108 lines
3.4 KiB
TypeScript
108 lines
3.4 KiB
TypeScript
import OpenAI from "openai";
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import storage from 'node-persist'
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import { sendMsg } from "../lib/qq";
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import prompt from './prompt.txt'
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await storage.init();
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storage.clear();
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const client = new OpenAI({
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baseURL: process.env.OPENAI_BASE_URL,
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apiKey: process.env.OPENAI_API_KEY,
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// logLevel: "debug"
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})
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const tools = [{
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type: "function" as const,
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name: "send_msg",
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description: "Send a message to the user. Always use this to respond to the user.",
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parameters: {
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type: "object",
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properties: {
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text: { type: "string", description: "The message content sent to the user through QQ." }
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},
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required: ["text"],
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additionalProperties: false
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},
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strict: true
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}]
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/**
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*
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* @param input 提问
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* @param target_id 用户 QQ 号
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*/
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export async function chat(input: string, target_id: string) {
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const chatHistoryKey = `chat_history_${target_id}`;
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let chatHistory: OpenAI.Responses.ResponseInput = await storage.getItem(chatHistoryKey) || [];
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// 添加新输入到对话历史
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chatHistory.push({ role: "user", content: input });
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// 保存更新后的对话历史
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console.log(`[LLM] 使用对话, 历史：`, chatHistory);
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await storage.setItem(chatHistoryKey, chatHistory);
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const response = await client.responses.create({
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model: process.env.CHAT_MODEL || "gpt-5-nano",
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instructions: prompt,
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reasoning: { effort: 'minimal' },
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input: chatHistory,
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tools
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});
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await storage.setItem(chatHistoryKey, chatHistory);
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// 继续调用工具，直到没有工具调用为止
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await toolUseCycle(response.output);
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async function toolUseCycle(outputArr: OpenAI.Responses.ResponseOutputItem[]) {
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chatHistory.push(...outputArr);
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const functionCalls = (outputArr ?? []).filter(item => item.type === 'function_call');
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console.log("进入 toolUseCycle, with functionCalls", functionCalls.length, "个");
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console.log(JSON.stringify(chatHistory, null, 2));
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if (functionCalls.length == 0) {
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let lastMessage = outputArr.at(-1);
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if (!lastMessage) return
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if (lastMessage.type != 'message') return
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if (lastMessage.role != 'assistant') return
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const msg = lastMessage.content.map(c => c.type == 'output_text' ? c.text : '').join('');
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if (msg.trim().length > 0) {
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// 结束，发送最后的消息
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sendMsg(msg, target_id);
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}
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return
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}
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for (const item of functionCalls ?? []) {
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if (item.name === "send_msg") {
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console.log(item.arguments);
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const { text } = JSON.parse(item.arguments);
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sendMsg(text, target_id);
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chatHistory.push({ type: "function_call_output", call_id: item.call_id, output: "OK" });
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}
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}
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await storage.setItem(chatHistoryKey, chatHistory);
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const response = await client.responses.create({
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model: process.env.CHAT_MODEL || "gpt-5-nano",
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instructions: prompt,
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reasoning: { effort: 'minimal' },
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input: chatHistory,
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tools
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});
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toolUseCycle(response.output);
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}
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}
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export async function resetChat(target_id: string) {
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const chatHistoryKey = `chat_history_${target_id}`;
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await storage.removeItem(chatHistoryKey);
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sendMsg("已为你重置对话历史。", target_id);
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} |