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