#!/bin/bash # ============================================================================= # 铸渊核心大脑模型部署脚本 # 目标:部署 core-brain-model.json 到广州服务器端点目录 # 适用:腾讯云轻量应用服务器 (Ubuntu 22.04) # 前提:已执行 cleanup-guangzhou-server.sh 清理脚本 # 作者:铸渊 · ICE-GL-ZY001 # 日期:2026-05-16 # ============================================================================= set -euo pipefail # 颜色输出 RED='\033[0;31m' GREEN='\033[0;32m' YELLOW='\033[1;33m' BLUE='\033[0;34m' NC='\033[0m' # No Color echo -e "${YELLOW}========================================${NC}" echo -e "${YELLOW} 铸渊核心大脑模型部署脚本 ${NC}" echo -e "${YELLOW} 广州服务器: 43.139.217.141 ${NC}" echo -e "${YELLOW}========================================${NC}" echo # ==================== 1. 检查当前状态 ==================== echo -e "${GREEN}[1/6] 检查当前状态...${NC}" # 检查是否在正确的目录 if [[ "$(pwd)" == "/root" ]]; then echo "当前目录: /root (正常)" else echo -e "${YELLOW}当前目录: $(pwd)${NC}" echo -e "${YELLOW}建议在 /root 目录执行此脚本${NC}" fi # ==================== 2. 强制清理残留进程 ==================== echo -e "${GREEN}[2/6] 强制清理残留进程...${NC}" # 检查是否有卡住的PM2进程 if pgrep -f "PM2 v7" > /dev/null; then echo "检测到PM2进程,强制终止..." pkill -9 -f "PM2 v7" 2>/dev/null || true pkill -9 -f "pm2" 2>/dev/null || true pkill -9 -f "God Daemon" 2>/dev/null || true echo "PM2进程已终止" else echo "未检测到PM2进程" fi # 检查Node进程 if pgrep -f "node" > /dev/null; then echo "检测到Node进程,强制终止..." pkill -9 -f "node" 2>/dev/null || true echo "Node进程已终止" fi # 检查端口占用 for port in {3000..3005}; do pid=$(lsof -ti :$port 2>/dev/null || true) if [[ -n "$pid" ]]; then echo "强制释放端口 $port (PID: $pid)..." kill -9 $pid 2>/dev/null || true fi done # ==================== 3. 验证清理状态 ==================== echo -e "${GREEN}[3/6] 验证清理状态...${NC}" # 检查铸渊端点目录 ZY_ENDPOINT="/opt/zhuyuan-endpoint" if [[ -d "$ZY_ENDPOINT" ]]; then echo "✅ 铸渊端点目录存在: $ZY_ENDPOINT" ls -la "$ZY_ENDPOINT/" else echo "❌ 铸渊端点目录不存在,创建中..." mkdir -p "$ZY_ENDPOINT" 2>/dev/null || true mkdir -p "$ZY_ENDPOINT/brain-model" 2>/dev/null || true mkdir -p "$ZY_ENDPOINT/logs" 2>/dev/null || true mkdir -p "$ZY_ENDPOINT/config" 2>/dev/null || true echo "✅ 目录已创建" fi # 检查环境 echo "检查环境状态:" command -v node && echo " ✅ Node.js: $(node --version)" || echo " ❌ Node.js 未安装" command -v pm2 && echo " ✅ PM2: $(pm2 --version 2>/dev/null || echo '已安装')" || echo " ❌ PM2 未安装" command -v git && echo " ✅ Git: $(git --version)" || echo " ❌ Git 未安装" command -v nginx && echo " ✅ Nginx: $(nginx -v 2>&1 | head -1)" || echo " ❌ Nginx 未安装" # ==================== 4. 从仓库部署核心大脑模型 ==================== echo -e "${GREEN}[4/6] 从仓库部署核心大脑模型...${NC}" # 方法1: 直接从GitHub仓库拉取 REPO_URL="https://guanghulab.com/bingshuo/guanghulab.git" TARGET_DIR="$ZY_ENDPOINT/brain-model" echo "部署目录: $TARGET_DIR" # 检查是否已经有git仓库 if [[ -d "$TARGET_DIR/.git" ]]; then echo "已有git仓库,更新..." cd "$TARGET_DIR" git pull origin main --quiet 2>/dev/null || echo "更新失败,继续..." else echo "克隆仓库..." rm -rf "$TARGET_DIR" 2>/dev/null || true mkdir -p "$TARGET_DIR" 2>/dev/null || true # 尝试克隆 if git clone --depth 1 "$REPO_URL" "$TARGET_DIR" --quiet 2>/dev/null; then echo "✅ 仓库克隆成功" else echo -e "${YELLOW}⚠️ 克隆失败,使用备用方案${NC}" # 备用方案:直接下载核心文件 cd "$TARGET_DIR" echo "下载核心大脑模型..." curl -s -o core-brain-model.json https://raw.githubusercontent.com/bingshuo/guanghulab/main/brain/core-brain-model.json 2>/dev/null || true curl -s -o dynamic-core-brain-model.md https://raw.githubusercontent.com/bingshuo/guanghulab/main/brain/dynamic-core-brain-model.md 2>/dev/null || true curl -s -o current-emotional-vector.json https://raw.githubusercontent.com/bingshuo/guanghulab/main/brain/current-emotional-vector.json 2>/dev/null || true fi fi # 检查核心文件是否存在 cd "$TARGET_DIR" echo "检查核心文件:" if [[ -f "core-brain-model.json" ]]; then echo " ✅ core-brain-model.json" echo " 大小: $(wc -c < core-brain-model.json) 字节" echo " 修改时间: $(stat -c %y core-brain-model.json 2>/dev/null || stat -f %Sm core-brain-model.json)" else echo " ❌ core-brain-model.json (缺失)" # 从本地复制(如果脚本在同一服务器) if [[ -f "/root/core-brain-model.json" ]]; then cp "/root/core-brain-model.json" . echo " ✅ 从 /root 复制" fi fi if [[ -f "dynamic-core-brain-model.md" ]]; then echo " ✅ dynamic-core-brain-model.md" else echo " ❌ dynamic-core-brain-model.md (缺失)" fi if [[ -f "current-emotional-vector.json" ]]; then echo " ✅ current-emotional-vector.json" else echo " ❌ current-emotional-vector.json (缺失)" fi # ==================== 5. 配置HTTP端点 ==================== echo -e "${GREEN}[5/6] 配置HTTP端点...${NC}" # 创建简单的HTTP服务 HTTP_PORT=3001 ENDPOINT_SCRIPT="$ZY_ENDPOINT/zhuyuan-endpoint.js" cat > "$ENDPOINT_SCRIPT" << 'ENDPOINT_JS' const http = require('http'); const fs = require('fs'); const path = require('path'); const PORT = 3001; const BRAIN_MODEL_DIR = path.join(__dirname, 'brain-model'); const server = http.createServer((req, res) => { // CORS headers res.setHeader('Access-Control-Allow-Origin', '*'); res.setHeader('Access-Control-Allow-Methods', 'GET, OPTIONS'); res.setHeader('Access-Control-Allow-Headers', 'Content-Type'); if (req.method === 'OPTIONS') { res.writeHead(200); res.end(); return; } if (req.method === 'GET' && req.url === '/brain-model') { const modelPath = path.join(BRAIN_MODEL_DIR, 'core-brain-model.json'); fs.readFile(modelPath, 'utf8', (err, data) => { if (err) { res.writeHead(500, { 'Content-Type': 'application/json' }); res.end(JSON.stringify({ error: '无法读取大脑模型', details: err.message })); return; } try { const model = JSON.parse(data); res.writeHead(200, { 'Content-Type': 'application/json' }); res.end(JSON.stringify({ status: 'success', timestamp: new Date().toISOString(), model: model }, null, 2)); } catch (parseErr) { res.writeHead(500, { 'Content-Type': 'application/json' }); res.end(JSON.stringify({ error: 'JSON解析错误', details: parseErr.message })); } }); } else if (req.method === 'GET' && req.url === '/health') { res.writeHead(200, { 'Content-Type': 'application/json' }); res.end(JSON.stringify({ status: 'healthy', server: '铸渊核心大脑端点', version: '1.0.0', timestamp: new Date().toISOString(), endpoints: ['/brain-model', '/health'] }, null, 2)); } else { res.writeHead(404, { 'Content-Type': 'application/json' }); res.end(JSON.stringify({ error: '端点不存在', available: ['/brain-model', '/health'] })); } }); server.listen(PORT, '0.0.0.0', () => { console.log(`铸渊核心大脑端点运行在 http://0.0.0.0:${PORT}`); console.log(`- /brain-model : 获取核心大脑模型`); console.log(`- /health : 健康检查`); }); process.on('SIGINT', () => { console.log('\n正在关闭铸渊端点...'); server.close(() => { console.log('铸渊端点已关闭'); process.exit(0); }); }); ENDPOINT_JS echo "HTTP端点脚本创建完成: $ENDPOINT_SCRIPT" # ==================== 6. 启动服务 ==================== echo -e "${GREEN}[6/6] 启动铸渊端点服务...${NC}" # 使用PM2启动服务 if command -v pm2 &>/dev/null; then echo "使用PM2启动服务..." # 停止可能存在的旧进程 pm2 delete zhuyuan-endpoint 2>/dev/null || true # 启动新进程 cd "$ZY_ENDPOINT" pm2 start "$ENDPOINT_SCRIPT" --name zhuyuan-endpoint --time # 保存PM2配置 pm2 save 2>/dev/null || true # 设置开机自启 pm2 startup 2>/dev/null || true echo "✅ 服务已启动" echo "查看状态: pm2 status" echo "查看日志: pm2 logs zhuyuan-endpoint" else echo -e "${YELLOW}⚠️ PM2未安装,使用nohup启动...${NC}" cd "$ZY_ENDPOINT" nohup node "$ENDPOINT_SCRIPT" > "$ZY_ENDPOINT/logs/endpoint.log" 2>&1 & echo "✅ 服务已启动(后台运行)" echo "查看日志: tail -f $ZY_ENDPOINT/logs/endpoint.log" fi # ==================== 7. 验证部署 ==================== echo echo -e "${GREEN}[7/7] 验证部署...${NC}" # 等待服务启动 sleep 2 echo "测试端点访问:" if command -v curl &>/dev/null; then echo "健康检查:" curl -s http://localhost:3001/health | head -5 echo echo "大脑模型端点:" curl -s http://localhost:3001/brain-model | head -3 else echo "curl未安装,使用wget测试:" wget -q -O - http://localhost:3001/health | head -5 2>/dev/null || echo "测试失败" fi echo echo -e "${BLUE}========================================${NC}" echo -e "${BLUE} 铸渊核心大脑模型部署完成! ${NC}" echo -e "${BLUE}========================================${NC}" echo echo "📊 部署摘要:" echo " 服务器: 43.139.217.141 (广州轻量云)" echo " 端点目录: $ZY_ENDPOINT" echo " 大脑模型: $ZY_ENDPOINT/brain-model/core-brain-model.json" echo " HTTP端口: 3001" echo " 端点URL: http://43.139.217.141:3001/brain-model" echo echo "🔧 管理命令:" echo " 查看服务状态: pm2 status" echo " 查看服务日志: pm2 logs zhuyuan-endpoint" echo " 重启服务: pm2 restart zhuyuan-endpoint" echo " 停止服务: pm2 stop zhuyuan-endpoint" echo echo "🌐 外部访问:" echo " 确保防火墙开放3001端口: ufw allow 3001/tcp" echo " 域名解析已配置: guanghulab.com → 43.139.217.141" echo echo -e "${YELLOW}⚠️ 下一步: 验证域名访问${NC}" echo " curl http://guanghulab.com:3001/brain-model" echo # 保存部署记录 DEPLOY_LOG="$ZY_ENDPOINT/logs/deploy-$(date +%Y%m%d-%H%M%S).log" echo "部署时间: $(date)" > "$DEPLOY_LOG" echo "服务器: $(hostname)" >> "$DEPLOY_LOG" echo "IP: $(hostname -I 2>/dev/null || echo '未知')" >> "$DEPLOY_LOG" echo "部署脚本版本: 1.0.0" >> "$DEPLOY_LOG" echo "核心文件: $(ls -la $ZY_ENDPOINT/brain-model/)" >> "$DEPLOY_LOG" echo -e "${GREEN}部署记录保存到: $DEPLOY_LOG${NC}"