🏗️ Agentic Infrastructure 详解

# OpenClaw Agentic Infrastructure - 多Agent集群管理示例
# 场景：同时启动多个专项Agent，分工协作处理复杂任务

from openclaw import sessions_spawn, sessions_list, sessions_send, session_status

# 1. 定义Agent集群配置
agent_cluster = [
    {
        "role": "researcher",
        "task": "搜索并分析当前热门的Agentic Infrastructure开源项目",
        "model": "tencentcodingplan/tc-code-latest"
    },
    {
        "role": "coder", 
        "task": "基于研究结果，设计一个简化的Agentic Infrastructure架构图",
        "model": "tencentcodingplan/tc-code-latest"
    },
    {
        "role": "reviewer",
        "task": "审查架构设计，给出安全性和扩展性建议",
        "model": "tencentcodingplan/tc-code-latest"
    }
]

# 2. 批量启动Agent（基础设施层自动处理资源调度）
session_ids = []
for agent in agent_cluster:
    result = sessions_spawn(
        runtime="subagent",
        mode="session",
        task=agent["task"],
        model=agent["model"],
        label=f"infra-{agent['role']}-{uuid.uuid4().hex[:8]}"
    )
    session_ids.append(result["sessionKey"])
    print(f"✅ 启动 {agent['role']} Agent: {result['sessionKey']}")

# 3. 监控所有Agent状态（可观测性层）
import time
while True:
    all_done = True
    for session_key in session_ids:
        status = session_status(sessionKey=session_key)
        print(f"Agent {session_key[:20]}... 状态: {status.get('status', 'unknown')}")
        if status.get("status") not in ["completed", "failed"]:
            all_done = False
    if all_done:
        break
    time.sleep(5)

print("🎉 所有Agent任务完成！")

// Agentic Infrastructure - 状态持久化与恢复的OpenClaw实现
// 场景：Agent重启后如何恢复之前的会话状态

// 1. 保存Agent状态到持久化存储
async function persistAgentState(sessionKey, state) {
    const stateData = {
        sessionKey,
        context: state.context,        // 对话上下文
        memory: state.memory,          // 长期记忆
        toolState: state.toolState,    // 工具调用状态
        timestamp: Date.now(),
        version: "1.0"
    };
    
    // 写入持久化层（OpenClaw内置）
    await openclaw.exec({
        command: `echo '${JSON.stringify(stateData)}' >> /root/.openclaw/memory-tdai/sessions/${sessionKey}.state.json`
    });
    
    console.log(`💾 Agent状态已持久化: ${sessionKey}`);
}

// 2. 恢复Agent状态
async function restoreAgentState(sessionKey) {
    try {
        const result = await openclaw.exec({
            command: `cat /root/.openclaw/memory-tdai/sessions/${sessionKey}.state.json`
        });
        
        if (result.stdout) {
            const state = JSON.parse(result.stdout);
            console.log(`🔄 Agent状态已恢复: ${sessionKey}, 版本: ${state.version}`);
            return state;
        }
    } catch (err) {
        console.log(`⚠️ 未找到持久化状态，启动新会话: ${sessionKey}`);
    }
    return null;
}

// 3. 基础设施健康检查
async function infraHealthCheck() {
    const checks = [
        { name: "Agent运行时", check: "ps aux | grep openclaw" },
        { name: "存储可用空间", check: "df -h /root/.openclaw" },
        { name: "内存使用", check: "free -m" },
        { name: "网络连接", check: "curl -I https://api.openclaw.ai" }
    ];
    
    for (const c of checks) {
        const result = await openclaw.exec({ command: c.check });
        console.log(`${result.exitCode === 0 ? '✅' : '❌'} ${c.name}: ${result.exitCode === 0 ? '正常' : '异常'}`);
    }
}