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feat: lafgpt。openapi schema

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This commit is contained in:
archer
2023-04-06 15:25:48 +08:00
parent 8a02b3b04a
commit f88c6031f5
6 changed files with 85 additions and 54 deletions
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4
src/pages/api/chat/vectorGpt.ts
View File

@@ -105,8 +105,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
throw new Error('对不起，我没有找到你的问题');
}
// textArr 筛选，最多 3000 tokens
const systemPrompt = systemPromptFilter(formatRedisPrompt, 3400);
// textArr 筛选，最多 3200 tokens
const systemPrompt = systemPromptFilter(formatRedisPrompt, 3200);
prompts.unshift({
obj: 'SYSTEM',

101
src/pages/api/openapi/lafGpt.ts
View File

@@ -1,20 +1,18 @@
import type { NextApiRequest, NextApiResponse } from 'next';
import { createParser, ParsedEvent, ReconnectInterval } from 'eventsource-parser';
import { connectToDatabase } from '@/service/mongo';
import { getOpenAIApi, authChat } from '@/service/utils/chat';
import { connectToDatabase, Model } from '@/service/mongo';
import { getOpenAIApi } from '@/service/utils/chat';
import { authToken } from '@/service/utils/tools';
import { httpsAgent, openaiChatFilter, systemPromptFilter } from '@/service/utils/tools';
import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
import { ChatItemType } from '@/types/chat';
import { jsonRes } from '@/service/response';
import type { ModelSchema } from '@/types/mongoSchema';
import { PassThrough } from 'stream';
import { modelList } from '@/constants/model';
import { ChatModelNameEnum, modelList, ChatModelNameMap } from '@/constants/model';
import { pushChatBill } from '@/service/events/pushBill';
import { connectRedis } from '@/service/redis';
import { VecModelDataPrefix } from '@/constants/redis';
import { vectorToBuffer } from '@/utils/tools';
import { openaiCreateEmbedding } from '@/service/utils/openai';
import { gpt35StreamResponse } from '@/service/utils/openai';
import { openaiCreateEmbedding, getOpenApiKey, gpt35StreamResponse } from '@/service/utils/openai';
/* 发送提示词 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -33,13 +31,13 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
});
try {
const { chatId, prompt } = req.body as {
const { prompt, modelId } = req.body as {
prompt: ChatItemType;
chatId: string;
modelId: string;
};
const { authorization } = req.headers;
if (!chatId || !prompt) {
if (!prompt) {
throw new Error('缺少参数');
}
@@ -47,49 +45,57 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const redis = await connectRedis();
let startTime = Date.now();
const { chat, userApiKey, systemKey, userId } = await authChat(chatId, authorization);
/* 凭证校验 */
const userId = await authToken(authorization);
const { userApiKey, systemKey } = await getOpenApiKey(userId);
const model: ModelSchema = chat.modelId;
const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
if (!modelConstantsData) {
throw new Error('模型加载异常');
/* 查找数据库里的模型信息 */
const model = await Model.findById(modelId);
if (!model) {
throw new Error('找不到模型');
}
const modelConstantsData = modelList.find(
(item) => item.model === ChatModelNameEnum.VECTOR_GPT
);
if (!modelConstantsData) {
throw new Error('模型已下架');
}
// 获取 chatAPI
const chatAPI = getOpenAIApi(userApiKey || systemKey);
// 请求一次 chatgpt 拆解需求
const promptResponse = await chatAPI.createChatCompletion(
{
model: model.service.chatModel,
model: ChatModelNameMap[ChatModelNameEnum.GPT35],
temperature: 0,
// max_tokens: modelConstantsData.maxToken,
messages: [
{
role: 'system',
content: `服务端逻辑生成器。根据用户输入的需求，拆解成代码实现的步骤，并按格式返回： 1.\n2.\n3.\n ......
content: `服务端逻辑生成器.根据用户输入的需求,拆解成代码实现的步骤,并按格式返回: 1.\n2.\n3.\n ......
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,不正确返回{error: "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}.
下面是一些例子：
实现一个手机号注册账号的方法，包含两个函数
* 发送手机验证码函数：
1. 从 query 中获取 phone
2. 校验手机号格式是否正确，不正确返回{error: "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}
* 注册函数
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{error: "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 {error:"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
---------------
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，为空则返回 {error: "博客ID不能为空"}
3. 校验 blogText 是否为空，为空则返回 {error: "博客内容不能为空"}
4. 校验 tags 是否为数组，不是则返回 {error: "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"}`
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{error: "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 {error:"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.
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,为空则返回 {error: "博客ID不能为空"}.
3. 校验 blogText 是否为空,为空则返回 {error: "博客内容不能为空"}.
4. 校验 tags 是否为数组,不是则返回 {error: "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"}.`
},
{
role: 'user',
@@ -120,16 +126,15 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
});
// 读取对话内容
const prompts = [...chat.content, prompt];
const prompts = [prompt];
// 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:${VecModelDataPrefix}:hash`,
`@modelId:{${String(
chat.modelId._id
model._id
)}} @vector:[VECTOR_RANGE 0.25 $blob]=>{$YIELD_DISTANCE_AS: score}`,
// `@modelId:{${String(chat.modelId._id)}}=>[KNN 10 @vector $blob AS score]`,
'RETURN',
'1',
'text',
@@ -162,8 +167,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
throw new Error('对不起，我没有找到你的问题');
}
// textArr 筛选，最多 3000 tokens
const systemPrompt = systemPromptFilter(formatRedisPrompt, 3400);
// textArr 筛选，最多 3200 tokens
const systemPrompt = systemPromptFilter(formatRedisPrompt, 3200);
prompts.unshift({
obj: 'SYSTEM',
@@ -185,7 +190,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
content: item.value
})
);
console.log(formatPrompts);
// console.log(formatPrompts);
// 计算温度
const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
@@ -207,7 +212,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}
);
console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
console.log('api response. time:', `${(Date.now() - startTime) / 1000}s`);
step = 1;
const { responseContent } = await gpt35StreamResponse({
@@ -215,6 +220,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
stream,
chatResponse
});
console.log('response done. time:', `${(Date.now() - startTime) / 1000}s`);
const promptsContent = formatPrompts.map((item) => item.content).join('');
// 只有使用平台的 key 才计费
@@ -222,7 +228,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
isPay: !userApiKey,
modelName: model.service.modelName,
userId,
chatId,
text: promptsContent + responseContent
});
} catch (err: any) {

1
src/pages/chat/index.tsx
View File

@@ -120,7 +120,6 @@ const Chat = ({ chatId }: { chatId: string }) => {
const urlMap: Record<string, string> = {
[ChatModelNameEnum.GPT35]: '/api/chat/chatGpt',
[ChatModelNameEnum.VECTOR_GPT]: '/api/chat/vectorGpt',
// [ChatModelNameEnum.VECTOR_GPT]: '/api/chat/lafGpt',
[ChatModelNameEnum.GPT3]: '/api/chat/gpt3'
};

2
src/service/events/pushBill.ts
View File

@@ -15,7 +15,7 @@ export const pushChatBill = async ({
isPay: boolean;
modelName: string;
userId: string;
chatId: string;
chatId?: string;
text: string;
}) => {
let billId;

20
src/service/models/openapi.ts Normal file
View File

@@ -0,0 +1,20 @@
import { Schema, model, models, Model } from 'mongoose';
import { OpenApiSchema } from '@/types/mongoSchema';
const OpenApiSchema = new Schema({
userId: {
type: Schema.Types.ObjectId,
ref: 'user',
required: true
},
createTime: {
type: Date,
default: () => new Date()
},
lastUsedTime: {
type: Date,
default: () => new Date()
}
});
export const OpenApi: Model<OpenApiSchema> = models['openapi'] || model('openapi', OpenApiSchema);

9
src/types/mongoSchema.d.ts vendored
View File

@@ -125,7 +125,7 @@ export interface DataSchema {
_id: string;
userId: string;
name: string;
createTime: string;
createTime: Date;
type: DataType;
}
@@ -148,3 +148,10 @@ export interface DataItemSchema {
export interface DataItemPopulate extends DataItemSchema {
userId: UserModelSchema;
}
export interface OpenApiSchema {
_id: string;
userId: string;
createTime: Date;
lastUsedTime: Date;
}