From f88c6031f527edce8028d6f6053f0869be2227c0 Mon Sep 17 00:00:00 2001 From: archer <545436317@qq.com> Date: Thu, 6 Apr 2023 15:25:48 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20lafgpt=E3=80=82openapi=20schema?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/pages/api/chat/vectorGpt.ts | 4 +- src/pages/api/openapi/lafGpt.ts | 103 +++++++++++++++++--------------- src/pages/chat/index.tsx | 1 - src/service/events/pushBill.ts | 2 +- src/service/models/openapi.ts | 20 +++++++ src/types/mongoSchema.d.ts | 9 ++- 6 files changed, 85 insertions(+), 54 deletions(-) create mode 100644 src/service/models/openapi.ts diff --git a/src/pages/api/chat/vectorGpt.ts b/src/pages/api/chat/vectorGpt.ts index 1426a7945..3e3786646 100644 --- a/src/pages/api/chat/vectorGpt.ts +++ b/src/pages/api/chat/vectorGpt.ts @@ -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', diff --git a/src/pages/api/openapi/lafGpt.ts b/src/pages/api/openapi/lafGpt.ts index 162d40d4c..9fac953ec 100644 --- a/src/pages/api/openapi/lafGpt.ts +++ b/src/pages/api/openapi/lafGpt.ts @@ -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 ...... - - 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"}` + 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}. + +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) { diff --git a/src/pages/chat/index.tsx b/src/pages/chat/index.tsx index 243e254e8..9cd93752e 100644 --- a/src/pages/chat/index.tsx +++ b/src/pages/chat/index.tsx @@ -120,7 +120,6 @@ const Chat = ({ chatId }: { chatId: string }) => { const urlMap: Record = { [ChatModelNameEnum.GPT35]: '/api/chat/chatGpt', [ChatModelNameEnum.VECTOR_GPT]: '/api/chat/vectorGpt', - // [ChatModelNameEnum.VECTOR_GPT]: '/api/chat/lafGpt', [ChatModelNameEnum.GPT3]: '/api/chat/gpt3' }; diff --git a/src/service/events/pushBill.ts b/src/service/events/pushBill.ts index db2523c15..b005caccf 100644 --- a/src/service/events/pushBill.ts +++ b/src/service/events/pushBill.ts @@ -15,7 +15,7 @@ export const pushChatBill = async ({ isPay: boolean; modelName: string; userId: string; - chatId: string; + chatId?: string; text: string; }) => { let billId; diff --git a/src/service/models/openapi.ts b/src/service/models/openapi.ts new file mode 100644 index 000000000..a76a01424 --- /dev/null +++ b/src/service/models/openapi.ts @@ -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 = models['openapi'] || model('openapi', OpenApiSchema); diff --git a/src/types/mongoSchema.d.ts b/src/types/mongoSchema.d.ts index a0f30578f..174583e10 100644 --- a/src/types/mongoSchema.d.ts +++ b/src/types/mongoSchema.d.ts @@ -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; +}