139 lines
3.5 KiB
TypeScript
139 lines
3.5 KiB
TypeScript
// Next.js API route support: https://nextjs.org/docs/api-routes/introduction
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import type { NextApiRequest, NextApiResponse } from 'next';
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import { jsonRes } from '@/service/response';
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import { adaptChatItem_openAI } from '@/utils/plugin/openai';
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import { ChatContextFilter } from '@/service/utils/chat/index';
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import type { ChatItemType } from '@/types/chat';
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import { ChatRoleEnum } from '@/constants/chat';
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import { getOpenAIApi, axiosConfig } from '@/service/ai/openai';
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import type { ClassifyQuestionAgentItemType } from '@/types/app';
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import { countModelPrice, pushTaskBillListItem } from '@/service/events/pushBill';
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import { getModel } from '@/service/utils/data';
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import { authUser } from '@/service/utils/auth';
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export type Props = {
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systemPrompt?: string;
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history?: ChatItemType[];
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userChatInput: string;
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agents: ClassifyQuestionAgentItemType[];
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billId?: string;
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};
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export type Response = { history: ChatItemType[] };
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const agentModel = 'gpt-3.5-turbo';
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const agentFunName = 'agent_user_question';
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export default async function handler(req: NextApiRequest, res: NextApiResponse) {
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try {
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await authUser({ req, authRoot: true });
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let { userChatInput } = req.body as Props;
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if (!userChatInput) {
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throw new Error('userChatInput is empty');
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}
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const response = await classifyQuestion(req.body);
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jsonRes(res, {
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data: response
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});
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} catch (err) {
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jsonRes(res, {
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code: 500,
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error: err
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});
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}
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}
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/* request openai chat */
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export async function classifyQuestion({
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agents,
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systemPrompt,
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history = [],
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userChatInput,
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billId
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}: Props) {
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const messages: ChatItemType[] = [
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...(systemPrompt
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? [
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{
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obj: ChatRoleEnum.System,
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value: systemPrompt
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}
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]
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: []),
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{
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obj: ChatRoleEnum.Human,
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value: userChatInput
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}
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];
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const filterMessages = ChatContextFilter({
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// @ts-ignore
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model: agentModel,
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prompts: messages,
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maxTokens: 1500
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});
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const adaptMessages = adaptChatItem_openAI({ messages: filterMessages, reserveId: false });
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// function body
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const agentFunction = {
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name: agentFunName,
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description: '判断用户问题的类型，并返回指定值',
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parameters: {
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type: 'object',
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properties: {
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type: {
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type: 'string',
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description: agents.map((item) => `${item.value}，返回：'${item.key}'`).join('；'),
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enum: agents.map((item) => item.key)
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}
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},
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required: ['type']
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}
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};
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const chatAPI = getOpenAIApi();
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const response = await chatAPI.createChatCompletion(
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{
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model: agentModel,
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temperature: 0,
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messages: [...adaptMessages],
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function_call: { name: agentFunName },
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functions: [agentFunction]
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},
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{
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...axiosConfig()
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}
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);
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const arg = JSON.parse(response.data.choices?.[0]?.message?.function_call?.arguments || '');
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if (!arg.type) {
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throw new Error('');
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}
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const totalTokens = response.data.usage?.total_tokens || 0;
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await pushTaskBillListItem({
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billId,
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moduleName: 'Classify Question',
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amount: countModelPrice({ model: agentModel, tokens: totalTokens }),
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model: getModel(agentModel)?.name,
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tokenLen: totalTokens
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});
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console.log(agents.map((item) => `${item.value}，返回: '${item.key}'`).join('；'), arg);
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const result = agents.find((item) => item.key === arg.type);
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if (result) {
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return {
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[arg.type]: 1
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};
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}
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return {
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[agents[0].key]: 1
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};
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}
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