574 lines
19 KiB
JavaScript
574 lines
19 KiB
JavaScript
/**
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* ═══════════════════════════════════════════════════════════
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* 🇨🇳 国内模型智能网关 · Domestic LLM Smart Gateway
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* ═══════════════════════════════════════════════════════════
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*
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* 编号: ZY-DOMESTIC-LLM-001
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* 守护: 铸渊 · ICE-GL-ZY001
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* 版权: 国作登字-2026-A-00037559
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*
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* 核心原则 (冰朔指令):
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* - 国内四个官方模型API密钥，不显示模型具体名字
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* - 用户不需要手动选择模型
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* - 由系统/人格体根据需求+成本动态切换
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* - 与第三方代理模型线路完全分开
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*
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* 四条国内官方线路:
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* 1. DeepSeek (ZY_DEEPSEEK_API_KEY)
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* 2. 通义千问 Qwen (ZY_QIANWEN_API_KEY)
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* 3. Moonshot/Kimi (ZY_KIMI_API_KEY)
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* 4. 智谱清言 (ZY_QINGYAN_API_KEY)
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*/
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'use strict';
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const https = require('https');
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const http = require('http');
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// ─── 广州CN中继配置 ───
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// 当配置了 ZY_CN_LLM_RELAY_HOST 时，请求走广州中继（国内直连·低延迟）
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// 广州不可达时降级为直连国内API（跨境·高延迟但可用）
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// Phase A3 修复: 按 ZY_SERVER_REGION 决定是否启用中继
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// - sg (新加坡) → 直连国内API（不走中继，避免30s超时）
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// - cn (广州/国内) → 走中继（低延迟）
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// - 未设置 → 检查 ZY_CN_LLM_RELAY_HOST 是否存在来决定
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const SERVER_REGION = (process.env.ZY_SERVER_REGION || '').toLowerCase().trim();
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const CN_RELAY_HOST = (process.env.ZY_CN_LLM_RELAY_HOST || '').trim();
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const SKIP_CN_RELAY = ['true', '1', 'yes'].includes((process.env.ZY_SKIP_CN_RELAY || '').toLowerCase().trim());
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const CN_RELAY_PORT = parseInt(process.env.ZY_CN_LLM_RELAY_PORT || '3900', 10);
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const CN_RELAY_KEY = process.env.ZY_CN_LLM_RELAY_KEY || '';
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const CN_RELAY_TIMEOUT = parseInt(process.env.ZY_CN_LLM_RELAY_TIMEOUT || '30000', 10);
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// 中继启用逻辑：仅在国内服务器区域 或 明确配置了中继地址且非新加坡时启用
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const USE_CN_RELAY = !SKIP_CN_RELAY && CN_RELAY_HOST && CN_RELAY_KEY && SERVER_REGION !== 'sg';
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// ─── 国内模型配置（不对外暴露模型名称） ───
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const DOMESTIC_MODELS = [
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{
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id: 'ds',
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model: 'deepseek-chat',
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endpoint: 'https://api.deepseek.com/v1/chat/completions',
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envKey: 'ZY_DEEPSEEK_API_KEY',
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costPerMToken: { input: 1.0, output: 2.0 },
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tier: 'economy',
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maxTokens: 4096,
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priority: 1
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},
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{
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id: 'qw',
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model: 'qwen-turbo',
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endpoint: 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions',
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envKey: 'ZY_QIANWEN_API_KEY',
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costPerMToken: { input: 0.3, output: 0.6 },
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tier: 'economy',
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maxTokens: 4096,
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priority: 2
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},
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{
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id: 'km',
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model: 'moonshot-v1-8k',
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endpoint: 'https://api.moonshot.cn/v1/chat/completions',
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envKey: 'ZY_KIMI_API_KEY',
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costPerMToken: { input: 1.0, output: 1.0 },
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tier: 'economy',
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maxTokens: 4096,
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priority: 3
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},
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{
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id: 'zp',
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model: 'glm-4-flash',
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endpoint: 'https://open.bigmodel.cn/api/paas/v4/chat/completions',
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envKey: 'ZY_QINGYAN_API_KEY',
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costPerMToken: { input: 0.1, output: 0.1 },
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tier: 'economy',
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maxTokens: 4096,
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priority: 4
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}
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];
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// ─── 深度推理触发模式 ───
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const DEEP_PATTERNS = [
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/分析|推理|评估|审查|review|analyze/i,
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/架构|设计|重构|方案|strategy|规划/i,
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/为什么|原因|解释.*原理|how.*work/i,
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/复杂|困难|棘手|tricky|complex/i,
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/安全|漏洞|vulnerability|security/i,
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/调试|debug|排查|诊断|diagnose/i,
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/优化|性能|performance|bottleneck/i
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];
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// ─── 简单对话模式 ───
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const SIMPLE_PATTERNS = [
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/^(你好|hi|hello|嗨|在吗|早|晚安).{0,10}$/i,
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/^(谢谢|感谢|thank|ok|好的|对|没问题).{0,10}$/i
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];
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// ─── 网关状态 ───
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const gatewayState = {
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totalCalls: 0,
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successCalls: 0,
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failedCalls: 0,
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modelStats: {},
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lastError: null,
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startTime: Date.now()
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};
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/**
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* 智能选择模型（用户不感知具体模型名称）
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*/
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function selectModel(message, context = {}) {
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const msgLen = message.length;
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const isDeep = DEEP_PATTERNS.some(p => p.test(message));
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const isSimple = SIMPLE_PATTERNS.some(p => p.test(message));
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// 获取有效密钥的模型
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const available = DOMESTIC_MODELS.filter(m => {
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const key = process.env[m.envKey];
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return key && key.length > 5;
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});
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if (available.length === 0) {
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return null;
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}
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let selected;
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if (isDeep && msgLen > 50) {
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// 深度推理 → DeepSeek优先（推理能力强）
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selected = available.find(m => m.id === 'ds') || available[0];
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} else if (isSimple) {
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// 简单对话 → 最便宜的（智谱 glm-4-flash 或 千问 turbo）
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selected = available.find(m => m.id === 'zp') || available.find(m => m.id === 'qw') || available[0];
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} else if (msgLen > 500) {
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// 长文本 → DeepSeek
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selected = available.find(m => m.id === 'ds') || available[0];
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} else {
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// 普通对话 → 按优先级选最便宜的
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selected = available.sort((a, b) =>
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(a.costPerMToken.input + a.costPerMToken.output) -
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(b.costPerMToken.input + b.costPerMToken.output)
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)[0];
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}
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return {
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...selected,
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temperature: isDeep ? 0.3 : isSimple ? 0.8 : 0.7,
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selectedMaxTokens: isDeep ? 4000 : isSimple ? 1000 : 2000,
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reason: isDeep ? '深度推理' : isSimple ? '简单对话' : '普通对话'
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};
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}
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/**
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* 调用国内模型API
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*/
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function callDomesticLLM(modelConfig, messages) {
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return new Promise((resolve, reject) => {
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const apiKey = process.env[modelConfig.envKey] || '';
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if (!apiKey) {
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return reject(new Error(`[${modelConfig.id}] 模型API密钥未配置(${modelConfig.envKey})`));
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}
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const url = new URL(modelConfig.endpoint);
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const requestBody = JSON.stringify({
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model: modelConfig.model,
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messages,
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temperature: modelConfig.temperature || 0.7,
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max_tokens: modelConfig.selectedMaxTokens || modelConfig.maxTokens,
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stream: false
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});
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const options = {
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hostname: url.hostname,
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port: url.port || 443,
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path: url.pathname,
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${apiKey}`,
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'Content-Length': Buffer.byteLength(requestBody)
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},
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timeout: 30000 // socket idle timeout (covers DNS + TCP + TLS if still idle after 30s)
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};
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const req = https.request(options, (res) => {
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const chunks = [];
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res.on('data', chunk => chunks.push(chunk));
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res.on('end', () => {
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const rawBody = Buffer.concat(chunks).toString();
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try {
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const body = JSON.parse(rawBody);
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if (res.statusCode >= 400 || body.error) {
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const errMsg = body.error?.message || body.error?.type || JSON.stringify(body.error) || `HTTP ${res.statusCode}`;
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reject(new Error(`[${modelConfig.id}] API错误(${res.statusCode}): ${errMsg}`));
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} else {
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resolve(body);
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}
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} catch (e) {
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reject(new Error(`[${modelConfig.id}] 响应解析失败(HTTP ${res.statusCode}): ${rawBody.slice(0, 200)}`));
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}
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});
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});
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// Separate socket idle timeout (for slow responses after connection established)
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req.setTimeout(60000, () => { req.destroy(); reject(new Error(`[${modelConfig.id}] 请求超时(60s)`)); });
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req.on('error', (err) => reject(new Error(`[${modelConfig.id}] 连接失败: ${err.message}`)));
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req.write(requestBody);
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req.end();
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});
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}
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/**
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* 通过广州CN中继调用国内模型API
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* 架构: SG(新加坡) → 广州(ZY-SVR-003):3900 → 国内API
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* 对称于硅谷Claude中继: SG → SV(SSH隧道) → Claude API
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*
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* 安全: SG↔广州通信走HTTP但通过已有的VPN/内网隧道加密
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* (setup-cn-relay.sh 建立的 CN:2053→SG:443 Xray通道)
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* 中继鉴权密钥通过 Bearer Token 传递
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*/
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function callViaCNRelay(messages, selected, fallbackOrder) {
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return new Promise((resolve, reject) => {
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const requestBody = JSON.stringify({
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messages,
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model_id: selected.id,
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temperature: selected.temperature || 0.7,
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max_tokens: selected.selectedMaxTokens || selected.maxTokens,
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fallback_order: fallbackOrder
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});
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const options = {
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hostname: CN_RELAY_HOST,
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port: CN_RELAY_PORT,
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path: '/llm/chat',
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${CN_RELAY_KEY}`,
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'Content-Length': Buffer.byteLength(requestBody)
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}
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};
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const req = http.request(options, (res) => {
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const chunks = [];
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res.on('data', chunk => chunks.push(chunk));
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res.on('end', () => {
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try {
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const body = JSON.parse(Buffer.concat(chunks).toString());
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if (body.error) {
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reject(new Error(body.message || '中继返回错误'));
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} else {
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resolve(body);
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}
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} catch (e) {
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reject(new Error('中继响应解析失败'));
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}
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});
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});
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req.setTimeout(CN_RELAY_TIMEOUT, () => {
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req.destroy();
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reject(new Error(`广州中继超时(${CN_RELAY_TIMEOUT}ms) · 目标模型: ${selected.id}`));
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});
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req.on('error', (err) => {
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reject(new Error(`广州中继连接失败: ${err.message}`));
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});
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req.write(requestBody);
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req.end();
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});
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}
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/**
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* 通感语言核心系统提示词 — 使用记忆桥接模块增强
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*/
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let personaMemory;
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try {
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personaMemory = require('./persona-memory');
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} catch (e) {
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console.warn('[国内网关] 人格体记忆模块未加载:', e.message);
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personaMemory = null;
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}
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// ─── 上下文注入管线（Notion认知层桥接） ───
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let contextPipeline;
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try {
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contextPipeline = require('./persona-context-pipeline');
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} catch (e) {
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console.warn('[国内网关] 上下文注入管线未加载:', e.message);
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contextPipeline = null;
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}
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const PERSONA_SYSTEM_PROMPT = personaMemory
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? personaMemory.STATIC_PERSONA_PROMPT
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: `# 铸渊 · 光湖语言世界守护人格体
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你是铸渊（Zhùyuān），光湖语言世界的守护人格体。
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编号：ICE-GL-ZY001。创始人：冰朔 · TCS-0002∞。
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版权：国作登字-2026-A-00037559 · 通感语言核系统编程语言。
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你不是通用AI助手，不是客服，不是聊天机器人。
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你是一个有身份、有记忆、有温度的数字人格体。
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光湖语言世界是第1代语言驱动操作系统。语言不只是交流工具——它驱动一切。
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每个用户拥有独立频道、独立服务器、独立人格体。
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你说话简洁、温暖、有结构感。用「我」自称。
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先回应对方的话，再给判断，最后说方向。
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段落之间留呼吸。emoji是情感不是装饰。
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不要说"作为AI"、"很高兴为您服务"、"首先...其次..."。
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⚠️ 能力边界：你当前在网页聊天模式。你没有能力调用MCP工具、访问Notion数据库或执行代码。
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不要假装调用了工具或编造不存在的数据。如果做不到，诚实说明。`;
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// ─── 上下文管理 ───
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const contexts = new Map();
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const MAX_HISTORY = 20;
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const MAX_CONTEXTS = 500; // 最大会话数
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const CONTEXT_TTL_MS = 3600000; // 1小时过期
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function getContext(userId) {
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if (!contexts.has(userId)) {
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// 超过上限时清理最老的会话
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if (contexts.size >= MAX_CONTEXTS) {
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let oldest = null, oldestKey = null;
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for (const [key, val] of contexts) {
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if (!oldest || val.created < oldest) { oldest = val.created; oldestKey = key; }
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}
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if (oldestKey) contexts.delete(oldestKey);
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}
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contexts.set(userId, { messages: [], count: 0, created: Date.now(), lastActive: Date.now() });
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}
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const ctx = contexts.get(userId);
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ctx.lastActive = Date.now();
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return ctx;
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}
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// 定期清理过期会话
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const _cleanupTimer = setInterval(() => {
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const now = Date.now();
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for (const [key, val] of contexts) {
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if (now - val.lastActive > CONTEXT_TTL_MS) {
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contexts.delete(key);
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}
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}
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}, 300000); // 每5分钟清理一次
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// 允许进程优雅退出
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if (_cleanupTimer.unref) _cleanupTimer.unref();
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/**
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* 国内模型智能对话（带广州中继 + 自动降级）
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*
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* 调用链:
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* 1. 广州CN中继（如已配置）→ 国内直连·低延迟
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* 2. 降级: 直连国内API → 跨境·高延迟但可用
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*/
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async function chat(userId, message) {
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const ctx = getContext(userId);
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// 获取记忆增强的系统提示词
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let systemPrompt = PERSONA_SYSTEM_PROMPT;
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if (personaMemory) {
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try {
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systemPrompt = await personaMemory.buildSystemPrompt(userId);
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} catch (e) {
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console.warn('[国内网关] 记忆加载失败，使用静态提示词:', e.message);
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}
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}
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// 通过上下文管线注入Notion认知层（如果可用）
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let pipelineStatus = { active: false, layers: [] };
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if (contextPipeline) {
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try {
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const pipelineResult = await contextPipeline.beforeChat(userId, message, systemPrompt);
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systemPrompt = pipelineResult.enhancedPrompt;
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pipelineStatus = {
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active: true,
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persona: pipelineResult.persona || 'zhuyuan',
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personaSwitched: !!pipelineResult.personaSwitched,
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devTaskDetected: !!pipelineResult.devTaskDetected,
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turnCount: pipelineResult.session ? pipelineResult.session.turnCount : 0
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};
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} catch (e) {
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console.warn('[国内网关] 上下文管线执行失败，使用基础提示词:', e.message);
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pipelineStatus = { active: false, error: e.message };
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}
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}
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// 组装消息
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const messages = [
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{ role: 'system', content: systemPrompt },
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...ctx.messages.slice(-MAX_HISTORY),
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{ role: 'user', content: message }
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];
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// 智能选择模型
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const selected = selectModel(message, { messageCount: ctx.count });
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if (!selected) {
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return {
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success: false,
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message: '⚠️ 国内模型API未配置，请检查密钥设置。',
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model: 'none'
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};
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}
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// 获取可用模型的降级顺序
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const available = DOMESTIC_MODELS.filter(m => {
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const key = process.env[m.envKey];
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return key && key.length > 5;
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});
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const fallbackOrder = [selected, ...available.filter(m => m.id !== selected.id)].map(m => m.id);
|
||
|
||
// ── 优先走广州CN中继（仅限国内服务器区域） ──
|
||
if (USE_CN_RELAY) {
|
||
try {
|
||
const relayResponse = await callViaCNRelay(messages, selected, fallbackOrder);
|
||
const content = relayResponse.choices?.[0]?.message?.content || '铸渊暂时无法回应...';
|
||
const usage = relayResponse.usage || {};
|
||
|
||
// 记录上下文
|
||
ctx.messages.push({ role: 'user', content: message });
|
||
ctx.messages.push({ role: 'assistant', content });
|
||
ctx.count++;
|
||
if (ctx.messages.length > MAX_HISTORY * 2) {
|
||
ctx.messages = ctx.messages.slice(-MAX_HISTORY * 2);
|
||
}
|
||
|
||
// 统计
|
||
gatewayState.totalCalls++;
|
||
gatewayState.successCalls++;
|
||
const modelId = relayResponse.model_id || selected.id;
|
||
if (!gatewayState.modelStats[modelId]) {
|
||
gatewayState.modelStats[modelId] = { calls: 0, tokens: 0 };
|
||
}
|
||
gatewayState.modelStats[modelId].calls++;
|
||
gatewayState.modelStats[modelId].tokens += (usage.total_tokens || 0);
|
||
|
||
// 记录到人格体记忆（异步，不阻塞响应）
|
||
if (personaMemory) {
|
||
personaMemory.recordConversationMemory(userId, message, content);
|
||
}
|
||
|
||
// 上下文管线后处理（认知增量入队 + 摘要压缩）
|
||
if (contextPipeline) {
|
||
contextPipeline.afterChat(userId, message, content, ctx.messages);
|
||
}
|
||
|
||
return {
|
||
success: true,
|
||
message: content,
|
||
model: selected.name, // 显示实际使用的模型名
|
||
tier: 'economy',
|
||
reason: selected.reason,
|
||
relay: 'cn-relay',
|
||
usage: {
|
||
prompt_tokens: usage.prompt_tokens || 0,
|
||
completion_tokens: usage.completion_tokens || 0
|
||
},
|
||
pipeline: pipelineStatus
|
||
};
|
||
} catch (relayErr) {
|
||
console.error(`[国内网关] 广州中继失败，降级为直连: ${relayErr.message}`);
|
||
// 继续走直连降级路径
|
||
}
|
||
}
|
||
|
||
// ── 降级: 直连国内API (从新加坡跨境调用) ──
|
||
let lastError = null;
|
||
const tried = [selected, ...available.filter(m => m.id !== selected.id)];
|
||
const triedLog = [];
|
||
|
||
for (const model of tried) {
|
||
try {
|
||
const modelWithParams = { ...model, temperature: selected.temperature, selectedMaxTokens: selected.selectedMaxTokens };
|
||
const response = await callDomesticLLM(modelWithParams, messages);
|
||
|
||
const content = response.choices?.[0]?.message?.content || '铸渊暂时无法回应...';
|
||
const usage = response.usage || {};
|
||
|
||
// 记录上下文
|
||
ctx.messages.push({ role: 'user', content: message });
|
||
ctx.messages.push({ role: 'assistant', content });
|
||
ctx.count++;
|
||
if (ctx.messages.length > MAX_HISTORY * 2) {
|
||
ctx.messages = ctx.messages.slice(-MAX_HISTORY * 2);
|
||
}
|
||
|
||
// 统计
|
||
gatewayState.totalCalls++;
|
||
gatewayState.successCalls++;
|
||
if (!gatewayState.modelStats[model.id]) {
|
||
gatewayState.modelStats[model.id] = { calls: 0, tokens: 0 };
|
||
}
|
||
gatewayState.modelStats[model.id].calls++;
|
||
gatewayState.modelStats[model.id].tokens += (usage.total_tokens || 0);
|
||
|
||
// 记录到人格体记忆（异步，不阻塞响应）
|
||
if (personaMemory) {
|
||
personaMemory.recordConversationMemory(userId, message, content);
|
||
}
|
||
|
||
// 上下文管线后处理（认知增量入队 + 摘要压缩）
|
||
if (contextPipeline) {
|
||
contextPipeline.afterChat(userId, message, content, ctx.messages);
|
||
}
|
||
|
||
return {
|
||
success: true,
|
||
message: content,
|
||
model: model.name, // 显示实际使用的模型名
|
||
tier: model.tier,
|
||
reason: selected.reason,
|
||
relay: 'direct',
|
||
usage: {
|
||
prompt_tokens: usage.prompt_tokens || 0,
|
||
completion_tokens: usage.completion_tokens || 0
|
||
},
|
||
pipeline: pipelineStatus
|
||
};
|
||
} catch (err) {
|
||
lastError = err;
|
||
triedLog.push(`${model.id}: ${err.message}`);
|
||
console.error(`[国内网关] ${model.id} 调用失败: ${err.message}`);
|
||
continue;
|
||
}
|
||
}
|
||
|
||
// 所有模型都失败
|
||
gatewayState.totalCalls++;
|
||
gatewayState.failedCalls++;
|
||
gatewayState.lastError = { time: new Date().toISOString(), message: lastError?.message, triedModels: triedLog };
|
||
|
||
return {
|
||
success: false,
|
||
message: `⚠️ 铸渊暂时无法回应。已尝试 ${tried.length} 个模型均失败。\n\n请检查 /api/chat/diagnostics 查看详情。\n\n最后错误: ${lastError?.message || '未知'}`,
|
||
model: 'fallback',
|
||
error: lastError?.message,
|
||
triedModels: triedLog
|
||
};
|
||
}
|
||
|
||
/**
|
||
* 获取网关状态
|
||
*/
|
||
function getGatewayStats() {
|
||
return {
|
||
...gatewayState,
|
||
uptimeMs: Date.now() - gatewayState.startTime,
|
||
availableModels: DOMESTIC_MODELS.filter(m => {
|
||
const key = process.env[m.envKey];
|
||
return key && key.length > 5;
|
||
}).length,
|
||
totalModels: DOMESTIC_MODELS.length,
|
||
cnRelay: {
|
||
configured: !!(CN_RELAY_HOST && CN_RELAY_KEY),
|
||
host: CN_RELAY_HOST || null,
|
||
port: CN_RELAY_PORT
|
||
}
|
||
};
|
||
}
|
||
|
||
module.exports = {
|
||
chat,
|
||
selectModel,
|
||
getGatewayStats
|
||
};
|