255 lines
8.9 KiB
TypeScript
255 lines
8.9 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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import type { ResponseFunctionToolCall, ResponseOutputMessage } from "openai/resources/responses/responses.mjs";
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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: OpenAI.Responses.Tool[] = [{ type: 'web_search' }]
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/**
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* 将错误对象转成简明可读的字符串，避免进程因未捕获异常退出
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*/
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function formatError(err: any): string {
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try {
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if (!err) return '未知错误';
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if (typeof err === 'string') return err;
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const msg = err.message || err.toString?.() || Object.prototype.toString.call(err);
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const status = err.status ?? err.statusCode ?? err.response?.status;
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const detail = err.error?.message
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?? err.response?.data?.error?.message
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?? err.response?.data?.message
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?? err.data?.error?.message
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?? '';
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const parts = [] as string[];
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if (status) parts.push(`HTTP ${status}`);
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if (msg) parts.push(String(msg));
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if (detail && detail !== msg) parts.push(`详情: ${String(detail)}`);
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return parts.join(' | ') || '未知错误';
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} catch {
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return String(err);
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}
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}
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/**
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*
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* @param input 提问
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* @param target_id 用户 QQ 号
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*/
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export async function chat(input: MessageData[], target_id: string) {
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const chatHistoryKey = `chat_history_${target_id}`;
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await waitForQueueEmpty(target_id);
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let chatHistory: OpenAI.Responses.ResponseInput = await storage.getItem(chatHistoryKey) || [];
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if(chatHistory.length > 40) {
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sendMsg(`[提示] 当前对话轮数：${chatHistory.length}，过长的对话会降低输出质量，如果你准备好了，建议输入"/reset"来重置对话历史。`, target_id);
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}
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if(chatHistory.length > 100) {
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sendMsg(`[提示] 当前对话轮数：${chatHistory.length}，对话过长可能导致模型无法正常工作，模型将只保留最近100条记录。`, target_id);
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chatHistory = chatHistory.slice(-40);
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await storage.setItem(chatHistoryKey, chatHistory);
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}
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// 添加新输入到对话历史
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const userContent: OpenAI.Responses.ResponseInputContent[] = []
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for (const element of input) {
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if (element.type == 'text') {
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userContent.push({ type: "input_text", text: element.data.text });
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} else if (element.type == 'image') {
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userContent.push({ type: "input_image", image_url: element.data.url, detail: 'low' });
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}
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}
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if (userContent.length === 0) {
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console.log("[LLM] 空消息，跳过");
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sendMsg("未能识别的消息类型。", target_id);
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return
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}
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chatHistory.push({ role: "user", content: userContent });
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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：`, JSON.stringify(chatHistory, null, 0));
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await storage.setItem(chatHistoryKey, chatHistory);
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let response: OpenAI.Responses.Response | undefined;
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try {
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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: process.env.CHAT_MODEL_REASONING_EFFORT as any || 'minimal' },
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input: chatHistory,
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tools
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});
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} catch (err) {
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const errText = formatError(err);
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console.error('[LLM] 首次调用 responses.create 失败:', errText);
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scheduleSendMsg(`[错误] 模型接口调用失败：${errText}`, target_id);
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return; // 终止本次对话流程，避免未捕获异常导致进程退出
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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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if (!response?.output || response.output.length === 0) {
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console.warn('[LLM] responses.create 返回空输出，结束本轮。');
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return;
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}
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await toolUseCycle(response.output);
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async function toolUseCycle(outputArr: OpenAI.Responses.ResponseOutputItem[]) {
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if (!outputArr || outputArr.length === 0) return;
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chatHistory.push(...outputArr);
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await storage.setItem(chatHistoryKey, chatHistory);
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const assistantReply = outputArr.filter(item => item.type === 'message' && item.role === 'assistant') as ResponseOutputMessage[];
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const functionCalls = outputArr.filter(item => item.type === 'function_call') as ResponseFunctionToolCall[];
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console.log("进入 toolUseCycle, with functionCalls", functionCalls.length, "个");
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console.log(JSON.stringify(chatHistory, null, 0));
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if (assistantReply.length > 0) {
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const replyText = assistantReply.map(item => item.content).flat().filter(con => con.type == 'output_text').map(con => con.text).join("[newline]");
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console.log(`[LLM] 回复:`, replyText);
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scheduleSendMsg(replyText, target_id);
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}
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if (functionCalls.length == 0) {
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return
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}
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for (const item of functionCalls ?? []) {
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}
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await storage.setItem(chatHistoryKey, chatHistory);
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let response: OpenAI.Responses.Response | undefined;
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try {
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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: process.env.CHAT_MODEL_REASONING_EFFORT as any || 'minimal' },
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input: chatHistory,
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tools
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});
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} catch (err) {
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const errText = formatError(err);
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console.error('[LLM] 工具循环内调用 responses.create 失败:', errText);
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scheduleSendMsg(`[错误] 工具调用阶段失败：${errText}`, target_id);
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return; // 结束工具循环，避免崩溃
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}
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if (!response?.output || response.output.length === 0) {
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console.warn('[LLM] 工具循环内 responses.create 返回空输出，结束循环。');
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return;
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}
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toolUseCycle(response.output);
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}
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}
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const msgQueue: Record<string, string[]> = {}
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const msgInQueue: Record<string, boolean> = {}
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const queueEmptyPromises: Record<string, (() => void)[]> = {}
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/** 统一的“队列已空”通知 */
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function resolveDrain(target_id: string) {
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const waiters = queueEmptyPromises[target_id];
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if (waiters && waiters.length) {
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// 逐个 resolve 并清空
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waiters.splice(0).forEach(resolve => resolve());
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}
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}
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/** 仅在需要时启动调度；空队列时会 resolve 等待者 */
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function startMsgScheduler(target_id: string) {
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// 确保队列存在
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const q = msgQueue[target_id] ?? (msgQueue[target_id] = []);
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// 若正在发送，交给当前发送完成后再递归调度
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if (msgInQueue[target_id]) return;
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// 队列空 => 通知等待者并返回
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if (q.length === 0) {
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resolveDrain(target_id);
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return;
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}
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// 取下一条并发送
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msgInQueue[target_id] = true;
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const msg = q.shift()!; // 这里一定有元素
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const msgDelay = Math.sqrt(msg.length) * 200 + 500; // 可按需加上限
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setTimeout(async () => {
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try {
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await sendMsg(msg, target_id);
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} catch (err) {
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console.error("[queue] sendMsg error:", err);
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// 可选：把消息放回队首重试
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// q.unshift(msg);
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} finally {
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// 本次发送结束
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msgInQueue[target_id] = false;
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// 如果此刻队列已空，立即通知等待者
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if (q.length === 0) {
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resolveDrain(target_id);
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}
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// 继续调度后续消息（若有）
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startMsgScheduler(target_id);
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}
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}, msgDelay);
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}
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function scheduleSendMsg(input: string, target_id: string) {
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if (!msgQueue[target_id]) {
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msgQueue[target_id] = [];
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}
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// 切分 + 去空白项
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const parts = input
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.split("[newline]")
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.map(s => s.trim())
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.filter(Boolean);
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if (parts.length === 0) return; // 全是空白，直接略过
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msgQueue[target_id].push(...parts);
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startMsgScheduler(target_id);
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}
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function waitForQueueEmpty(target_id: string) {
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return new Promise<void>((resolve) => {
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const q = msgQueue[target_id];
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// 条件：不在发送中，且队列不存在或为空
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const isIdle = !msgInQueue[target_id];
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const isEmpty = !q || q.length === 0;
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if (isIdle && isEmpty) {
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resolve();
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return;
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}
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if (!queueEmptyPromises[target_id]) {
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queueEmptyPromises[target_id] = [];
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}
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queueEmptyPromises[target_id].push(resolve);
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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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} |