Compare commits
5 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
6ff5db7b41 | ||
|
|
56a0b48b97 | ||
|
|
ff24042df5 | ||
|
|
c31d247f07 | ||
|
|
e903eb5b94 |
2
Makefile
2
Makefile
@@ -34,7 +34,7 @@ run: ## Run a dev service from host.
|
||||
|
||||
.PHONY: docker-build
|
||||
docker-build: ## Build docker image with the desktop-frontend.
|
||||
docker build -t c121914yu/fast-gpt:latest .
|
||||
docker build -t c121914yu/fast-gpt:latest . --network host --build-arg HTTP_PROXY=http://127.0.0.1:7890 --build-arg HTTPS_PROXY=http://127.0.0.1:7890
|
||||
|
||||
##@ Deployment
|
||||
|
||||
|
||||
@@ -49,6 +49,7 @@ export const getModelTrainings = (id: string) =>
|
||||
|
||||
type GetModelDataListProps = RequestPaging & {
|
||||
modelId: string;
|
||||
searchText: string;
|
||||
};
|
||||
/**
|
||||
* 获取模型的知识库数据
|
||||
|
||||
@@ -4,20 +4,20 @@ import { connectToDatabase } from '@/service/mongo';
|
||||
import { authToken } from '@/service/utils/tools';
|
||||
import { connectRedis } from '@/service/redis';
|
||||
import { VecModelDataIdx } from '@/constants/redis';
|
||||
import { SearchOptions } from 'redis';
|
||||
|
||||
export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
|
||||
try {
|
||||
let {
|
||||
modelId,
|
||||
pageNum = 1,
|
||||
pageSize = 10
|
||||
pageSize = 10,
|
||||
searchText = ''
|
||||
} = req.query as {
|
||||
modelId: string;
|
||||
pageNum: string;
|
||||
pageSize: string;
|
||||
searchText: string;
|
||||
};
|
||||
|
||||
const { authorization } = req.headers;
|
||||
|
||||
pageNum = +pageNum;
|
||||
@@ -40,7 +40,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
|
||||
// 从 redis 中获取数据
|
||||
const searchRes = await redis.ft.search(
|
||||
VecModelDataIdx,
|
||||
`@modelId:{${modelId}} @userId:{${userId}}`,
|
||||
`@modelId:{${modelId}} @userId:{${userId}} ${searchText ? `*${searchText}*` : ''}`,
|
||||
{
|
||||
RETURN: ['q', 'text', 'status'],
|
||||
LIMIT: {
|
||||
|
||||
158
src/pages/api/openapi/chat/chatGpt.ts
Normal file
158
src/pages/api/openapi/chat/chatGpt.ts
Normal file
@@ -0,0 +1,158 @@
|
||||
import type { NextApiRequest, NextApiResponse } from 'next';
|
||||
import { connectToDatabase, Model } from '@/service/mongo';
|
||||
import { getOpenAIApi } from '@/service/utils/chat';
|
||||
import { httpsAgent, openaiChatFilter, authOpenApiKey } from '@/service/utils/tools';
|
||||
import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
|
||||
import { ChatItemType } from '@/types/chat';
|
||||
import { jsonRes } from '@/service/response';
|
||||
import { PassThrough } from 'stream';
|
||||
import { modelList } from '@/constants/model';
|
||||
import { pushChatBill } from '@/service/events/pushBill';
|
||||
import { gpt35StreamResponse } from '@/service/utils/openai';
|
||||
|
||||
/* 发送提示词 */
|
||||
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
|
||||
let step = 0; // step=1时,表示开始了流响应
|
||||
const stream = new PassThrough();
|
||||
stream.on('error', () => {
|
||||
console.log('error: ', 'stream error');
|
||||
stream.destroy();
|
||||
});
|
||||
res.on('close', () => {
|
||||
stream.destroy();
|
||||
});
|
||||
res.on('error', () => {
|
||||
console.log('error: ', 'request error');
|
||||
stream.destroy();
|
||||
});
|
||||
|
||||
try {
|
||||
const {
|
||||
prompts,
|
||||
modelId,
|
||||
isStream = true
|
||||
} = req.body as {
|
||||
prompts: ChatItemType[];
|
||||
modelId: string;
|
||||
isStream: boolean;
|
||||
};
|
||||
|
||||
if (!prompts || !modelId) {
|
||||
throw new Error('缺少参数');
|
||||
}
|
||||
if (!Array.isArray(prompts)) {
|
||||
throw new Error('prompts is not array');
|
||||
}
|
||||
if (prompts.length > 30 || prompts.length === 0) {
|
||||
throw new Error('prompts length range 1-30');
|
||||
}
|
||||
|
||||
await connectToDatabase();
|
||||
let startTime = Date.now();
|
||||
|
||||
const { apiKey, userId } = await authOpenApiKey(req);
|
||||
|
||||
const model = await Model.findOne({
|
||||
_id: modelId,
|
||||
userId
|
||||
});
|
||||
|
||||
if (!model) {
|
||||
throw new Error('无权使用该模型');
|
||||
}
|
||||
|
||||
const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
|
||||
if (!modelConstantsData) {
|
||||
throw new Error('模型加载异常');
|
||||
}
|
||||
|
||||
// 如果有系统提示词,自动插入
|
||||
if (model.systemPrompt) {
|
||||
prompts.unshift({
|
||||
obj: 'SYSTEM',
|
||||
value: model.systemPrompt
|
||||
});
|
||||
}
|
||||
|
||||
// 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[] = 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);
|
||||
|
||||
// 获取 chatAPI
|
||||
const chatAPI = getOpenAIApi(apiKey);
|
||||
// 发出请求
|
||||
const chatResponse = await chatAPI.createChatCompletion(
|
||||
{
|
||||
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: isStream,
|
||||
stop: ['.!?。']
|
||||
},
|
||||
{
|
||||
timeout: 40000,
|
||||
responseType: isStream ? 'stream' : 'json',
|
||||
httpsAgent: httpsAgent(true)
|
||||
}
|
||||
);
|
||||
|
||||
console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
|
||||
|
||||
step = 1;
|
||||
let responseContent = '';
|
||||
|
||||
if (isStream) {
|
||||
const streamResponse = await gpt35StreamResponse({
|
||||
res,
|
||||
stream,
|
||||
chatResponse
|
||||
});
|
||||
responseContent = streamResponse.responseContent;
|
||||
} else {
|
||||
responseContent = chatResponse.data.choices?.[0]?.message?.content || '';
|
||||
jsonRes(res, {
|
||||
data: responseContent
|
||||
});
|
||||
}
|
||||
|
||||
const promptsContent = formatPrompts.map((item) => item.content).join('');
|
||||
|
||||
// 只有使用平台的 key 才计费
|
||||
pushChatBill({
|
||||
isPay: true,
|
||||
modelName: model.service.modelName,
|
||||
userId,
|
||||
text: promptsContent + responseContent
|
||||
});
|
||||
} catch (err: any) {
|
||||
if (step === 1) {
|
||||
// 直接结束流
|
||||
console.log('error,结束');
|
||||
stream.destroy();
|
||||
} else {
|
||||
res.status(500);
|
||||
jsonRes(res, {
|
||||
code: 500,
|
||||
error: err
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -83,25 +83,26 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
|
||||
下面是一些例子:
|
||||
实现一个手机号发生注册验证码方法.
|
||||
1. 从 query 中获取 phone.
|
||||
2. 校验手机号格式是否正确,不正确则返回错误响应,消息为:手机号格式错误.
|
||||
2. 校验手机号格式是否正确,不正确则返回错误码501,原因为:手机号格式错误.
|
||||
3. 给 phone 发送一个短信验证码,验证码长度为6位字符串,内容为:你正在注册laf,验证码为:code.
|
||||
4. 数据库添加数据,表为"codes",内容为 {phone, code}.
|
||||
|
||||
实现根据手机号注册账号,需要验证手机验证码.
|
||||
1. 从 body 中获取 phone 和 code.
|
||||
2. 校验手机号格式是否正确,不正确返回错误响应,消息为:手机号格式错误.
|
||||
2. 获取数据库数据,表为"codes",查找是否有符合 phone, code 等于body参数的记录,没有的话错误响应,消息为:验证码不正确.
|
||||
2. 校验手机号格式是否正确,不正确则返回错误码501,原因为:手机号格式错误.
|
||||
2. 获取数据库数据,表为"codes",查找是否有符合 phone, code 等于body参数的记录,没有的话返回错误码500,原因为:验证码不正确.
|
||||
4. 添加数据库数据,表为"users" ,内容为{phone, code, createTime}.
|
||||
5. 删除数据库数据,删除 code 记录.
|
||||
6. 返回新建用户的Id: return {userId}
|
||||
|
||||
更新博客记录。传入blogId,blogText,tags,还需要记录更新的时间.
|
||||
1. 从 body 中获取 blogId,blogText 和 tags.
|
||||
2. 校验 blogId 是否为空,为空则错误响应,消息为:博客ID不能为空.
|
||||
3. 校验 blogText 是否为空,为空则错误响应,消息为:博客内容不能为空.
|
||||
4. 校验 tags 是否为数组,不是则错误响应,消息为:标签必须为数组.
|
||||
2. 校验 blogId 是否为空,为空则返回错误码500,原因为:博客ID不能为空.
|
||||
3. 校验 blogText 是否为空,为空则返回错误码500,原因为:博客内容不能为空.
|
||||
4. 校验 tags 是否为数组,不是则返回错误码500,原因为:标签必须为数组.
|
||||
5. 获取当前时间,记录为 updateTime.
|
||||
6. 更新数据库数据,表为"blogs",更新符合 blogId 的记录的内容为{blogText, tags, updateTime}.
|
||||
7. 返回结果 {message: "更新博客记录成功"}.`
|
||||
7. 返回结果 "更新博客记录成功"`
|
||||
},
|
||||
{
|
||||
role: 'user',
|
||||
@@ -161,8 +162,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
|
||||
}
|
||||
}
|
||||
|
||||
// textArr 筛选,最多 3200 tokens
|
||||
const systemPrompt = systemPromptFilter(formatRedisPrompt, 3200);
|
||||
// textArr 筛选,最多 3000 tokens
|
||||
const systemPrompt = systemPromptFilter(formatRedisPrompt, 3000);
|
||||
|
||||
prompts.unshift({
|
||||
obj: 'SYSTEM',
|
||||
|
||||
@@ -10,7 +10,7 @@ import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } fr
|
||||
import { ChatItemType } from '@/types/chat';
|
||||
import { jsonRes } from '@/service/response';
|
||||
import { PassThrough } from 'stream';
|
||||
import { modelList } from '@/constants/model';
|
||||
import { modelList, ModelVectorSearchModeMap, ModelVectorSearchModeEnum } from '@/constants/model';
|
||||
import { pushChatBill } from '@/service/events/pushBill';
|
||||
import { connectRedis } from '@/service/redis';
|
||||
import { VecModelDataPrefix } from '@/constants/redis';
|
||||
@@ -84,11 +84,13 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
|
||||
text: prompts[prompts.length - 1].value // 取最后一个
|
||||
});
|
||||
|
||||
// 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
|
||||
const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
|
||||
// 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
|
||||
const redisData: any[] = await redis.sendCommand([
|
||||
'FT.SEARCH',
|
||||
`idx:${VecModelDataPrefix}:hash`,
|
||||
`@modelId:{${modelId}} @vector:[VECTOR_RANGE 0.22 $blob]=>{$YIELD_DISTANCE_AS: score}`,
|
||||
`@modelId:{${modelId}} @vector:[VECTOR_RANGE ${similarity} $blob]=>{$YIELD_DISTANCE_AS: score}`,
|
||||
'RETURN',
|
||||
'1',
|
||||
'text',
|
||||
@@ -120,7 +122,24 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
|
||||
formatRedisPrompt.unshift(prompts.shift()?.value || '');
|
||||
}
|
||||
|
||||
if (formatRedisPrompt.length > 0) {
|
||||
/* 高相似度+退出,无法匹配时直接退出 */
|
||||
if (
|
||||
formatRedisPrompt.length === 0 &&
|
||||
model.search.mode === ModelVectorSearchModeEnum.hightSimilarity
|
||||
) {
|
||||
return res.send('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 */
|
||||
if (
|
||||
formatRedisPrompt.length === 0 &&
|
||||
model.search.mode === ModelVectorSearchModeEnum.noContext
|
||||
) {
|
||||
prompts.unshift({
|
||||
obj: 'SYSTEM',
|
||||
value: model.systemPrompt
|
||||
});
|
||||
} else {
|
||||
// 有匹配或者低匹配度模式情况下,添加知识库内容。
|
||||
// 系统提示词过滤,最多 2800 tokens
|
||||
const systemPrompt = systemPromptFilter(formatRedisPrompt, 2800);
|
||||
|
||||
@@ -130,8 +149,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
|
||||
'YYYY/MM/DD HH:mm:ss'
|
||||
)} ${systemPrompt}"`
|
||||
});
|
||||
} else {
|
||||
return res.send('对不起,你的问题不在知识库中。');
|
||||
}
|
||||
|
||||
// 控制在 tokens 数量,防止超出
|
||||
|
||||
@@ -15,7 +15,8 @@ import {
|
||||
Menu,
|
||||
MenuButton,
|
||||
MenuList,
|
||||
MenuItem
|
||||
MenuItem,
|
||||
Input
|
||||
} from '@chakra-ui/react';
|
||||
import type { ModelSchema } from '@/types/mongoSchema';
|
||||
import type { RedisModelDataItemType } from '@/types/redis';
|
||||
@@ -40,9 +41,11 @@ const SelectFileModel = dynamic(() => import('./SelectFileModal'));
|
||||
const SelectUrlModel = dynamic(() => import('./SelectUrlModal'));
|
||||
const SelectCsvModal = dynamic(() => import('./SelectCsvModal'));
|
||||
|
||||
let lastSearch = '';
|
||||
|
||||
const ModelDataCard = ({ model }: { model: ModelSchema }) => {
|
||||
const { Loading, setIsLoading } = useLoading();
|
||||
|
||||
const [searchText, setSearchText] = useState('');
|
||||
const {
|
||||
data: modelDataList,
|
||||
isLoading,
|
||||
@@ -54,7 +57,8 @@ const ModelDataCard = ({ model }: { model: ModelSchema }) => {
|
||||
api: getModelDataList,
|
||||
pageSize: 8,
|
||||
params: {
|
||||
modelId: model._id
|
||||
modelId: model._id,
|
||||
searchText
|
||||
}
|
||||
});
|
||||
|
||||
@@ -158,9 +162,33 @@ const ModelDataCard = ({ model }: { model: ModelSchema }) => {
|
||||
</MenuList>
|
||||
</Menu>
|
||||
</Flex>
|
||||
{!!(splitDataLen && splitDataLen > 0) && (
|
||||
<Box fontSize={'xs'}>{splitDataLen}条数据正在拆分...</Box>
|
||||
)}
|
||||
<Flex mt={4}>
|
||||
{/* 拆分数据提示 */}
|
||||
{!!(splitDataLen && splitDataLen > 0) && (
|
||||
<Box fontSize={'xs'}>{splitDataLen}条数据正在拆分...</Box>
|
||||
)}
|
||||
<Box flex={1}></Box>
|
||||
<Input
|
||||
maxW={'240px'}
|
||||
size={'sm'}
|
||||
value={searchText}
|
||||
placeholder="搜索相关问题和答案,回车确认"
|
||||
onChange={(e) => setSearchText(e.target.value)}
|
||||
onBlur={() => {
|
||||
if (searchText === lastSearch) return;
|
||||
getData(1);
|
||||
lastSearch = searchText;
|
||||
}}
|
||||
onKeyDown={(e) => {
|
||||
if (searchText === lastSearch) return;
|
||||
if (e.key === 'Enter') {
|
||||
getData(1);
|
||||
lastSearch = searchText;
|
||||
}
|
||||
}}
|
||||
/>
|
||||
</Flex>
|
||||
|
||||
<Box mt={4}>
|
||||
<TableContainer minH={'500px'}>
|
||||
<Table variant={'simple'}>
|
||||
|
||||
@@ -54,20 +54,20 @@ const ModelEditForm = ({
|
||||
})}
|
||||
></Input>
|
||||
</Flex>
|
||||
<Flex alignItems={'center'} mt={4}>
|
||||
<Flex alignItems={'center'} mt={5}>
|
||||
<Box flex={'0 0 80px'} w={0}>
|
||||
modelId:
|
||||
</Box>
|
||||
<Box>{getValues('_id')}</Box>
|
||||
</Flex>
|
||||
</FormControl>
|
||||
<Flex alignItems={'center'} mt={4}>
|
||||
<Flex alignItems={'center'} mt={5}>
|
||||
<Box flex={'0 0 80px'} w={0}>
|
||||
底层模型:
|
||||
模型类型:
|
||||
</Box>
|
||||
<Box>{getValues('service.modelName')}</Box>
|
||||
<Box>{modelList.find((item) => item.model === getValues('service.modelName'))?.name}</Box>
|
||||
</Flex>
|
||||
<Flex alignItems={'center'} mt={4}>
|
||||
<Flex alignItems={'center'} mt={5}>
|
||||
<Box flex={'0 0 80px'} w={0}>
|
||||
价格:
|
||||
</Box>
|
||||
@@ -80,7 +80,7 @@ const ModelEditForm = ({
|
||||
</Box>
|
||||
</Flex>
|
||||
<Flex mt={5} alignItems={'center'}>
|
||||
<Box flex={'0 0 80px'}>删除:</Box>
|
||||
<Box flex={'0 0 150px'}>删除模型和数据集</Box>
|
||||
<Button
|
||||
colorScheme={'gray'}
|
||||
variant={'outline'}
|
||||
|
||||
@@ -21,7 +21,6 @@ const ModelDetail = ({ modelId }: { modelId: string }) => {
|
||||
const { isPc, media } = useScreen();
|
||||
const { setLoading } = useGlobalStore();
|
||||
|
||||
// const SelectFileDom = useRef<HTMLInputElement>(null);
|
||||
const [model, setModel] = useState<ModelSchema>(defaultModel);
|
||||
const formHooks = useForm<ModelSchema>({
|
||||
defaultValues: model
|
||||
@@ -243,11 +242,6 @@ const ModelDetail = ({ modelId }: { modelId: string }) => {
|
||||
<Grid mt={5} gridTemplateColumns={media('1fr 1fr', '1fr')} gridGap={5}>
|
||||
<ModelEditForm formHooks={formHooks} handleDelModel={handleDelModel} canTrain={canTrain} />
|
||||
|
||||
{/* {canTrain && (
|
||||
<Card p={4}>
|
||||
<Training model={model} />
|
||||
</Card>
|
||||
)} */}
|
||||
{canTrain && model._id && (
|
||||
<Card
|
||||
p={4}
|
||||
@@ -263,11 +257,6 @@ const ModelDetail = ({ modelId }: { modelId: string }) => {
|
||||
</Card>
|
||||
)}
|
||||
</Grid>
|
||||
|
||||
{/* 文件选择 */}
|
||||
{/* <Box position={'absolute'} w={0} h={0} overflow={'hidden'}>
|
||||
<input ref={SelectFileDom} type="file" accept=".jsonl" onChange={startTraining} />
|
||||
</Box> */}
|
||||
</>
|
||||
);
|
||||
};
|
||||
|
||||
@@ -16,6 +16,7 @@ import { formatModelStatus } from '@/constants/model';
|
||||
import dayjs from 'dayjs';
|
||||
import type { ModelSchema } from '@/types/mongoSchema';
|
||||
import { useRouter } from 'next/router';
|
||||
import { modelList } from '@/constants/model';
|
||||
|
||||
const ModelTable = ({
|
||||
models = [],
|
||||
@@ -31,6 +32,15 @@ const ModelTable = ({
|
||||
key: 'name',
|
||||
dataIndex: 'name'
|
||||
},
|
||||
{
|
||||
title: '模型类型',
|
||||
key: 'service',
|
||||
render: (model: ModelSchema) => (
|
||||
<Box fontWeight={'bold'} whiteSpace={'pre-wrap'} maxW={'200px'}>
|
||||
{modelList.find((item) => item.model === model.service.modelName)?.name}
|
||||
</Box>
|
||||
)
|
||||
},
|
||||
{
|
||||
title: '最后更新时间',
|
||||
key: 'updateTime',
|
||||
@@ -51,15 +61,7 @@ const ModelTable = ({
|
||||
</Tag>
|
||||
)
|
||||
},
|
||||
{
|
||||
title: 'AI模型',
|
||||
key: 'service',
|
||||
render: (item: ModelSchema) => (
|
||||
<Box wordBreak={'break-all'} whiteSpace={'pre-wrap'} maxW={'200px'}>
|
||||
{item.service.modelName}
|
||||
</Box>
|
||||
)
|
||||
},
|
||||
|
||||
{
|
||||
title: '操作',
|
||||
key: 'control',
|
||||
@@ -69,7 +71,7 @@ const ModelTable = ({
|
||||
对话
|
||||
</Button>
|
||||
<Button
|
||||
colorScheme={'gray'}
|
||||
variant={'outline'}
|
||||
onClick={() => router.push(`/model/detail?modelId=${item._id}`)}
|
||||
>
|
||||
编辑
|
||||
|
||||
@@ -30,7 +30,7 @@ const BillTable = () => {
|
||||
<Th>类型</Th>
|
||||
<Th>内容长度</Th>
|
||||
<Th>Tokens 长度</Th>
|
||||
<Th>消费</Th>
|
||||
<Th>金额</Th>
|
||||
</Tr>
|
||||
</Thead>
|
||||
<Tbody fontSize={'sm'}>
|
||||
|
||||
@@ -77,7 +77,7 @@ const PayRecordTable = () => {
|
||||
<Th>订单号</Th>
|
||||
<Th>时间</Th>
|
||||
<Th>金额</Th>
|
||||
<Th>消费</Th>
|
||||
<Th>状态</Th>
|
||||
<Th></Th>
|
||||
</Tr>
|
||||
</Thead>
|
||||
|
||||
@@ -21,7 +21,7 @@ export const pushChatBill = async ({
|
||||
|
||||
try {
|
||||
// 计算 token 数量
|
||||
const tokens = Math.floor(encode(text).length * 0.7);
|
||||
const tokens = Math.floor(encode(text).length * 0.75);
|
||||
|
||||
console.log(`chat generate success. text len: ${text.length}. token len: ${tokens}`);
|
||||
|
||||
|
||||
Reference in New Issue
Block a user