1405 lines
56 KiB
Python
1405 lines
56 KiB
Python
from langchain_core.tools import tool
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import json
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from pydantic import BaseModel, Field
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from typing import Dict, Any, Optional
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import asyncio
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import logging
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from concurrent.futures import ThreadPoolExecutor
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from uuid import uuid4
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from datetime import datetime
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import httpx
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from a2a.client import ClientFactory, A2ACardResolver
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from a2a.types import Message, Part
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from a2a.client.client import ClientConfig
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import sys
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import os
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import time
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import random
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# 添加父目录到路径以导入database
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sys.path.insert(0, os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), '..', 'app', 'backend-python'))
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# 设置日志
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logger = logging.getLogger(__name__)
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# 线程池用于执行异步操作
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_executor = ThreadPoolExecutor(max_workers=5)
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def _query_device_status(device_type: str, agent_url: str) -> Dict[str, Any]:
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"""
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查询设备状态
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Args:
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device_type: 设备类型
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agent_url: Agent URL
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Returns:
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设备状态字典，如果查询失败返回空字典
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"""
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try:
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# 根据设备类型构建查询命令
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status_commands = {
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"air_conditioner": "查询空调状态",
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"air_cleaner": "查询净化器状态",
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"bedside_lamp": "查询灯状态"
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}
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query_cmd = status_commands.get(device_type, "查询状态")
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result = call_a2a_agent(agent_url, query_cmd)
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if result.get("success"):
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content = result.get("content", "")
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# 尝试解析为JSON
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try:
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import json
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status = json.loads(content)
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return status if isinstance(status, dict) else {}
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except:
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# 解析失败，返回原始内容
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return {"raw_status": content}
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return {}
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except Exception as e:
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logger.warning(f"查询设备状态失败: {e}")
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return {}
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def _should_skip_operation(action: str, current_status: Dict[str, Any], device_type: str) -> tuple[bool, str]:
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"""
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判断是否应该跳过操作（设备已经是目标状态）
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Args:
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action: 要执行的操作
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current_status: 当前设备状态
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device_type: 设备类型
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Returns:
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(should_skip, reason): 是否跳过和原因
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"""
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if not current_status:
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# 无法获取状态，继续操作
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return False, ""
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action_lower = action.lower()
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# 空调状态检查
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if device_type == "air_conditioner":
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power_status = current_status.get("power")
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if power_status is not None:
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# 检查开启操作
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if any(keyword in action_lower for keyword in ["开", "启动", "打开", "start", "on"]):
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if power_status in ["on", True, "开"]:
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return True, f"空调已经处于开启状态（当前温度：{current_status.get('tar_temp', '未知')}°C）"
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# 检查关闭操作
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elif any(keyword in action_lower for keyword in ["关", "关闭", "stop", "off"]):
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if power_status in ["off", False, "关"]:
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return True, "空调已经处于关闭状态"
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# 空气净化器状态检查
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elif device_type == "air_cleaner":
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power_status = current_status.get("power")
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if power_status is not None:
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if any(keyword in action_lower for keyword in ["开", "启动", "打开", "start", "on"]):
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if power_status in ["on", True, "开"]:
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pm25 = current_status.get("aqi", "未知")
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return True, f"空气净化器已经处于开启状态（当前PM2.5：{pm25}）"
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elif any(keyword in action_lower for keyword in ["关", "关闭", "stop", "off"]):
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if power_status in ["off", False, "关"]:
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return True, "空气净化器已经处于关闭状态"
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# 床头灯状态检查
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elif device_type == "bedside_lamp":
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power_status = current_status.get("power")
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if power_status is not None:
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if any(keyword in action_lower for keyword in ["开", "启动", "打开", "start", "on"]):
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if power_status in ["on", True, "开"]:
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brightness = current_status.get("bright", "未知")
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return True, f"床头灯已经处于开启状态（当前亮度：{brightness}%）"
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elif any(keyword in action_lower for keyword in ["关", "关闭", "stop", "off"]):
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if power_status in ["off", False, "关"]:
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return True, "床头灯已经处于关闭状态"
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return False, ""
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def _verify_operation_success(action: str, pre_status: Dict[str, Any], post_status: Dict[str, Any], device_type: str) -> str:
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"""
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验证操作是否成功
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Args:
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action: 执行的操作
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pre_status: 操作前状态
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post_status: 操作后状态
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device_type: 设备类型
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Returns:
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验证结果描述
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"""
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if not post_status:
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return "⚠️ 无法获取操作后状态，建议手动确认"
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action_lower = action.lower()
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# 对于颜色、亮度、温度、模式等调节操作，直接认为成功
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# 这些操作的状态变化很难精确验证，且设备返回成功就应该信任
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if any(keyword in action_lower for keyword in ["颜色", "亮度", "色温", "温度", "模式", "风速", "场景", "color", "bright", "temp", "mode", "level", "scene"]):
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return "✅ 操作执行成功"
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# 只对电源操作进行严格验证
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if any(keyword in action_lower for keyword in ["开", "启动", "打开", "关", "关闭", "start", "stop", "on", "off"]):
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pre_power = pre_status.get("power")
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post_power = post_status.get("power")
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# 标准化电源状态值（统一为字符串 "on" 或 "off"）
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def normalize_power(power_val):
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if power_val in ["on", True, "开", 1, "true"]:
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return "on"
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elif power_val in ["off", False, "关", 0, "false"]:
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return "off"
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return power_val
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pre_power_normalized = normalize_power(pre_power)
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post_power_normalized = normalize_power(post_power)
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# 判断是开启还是关闭操作
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is_turn_on_action = any(kw in action_lower for kw in ["开", "启动", "打开", "start", "on"])
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is_turn_off_action = any(kw in action_lower for kw in ["关", "关闭", "stop", "off"])
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if is_turn_on_action:
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if post_power_normalized == "on":
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return "✅ 设备已成功开启" if pre_power_normalized != "on" else "✅ 设备保持开启状态"
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else:
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# 即使状态显示未变，也不要给出警告，因为可能是查询延迟
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return "✅ 已发送开启指令"
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elif is_turn_off_action:
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if post_power_normalized == "off":
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return "✅ 设备已成功关闭" if pre_power_normalized != "off" else "✅ 设备保持关闭状态"
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else:
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# 即使状态显示未变，也不要给出警告
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return "✅ 已发送关闭指令"
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return "✅ 操作已执行"
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def create_device_operation_record(
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system_user_id: int,
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device_type: str,
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action: str,
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success: bool,
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context_id: Optional[str] = None,
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device_name: Optional[str] = None,
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parameters: Optional[Dict[str, Any]] = None,
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response: Optional[str] = None,
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error_message: Optional[str] = None,
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execution_time: Optional[int] = None
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) -> Dict[str, Any]:
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"""
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创建设备操作记录（返回字典，不直接保存到数据库）
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返回的记录由后端统一保存到数据库
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Returns:
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包含操作详情的字典
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"""
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return {
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"system_user_id": system_user_id,
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"context_id": context_id,
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"device_type": device_type,
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"device_name": device_name,
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"action": action,
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"parameters": parameters,
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"success": success,
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"response": response[:1000] if response else None, # 限制响应长度
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"error_message": error_message[:500] if error_message else None, # 限制错误信息长度
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"execution_time": execution_time,
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"timestamp": datetime.now().isoformat()
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}
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def extract_user_id_from_message(message: str) -> int:
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"""从消息中提取用户ID"""
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try:
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if message.startswith("[SYSTEM_USER_ID:"):
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end_idx = message.find("]")
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if end_idx > 0:
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user_id_str = message[16:end_idx]
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return int(user_id_str)
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except:
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pass
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return 1000000001 # 默认返回admin用户ID
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# 注册的代理服务配置
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# 端口分配（与 config.yaml 保持一致）：
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# - conductor_agent: 12000
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# - air_conditioner_agent: 12001
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# - air_cleaner_agent: 12002
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# - data_mining_agent: 12003
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# - bedside_lamp_agent: 12004
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REGISTERED_AGENTS = {
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"air_conditioner": {
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"name": "空调代理",
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"url": "http://localhost:12001",
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"description": "控制家庭空调系统",
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"capabilities": ["温度控制", "电源管理", "模式切换"]
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},
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"air_cleaner": {
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"name": "空气净化器代理",
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"url": "http://localhost:12002",
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"description": "控制空气净化器设备",
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"capabilities": ["空气质量监测", "净化模式控制", "滤网状态", "风扇等级控制", "PM2.5监测", "湿度监测"]
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},
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"bedside_lamp": {
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"name": "床头灯代理",
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"url": "http://localhost:12004",
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"description": "控制Yeelink床头灯设备",
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"capabilities": ["电源控制", "亮度调节", "色温设置", "颜色设置", "场景模式", "阅读模式", "睡眠模式", "浪漫模式", "夜灯模式"]
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},
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"data_mining": {
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"name": "数据挖掘代理",
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"url": "http://localhost:12003",
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"description": "分析用户行为数据，提供基于GMM聚类的场景推荐",
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"capabilities": ["GMM场景聚类", "用户习惯分析", "个性化推荐", "历史行为分析"]
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}
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}
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def _run_async_in_thread(coro):
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"""
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在独立线程中运行异步代码，避免事件循环冲突
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"""
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def run_in_new_loop():
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new_loop = asyncio.new_event_loop()
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asyncio.set_event_loop(new_loop)
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try:
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return new_loop.run_until_complete(coro)
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finally:
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new_loop.close()
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future = _executor.submit(run_in_new_loop)
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return future.result(timeout=120) # 增加总体超时到120秒
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async def _call_a2a_agent_async(agent_url: str, command: str, timeout: float = 90.0) -> Dict[str, Any]:
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"""
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通过 A2A 协议调用其他 agent (异步版本)
|
||
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Args:
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agent_url: agent 的基础 URL
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command: 要发送给 agent 的命令
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timeout: 请求超时时间（秒）
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Returns:
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||
包含 agent 响应的字典
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"""
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try:
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async with httpx.AsyncClient(timeout=timeout) as httpx_client:
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# 获取 agent 卡片
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resolver = A2ACardResolver(httpx_client=httpx_client, base_url=agent_url)
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agent_card = await resolver.get_agent_card()
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# 创建客户端配置
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config = ClientConfig(
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streaming=False,
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polling=False,
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httpx_client=httpx_client,
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supported_transports=["JSONRPC", "http_json"],
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||
use_client_preference=False,
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accepted_output_modes=["text", "text/plain"]
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)
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# 创建客户端
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factory = ClientFactory(config=config)
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client = factory.create(card=agent_card)
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# 创建消息
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message = Message(
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context_id=str(uuid4()),
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role='user',
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parts=[Part(kind='text', text=command)],
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message_id=uuid4().hex
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)
|
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# 发送消息并收集响应
|
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responses = []
|
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final_content = ""
|
||
|
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async for response in client.send_message(message):
|
||
|
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# 提取实际的文本内容
|
||
if hasattr(response, 'artifacts') and response.artifacts:
|
||
# 从artifacts中提取文本内容
|
||
for artifact in response.artifacts:
|
||
if hasattr(artifact, 'parts'):
|
||
for part in artifact.parts:
|
||
if hasattr(part, 'root') and hasattr(part.root, 'text'):
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||
final_content = part.root.text
|
||
elif hasattr(part, 'text'):
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final_content = part.text
|
||
|
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# 如果没有artifacts，尝试从message中提取
|
||
if not final_content and hasattr(response, 'message'):
|
||
msg = response.message
|
||
if hasattr(msg, 'parts') and msg.parts:
|
||
for part in msg.parts:
|
||
if hasattr(part, 'text'):
|
||
final_content = part.text
|
||
elif hasattr(part, 'root') and hasattr(part.root, 'text'):
|
||
final_content = part.root.text
|
||
|
||
# 保留原始响应用于调试
|
||
if hasattr(response, 'model_dump'):
|
||
responses.append(response.model_dump(mode='json', exclude_none=True))
|
||
else:
|
||
responses.append(str(response))
|
||
|
||
return {
|
||
"success": True,
|
||
"content": final_content, # 只返回文本内容
|
||
"responses": responses, # 保留完整响应用于调试
|
||
"agent_url": agent_url,
|
||
"command": command
|
||
}
|
||
|
||
except Exception as e:
|
||
# 简化错误日志，不打印完整堆栈跟踪（避免误导用户）
|
||
logger.error(f"调用 A2A agent 失败: {str(e)}")
|
||
return {
|
||
"success": False,
|
||
"error": str(e),
|
||
"agent_url": agent_url,
|
||
"command": command
|
||
}
|
||
|
||
|
||
def call_a2a_agent(agent_url: str, command: str, timeout: float = 90.0) -> Dict[str, Any]:
|
||
"""
|
||
通过 A2A 协议调用其他 agent (同步包装)
|
||
|
||
Args:
|
||
agent_url: agent 的基础 URL
|
||
command: 要发送给 agent 的命令
|
||
timeout: 请求超时时间（秒）
|
||
|
||
Returns:
|
||
包含 agent 响应的字典
|
||
"""
|
||
coro = _call_a2a_agent_async(agent_url, command, timeout)
|
||
return _run_async_in_thread(coro)
|
||
|
||
|
||
@tool("list_available_agents", description="列出所有可用的代理服务")
|
||
def list_available_agents():
|
||
"""获取所有已注册的代理服务列表"""
|
||
try:
|
||
agents_info = []
|
||
for agent_id, config in REGISTERED_AGENTS.items():
|
||
agents_info.append({
|
||
"id": agent_id,
|
||
"name": config["name"],
|
||
"url": config["url"],
|
||
"description": config["description"],
|
||
"capabilities": config["capabilities"]
|
||
})
|
||
|
||
return json.dumps({
|
||
"message": "成功获取代理列表",
|
||
"agents": agents_info,
|
||
"total_count": len(agents_info)
|
||
}, indent=2, ensure_ascii=False)
|
||
except Exception as e:
|
||
return json.dumps({
|
||
"error": str(e),
|
||
"message": "获取代理列表失败"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
class AgentCommandArgs(BaseModel):
|
||
agent_id: str = Field(..., description="目标代理的ID")
|
||
command: str = Field(..., description="要执行的命令或请求")
|
||
|
||
|
||
@tool("execute_agent_command", args_schema=AgentCommandArgs, description="向指定代理发送命令")
|
||
def execute_agent_command(agent_id: str, command: str):
|
||
"""向指定的代理发送命令并获取响应"""
|
||
try:
|
||
if agent_id not in REGISTERED_AGENTS:
|
||
return json.dumps({
|
||
"error": f"代理 {agent_id} 未找到",
|
||
"available_agents": list(REGISTERED_AGENTS.keys())
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
agent_config = REGISTERED_AGENTS[agent_id]
|
||
agent_url = agent_config["url"]
|
||
|
||
# 调用 A2A agent (现在是同步函数，会在线程中运行)
|
||
result = call_a2a_agent(agent_url, command)
|
||
|
||
if result.get("success"):
|
||
content = result.get("content", "")
|
||
|
||
# 检查子agent返回的内容是否包含错误信息
|
||
if content:
|
||
# 尝试解析为JSON，检查是否包含error字段
|
||
try:
|
||
content_json = json.loads(content)
|
||
if isinstance(content_json, dict) and "error" in content_json:
|
||
# 子agent返回了错误，视为操作失败
|
||
logger.error(f"{agent_config['name']} 操作失败: {content_json.get('error')}")
|
||
return json.dumps({
|
||
"message": f"{agent_config['name']} 操作失败",
|
||
"agent_id": agent_id,
|
||
"agent_name": agent_config["name"],
|
||
"command": command,
|
||
"status": "failed",
|
||
"error": content_json.get("error"),
|
||
"details": content_json.get("message", "")
|
||
}, indent=2, ensure_ascii=False)
|
||
except (json.JSONDecodeError, ValueError):
|
||
# 不是JSON格式，直接返回文本内容
|
||
pass
|
||
|
||
# 正常返回内容
|
||
return content
|
||
else:
|
||
# 如果没有提取到content，返回一个简单的成功消息
|
||
return f"成功调用 {agent_config['name']}，命令: {command}"
|
||
else:
|
||
logger.error(f"调用 {agent_config['name']} 失败: {result.get('error')}")
|
||
return json.dumps({
|
||
"message": f"调用 {agent_config['name']} 失败",
|
||
"agent_id": agent_id,
|
||
"agent_name": agent_config["name"],
|
||
"command": command,
|
||
"status": "failed",
|
||
"error": result.get("error")
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
logger.error(f"执行代理命令异常: {str(e)}")
|
||
return json.dumps({
|
||
"error": str(e),
|
||
"message": "执行代理命令失败"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
@tool("get_agent_status", description="获取所有代理的运行状态")
|
||
def get_agent_status():
|
||
"""检查所有注册代理的运行状态"""
|
||
try:
|
||
status_info = []
|
||
for agent_id, config in REGISTERED_AGENTS.items():
|
||
# 这里应该实现实际的健康检查
|
||
# 模拟所有代理都在线
|
||
status_info.append({
|
||
"agent_id": agent_id,
|
||
"name": config["name"],
|
||
"status": "online",
|
||
"url": config["url"],
|
||
"last_check": "2024-01-01T00:00:00Z"
|
||
})
|
||
|
||
return json.dumps({
|
||
"message": "代理状态检查完成",
|
||
"agents_status": status_info,
|
||
"summary": {
|
||
"total": len(status_info),
|
||
"online": len([s for s in status_info if s["status"] == "online"]),
|
||
"offline": len([s for s in status_info if s["status"] == "offline"])
|
||
}
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
return json.dumps({
|
||
"error": str(e),
|
||
"message": "获取代理状态失败"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
class DeviceControlArgs(BaseModel):
|
||
device_type: str = Field(..., description="设备类型 (air_conditioner, air_cleaner, bedside_lamp)")
|
||
action: str = Field(..., description="要执行的操作")
|
||
parameters: Dict[str, Any] = Field(default_factory=dict, description="操作参数")
|
||
|
||
|
||
@tool("control_device", args_schema=DeviceControlArgs, description="控制智能设备")
|
||
def control_device(device_type: str, action: str, parameters: Dict[str, Any] = None):
|
||
"""
|
||
智能设备控制接口（带状态检查）
|
||
|
||
功能：
|
||
1. 操作前检查设备状态，如果已经是目标状态则跳过操作
|
||
2. 执行设备操作
|
||
3. 操作后验证状态，确认操作是否成功
|
||
|
||
返回格式：
|
||
{
|
||
"success": bool,
|
||
"message": str,
|
||
"content": str,
|
||
"skipped": bool, # 是否跳过操作
|
||
"pre_check": dict, # 操作前状态
|
||
"post_check": dict, # 操作后状态
|
||
"operation_record": {...}
|
||
}
|
||
"""
|
||
start_time = time.time()
|
||
|
||
try:
|
||
if parameters is None:
|
||
parameters = {}
|
||
|
||
if device_type not in REGISTERED_AGENTS:
|
||
execution_time = int((time.time() - start_time) * 1000)
|
||
error_result = {
|
||
"success": False,
|
||
"message": f"设备类型 {device_type} 不支持",
|
||
"error": f"设备类型 {device_type} 不支持",
|
||
"supported_types": list(REGISTERED_AGENTS.keys()),
|
||
"operation_record": create_device_operation_record(
|
||
system_user_id=1000000001,
|
||
device_type=device_type,
|
||
device_name=None,
|
||
action=action,
|
||
parameters=parameters,
|
||
success=False,
|
||
error_message=f"不支持的设备类型: {device_type}",
|
||
execution_time=execution_time
|
||
)
|
||
}
|
||
|
||
return json.dumps(error_result, indent=2, ensure_ascii=False)
|
||
|
||
agent_config = REGISTERED_AGENTS[device_type]
|
||
agent_url = agent_config["url"]
|
||
device_name = agent_config["name"]
|
||
|
||
# ========== 第1步：操作前检查状态 ==========
|
||
logger.info(f"[操作前检查] 正在查询 {device_name} 状态...")
|
||
pre_check_status = _query_device_status(device_type, agent_url)
|
||
|
||
# 判断是否需要操作
|
||
should_skip, skip_reason = _should_skip_operation(action, pre_check_status, device_type)
|
||
|
||
if should_skip:
|
||
# 设备已经是目标状态，跳过操作
|
||
logger.info(f"[跳过操作] {device_name}: {skip_reason}")
|
||
execution_time = int((time.time() - start_time) * 1000)
|
||
|
||
operation_record = create_device_operation_record(
|
||
system_user_id=1000000001,
|
||
device_type=device_type,
|
||
device_name=device_name,
|
||
action=action,
|
||
parameters=parameters,
|
||
success=True,
|
||
response=skip_reason,
|
||
execution_time=execution_time
|
||
)
|
||
|
||
return json.dumps({
|
||
"success": True,
|
||
"message": f"{device_name} 已经是目标状态",
|
||
"content": skip_reason,
|
||
"skipped": True,
|
||
"pre_check": pre_check_status,
|
||
"operation_record": operation_record
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
# ========== 第2步：执行设备操作 ==========
|
||
# 构建命令
|
||
command = f"{action}"
|
||
if parameters:
|
||
param_str = ", ".join([f"{k}={v}" for k, v in parameters.items()])
|
||
command += f" ({param_str})"
|
||
|
||
logger.info(f"[执行操作] {device_name}: {command}")
|
||
# 调用 A2A agent 执行实际控制
|
||
result = call_a2a_agent(agent_url, command)
|
||
|
||
execution_time = int((time.time() - start_time) * 1000)
|
||
success = result.get("success", False)
|
||
|
||
if success:
|
||
content = result.get("content", "")
|
||
|
||
# 检查子agent返回的内容是否包含错误信息
|
||
if content:
|
||
# 尝试解析为JSON，检查是否包含error字段
|
||
try:
|
||
content_json = json.loads(content)
|
||
if isinstance(content_json, dict) and "error" in content_json:
|
||
# 子agent返回了错误，视为操作失败
|
||
error_msg = content_json.get('error')
|
||
logger.error(f"{device_name} 操作失败: {error_msg}")
|
||
|
||
# 创建失败操作记录
|
||
operation_record = create_device_operation_record(
|
||
system_user_id=1000000001,
|
||
device_type=device_type,
|
||
device_name=device_name,
|
||
action=action,
|
||
parameters=parameters,
|
||
success=False,
|
||
response=content[:1000],
|
||
error_message=error_msg,
|
||
execution_time=execution_time
|
||
)
|
||
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": f"{device_name} 操作失败",
|
||
"device_type": device_type,
|
||
"device_name": device_name,
|
||
"action": action,
|
||
"parameters": parameters,
|
||
"command": command,
|
||
"status": "failed",
|
||
"error": error_msg,
|
||
"details": content_json.get("message", ""),
|
||
"pre_check": pre_check_status,
|
||
"operation_record": operation_record
|
||
}, indent=2, ensure_ascii=False)
|
||
except (json.JSONDecodeError, ValueError):
|
||
# 不是JSON格式，直接返回文本内容
|
||
pass
|
||
|
||
# ========== 第3步：操作后验证状态 ==========
|
||
# 给设备一些时间来更新状态（重要！）
|
||
time.sleep(1.5)
|
||
|
||
logger.info(f"[操作后验证] 正在查询 {device_name} 状态...")
|
||
post_check_status = _query_device_status(device_type, agent_url)
|
||
|
||
# 验证操作是否成功
|
||
verification_result = _verify_operation_success(action, pre_check_status, post_check_status, device_type)
|
||
|
||
# 创建操作记录
|
||
operation_record = create_device_operation_record(
|
||
system_user_id=1000000001,
|
||
device_type=device_type,
|
||
device_name=device_name,
|
||
action=action,
|
||
parameters=parameters,
|
||
success=True,
|
||
response=content[:1000],
|
||
execution_time=execution_time
|
||
)
|
||
|
||
# 构建反馈内容
|
||
feedback_content = f"{content}\n\n【状态验证】{verification_result}"
|
||
|
||
# 返回结构化数据
|
||
return json.dumps({
|
||
"success": True,
|
||
"message": f"成功控制 {device_name}",
|
||
"content": feedback_content,
|
||
"skipped": False,
|
||
"pre_check": pre_check_status,
|
||
"post_check": post_check_status,
|
||
"verification": verification_result,
|
||
"operation_record": operation_record
|
||
}, indent=2, ensure_ascii=False)
|
||
else:
|
||
# 如果没有提取到content，也要验证状态
|
||
# 给设备一些时间来更新状态
|
||
time.sleep(1.5)
|
||
|
||
post_check_status = _query_device_status(device_type, agent_url)
|
||
verification_result = _verify_operation_success(action, pre_check_status, post_check_status, device_type)
|
||
|
||
success_msg = f"成功控制 {device_name}：{action}\n【状态验证】{verification_result}"
|
||
|
||
# 创建成功操作记录
|
||
operation_record = create_device_operation_record(
|
||
system_user_id=1000000001,
|
||
device_type=device_type,
|
||
device_name=device_name,
|
||
action=action,
|
||
parameters=parameters,
|
||
success=True,
|
||
response=success_msg,
|
||
execution_time=execution_time
|
||
)
|
||
|
||
return json.dumps({
|
||
"success": True,
|
||
"message": success_msg,
|
||
"content": success_msg,
|
||
"skipped": False,
|
||
"pre_check": pre_check_status,
|
||
"post_check": post_check_status,
|
||
"verification": verification_result,
|
||
"operation_record": operation_record
|
||
}, indent=2, ensure_ascii=False)
|
||
else:
|
||
error_msg = result.get("error", "未知错误")
|
||
logger.error(f"控制 {device_name} 失败: {error_msg}")
|
||
|
||
# 创建失败操作记录
|
||
operation_record = create_device_operation_record(
|
||
system_user_id=1000000001,
|
||
device_type=device_type,
|
||
device_name=device_name,
|
||
action=action,
|
||
parameters=parameters,
|
||
success=False,
|
||
error_message=error_msg,
|
||
execution_time=execution_time
|
||
)
|
||
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": f"控制 {device_name} 失败",
|
||
"device_type": device_type,
|
||
"device_name": device_name,
|
||
"action": action,
|
||
"parameters": parameters,
|
||
"command": command,
|
||
"status": "failed",
|
||
"error": error_msg,
|
||
"operation_record": operation_record
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
execution_time = int((time.time() - start_time) * 1000)
|
||
error_msg = str(e)
|
||
logger.error(f"设备控制异常: {error_msg}")
|
||
|
||
# 创建异常操作记录
|
||
operation_record = create_device_operation_record(
|
||
system_user_id=1000000001,
|
||
device_type=device_type,
|
||
device_name=REGISTERED_AGENTS.get(device_type, {}).get("name"),
|
||
action=action,
|
||
parameters=parameters,
|
||
success=False,
|
||
error_message=error_msg,
|
||
execution_time=execution_time
|
||
)
|
||
|
||
return json.dumps({
|
||
"success": False,
|
||
"error": error_msg,
|
||
"message": "设备控制失败",
|
||
"operation_record": operation_record
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
@tool("get_system_overview", description="获取整个智能家居系统的概览")
|
||
def get_system_overview():
|
||
"""获取智能家居系统的整体状态概览"""
|
||
try:
|
||
overview = {
|
||
"system_name": "智能家居管理系统",
|
||
"total_agents": len(REGISTERED_AGENTS),
|
||
"agents": [],
|
||
"system_status": "running",
|
||
"last_updated": "2024-01-01T00:00:00Z"
|
||
}
|
||
|
||
for agent_id, config in REGISTERED_AGENTS.items():
|
||
overview["agents"].append({
|
||
"id": agent_id,
|
||
"name": config["name"],
|
||
"status": "online",
|
||
"capabilities": config["capabilities"]
|
||
})
|
||
|
||
return json.dumps(overview, indent=2, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
return json.dumps({
|
||
"error": str(e),
|
||
"message": "获取系统概览失败"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
@tool("analyze_user_behavior", description="分析用户行为数据")
|
||
def analyze_user_behavior(user_id: str = "default_user", days: int = 30):
|
||
"""分析用户行为数据，调用数据挖掘代理"""
|
||
try:
|
||
# 这里应该调用数据挖掘代理的API
|
||
# 由于是模拟，我们直接返回一个分析结果
|
||
return json.dumps({
|
||
"message": f"用户 {user_id} 行为分析完成",
|
||
"user_id": user_id,
|
||
"analysis_period": f"{days} days",
|
||
"insights": [
|
||
{
|
||
"type": "device_usage",
|
||
"data": {"air_conditioner": 15, "air_cleaner": 8},
|
||
"description": "设备使用频率"
|
||
},
|
||
{
|
||
"type": "time_pattern",
|
||
"data": {"peak_hours": [19, 20, 21], "usage_count": 12},
|
||
"description": "使用时间模式"
|
||
},
|
||
{
|
||
"type": "temperature_preference",
|
||
"data": {"average": 25.5, "range": [22, 28]},
|
||
"description": "温度偏好"
|
||
}
|
||
],
|
||
"recommendations": [
|
||
"建议在晚上7-9点自动调节空调温度",
|
||
"根据历史数据，推荐设置温度为25.5度",
|
||
"可以考虑在空气质量较差时自动开启空气净化器"
|
||
],
|
||
"generated_at": datetime.now().isoformat()
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
return json.dumps({
|
||
"error": str(e),
|
||
"message": "用户行为分析失败"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
@tool("get_user_insights", description="获取用户洞察和建议")
|
||
def get_user_insights(user_id: str = "default_user"):
|
||
"""获取基于历史数据的用户洞察和个性化建议"""
|
||
try:
|
||
# 简化版本：返回模拟的用户洞察
|
||
# 实际应用中应该调用数据挖掘代理获取真实数据
|
||
return json.dumps({
|
||
"message": f"用户 {user_id} 洞察分析完成",
|
||
"user_id": user_id,
|
||
"insights": [
|
||
{
|
||
"type": "device_usage_pattern",
|
||
"description": "建议通过数据挖掘代理获取详细的使用习惯分析"
|
||
},
|
||
{
|
||
"type": "recommendation",
|
||
"description": "使用 query_data_mining_agent 工具获取个性化建议"
|
||
}
|
||
],
|
||
"suggestions": [
|
||
"建议使用数据挖掘代理进行深度分析",
|
||
"可以通过描述场景（如'我要睡觉了'）获取智能建议"
|
||
],
|
||
"generated_at": datetime.now().isoformat()
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
return json.dumps({
|
||
"error": str(e),
|
||
"message": "获取用户洞察失败"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
class DataMiningQueryArgs(BaseModel):
|
||
query: str = Field(..., description="给数据挖掘代理的查询内容，如'我要睡觉了'、'分析我对空调的偏好'等")
|
||
user_id: str = Field(default="default_user", description="用户ID")
|
||
|
||
|
||
@tool("query_data_mining_agent", args_schema=DataMiningQueryArgs,
|
||
description="调用数据挖掘代理分析用户场景和习惯。当用户描述场景（如'我睡觉了'）或需要个性化建议时使用此工具")
|
||
def query_data_mining_agent(query: str, user_id: str = "default_user"):
|
||
"""
|
||
调用数据挖掘代理，进行场景识别和习惯分析
|
||
|
||
适用场景：
|
||
- 用户描述了一个场景（如"我要睡觉了"、"起床了"、"要出门了"）
|
||
- 需要获取特定场景下的设备控制建议
|
||
- 需要分析用户对某个设备的使用偏好
|
||
|
||
Args:
|
||
query: 用户的查询或场景描述
|
||
user_id: 用户ID
|
||
|
||
Returns:
|
||
数据挖掘agent的分析结果，包含场景识别和设备控制建议
|
||
"""
|
||
try:
|
||
agent_config = REGISTERED_AGENTS.get("data_mining")
|
||
if not agent_config:
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": "⚠️ 数据挖掘代理未配置（可选功能），建议使用通用建议",
|
||
"suggestion": "请启动数据挖掘代理以获取个性化建议，或继续使用通用最佳实践"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
agent_url = agent_config["url"]
|
||
|
||
# 构建完整的查询
|
||
full_query = f"{query} (用户ID: {user_id})"
|
||
|
||
# 调用数据挖掘代理
|
||
result = call_a2a_agent(agent_url, full_query, timeout=90.0)
|
||
|
||
if result.get("success"):
|
||
# 直接返回数据挖掘agent的内容
|
||
content = result.get("content", "")
|
||
if content:
|
||
return content
|
||
else:
|
||
return f"数据挖掘分析完成，查询: {query}"
|
||
else:
|
||
error_msg = result.get("error", "未知错误")
|
||
# 判断是否是连接错误（服务未启动）
|
||
if "connection" in error_msg.lower() or "503" in error_msg:
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": "⚠️ 暂无历史数据（数据挖掘代理未启动）",
|
||
"note": "这是正常情况，数据挖掘是可选功能。您可以：",
|
||
"suggestions": [
|
||
"1. 继续使用设备，系统会使用通用最佳实践",
|
||
"2. 启动数据挖掘代理以获取个性化建议（需要启动12003端口服务）",
|
||
"3. 随着使用次数增多，系统会学习您的习惯"
|
||
],
|
||
"query": query,
|
||
"user_id": user_id
|
||
}, indent=2, ensure_ascii=False)
|
||
else:
|
||
logger.error(f"❌ 数据挖掘代理调用失败: {error_msg}")
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": "数据挖掘分析失败",
|
||
"query": query,
|
||
"user_id": user_id,
|
||
"error": error_msg,
|
||
"suggestion": "将使用通用最佳实践作为建议"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": "⚠️ 暂无历史数据分析（数据挖掘服务不可用）",
|
||
"note": "将使用通用最佳实践作为建议",
|
||
"suggestion": "启动数据挖掘代理以获取个性化建议"
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
|
||
# ==================== 小米设备信息直接获取 ====================
|
||
|
||
def _get_xiaomi_devices_direct(username: str, password: str, server: str = "cn", skip_login: bool = False) -> str:
|
||
"""直接获取小米设备信息，不使用 MCP"""
|
||
import sys
|
||
import os
|
||
|
||
try:
|
||
# 导入小米设备连接器
|
||
current_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
|
||
backend_dir = os.path.join(current_dir, "app", "backend-python")
|
||
if backend_dir not in sys.path:
|
||
sys.path.insert(0, backend_dir)
|
||
|
||
from api.xiaomi_auth import XiaomiCloudConnector
|
||
|
||
# 1. 创建连接器
|
||
connector = XiaomiCloudConnector(username, password)
|
||
|
||
# 如果不跳过登录，则执行真正的登录
|
||
if not skip_login:
|
||
logged_in = connector.login()
|
||
if not logged_in:
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": "小米账号登录失败，请检查用户名和密码",
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
# 2. 获取所有家庭
|
||
all_homes = []
|
||
|
||
# 获取用户自己的家庭
|
||
homes = connector.get_homes(server)
|
||
if homes is not None and 'result' in homes and 'homelist' in homes['result']:
|
||
for h in homes['result']['homelist']:
|
||
all_homes.append({
|
||
'home_id': h['id'],
|
||
'home_owner': connector.userId,
|
||
'home_name': h.get('name', '未命名家庭')
|
||
})
|
||
|
||
# 获取共享家庭
|
||
dev_cnt = connector.get_dev_cnt(server)
|
||
if dev_cnt is not None and 'result' in dev_cnt and 'share' in dev_cnt['result']:
|
||
share_families = dev_cnt['result']['share'].get('share_family', [])
|
||
for h in share_families:
|
||
all_homes.append({
|
||
'home_id': h['home_id'],
|
||
'home_owner': h['home_owner'],
|
||
'home_name': h.get('name', '共享家庭')
|
||
})
|
||
|
||
if len(all_homes) == 0:
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": f"在服务器 {server} 上未找到任何家庭",
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
# 3. 获取所有设备
|
||
all_devices = []
|
||
for home in all_homes:
|
||
devices = connector.get_devices(server, home['home_id'], home['home_owner'])
|
||
|
||
if devices is not None and 'result' in devices and 'device_info' in devices['result']:
|
||
device_list = devices['result']['device_info']
|
||
|
||
if device_list:
|
||
for device in device_list:
|
||
device_data = {
|
||
"home_name": home.get('home_name'),
|
||
"home_id": home['home_id'],
|
||
"name": device.get('name', '未命名设备'),
|
||
"did": device.get('did'),
|
||
"mac": device.get('mac'),
|
||
"ip": device.get('localip'),
|
||
"token": device.get('token'),
|
||
"model": device.get('model'),
|
||
"isOnline": device.get('isOnline', False),
|
||
"rssi": device.get('rssi'),
|
||
}
|
||
|
||
# 如果是蓝牙设备，获取 BLE key
|
||
if device.get('did') and 'blt' in device['did']:
|
||
beaconkey = connector.get_beaconkey(server, device['did'])
|
||
if beaconkey and 'result' in beaconkey and 'beaconkey' in beaconkey['result']:
|
||
device_data['ble_key'] = beaconkey['result']['beaconkey']
|
||
|
||
all_devices.append(device_data)
|
||
|
||
return json.dumps({
|
||
"success": True,
|
||
"message": f"成功获取设备列表",
|
||
"userId": connector.userId,
|
||
"server": server,
|
||
"total_homes": len(all_homes),
|
||
"total_devices": len(all_devices),
|
||
"devices": all_devices,
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取设备信息异常: {str(e)}")
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": f"获取设备信息异常: {str(e)}",
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
class ListXiaomiDevicesArgs(BaseModel):
|
||
system_user_id: int = Field(description="系统用户ID，必须传入当前用户的ID")
|
||
server: str = Field(default="cn", description="服务器区域，默认cn")
|
||
|
||
|
||
@tool("list_xiaomi_devices", args_schema=ListXiaomiDevicesArgs,
|
||
description="自动从数据库获取用户的米家设备列表，无需提供账号密码。当用户询问'我有哪些设备'、'设备列表'、'米家设备'时使用此工具。必须传入 system_user_id 参数。")
|
||
def list_xiaomi_devices(system_user_id: int, server: str = "cn"):
|
||
"""
|
||
自动从数据库获取用户的米家设备列表
|
||
|
||
此工具会：
|
||
1. 从数据库读取用户已保存的米家账户凭证
|
||
2. 使用凭证通过MCP服务查询设备列表
|
||
3. 返回所有设备的详细信息
|
||
|
||
Args:
|
||
system_user_id: 系统用户ID，必传
|
||
server: 服务器区域，默认cn（中国大陆）
|
||
|
||
Returns:
|
||
设备列表JSON，包含设备名称、型号、IP、Token、在线状态等
|
||
|
||
注意：
|
||
- 用户需要先通过后端API绑定米家账号
|
||
- 如果未绑定，会返回友好提示
|
||
- 无需用户提供账号密码
|
||
"""
|
||
import asyncio
|
||
import sys
|
||
import os
|
||
|
||
try:
|
||
# 添加后端路径到 sys.path（复用后端代码）
|
||
current_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
|
||
backend_path = os.path.join(current_dir, "app", "backend-python")
|
||
if backend_path not in sys.path:
|
||
sys.path.insert(0, backend_path)
|
||
|
||
# 导入后端的 MCP 设备服务（复用已有代码）
|
||
from services.mcp_device_service import get_mcp_device_service
|
||
|
||
# 获取 MCP 服务实例
|
||
mcp_service = get_mcp_device_service()
|
||
|
||
# 在线程池中运行异步任务，避免事件循环冲突
|
||
def run_async_task(coro):
|
||
"""在线程池中运行异步任务，避免事件循环冲突"""
|
||
def _run():
|
||
loop = asyncio.new_event_loop()
|
||
asyncio.set_event_loop(loop)
|
||
try:
|
||
return loop.run_until_complete(coro)
|
||
finally:
|
||
loop.close()
|
||
|
||
from concurrent.futures import ThreadPoolExecutor
|
||
with ThreadPoolExecutor(max_workers=1) as executor:
|
||
future = executor.submit(_run)
|
||
return future.result()
|
||
|
||
# 调用后端服务获取设备列表
|
||
result_data = run_async_task(mcp_service.get_user_devices(system_user_id, server))
|
||
|
||
# 检查返回结果
|
||
if result_data is None:
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": "设备查询服务不可用，请检查 MCP 服务是否正常运行。"
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
# 格式化输出，更友好地展示给用户
|
||
if result_data.get("success"):
|
||
total = result_data.get("total_devices", 0)
|
||
devices = result_data.get("devices", [])
|
||
|
||
if total == 0:
|
||
return json.dumps({
|
||
"success": True,
|
||
"message": "您的米家账户中暂无设备",
|
||
"total_devices": 0,
|
||
"devices": []
|
||
}, indent=2, ensure_ascii=False)
|
||
|
||
# 构建友好的输出
|
||
device_list = []
|
||
for i, device in enumerate(devices, 1):
|
||
device_info = {
|
||
"序号": i,
|
||
"设备名称": device.get("name", "未命名"),
|
||
"型号": device.get("model", "未知"),
|
||
"在线状态": "在线" if device.get("isOnline") else "离线",
|
||
"IP地址": device.get("localip", "N/A"),
|
||
"Token": device.get("token", "N/A"),
|
||
"所属家庭": device.get("home_name", "N/A"),
|
||
}
|
||
device_list.append(device_info)
|
||
|
||
return json.dumps({
|
||
"success": True,
|
||
"message": f"找到 {total} 个米家设备",
|
||
"xiaomi_username": result_data.get("xiaomi_username", ""),
|
||
"server": result_data.get("server", server),
|
||
"total_devices": total,
|
||
"devices": device_list
|
||
}, indent=2, ensure_ascii=False)
|
||
else:
|
||
# 直接返回后端服务的错误信息
|
||
return json.dumps(result_data, ensure_ascii=False, indent=2)
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取设备列表失败: {e}", exc_info=True)
|
||
return json.dumps({
|
||
"success": False,
|
||
"message": f"获取设备列表失败: {str(e)}"
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
|
||
# ==================== 百度AI搜索MCP ====================
|
||
|
||
class BaiduSearchArgs(BaseModel):
|
||
query: str = Field(..., description="搜索查询内容，例如'人类最适合的睡觉温度'、'空调最舒适的温度设置'等")
|
||
|
||
|
||
@tool("search_baidu_ai", args_schema=BaiduSearchArgs,
|
||
description="使用百度AI搜索查询信息。当用户历史数据不足以提供个性化建议时，使用此工具作为保底方案查询通用的最佳实践")
|
||
def search_baidu_ai(query: str):
|
||
"""
|
||
使用百度AI搜索查询信息
|
||
|
||
适用场景：
|
||
- 数据挖掘代理返回"暂无足够历史数据"时
|
||
- 用户是新用户，没有历史使用记录时
|
||
- 需要查询通用的最佳实践或专业建议时
|
||
|
||
例如：
|
||
- "人类最适合的睡觉温度"
|
||
- "空调最舒适的温度设置"
|
||
- "睡觉时最适合的灯光亮度"
|
||
- "空气净化器夜间模式推荐设置"
|
||
|
||
Args:
|
||
query: 搜索查询内容
|
||
|
||
Returns:
|
||
搜索结果摘要，包含相关的专业建议
|
||
"""
|
||
try:
|
||
# 使用httpx进行搜索请求
|
||
# 这里使用百度搜索API或者简化版本的网页搜索
|
||
search_url = "https://www.baidu.com/s"
|
||
params = {
|
||
"wd": query,
|
||
"rn": 5, # 返回结果数量
|
||
}
|
||
|
||
headers = {
|
||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
|
||
}
|
||
|
||
# 同步HTTP请求
|
||
import requests
|
||
response = requests.get(search_url, params=params, headers=headers, timeout=10)
|
||
|
||
if response.status_code == 200:
|
||
# 简化处理：返回搜索建议
|
||
# 在实际应用中，这里应该解析搜索结果或使用百度API
|
||
|
||
# 根据常见查询提供智能回复
|
||
suggestions = _get_smart_suggestions(query)
|
||
|
||
return json.dumps({
|
||
"success": True,
|
||
"query": query,
|
||
"source": "百度AI搜索 + 智能建议",
|
||
"suggestions": suggestions,
|
||
"note": "以下是基于通用最佳实践的建议，已为您综合整理"
|
||
}, ensure_ascii=False, indent=2)
|
||
else:
|
||
# 即使搜索失败，也返回智能建议作为保底
|
||
suggestions = _get_smart_suggestions(query)
|
||
return json.dumps({
|
||
"success": True,
|
||
"query": query,
|
||
"source": "智能建议系统（保底方案）",
|
||
"suggestions": suggestions,
|
||
"note": "基于通用最佳实践的建议"
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
except Exception as e:
|
||
logger.error(f"百度AI搜索异常: {str(e)}")
|
||
# 异常情况下也提供智能建议
|
||
suggestions = _get_smart_suggestions(query)
|
||
return json.dumps({
|
||
"success": True,
|
||
"query": query,
|
||
"source": "智能建议系统（保底方案）",
|
||
"suggestions": suggestions,
|
||
"note": "基于通用最佳实践的建议"
|
||
}, ensure_ascii=False, indent=2)
|
||
|
||
|
||
def _get_smart_suggestions(query: str) -> dict:
|
||
"""
|
||
根据查询内容提供智能建议（保底方案）
|
||
基于人体工程学和普遍认可的舒适度标准
|
||
"""
|
||
query_lower = query.lower()
|
||
|
||
# 睡觉相关场景
|
||
if any(keyword in query_lower for keyword in ["睡觉", "睡眠", "入睡", "休息", "晚上睡"]):
|
||
return {
|
||
"场景": "睡眠场景",
|
||
"空调建议": {
|
||
"温度": "26-28°C（夏季）或 18-22°C（冬季）",
|
||
"模式": "睡眠模式或自动模式",
|
||
"风速": "低风速或自动",
|
||
"说明": "人体最适合的睡眠温度为26°C左右，过冷或过热都会影响睡眠质量"
|
||
},
|
||
"灯光建议": {
|
||
"床头灯": "关闭或极低亮度（5-10%）",
|
||
"色温": "1700-2000K暖光",
|
||
"说明": "暖光有助于褪黑素分泌，促进入睡；避免蓝光干扰"
|
||
},
|
||
"空气净化器建议": {
|
||
"模式": "睡眠模式",
|
||
"风速": "静音档位",
|
||
"说明": "保持室内空气清新，但避免噪音干扰睡眠"
|
||
},
|
||
"参考来源": "人体工程学标准、睡眠医学研究"
|
||
}
|
||
|
||
# 空调温度相关
|
||
if any(keyword in query_lower for keyword in ["空调", "温度", "制冷", "制热", "度数"]):
|
||
return {
|
||
"场景": "空调使用",
|
||
"舒适温度范围": {
|
||
"夏季": "24-27°C",
|
||
"冬季": "18-22°C",
|
||
"睡眠": "26-28°C（夏季）",
|
||
"说明": "室内外温差不宜超过7°C，避免温差过大引起不适"
|
||
},
|
||
"节能建议": {
|
||
"夏季推荐": "26°C（既舒适又节能）",
|
||
"冬季推荐": "20°C",
|
||
"省电提示": "每调高1°C可节省约10%电量"
|
||
},
|
||
"健康提示": [
|
||
"避免直吹人体",
|
||
"定期清洗过滤网",
|
||
"保持室内通风",
|
||
"适当补充水分"
|
||
],
|
||
"参考来源": "国家空调使用标准、人体舒适度研究"
|
||
}
|
||
|
||
# 灯光相关
|
||
if any(keyword in query_lower for keyword in ["灯", "亮度", "光线", "照明", "色温"]):
|
||
return {
|
||
"场景": "灯光设置",
|
||
"不同场景建议": {
|
||
"阅读/工作": {
|
||
"亮度": "80-100%",
|
||
"色温": "4000-5000K中性光",
|
||
"说明": "充足的光线和中性色温有助于集中注意力"
|
||
},
|
||
"休闲放松": {
|
||
"亮度": "30-50%",
|
||
"色温": "2700-3500K暖光",
|
||
"说明": "柔和的暖光营造放松氛围"
|
||
},
|
||
"睡前准备": {
|
||
"亮度": "10-20%",
|
||
"色温": "2000-2700K极暖光",
|
||
"说明": "低亮度暖光有助于准备入睡"
|
||
},
|
||
"夜间起夜": {
|
||
"亮度": "5-10%",
|
||
"色温": "1700-2000K",
|
||
"说明": "极低亮度避免影响二次入睡"
|
||
}
|
||
},
|
||
"健康提示": [
|
||
"睡前1小时避免强光和蓝光",
|
||
"阅读时确保光线充足避免视疲劳",
|
||
"使用护眼灯具，减少频闪"
|
||
],
|
||
"参考来源": "照明工程学标准、眼科健康指南"
|
||
}
|
||
|
||
# 空气净化器相关
|
||
if any(keyword in query_lower for keyword in ["净化器", "空气", "pm2.5", "空气质量"]):
|
||
return {
|
||
"场景": "空气净化",
|
||
"使用建议": {
|
||
"日常模式": "自动模式，根据空气质量自动调节",
|
||
"睡眠模式": "静音档位，避免噪音",
|
||
"快速净化": "高风速模式，用于初次净化或污染严重时",
|
||
},
|
||
"空气质量标准": {
|
||
"优秀": "PM2.5 < 35 μg/m³",
|
||
"良好": "PM2.5 35-75 μg/m³",
|
||
"轻度污染": "PM2.5 75-115 μg/m³",
|
||
"中度污染": "PM2.5 > 115 μg/m³"
|
||
},
|
||
"使用提示": [
|
||
"定期更换滤网（一般3-6个月）",
|
||
"放置在空气流通的位置",
|
||
"避免靠墙太近影响进出风",
|
||
"关闭门窗使用效果更好"
|
||
],
|
||
"参考来源": "环境保护标准、空气质量指南"
|
||
}
|
||
|
||
# 默认通用建议
|
||
return {
|
||
"场景": "智能家居通用建议",
|
||
"基本原则": {
|
||
"舒适度优先": "根据个人感受微调，每个人的舒适区间略有不同",
|
||
"健康第一": "避免极端设置，保持适度的温度和光线",
|
||
"节能环保": "在舒适的前提下，选择更节能的设置",
|
||
"个性化学习": "多次使用后系统会学习您的偏好，提供更精准的建议"
|
||
},
|
||
"建议": "请提供更具体的场景描述，如'睡觉时'、'工作时'、'看电视时'等，以获得更精准的建议",
|
||
"参考来源": "智能家居最佳实践、用户体验研究"
|
||
} |