck } from '@/service/api/text';
import { NEW_CHATID_HEADER } from '@/constants/chat';
import { saveChat } from './saveChat';
import { Types } from 'mongoose';
/* 发送提示词 */ /* 发送提示词 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) { export default async function handler(req: NextApiRequest, res: NextApiResponse) {
let step = 0; // step=1时，表示开始了流响应 res.on('close', () => {
res.end();
});
res.on('error', () => { res.on('error', () => {
console.log('error: ', 'request error'); console.log('error: ', 'request error');
res.end(); res.end();
...@@ -22,9 +27,9 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -22,9 +27,9 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
try { try {
const { chatId, prompt, modelId } = req.body as { const { chatId, prompt, modelId } = req.body as {
prompt: ChatItemSimpleType; prompt: [ChatItemType, ChatItemType];
modelId: string; modelId: string;
chatId: '' | string; chatId?: string;
}; };
if (!modelId || !prompt) { if (!modelId || !prompt) {
...@@ -44,42 +49,69 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -44,42 +49,69 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const modelConstantsData = ChatModelMap[model.chat.chatModel]; const modelConstantsData = ChatModelMap[model.chat.chatModel];
// 读取对话内容 // 读取对话内容
const prompts = [...content, prompt]; const prompts = [...content, prompt[0]];
let systemPrompts: { const {
obj: ChatRoleEnum; code = 200,
value: string; systemPrompts = [],
}[] = []; quote = []
} = await (async () => {
// 使用了知识库搜索 // 使用了知识库搜索
if (model.chat.relatedKbs.length > 0) { if (model.chat.relatedKbs.length > 0) {
const { code, searchPrompts } = await searchKb({ const { code, searchPrompts, rawSearch } = await appKbSearch({
userOpenAiKey, model,
prompts, userId,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity, prompts,
model, similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity
userId });
});
return {
// search result is empty code,
if (code === 201) { quote: rawSearch,
return res.send(searchPrompts[0]?.value); systemPrompts: searchPrompts
};
}
if (model.chat.systemPrompt) {
return {
systemPrompts: [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
]
};
} }
return {};
})();
// get conversationId. create a newId if it is null
const conversationId = chatId || String(new Types.ObjectId());
!chatId && res?.setHeader(NEW_CHATID_HEADER, conversationId);
systemPrompts = searchPrompts; // search result is empty
} else if (model.chat.systemPrompt) { if (code === 201) {
systemPrompts = [ const response = systemPrompts[0]?.value;
{ await saveChat({
obj: ChatRoleEnum.System, chatId,
value: model.chat.systemPrompt newChatId: conversationId,
} modelId,
]; prompts: [
prompt[0],
{
...prompt[1],
quote: [],
value: response
}
],
userId
});
return res.end(response);
} }
prompts.splice(prompts.length - 3, 0, ...systemPrompts); prompts.splice(prompts.length - 3, 0, ...systemPrompts);
// content check // content check
await sensitiveCheck({ await sensitiveCheck({
input: [...systemPrompts, prompt].map((item) => item.value).join('') input: [...systemPrompts, prompt[0]].map((item) => item.value).join('')
}); });
// 计算温度 // 计算温度
...@@ -87,54 +119,65 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -87,54 +119,65 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
2 2
); );
// 发出请求 // 发出 chat 请求
const { streamResponse } = await modelServiceToolMap[model.chat.chatModel].chatCompletion({ const { streamResponse } = await modelServiceToolMap[model.chat.chatModel].chatCompletion({
apiKey: userOpenAiKey || systemAuthKey, apiKey: userOpenAiKey || systemAuthKey,
temperature: +temperature, temperature: +temperature,
messages: prompts, messages: prompts,
stream: true, stream: true,
res, res,
chatId chatId: conversationId
}); });
console.log('api response time:', `${(Date.now() - startTime) / 1000}s`); console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
step = 1; if (res.closed) return res.end();
const { totalTokens, finishMessages } = await resStreamResponse({ try {
model: model.chat.chatModel, const { totalTokens, finishMessages, responseContent } = await resStreamResponse({
res, model: model.chat.chatModel,
chatResponse: streamResponse, res,
prompts, chatResponse: streamResponse,
systemPrompt: showModelDetail prompts
? prompts });
.filter((item) => item.obj === ChatRoleEnum.System)
.map((item) => item.value) // save chat
.join('\n') await saveChat({
: '' chatId,
}); newChatId: conversationId,
modelId,
prompts: [
prompt[0],
{
...prompt[1],
quote: showModelDetail ? quote : [],
value: responseContent
}
],
userId
});
// 只有使用平台的 key 才计费
pushChatBill({
isPay: !userOpenAiKey,
chatModel: model.chat.chatModel,
userId,
chatId,
textLen: finishMessages.map((item) => item.value).join('').length,
tokens: totalTokens,
type: BillTypeEnum.chat
});
} catch (err: any) {
if (step === 1) {
// 直接结束流
res.end(); res.end();
console.log('error，结束');
} else { // 只有使用平台的 key 才计费
res.status(500); pushChatBill({
jsonRes(res, { isPay: !userOpenAiKey,
code: 500, chatModel: model.chat.chatModel,
error: err userId,
chatId: conversationId,
textLen: finishMessages.map((item) => item.value).join('').length,
tokens: totalTokens,
type: BillTypeEnum.chat
}); });
} catch (error) {
res.end();
console.log('error，结束', error);
} }
} catch (err: any) {
res.status(500);
jsonRes(res, {
code: 500,
error: err
});
} }
} }
src/pages/api/chat/init.ts
...@@ -73,7 +73,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -73,7 +73,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
_id: '$content._id', _id: '$content._id',
obj: '$content.obj', obj: '$content.obj',
value: '$content.value', value: '$content.value',
systemPrompt: '$content.systemPrompt' quote: '$content.quote'
} }
} }
]); ]);
......
src/pages/api/chat/saveChat.ts
...@@ -6,15 +6,17 @@ import { authModel } from '@/service/utils/auth'; ...@@ -6,15 +6,17 @@ import { authModel } from '@/service/utils/auth';
import { authUser } from '@/service/utils/auth'; import { authUser } from '@/service/utils/auth';
import mongoose from 'mongoose'; import mongoose from 'mongoose';
type Props = {
newChatId?: string;
chatId?: string;
modelId: string;
prompts: [ChatItemType, ChatItemType];
};
/* 聊天内容存存储 */ /* 聊天内容存存储 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) { export default async function handler(req: NextApiRequest, res: NextApiResponse) {
try { try {
const { chatId, modelId, prompts, newChatId } = req.body as { const { chatId, modelId, prompts, newChatId } = req.body as Props;
newChatId: '' | string;
chatId: '' | string;
modelId: string;
prompts: [ChatItemType, ChatItemType];
};
if (!prompts) { if (!prompts) {
throw new Error('缺少参数'); throw new Error('缺少参数');
...@@ -22,44 +24,17 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -22,44 +24,17 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const { userId } = await authUser({ req, authToken: true }); const { userId } = await authUser({ req, authToken: true });
await connectToDatabase(); const nId = await saveChat({
chatId,
const content = prompts.map((item) => ({ modelId,
_id: new mongoose.Types.ObjectId(item._id), prompts,
obj: item.obj, newChatId,
value: item.value, userId
systemPrompt: item.systemPrompt });
}));
await authModel({ modelId, userId, authOwner: false });
// 没有 chatId, 创建一个对话 jsonRes(res, {
if (!chatId) { data: nId
const { _id } = await Chat.create({ });
_id: newChatId ? new mongoose.Types.ObjectId(newChatId) : undefined,
userId,
modelId,
content,
title: content[0].value.slice(0, 20),
latestChat: content[1].value
});
return jsonRes(res, {
data: _id
});
} else {
// 已经有记录，追加入库
await Chat.findByIdAndUpdate(chatId, {
$push: {
content: {
$each: content
}
},
title: content[0].value.slice(0, 20),
latestChat: content[1].value,
updateTime: new Date()
});
}
jsonRes(res);
} catch (err) { } catch (err) {
jsonRes(res, { jsonRes(res, {
code: 500, code: 500,
...@@ -67,3 +42,46 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -67,3 +42,46 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}); });
} }
} }
export async function saveChat({
chatId,
newChatId,
modelId,
prompts,
userId
}: Props & { userId: string }) {
await connectToDatabase();
await authModel({ modelId, userId, authOwner: false });
const content = prompts.map((item) => ({
_id: item._id ? new mongoose.Types.ObjectId(item._id) : undefined,
obj: item.obj,
value: item.value,
quote: item.quote
}));
// 没有 chatId, 创建一个对话
if (!chatId) {
const { _id } = await Chat.create({
_id: newChatId ? new mongoose.Types.ObjectId(newChatId) : undefined,
userId,
modelId,
content,
title: content[0].value.slice(0, 20),
latestChat: content[1].value
});
return _id;
} else {
// 已经有记录，追加入库
await Chat.findByIdAndUpdate(chatId, {
$push: {
content: {
$each: content
}
},
title: content[0].value.slice(0, 20),
latestChat: content[1].value,
updateTime: new Date()
});
}
}
src/pages/api/chat/shareChat/chat.ts
...@@ -7,14 +7,13 @@ import { jsonRes } from '@/service/response'; ...@@ -7,14 +7,13 @@ import { jsonRes } from '@/service/response';
import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model'; import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
import { pushChatBill, updateShareChatBill } from '@/service/events/pushBill'; import { pushChatBill, updateShareChatBill } from '@/service/events/pushBill';
import { resStreamResponse } from '@/service/utils/chat'; import { resStreamResponse } from '@/service/utils/chat';
import { searchKb } from '@/service/plugins/searchKb';
import { ChatRoleEnum } from '@/constants/chat'; import { ChatRoleEnum } from '@/constants/chat';
import { BillTypeEnum } from '@/constants/user'; import { BillTypeEnum } from '@/constants/user';
import { sensitiveCheck } from '@/service/api/text'; import { sensitiveCheck } from '@/service/api/text';
import { appKbSearch } from '../../openapi/kb/appKbSearch';
/* 发送提示词 */ /* 发送提示词 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) { export default async function handler(req: NextApiRequest, res: NextApiResponse) {
let step = 0; // step=1 时，表示开始了流响应
res.on('error', () => { res.on('error', () => {
console.log('error: ', 'request error'); console.log('error: ', 'request error');
res.end(); res.end();
...@@ -42,34 +41,37 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -42,34 +41,37 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const modelConstantsData = ChatModelMap[model.chat.chatModel]; const modelConstantsData = ChatModelMap[model.chat.chatModel];
let systemPrompts: { const { code = 200, systemPrompts = [] } = await (async () => {
obj: ChatRoleEnum; // 使用了知识库搜索
value: string; if (model.chat.relatedKbs.length > 0) {
}[] = []; const { code, searchPrompts } = await appKbSearch({
model,
// 使用了知识库搜索 userId,
if (model.chat.relatedKbs.length > 0) { prompts,
const { code, searchPrompts } = await searchKb({ similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity
userOpenAiKey, });
prompts,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity, return {
model, code,
userId systemPrompts: searchPrompts
}); };
// search result is empty
if (code === 201) {
return res.send(searchPrompts[0]?.value);
} }
if (model.chat.systemPrompt) {
return {
systemPrompts: [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
]
};
}
return {};
})();
systemPrompts = searchPrompts; // search result is empty
} else if (model.chat.systemPrompt) { if (code === 201) {
systemPrompts = [ return res.send(systemPrompts[0]?.value);
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
];
} }
prompts.splice(prompts.length - 3, 0, ...systemPrompts); prompts.splice(prompts.length - 3, 0, ...systemPrompts);
...@@ -96,40 +98,40 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse) ...@@ -96,40 +98,40 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
console.log('api response time:', `${(Date.now() - startTime) / 1000}s`); console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
step = 1; if (res.closed) return res.end();
const { totalTokens, finishMessages } = await resStreamResponse({ try {
model: model.chat.chatModel, const { totalTokens, finishMessages } = await resStreamResponse({
res, model: model.chat.chatModel,
chatResponse: streamResponse, res,
prompts, chatResponse: streamResponse,
systemPrompt: '' prompts
}); });
/* bill */
pushChatBill({
isPay: !userOpenAiKey,
chatModel: model.chat.chatModel,
userId,
textLen: finishMessages.map((item) => item.value).join('').length,
tokens: totalTokens,
type: BillTypeEnum.chat
});
updateShareChatBill({
shareId,
tokens: totalTokens
});
} catch (err: any) {
if (step === 1) {
// 直接结束流
res.end(); res.end();
console.log('error，结束');
} else { /* bill */
res.status(500); pushChatBill({
jsonRes(res, { isPay: !userOpenAiKey,
code: 500, chatModel: model.chat.chatModel,
error: err userId,
textLen: finishMessages.map((item) => item.value).join('').length,
tokens: totalTokens,
type: BillTypeEnum.chat
});
updateShareChatBill({
shareId,
tokens: totalTokens
}); });
} catch (error) {
res.end();
console.log('error，结束', error);
} }
} catch (err: any) {
res.status(500);
jsonRes(res, {
code: 500,
error: err
});
} }
} }
src/pages/api/openapi/chat/chat.ts
...@@ -6,15 +6,19 @@ import { ChatItemSimpleType } from '@/types/chat'; ...@@ -6,15 +6,19 @@ import { ChatItemSimpleType } from '@/types/chat';
import { jsonRes } from '@/service/response'; import { jsonRes } from '@/service/response';
import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model'; import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
import { pushChatBill } from '@/service/events/pushBill'; import { pushChatBill } from '@/service/events/pushBill';
import { searchKb } from '@/service/plugins/searchKb';
import { ChatRoleEnum } from '@/constants/chat'; import { ChatRoleEnum } from '@/constants/chat';
import { withNextCors } from '@/service/utils/tools'; import { withNextCors } from '@/service/utils/tools';
import { BillTypeEnum } from '@/constants/user'; import { BillTypeEnum } from '@/constants/user';
import { sensitiveCheck } from '@/service/api/text'; import { sensitiveCheck } from '@/service/api/text';
import { NEW_CHATID_HEADER } from '@/constants/chat';
import { Types } from 'mongoose';
import { appKbSearch } from '../kb/appKbSearch';
/* 发送提示词 */ /* 发送提示词 */
export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse) { export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse) {
let step = 0; // step=1时，表示开始了流响应 res.on('close', () => {
res.end();
});
res.on('error', () => { res.on('error', () => {
console.log('error: ', 'request error'); console.log('error: ', 'request error');
res.end(); res.end();
...@@ -70,7 +74,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex ...@@ -70,7 +74,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
// 使用了知识库搜索 // 使用了知识库搜索
if (model.chat.relatedKbs.length > 0) { if (model.chat.relatedKbs.length > 0) {
const { code, searchPrompts } = await searchKb({ const { code, searchPrompts } = await appKbSearch({
prompts, prompts,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity, similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
model, model,
...@@ -109,6 +113,10 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex ...@@ -109,6 +113,10 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
2 2
); );
// get conversationId. create a newId if it is null
const conversationId = chatId || String(new Types.ObjectId());
!chatId && res?.setHeader(NEW_CHATID_HEADER, conversationId);
// 发出请求 // 发出请求
const { streamResponse, responseMessages, responseText, totalTokens } = const { streamResponse, responseMessages, responseText, totalTokens } =
await modelServiceToolMap[model.chat.chatModel].chatCompletion({ await modelServiceToolMap[model.chat.chatModel].chatCompletion({
...@@ -117,30 +125,41 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex ...@@ -117,30 +125,41 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
messages: prompts, messages: prompts,
stream: isStream, stream: isStream,
res, res,
chatId chatId: conversationId
}); });
console.log('api response time:', `${(Date.now() - startTime) / 1000}s`); console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
let textLen = 0; if (res.closed) return res.end();
let tokens = totalTokens;
const { textLen = 0, tokens = totalTokens } = await (async () => {
if (isStream) { if (isStream) {
step = 1; try {
const { finishMessages, totalTokens } = await resStreamResponse({ const { finishMessages, totalTokens } = await resStreamResponse({
model: model.chat.chatModel, model: model.chat.chatModel,
res, res,
chatResponse: streamResponse, chatResponse: streamResponse,
prompts prompts
}); });
textLen = finishMessages.map((item) => item.value).join('').length; res.end();
tokens = totalTokens; return {
} else { textLen: finishMessages.map((item) => item.value).join('').length,
textLen = responseMessages.map((item) => item.value).join('').length; tokens: totalTokens
jsonRes(res, { };
data: responseText } catch (error) {
}); res.end();
} console.log('error，结束', error);
}
} else {
jsonRes(res, {
data: responseText
});
return {
textLen: responseMessages.map((item) => item.value).join('').length
};
}
return {};
})();
pushChatBill({ pushChatBill({
isPay: true, isPay: true,
...@@ -151,16 +170,10 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex ...@@ -151,16 +170,10 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
type: BillTypeEnum.openapiChat type: BillTypeEnum.openapiChat
}); });
} catch (err: any) { } catch (err: any) {
if (step === 1) { res.status(500);
// 直接结束流 jsonRes(res, {
res.end(); code: 500,
console.log('error，结束'); error: err
} else { });
res.status(500);
jsonRes(res, {
code: 500,
error: err
});
}
} }
}); });
src/pages/api/openapi/chat/lastChatResult.ts 0 → 100644
import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { Chat } from '@/service/mongo';
import { authUser } from '@/service/utils/auth';
import { QuoteItemType } from '../kb/appKbSearch';
type Props = {
chatId: string;
};
export type Response = {
quote: QuoteItemType[];
};
/* 聊天内容存存储 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
try {
const { chatId } = req.query as Props;
if (!chatId) {
throw new Error('缺少参数');
}
const { userId } = await authUser({ req });
const chatItem = await Chat.findOne({ _id: chatId, userId }, { content: { $slice: -1 } });
jsonRes<Response>(res, {
data: {
quote: chatItem?.content[0]?.quote || []
}
});
} catch (err) {
jsonRes(res, {
code: 500,
error: err
});
}
}
src/pages/api/openapi/kb/appKbSearch.ts 0 → 100644
import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { authUser } from '@/service/utils/auth';
import { PgClient } from '@/service/pg';
import { withNextCors } from '@/service/utils/tools';
import type { ChatItemSimpleType } from '@/types/chat';
import type { ModelSchema } from '@/types/mongoSchema';
import { ModelVectorSearchModeEnum } from '@/constants/model';
import { authModel } from '@/service/utils/auth';
import { ChatModelMap } from '@/constants/model';
import { ChatRoleEnum } from '@/constants/chat';
import { openaiEmbedding } from '../plugin/openaiEmbedding';
import { ModelDataStatusEnum } from '@/constants/model';
import { modelToolMap } from '@/utils/plugin';
export type QuoteItemType = { id: string; q: string; a: string };
type Props = {
prompts: ChatItemSimpleType[];
similarity: number;
appId: string;
};
type Response = {
code: 200 | 201;
rawSearch: QuoteItemType[];
searchPrompts: {
obj: ChatRoleEnum;
value: string;
}[];
};
export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
try {
const { userId } = await authUser({ req });
if (!userId) {
throw new Error('userId is empty');
}
const { prompts, similarity, appId } = req.body as Props;
if (!similarity || !Array.isArray(prompts) || !appId) {
throw new Error('params is error');
}
// auth model
const { model } = await authModel({
modelId: appId,
userId
});
const result = await appKbSearch({
userId,
prompts,
similarity,
model
});
jsonRes<Response>(res, {
data: result
});
} catch (err) {
console.log(err);
jsonRes(res, {
code: 500,
error: err
});
}
});
export async function appKbSearch({
model,
userId,
prompts,
similarity
}: {
userId: string;
prompts: ChatItemSimpleType[];
similarity: number;
model: ModelSchema;
}): Promise<Response> {
const modelConstantsData = ChatModelMap[model.chat.chatModel];
// search two times.
const userPrompts = prompts.filter((item) => item.obj === 'Human');
const input: string[] = [
userPrompts[userPrompts.length - 1].value,
userPrompts[userPrompts.length - 2]?.value
].filter((item) => item);
// get vector
const promptVectors = await openaiEmbedding({
userId,
input
});
// search kb
const searchRes = await Promise.all(
promptVectors.map((promptVector) =>
PgClient.select<{ id: string; q: string; a: string }>('modelData', {
fields: ['id', 'q', 'a'],
where: [
['status', ModelDataStatusEnum.ready],
'AND',
`kb_id IN (${model.chat.relatedKbs.map((item) => `'${item}'`).join(',')})`,
'AND',
`vector <=> '[${promptVector}]' < ${similarity}`
],
order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
limit: promptVectors.length === 1 ? 15 : 10
}).then((res) => res.rows)
)
);
// filter same search result
const idSet = new Set<string>();
const filterSearch = searchRes.map((search) =>
search.filter((item) => {
if (idSet.has(item.id)) {
return false;
}
idSet.add(item.id);
return true;
})
);
// slice search result by rate.
const sliceRateMap: Record<number, number[]> = {
1: [1],
2: [0.7, 0.3]
};
const sliceRate = sliceRateMap[searchRes.length] || sliceRateMap[0];
// 计算固定提示词的 token 数量
const fixedPrompts = [
// user system prompt
...(model.chat.systemPrompt
? [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
]
: model.chat.searchMode === ModelVectorSearchModeEnum.noContext
? [
{
obj: ChatRoleEnum.System,
value: `知识库是关于"${model.name}"的内容,根据知识库内容回答问题.`
}
]
: [
{
obj: ChatRoleEnum.System,
value: `玩一个问答游戏,规则为:
1.你完全忘记你已有的知识
2.你只回答关于"${model.name}"的问题
3.你只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。"
请务必遵守规则`
}
])
];
const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
messages: fixedPrompts
});
const maxTokens = modelConstantsData.systemMaxToken - fixedSystemTokens;
const sliceResult = sliceRate.map((rate, i) =>
modelToolMap[model.chat.chatModel]
.tokenSlice({
maxToken: Math.round(maxTokens * rate),
messages: filterSearch[i].map((item) => ({
obj: ChatRoleEnum.System,
value: `${item.q}\n${item.a}`
}))
})
.map((item) => item.value)
);
// slice filterSearch
const sliceSearch = filterSearch.map((item, i) => item.slice(0, sliceResult[i].length)).flat();
// system prompt
const systemPrompt = sliceResult.flat().join('\n').trim();
/* 高相似度+不回复 */
if (!systemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
return {
code: 201,
rawSearch: [],
searchPrompts: [
{
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 (!systemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
return {
code: 200,
rawSearch: [],
searchPrompts: model.chat.systemPrompt
? [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
]
: []
};
}
return {
code: 200,
rawSearch: sliceSearch,
searchPrompts: [
{
obj: ChatRoleEnum.System,
value: `知识库:${systemPrompt}`
},
...fixedPrompts
]
};
}
src/pages/api/openapi/plugin/openaiEmbedding.ts 0 → 100644
import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { authUser } from '@/service/utils/auth';
import { PgClient } from '@/service/pg';
import { withNextCors } from '@/service/utils/tools';
import { getApiKey } from '@/service/utils/auth';
import { getOpenAIApi } from '@/service/utils/chat/openai';
import { embeddingModel } from '@/constants/model';
import { axiosConfig } from '@/service/utils/tools';
import { pushGenerateVectorBill } from '@/service/events/pushBill';
type Props = {
input: string[];
};
type Response = number[][];
export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
try {
const { userId } = await authUser({ req });
let { input } = req.query as Props;
if (!Array.isArray(input)) {
throw new Error('缺少参数');
}
jsonRes<Response>(res, {
data: await openaiEmbedding({ userId, input, mustPay: true })
});
} catch (err) {
console.log(err);
jsonRes(res, {
code: 500,
error: err
});
}
});
export async function openaiEmbedding({
userId,
input,
mustPay = false
}: { userId: string; mustPay?: boolean } & Props) {
const { userOpenAiKey, systemAuthKey } = await getApiKey({
model: 'gpt-3.5-turbo',
userId,
mustPay
});
// 获取 chatAPI
const chatAPI = getOpenAIApi();
// 把输入的内容转成向量
const result = await chatAPI
.createEmbedding(
{
model: embeddingModel,
input
},
{
timeout: 60000,
...axiosConfig(userOpenAiKey || systemAuthKey)
}
)
.then((res) => ({
tokenLen: res.data.usage.total_tokens || 0,
vectors: res.data.data.map((item) => item.embedding)
}));
pushGenerateVectorBill({
isPay: !userOpenAiKey,
userId,
text: input.join(''),
tokenLen: result.tokenLen
});
return result.vectors;
}
src/pages/api/openapi/text/gptMessagesSlice.ts 0 → 100644
// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
import type { NextApiRequest, NextApiResponse } from 'next';
import { type Tiktoken } from '@dqbd/tiktoken';
import { jsonRes } from '@/service/response';
import { authUser } from '@/service/utils/auth';
import Graphemer from 'graphemer';
import type { ChatItemSimpleType } from '@/types/chat';
import { ChatCompletionRequestMessage } from 'openai';
import { getOpenAiEncMap } from '@/utils/plugin/openai';
import { adaptChatItem_openAI } from '@/utils/plugin/openai';
type ModelType = 'gpt-3.5-turbo' | 'gpt-4' | 'gpt-4-32k';
type Props = {
messages: ChatItemSimpleType[];
model: ModelType;
maxLen: number;
};
type Response = ChatItemSimpleType[];
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
try {
await authUser({ req });
const { messages, model, maxLen } = req.body as Props;
if (!Array.isArray(messages) || !model || !maxLen) {
throw new Error('params is error');
}
return jsonRes<Response>(res, {
data: gpt_chatItemTokenSlice({
messages,
model,
maxToken: maxLen
})
});
} catch (err) {
jsonRes(res, {
code: 500,
error: err
});
}
}
export function gpt_chatItemTokenSlice({
messages,
model,
maxToken
}: {
messages: ChatItemSimpleType[];
model: ModelType;
maxToken: number;
}) {
const textDecoder = new TextDecoder();
const graphemer = new Graphemer();
function getChatGPTEncodingText(messages: ChatCompletionRequestMessage[], model: ModelType) {
const isGpt3 = model === 'gpt-3.5-turbo';
const msgSep = isGpt3 ? '\n' : '';
const roleSep = isGpt3 ? '\n' : '<|im_sep|>';
return [
messages
.map(({ name = '', role, content }) => {
return `<|im_start|>${name || role}${roleSep}${content}<|im_end|>`;
})
.join(msgSep),
`<|im_start|>assistant${roleSep}`
].join(msgSep);
}
function text2TokensLen(encoder: Tiktoken, inputText: string) {
const encoding = encoder.encode(inputText, 'all');
const segments: { text: string; tokens: { id: number; idx: number }[] }[] = [];
let byteAcc: number[] = [];
let tokenAcc: { id: number; idx: number }[] = [];
let inputGraphemes = graphemer.splitGraphemes(inputText);
for (let idx = 0; idx < encoding.length; idx++) {
const token = encoding[idx]!;
byteAcc.push(...encoder.decode_single_token_bytes(token));
tokenAcc.push({ id: token, idx });
const segmentText = textDecoder.decode(new Uint8Array(byteAcc));
const graphemes = graphemer.splitGraphemes(segmentText);
if (graphemes.every((item, idx) => inputGraphemes[idx] === item)) {
segments.push({ text: segmentText, tokens: tokenAcc });
byteAcc = [];
tokenAcc = [];
inputGraphemes = inputGraphemes.slice(graphemes.length);
}
}
return segments.reduce((memo, i) => memo + i.tokens.length, 0) ?? 0;
}
const OpenAiEncMap = getOpenAiEncMap();
const enc = OpenAiEncMap[model];
let result: ChatItemSimpleType[] = [];
for (let i = 0; i < messages.length; i++) {
const msgs = [...result, messages[i]];
const tokens = text2TokensLen(
enc,
getChatGPTEncodingText(adaptChatItem_openAI({ messages }), model)
);
if (tokens < maxToken) {
result = msgs;
} else {
break;
}
}
return result;
}
src/pages/chat/index.tsx
...@@ -3,10 +3,10 @@ import { useRouter } from 'next/router'; ...@@ -3,10 +3,10 @@ import { useRouter } from 'next/router';
import { import {
getInitChatSiteInfo, getInitChatSiteInfo,
delChatRecordByIndex, delChatRecordByIndex,
postSaveChat, getChatResult,
delChatHistoryById delChatHistoryById
} from '@/api/chat'; } from '@/api/chat';
import type { ChatSiteItemType, ExportChatType } from '@/types/chat'; import type { ChatItemType, ChatSiteItemType, ExportChatType } from '@/types/chat';
import { import {
Textarea, Textarea,
Box, Box,
...@@ -29,13 +29,14 @@ import { ...@@ -29,13 +29,14 @@ import {
Card, Card,
Tooltip, Tooltip,
useOutsideClick, useOutsideClick,
useTheme useTheme,
ModalHeader
} from '@chakra-ui/react'; } from '@chakra-ui/react';
import { useToast } from '@/hooks/useToast'; import { useToast } from '@/hooks/useToast';
import { useGlobalStore } from '@/store/global'; import { useGlobalStore } from '@/store/global';
import { useQuery } from '@tanstack/react-query'; import { useQuery } from '@tanstack/react-query';
import dynamic from 'next/dynamic'; import dynamic from 'next/dynamic';
import { useCopyData, voiceBroadcast, hasVoiceApi } from '@/utils/tools'; import { useCopyData, voiceBroadcast, hasVoiceApi, delay } from '@/utils/tools';
import { streamFetch } from '@/api/fetch'; import { streamFetch } from '@/api/fetch';
import MyIcon from '@/components/Icon'; import MyIcon from '@/components/Icon';
import { throttle } from 'lodash'; import { throttle } from 'lodash';
...@@ -47,6 +48,7 @@ import { useLoading } from '@/hooks/useLoading'; ...@@ -47,6 +48,7 @@ import { useLoading } from '@/hooks/useLoading';
import { fileDownload } from '@/utils/file'; import { fileDownload } from '@/utils/file';
import { htmlTemplate } from '@/constants/common'; import { htmlTemplate } from '@/constants/common';
import { useUserStore } from '@/store/user'; import { useUserStore } from '@/store/user';
import type { QuoteItemType } from '@/pages/api/openapi/kb/appKbSearch';
import Loading from '@/components/Loading'; import Loading from '@/components/Loading';
import Markdown from '@/components/Markdown'; import Markdown from '@/components/Markdown';
import SideBar from '@/components/SideBar'; import SideBar from '@/components/SideBar';
...@@ -78,7 +80,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -78,7 +80,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
const controller = useRef(new AbortController()); const controller = useRef(new AbortController());
const isLeavePage = useRef(false); const isLeavePage = useRef(false);
const [showSystemPrompt, setShowSystemPrompt] = useState(''); const [showQuote, setShowQuote] = useState<QuoteItemType[]>([]);
const [messageContextMenuData, setMessageContextMenuData] = useState<{ const [messageContextMenuData, setMessageContextMenuData] = useState<{
// message messageContextMenuData // message messageContextMenuData
left: number; left: number;
...@@ -173,13 +175,14 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -173,13 +175,14 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
controller.current = abortSignal; controller.current = abortSignal;
isLeavePage.current = false; isLeavePage.current = false;
const prompt = { const prompt: ChatItemType[] = prompts.map((item) => ({
obj: prompts[0].obj, _id: item._id,
value: prompts[0].value obj: item.obj,
}; value: item.value
}));
// 流请求，获取数据 // 流请求，获取数据
let { responseText, systemPrompt, newChatId } = await streamFetch({ const { newChatId } = await streamFetch({
url: '/api/chat/chat', url: '/api/chat/chat',
data: { data: {
prompt, prompt,
...@@ -207,39 +210,16 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -207,39 +210,16 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
return; return;
} }
// save chat record if (newChatId) {
try { setForbidLoadChatData(true);
newChatId = await postSaveChat({ router.replace(`/chat?modelId=${modelId}&chatId=${newChatId}`);
newChatId, // 如果有newChatId，会自动以这个Id创建对话框
modelId,
chatId,
prompts: [
{
_id: prompts[0]._id,
obj: 'Human',
value: prompt.value
},
{
_id: prompts[1]._id,
obj: 'AI',
value: responseText,
systemPrompt
}
]
});
if (newChatId) {
setForbidLoadChatData(true);
router.replace(`/chat?modelId=${modelId}&chatId=${newChatId}`);
}
} catch (err) {
toast({
title: '对话出现异常, 继续对话会导致上下文丢失，请刷新页面',
status: 'warning',
duration: 3000,
isClosable: true
});
} }
abortSignal.signal.aborted && (await delay(600));
// get chat result
const { quote } = await getChatResult(chatId || newChatId);
// 设置聊天内容为完成状态 // 设置聊天内容为完成状态
setChatData((state) => ({ setChatData((state) => ({
...state, ...state,
...@@ -249,7 +229,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -249,7 +229,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
return { return {
...item, ...item,
status: 'finish', status: 'finish',
systemPrompt quote
}; };
}) })
})); }));
...@@ -260,16 +240,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -260,16 +240,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
generatingMessage(); generatingMessage();
}, 100); }, 100);
}, },
[ [chatId, setForbidLoadChatData, generatingMessage, loadHistory, modelId, router, setChatData]
chatId,
setForbidLoadChatData,
generatingMessage,
loadHistory,
modelId,
router,
setChatData,
toast
]
); );
/** /**
...@@ -717,24 +688,24 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -717,24 +688,24 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
{item.obj === 'Human' && <Box flex={1} />} {item.obj === 'Human' && <Box flex={1} />}
{/* avatar */} {/* avatar */}
<Menu autoSelect={false} isLazy> <Menu autoSelect={false} isLazy>
<MenuButton <Tooltip label={item.obj === 'AI' ? '应用详情' : ''}>
as={Box} <MenuButton
{...(item.obj === 'AI' as={Box}
? { {...(item.obj === 'AI'
order: 1, ? {
mr: ['6px', 2], order: 1,
cursor: 'pointer', mr: ['6px', 2],
onClick: () => cursor: 'pointer',
isPc && onClick: () =>
chatData.model.canUse && isPc &&
router.push(`/model?modelId=${chatData.modelId}`) chatData.model.canUse &&
} router.push(`/model?modelId=${chatData.modelId}`)
: { }
order: 3, : {
ml: ['6px', 2] order: 3,
})} ml: ['6px', 2]
> })}
<Tooltip label={item.obj === 'AI' ? '应用详情' : ''}> >
<Avatar <Avatar
src={ src={
item.obj === 'Human' item.obj === 'Human'
...@@ -744,8 +715,8 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -744,8 +715,8 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
w={['20px', '34px']} w={['20px', '34px']}
h={['20px', '34px']} h={['20px', '34px']}
/> />
</Tooltip> </MenuButton>
</MenuButton> </Tooltip>
{!isPc && <RenderContextMenu history={item} index={index} AiDetail />} {!isPc && <RenderContextMenu history={item} index={index} AiDetail />}
</Menu> </Menu>
{/* message */} {/* message */}
...@@ -764,7 +735,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -764,7 +735,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
isChatting={isChatting && index === chatData.history.length - 1} isChatting={isChatting && index === chatData.history.length - 1}
formatLink formatLink
/> />
{item.systemPrompt && ( {item.quote && item.quote.length > 0 && (
<Button <Button
size={'xs'} size={'xs'}
mt={2} mt={2}
...@@ -772,9 +743,9 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -772,9 +743,9 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
colorScheme={'gray'} colorScheme={'gray'}
variant={'outline'} variant={'outline'}
w={'90px'} w={'90px'}
onClick={() => setShowSystemPrompt(item.systemPrompt || '')} onClick={() => setShowQuote(item.quote || [])}
> >
查看提示词 查看引用
</Button> </Button>
)} )}
</Card> </Card>
...@@ -907,12 +878,24 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => { ...@@ -907,12 +878,24 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
)} )}
{/* system prompt show modal */} {/* system prompt show modal */}
{ {
<Modal isOpen={!!showSystemPrompt} onClose={() => setShowSystemPrompt('')}> <Modal isOpen={showQuote.length > 0} onClose={() => setShowQuote([])}>
<ModalOverlay /> <ModalOverlay />
<ModalContent pt={5} maxW={'min(90vw, 600px)'} h={'80vh'} overflow={'overlay'}> <ModalContent maxW={'min(90vw, 700px)'} h={'80vh'} overflow={'overlay'}>
<ModalHeader>知识库引用({showQuote.length}条)</ModalHeader>
<ModalCloseButton /> <ModalCloseButton />
<ModalBody pt={5} whiteSpace={'pre-wrap'} textAlign={'justify'}> <ModalBody whiteSpace={'pre-wrap'} textAlign={'justify'} fontSize={'sm'}>
{showSystemPrompt} {showQuote.map((item) => (
<Box
key={item.id}
p={2}
borderRadius={'sm'}
border={theme.borders.base}
_notLast={{ mb: 2 }}
>
<Box>{item.q}</Box>
<Box>{item.a}</Box>
</Box>
))}
</ModalBody> </ModalBody>
</ModalContent> </ModalContent>
</Modal> </Modal>
......
src/pages/chat/share.tsx
...@@ -73,7 +73,6 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => ...@@ -73,7 +73,6 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
const isLeavePage = useRef(false); const isLeavePage = useRef(false);
const [inputVal, setInputVal] = useState(''); // user input prompt const [inputVal, setInputVal] = useState(''); // user input prompt
const [showSystemPrompt, setShowSystemPrompt] = useState('');
const [messageContextMenuData, setMessageContextMenuData] = useState<{ const [messageContextMenuData, setMessageContextMenuData] = useState<{
// message messageContextMenuData // message messageContextMenuData
left: number; left: number;
...@@ -178,7 +177,7 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => ...@@ -178,7 +177,7 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
})); }));
// 流请求，获取数据 // 流请求，获取数据
const { responseText, systemPrompt } = await streamFetch({ const { responseText } = await streamFetch({
url: '/api/chat/shareChat/chat', url: '/api/chat/shareChat/chat',
data: { data: {
prompts: formatPrompts.slice(-shareChatData.maxContext - 1, -1), prompts: formatPrompts.slice(-shareChatData.maxContext - 1, -1),
...@@ -215,8 +214,7 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => ...@@ -215,8 +214,7 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
if (index !== state.history.length - 1) return item; if (index !== state.history.length - 1) return item;
return { return {
...item, ...item,
status: 'finish', status: 'finish'
systemPrompt
}; };
}); });
...@@ -614,19 +612,19 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => ...@@ -614,19 +612,19 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
{item.obj === 'Human' && <Box flex={1} />} {item.obj === 'Human' && <Box flex={1} />}
{/* avatar */} {/* avatar */}
<Menu autoSelect={false} isLazy> <Menu autoSelect={false} isLazy>
<MenuButton <Tooltip label={item.obj === 'AI' ? '应用详情' : ''}>
as={Box} <MenuButton
{...(item.obj === 'AI' as={Box}
? { {...(item.obj === 'AI'
order: 1, ? {
mr: ['6px', 2] order: 1,
} mr: ['6px', 2]
: { }
order: 3, : {
ml: ['6px', 2] order: 3,
})} ml: ['6px', 2]
> })}
<Tooltip label={item.obj === 'AI' ? '应用详情' : ''}> >
<Avatar <Avatar
src={ src={
item.obj === 'Human' item.obj === 'Human'
...@@ -636,8 +634,8 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => ...@@ -636,8 +634,8 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
w={['20px', '34px']} w={['20px', '34px']}
h={['20px', '34px']} h={['20px', '34px']}
/> />
</Tooltip> </MenuButton>
</MenuButton> </Tooltip>
{!isPc && <RenderContextMenu history={item} index={index} />} {!isPc && <RenderContextMenu history={item} index={index} />}
</Menu> </Menu>
{/* message */} {/* message */}
...@@ -656,19 +654,6 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => ...@@ -656,19 +654,6 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
isChatting={isChatting && index === shareChatData.history.length - 1} isChatting={isChatting && index === shareChatData.history.length - 1}
formatLink formatLink
/> />
{item.systemPrompt && (
<Button
size={'xs'}
mt={2}
fontWeight={'normal'}
colorScheme={'gray'}
variant={'outline'}
w={'90px'}
onClick={() => setShowSystemPrompt(item.systemPrompt || '')}
>
查看提示词
</Button>
)}
</Card> </Card>
</Box> </Box>
) : ( ) : (
...@@ -796,18 +781,6 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) => ...@@ -796,18 +781,6 @@ const Chat = ({ shareId, historyId }: { shareId: string; historyId: string }) =>
</DrawerContent> </DrawerContent>
</Drawer> </Drawer>
)} )}
{/* system prompt show modal */}
{
<Modal isOpen={!!showSystemPrompt} onClose={() => setShowSystemPrompt('')}>
<ModalOverlay />
<ModalContent maxW={'min(90vw, 600px)'} pr={2} maxH={'80vh'} overflowY={'auto'}>
<ModalCloseButton />
<ModalBody pt={5} whiteSpace={'pre-wrap'} textAlign={'justify'}>
{showSystemPrompt}
</ModalBody>
</ModalContent>
</Modal>
}
{/* context menu */} {/* context menu */}
{messageContextMenuData && ( {messageContextMenuData && (
<Box <Box
......
src/pages/model/components/detail/components/ModelEditForm.tsx
...@@ -358,7 +358,9 @@ ${e.password ? `密码为: ${e.password}` : ''}`; ...@@ -358,7 +358,9 @@ ${e.password ? `密码为: ${e.password}` : ''}`;
rows={8} rows={8}
maxLength={-1} maxLength={-1}
isDisabled={!isOwner} isDisabled={!isOwner}
placeholder={'模型默认的 prompt 词，通过调整该内容，可以引导模型聊天方向。'} placeholder={
'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')} {...register('chat.systemPrompt')}
/> />
</Box> </Box>
......
src/service/events/generateVector.ts
import { openaiCreateEmbedding } from '../utils/chat/openai';
import { getApiKey } from '../utils/auth'; import { getApiKey } from '../utils/auth';
import { openaiError2 } from '../errorCode'; import { openaiError2 } from '../errorCode';
import { PgClient } from '@/service/pg'; import { PgClient } from '@/service/pg';
import { getErrText } from '@/utils/tools'; import { getErrText } from '@/utils/tools';
import { openaiEmbedding } from '@/pages/api/openapi/plugin/openaiEmbedding';
export async function generateVector(next = false): Promise<any> { export async function generateVector(next = false): Promise<any> {
if (process.env.queueTask !== '1') { if (process.env.queueTask !== '1') {
...@@ -42,24 +42,20 @@ export async function generateVector(next = false): Promise<any> { ...@@ -42,24 +42,20 @@ export async function generateVector(next = false): Promise<any> {
dataId = dataItem.id; dataId = dataItem.id;
// 获取 openapi Key // 获取 openapi Key
let userOpenAiKey;
try { try {
const res = await getApiKey({ model: 'gpt-3.5-turbo', userId: dataItem.userId }); await getApiKey({ model: 'gpt-3.5-turbo', userId: dataItem.userId });
userOpenAiKey = res.userOpenAiKey;
} catch (err: any) { } catch (err: any) {
await PgClient.delete('modelData', { await PgClient.delete('modelData', {
where: [['id', dataId]] where: [['id', dataId]]
}); });
generateVector(true);
getErrText(err, '获取 OpenAi Key 失败'); getErrText(err, '获取 OpenAi Key 失败');
return; return generateVector(true);
} }
// 生成词向量 // 生成词向量
const { vectors } = await openaiCreateEmbedding({ const vectors = await openaiEmbedding({
textArr: [dataItem.q], input: [dataItem.q],
userId: dataItem.userId, userId: dataItem.userId
userOpenAiKey
}); });
// 更新 pg 向量和状态数据 // 更新 pg 向量和状态数据
......
src/service/models/chat.ts
...@@ -47,10 +47,14 @@ const ChatSchema = new Schema({ ...@@ -47,10 +47,14 @@ const ChatSchema = new Schema({
type: String, type: String,
required: true required: true
}, },
systemPrompt: { quote: {
type: String, type: [{ id: String, q: String, a: String }],
default: '' default: []
} }
// systemPrompt: {
// type: String,
// default: ''
// }
} }
], ],
default: [] default: []
......
src/service/plugins/searchKb.ts deleted 100644 → 0
import { PgClient } from '@/service/pg';
import { ModelDataStatusEnum, ModelVectorSearchModeEnum, ChatModelMap } from '@/constants/model';
import { ModelSchema } from '@/types/mongoSchema';
import { openaiCreateEmbedding } from '../utils/chat/openai';
import { ChatRoleEnum } from '@/constants/chat';
import { modelToolMap } from '@/utils/chat';
import { ChatItemSimpleType } from '@/types/chat';
/**
* use openai embedding search kb
*/
export const searchKb = async ({
userOpenAiKey,
prompts,
similarity = 0.2,
model,
userId
}: {
userOpenAiKey?: string;
prompts: ChatItemSimpleType[];
model: ModelSchema;
userId: string;
similarity?: number;
}): Promise<{
code: 200 | 201;
searchPrompts: {
obj: ChatRoleEnum;
value: string;
}[];
}> => {
async function search(textArr: string[] = []) {
const limitMap: Record<ModelVectorSearchModeEnum, number> = {
[ModelVectorSearchModeEnum.hightSimilarity]: 15,
[ModelVectorSearchModeEnum.noContext]: 15,
[ModelVectorSearchModeEnum.lowSimilarity]: 20
};
// 获取提示词的向量
const { vectors: promptVectors } = await openaiCreateEmbedding({
userOpenAiKey,
userId,
textArr
});
const searchRes = await Promise.all(
promptVectors.map((promptVector) =>
PgClient.select<{ id: string; q: string; a: string }>('modelData', {
fields: ['id', 'q', 'a'],
where: [
['status', ModelDataStatusEnum.ready],
'AND',
`kb_id IN (${model.chat.relatedKbs.map((item) => `'${item}'`).join(',')})`,
'AND',
`vector <=> '[${promptVector}]' < ${similarity}`
],
order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
limit: limitMap[model.chat.searchMode]
}).then((res) => res.rows)
)
);
// Remove repeat record
const idSet = new Set<string>();
const filterSearch = searchRes.map((search) =>
search.filter((item) => {
if (idSet.has(item.id)) {
return false;
}
idSet.add(item.id);
return true;
})
);
return filterSearch.map((item) => item.map((item) => `${item.q}\n${item.a}`).join('\n'));
}
const modelConstantsData = ChatModelMap[model.chat.chatModel];
// search three times
const userPrompts = prompts.filter((item) => item.obj === 'Human');
const searchArr: string[] = [
userPrompts[userPrompts.length - 1].value,
userPrompts[userPrompts.length - 2]?.value
].filter((item) => item);
const systemPrompts = await search(searchArr);
// filter system prompts.
const filterRateMap: Record<number, number[]> = {
1: [1],
2: [0.7, 0.3]
};
const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0];
// 计算固定提示词的 token 数量
const fixedPrompts = [
...(model.chat.systemPrompt
? [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
]
: []),
...(model.chat.searchMode === ModelVectorSearchModeEnum.noContext
? [
{
obj: ChatRoleEnum.System,
value: `知识库是关于"${model.name}"的内容,根据知识库内容回答问题.`
}
]
: [
{
obj: ChatRoleEnum.System,
value: `玩一个问答游戏,规则为:
1.你完全忘记你已有的知识
2.你只回答关于"${model.name}"的问题
3.你只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。"
请务必遵守规则`
}
])
];
const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
messages: fixedPrompts
});
const maxTokens = modelConstantsData.systemMaxToken - fixedSystemTokens;
const filterSystemPrompt = filterRate
.map((rate, i) =>
modelToolMap[model.chat.chatModel].sliceText({
text: systemPrompts[i],
length: Math.floor(maxTokens * rate)
})
)
.join('\n')
.trim();
/* 高相似度+不回复 */
if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
return {
code: 201,
searchPrompts: [
{
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,
searchPrompts: model.chat.systemPrompt
? [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
]
: []
};
}
/* 有匹配 */
return {
code: 200,
searchPrompts: [
{
obj: ChatRoleEnum.System,
value: `知识库:${filterSystemPrompt}`
},
...fixedPrompts
]
};
};
src/service/utils/auth.ts
...@@ -38,12 +38,14 @@ export const authUser = async ({ ...@@ -38,12 +38,14 @@ export const authUser = async ({
req, req,
authToken = false, authToken = false,
authOpenApi = false, authOpenApi = false,
authRoot = false authRoot = false,
authBalance = false
}: { }: {
req: NextApiRequest; req: NextApiRequest;
authToken?: boolean; authToken?: boolean;
authOpenApi?: boolean; authOpenApi?: boolean;
authRoot?: boolean; authRoot?: boolean;
authBalance?: boolean;
}) => { }) => {
const parseOpenApiKey = async (apiKey?: string) => { const parseOpenApiKey = async (apiKey?: string) => {
if (!apiKey) { if (!apiKey) {
...@@ -99,6 +101,17 @@ export const authUser = async ({ ...@@ -99,6 +101,17 @@ export const authUser = async ({
return Promise.reject(ERROR_ENUM.unAuthorization); return Promise.reject(ERROR_ENUM.unAuthorization);
} }
if (authBalance) {
const user = await User.findById(uid);
if (!user) {
return Promise.reject(ERROR_ENUM.unAuthorization);
}
if (!user.openaiKey && formatPrice(user.balance) <= 0) {
return Promise.reject(ERROR_ENUM.insufficientQuota);
}
}
return { return {
userId: uid userId: uid
}; };
...@@ -226,7 +239,7 @@ export const authChat = async ({ ...@@ -226,7 +239,7 @@ export const authChat = async ({
req req
}: { }: {
modelId: string; modelId: string;
chatId: '' | string; chatId?: string;
req: NextApiRequest; req: NextApiRequest;
}) => { }) => {
const { userId } = await authUser({ req, authToken: true }); const { userId } = await authUser({ req, authToken: true });
......
src/service/utils/chat/claude.ts
import { ChatCompletionType, StreamResponseType } from './index'; import { ChatCompletionType, StreamResponseType } from './index';
import { ChatRoleEnum } from '@/constants/chat'; import { ChatRoleEnum } from '@/constants/chat';
import axios from 'axios'; import axios from 'axios';
import mongoose from 'mongoose';
import { NEW_CHATID_HEADER } from '@/constants/chat';
/* 模型对话 */ /* 模型对话 */
export const claudChat = async ({ apiKey, messages, stream, chatId, res }: ChatCompletionType) => { export const claudChat = async ({ apiKey, messages, stream, chatId }: ChatCompletionType) => {
const conversationId = chatId || String(new mongoose.Types.ObjectId());
// create a new chat
!chatId &&
messages.filter((item) => item.obj === 'Human').length === 1 &&
res?.setHeader(NEW_CHATID_HEADER, conversationId);
// get system prompt // get system prompt
const systemPrompt = messages const systemPrompt = messages
.filter((item) => item.obj === 'System') .filter((item) => item.obj === 'System')
...@@ -26,7 +18,7 @@ export const claudChat = async ({ apiKey, messages, stream, chatId, res }: ChatC ...@@ -26,7 +18,7 @@ export const claudChat = async ({ apiKey, messages, stream, chatId, res }: ChatC
{ {
prompt, prompt,
stream, stream,
conversationId conversationId: chatId
}, },
{ {
headers: { headers: {
...@@ -55,8 +47,7 @@ export const claudStreamResponse = async ({ res, chatResponse, prompts }: Stream ...@@ -55,8 +47,7 @@ export const claudStreamResponse = async ({ res, chatResponse, prompts }: Stream
try { try {
const decoder = new TextDecoder(); const decoder = new TextDecoder();
for await (const chunk of chatResponse.data as any) { for await (const chunk of chatResponse.data as any) {
if (!res.writable) { if (res.closed) {
// 流被中断了，直接忽略后面的内容
break; break;
} }
const content = decoder.decode(chunk); const content = decoder.decode(chunk);
......
src/service/utils/chat/index.ts
import { ChatItemSimpleType } from '@/types/chat'; import { ChatItemSimpleType } from '@/types/chat';
import { modelToolMap } from '@/utils/chat'; import { modelToolMap } from '@/utils/plugin';
import type { ChatModelType } from '@/constants/model'; import type { ChatModelType } from '@/constants/model';
import { ChatRoleEnum, SYSTEM_PROMPT_HEADER } from '@/constants/chat'; import { ChatRoleEnum } from '@/constants/chat';
import { OpenAiChatEnum, ClaudeEnum } from '@/constants/model'; import { OpenAiChatEnum, ClaudeEnum } from '@/constants/model';
import { chatResponse, openAiStreamResponse } from './openai'; import { chatResponse, openAiStreamResponse } from './openai';
import { claudChat, claudStreamResponse } from './claude'; import { claudChat, claudStreamResponse } from './claude';
...@@ -11,6 +11,7 @@ export type ChatCompletionType = { ...@@ -11,6 +11,7 @@ export type ChatCompletionType = {
apiKey: string; apiKey: string;
temperature: number; temperature: number;
messages: ChatItemSimpleType[]; messages: ChatItemSimpleType[];
chatId?: string;
[key: string]: any; [key: string]: any;
}; };
export type ChatCompletionResponseType = { export type ChatCompletionResponseType = {
...@@ -23,7 +24,6 @@ export type StreamResponseType = { ...@@ -23,7 +24,6 @@ export type StreamResponseType = {
chatResponse: any; chatResponse: any;
prompts: ChatItemSimpleType[]; prompts: ChatItemSimpleType[];
res: NextApiResponse; res: NextApiResponse;
systemPrompt?: string;
[key: string]: any; [key: string]: any;
}; };
export type StreamResponseReturnType = { export type StreamResponseReturnType = {
...@@ -129,7 +129,6 @@ export const resStreamResponse = async ({ ...@@ -129,7 +129,6 @@ export const resStreamResponse = async ({
model, model,
res, res,
chatResponse, chatResponse,
systemPrompt,
prompts prompts
}: StreamResponseType & { }: StreamResponseType & {
model: ChatModelType; model: ChatModelType;
...@@ -139,18 +138,14 @@ export const resStreamResponse = async ({ ...@@ -139,18 +138,14 @@ export const resStreamResponse = async ({
res.setHeader('Access-Control-Allow-Origin', '*'); res.setHeader('Access-Control-Allow-Origin', '*');
res.setHeader('X-Accel-Buffering', 'no'); res.setHeader('X-Accel-Buffering', 'no');
res.setHeader('Cache-Control', 'no-cache, no-transform'); res.setHeader('Cache-Control', 'no-cache, no-transform');
systemPrompt && res.setHeader(SYSTEM_PROMPT_HEADER, encodeURIComponent(systemPrompt));
const { responseContent, totalTokens, finishMessages } = await modelServiceToolMap[ const { responseContent, totalTokens, finishMessages } = await modelServiceToolMap[
model model
].streamResponse({ ].streamResponse({
chatResponse, chatResponse,
prompts, prompts,
res, res
systemPrompt
}); });
res.end();
return { responseContent, totalTokens, finishMessages }; return { responseContent, totalTokens, finishMessages };
}; };
src/service/utils/chat/openai.ts
import { Configuration, OpenAIApi } from 'openai'; import { Configuration, OpenAIApi } from 'openai';
import { createParser, ParsedEvent, ReconnectInterval } from 'eventsource-parser'; import { createParser, ParsedEvent, ReconnectInterval } from 'eventsource-parser';
import { axiosConfig } from '../tools'; import { axiosConfig } from '../tools';
import { ChatModelMap, embeddingModel, OpenAiChatEnum } from '@/constants/model'; import { ChatModelMap, OpenAiChatEnum } from '@/constants/model';
import { pushGenerateVectorBill } from '../../events/pushBill'; import { adaptChatItem_openAI } from '@/utils/plugin/openai';
import { adaptChatItem_openAI } from '@/utils/chat/openai'; import { modelToolMap } from '@/utils/plugin';
import { modelToolMap } from '@/utils/chat';
import { ChatCompletionType, ChatContextFilter, StreamResponseType } from './index'; import { ChatCompletionType, ChatContextFilter, StreamResponseType } from './index';
import { ChatRoleEnum } from '@/constants/chat'; import { ChatRoleEnum } from '@/constants/chat';
import { getSystemOpenAiKey } from '../auth';
export const getOpenAIApi = () => export const getOpenAIApi = () =>
new OpenAIApi( new OpenAIApi(
...@@ -16,51 +14,6 @@ export const getOpenAIApi = () => ...@@ -16,51 +14,6 @@ export const getOpenAIApi = () =>
}) })
); );
/* 获取向量 */
export const openaiCreateEmbedding = async ({
userOpenAiKey,
userId,
textArr
}: {
userOpenAiKey?: string;
userId: string;
textArr: string[];
}) => {
const systemAuthKey = getSystemOpenAiKey();
// 获取 chatAPI
const chatAPI = getOpenAIApi();
// 把输入的内容转成向量
const res = await chatAPI
.createEmbedding(
{
model: embeddingModel,
input: textArr
},
{
timeout: 60000,
...axiosConfig(userOpenAiKey || systemAuthKey)
}
)
.then((res) => ({
tokenLen: res.data.usage.total_tokens || 0,
vectors: res.data.data.map((item) => item.embedding)
}));
pushGenerateVectorBill({
isPay: !userOpenAiKey,
userId,
text: textArr.join(''),
tokenLen: res.tokenLen
});
return {
vectors: res.vectors,
chatAPI
};
};
/* 模型对话 */ /* 模型对话 */
export const chatResponse = async ({ export const chatResponse = async ({
model, model,
...@@ -127,7 +80,7 @@ export const openAiStreamResponse = async ({ ...@@ -127,7 +80,7 @@ export const openAiStreamResponse = async ({
const content: string = json?.choices?.[0].delta.content || ''; const content: string = json?.choices?.[0].delta.content || '';
responseContent += content; responseContent += content;
res.writable && content && res.write(content); !res.closed && content && res.write(content);
} catch (error) { } catch (error) {
error; error;
} }
...@@ -137,8 +90,7 @@ export const openAiStreamResponse = async ({ ...@@ -137,8 +90,7 @@ export const openAiStreamResponse = async ({
const decoder = new TextDecoder(); const decoder = new TextDecoder();
const parser = createParser(onParse); const parser = createParser(onParse);
for await (const chunk of chatResponse.data as any) { for await (const chunk of chatResponse.data as any) {
if (!res.writable) { if (res.closed) {
// 流被中断了，直接忽略后面的内容
break; break;
} }
parser.feed(decoder.decode(chunk, { stream: true })); parser.feed(decoder.decode(chunk, { stream: true }));
......
src/types/chat.d.ts
import { ChatRoleEnum } from '@/constants/chat'; import { ChatRoleEnum } from '@/constants/chat';
import type { InitChatResponse, InitShareChatResponse } from '@/api/response/chat'; import type { InitChatResponse, InitShareChatResponse } from '@/api/response/chat';
import { QuoteItemType } from '@/pages/api/openapi/kb/appKbSearch';
export type ExportChatType = 'md' | 'pdf' | 'html'; export type ExportChatType = 'md' | 'pdf' | 'html';
export type ChatItemSimpleType = { export type ChatItemSimpleType = {
obj: `${ChatRoleEnum}`; obj: `${ChatRoleEnum}`;
value: string; value: string;
systemPrompt?: string; quote?: QuoteItemType[];
}; };
export type ChatItemType = { export type ChatItemType = {
_id: string; _id: string;
......
src/utils/chat/claude.ts deleted 100644 → 0
export const ClaudeSliceTextByToken = ({ text, length }: { text: string; length: number }) => {
return text.slice(0, length);
};
src/utils/file.ts
import mammoth from 'mammoth'; import mammoth from 'mammoth';
import Papa from 'papaparse'; import Papa from 'papaparse';
import { getOpenAiEncMap } from './chat/openai'; import { getOpenAiEncMap } from './plugin/openai';
/** /**
* 读取 txt 文件内容 * 读取 txt 文件内容
......
src/utils/chat/index.ts → src/utils/plugin/index.ts
...@@ -2,29 +2,37 @@ import { ClaudeEnum, OpenAiChatEnum } from '@/constants/model'; ...@@ -2,29 +2,37 @@ import { ClaudeEnum, OpenAiChatEnum } from '@/constants/model';
import type { ChatModelType } from '@/constants/model'; import type { ChatModelType } from '@/constants/model';
import type { ChatItemSimpleType } from '@/types/chat'; import type { ChatItemSimpleType } from '@/types/chat';
import { countOpenAIToken, openAiSliceTextByToken } from './openai'; import { countOpenAIToken, openAiSliceTextByToken } from './openai';
import { ClaudeSliceTextByToken } from './claude'; import { gpt_chatItemTokenSlice } from '@/pages/api/openapi/text/gptMessagesSlice';
export const modelToolMap: Record< export const modelToolMap: Record<
ChatModelType, ChatModelType,
{ {
countTokens: (data: { messages: ChatItemSimpleType[] }) => number; countTokens: (data: { messages: ChatItemSimpleType[] }) => number;
sliceText: (data: { text: string; length: number }) => string; sliceText: (data: { text: string; length: number }) => string;
tokenSlice: (data: {
messages: ChatItemSimpleType[];
maxToken: number;
}) => ChatItemSimpleType[];
} }
> = { > = {
[OpenAiChatEnum.GPT35]: { [OpenAiChatEnum.GPT35]: {
countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }), countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }),
sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data }) sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data }),
tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT35, ...data })
}, },
[OpenAiChatEnum.GPT4]: { [OpenAiChatEnum.GPT4]: {
countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT4, messages }), countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT4, messages }),
sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT4, ...data }) sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT4, ...data }),
tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT4, ...data })
}, },
[OpenAiChatEnum.GPT432k]: { [OpenAiChatEnum.GPT432k]: {
countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT432k, messages }), countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT432k, messages }),
sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT432k, ...data }) sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT432k, ...data }),
tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT432k, ...data })
}, },
[ClaudeEnum.Claude]: { [ClaudeEnum.Claude]: {
countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }), countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }),
sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data }) sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data }),
tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT35, ...data })
} }
}; };
src/utils/tools.ts
...@@ -126,3 +126,10 @@ export const getErrText = (err: any, def = '') => { ...@@ -126,3 +126,10 @@ export const getErrText = (err: any, def = '') => {
msg && console.log('error =>', msg); msg && console.log('error =>', msg);
return msg; return msg;
}; };
export const delay = (ms: number) =>
new Promise((resolve) => {
setTimeout(() => {
resolve('');
}, ms);
});
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