OpenClaw不仅仅是聊天框，还是Agent后台引擎，通过API接入现有平台

import requests
OPENCLAW_GATEWAY = "http://localhost:18789"
def on_alert(alert_msg: str):
    """告警回调。直接调 OpenClaw API"""
    # 创建一个 Session，OpenClaw 会返回 session_id，后续追问可以复用
    resp = requests.post(
        f"{OPENCLAW_GATEWAY}/api/sessions",
        json={"label": f"告警-{alert_msg[:30]}"},
        timeout=10,
    )
    session_id = resp.json()["id"]
    # 向 Agent 发送消息，OpenClaw 内部走 ReAct Loop 处理
    resp = requests.post(
        f"{OPENCLAW_GATEWAY}/api/sessions/{session_id}/messages",
        json={
            "content": alert_msg,
            "tools": ["get_device_info", "calculate_impact",
                       "get_topology", "send_wework"],
        },
        timeout=60,
    )
    data = resp.json()
    # data["reply"]   → Agent 的最终回复
    # data["tool_calls"] → Agent 调了哪些工具、各返回了什么
    return data

# openclaw.config.yamlagents:  supervisor:    name: 告警调度员    model: claude-sonnet-4-6    system_prompt: |      你是一个告警处理调度器。收到告警后：      1. 分析告警内容，判断需要哪些信息      2. 调用 get_device_info 获取设备详情      3. 调用 get_topology + calculate_impact 评估影响范围      4. 综合以上信息，生成处理建议      5. 调用 send_wework 推送到运维群      工具调用顺序遵循：先查信息，再计算，最后发通知。    tools:      - get_device_info      - get_topology      - calculate_impact      - send_wework    max_tool_rounds: 5
# openclaw.config.yaml
agents:
  supervisor:
    name: 告警调度员
    model: claude-sonnet-4-6
    system_prompt: |
      你是一个告警处理调度器。收到告警后：
      1. 分析告警内容，判断需要哪些信息
      2. 调用 get_device_info 获取设备详情
      3. 调用 get_topology + calculate_impact 评估影响范围
      4. 综合以上信息，生成处理建议
      5. 调用 send_wework 推送到运维群
      工具调用顺序遵循：先查信息，再计算，最后发通知。
    tools:
      - get_device_info
      - get_topology
      - calculate_impact
      - send_wework
    max_tool_rounds: 5

# tools/get_device_info.py
import requests
def run(device_id: str) -> dict:
    """根据设备ID查询设备详情、历史告警"""
    resp = requests.get(
        f"http://cmdb.internal/api/devices/{device_id}",
        headers={"Authorization": "Bearer {CMDB_TOKEN}"},
        timeout=5,
    )
    data = resp.json()
    return {
        "device_name": data["name"],
        "location": data["location"],
        "owner": data["owner"],
        "recent_alerts": data["alert_history"][:5],
    }
# 工具元数据：Agent 通过 description 判断何时调用
TOOL_META = {
    "name": "get_device_info",
    "description": "查询设备详情、机房位置、维护责任人、近期告警历史。"
                   "当告警中包含设备名称或设备ID时调用此工具。",
    "parameters": {
        "type": "object",
        "properties": {
            "device_id": {"type": "string", "description": "设备唯一标识"}
        },
        "required": ["device_id"],
    },
}

# tools/calculate_impact.py
def run(alert_level: str, device_id: str) -> dict:
    """计算告警影响范围"""
    # 1. 调拓扑服务拿下游依赖
    topo = requests.get(
        f"http://topo.internal/api/devices/{device_id}/downstream",
        timeout=5,
    ).json()
    # 2. 根据告警级别 + 下游依赖查业务权重表
    # ...计算逻辑
    return {
        "affected_businesses": ["业务A", "业务B"],
        "estimated_users": 2000,
        "estimated_recovery_minutes": 15,
    }
TOOL_META = {
    "name": "calculate_impact",
    "description": "计算告警影响范围，返回受影响的业务列表、预估用户数、预估恢复时间。"
                   "等级为 P1 或影响核心设备时优先调用。",
    "parameters": {
        "type": "object",
        "properties": {
            "alert_level": {"type": "string", "description": "P1/P2/P3"},
            "device_id": {"type": "string", "description": "告警设备ID"},
        },
        "required": ["alert_level", "device_id"],
    },
}

[Service]
ExecStart=/usr/local/bin/openclaw gateway --port 18789 --config /etc/openclaw/config.yaml
Restart=always
RestartSec=5