# 框架抽象层管理器类设计

## 1. 概述

本文档详细描述了统一Agent框架中框架抽象层的管理器类设计。管理器类是框架抽象层的重要组成部分，它负责管理各种对象的生命周期、状态和交互，如智能体、任务、上下文等，使上层应用能够以统一的方式管理这些对象，而不必关心具体的实现细节。

## 2. 设计原则

管理器类的设计遵循以下原则：

- **单一职责**：每个管理器类只负责管理一种类型的对象
- **生命周期管理**：负责对象的创建、初始化、运行、暂停、恢复和销毁
- **状态管理**：跟踪和管理对象的状态变化
- **事件驱动**：支持事件通知和回调机制
- **可扩展性**：支持添加新的管理功能和策略
- **线程安全**：保证在多线程环境下的安全性
- **资源优化**：优化资源使用，避免资源泄漏

## 3. 核心管理器类

### 3.1 AgentManager

`AgentManager`负责管理智能体的生命周期和状态，它提供了创建、初始化、运行、暂停、恢复和销毁智能体的方法，以及获取智能体状态和信息的方法。

```python
from typing import Dict, List, Optional, Callable, Any
from unified_agent.framework.interfaces import AgentInterface
from unified_agent.framework.factories import AgentFactory
import threading

class AgentManager:
    """智能体管理器，负责管理智能体的生命周期和状态"""
    
    _instance = None
    
    @classmethod
    def get_instance(cls) -> 'AgentManager':
        """获取单例实例"""
        if cls._instance is None:
            cls._instance = cls()
        return cls._instance
    
    def __init__(self):
        """初始化智能体管理器"""
        self._agents: Dict[str, AgentInterface] = {}
        self._agent_states: Dict[str, str] = {}
        self._agent_factory = AgentFactory.get_instance()
        self._lock = threading.RLock()
        self._event_listeners: Dict[str, List[Callable]] = {}
    
    def create_agent(self, config: dict, adapter_name: Optional[str] = None) -> AgentInterface:
        """创建智能体
        
        Args:
            config: 智能体配置
            adapter_name: 适配器名称，如果为None，则使用默认适配器
            
        Returns:
            AgentInterface: 智能体实例
            
        Raises:
            ValueError: 如果智能体ID已存在或创建智能体失败
        """
        with self._lock:
            # 创建智能体
            agent = self._agent_factory.create(config, adapter_name)
            
            # 检查智能体ID是否已存在
            agent_id = agent.get_id()
            if agent_id in self._agents:
                raise ValueError(f"Agent with ID '{agent_id}' already exists")
            
            # 添加智能体到管理器
            self._agents[agent_id] = agent
            self._agent_states[agent_id] = 'created'
            
            # 触发事件
            self._trigger_event('agent_created', agent_id, agent)
            
            return agent
    
    def get_agent(self, agent_id: str) -> Optional[AgentInterface]:
        """获取智能体
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            Optional[AgentInterface]: 智能体实例，如果不存在则返回None
        """
        with self._lock:
            return self._agents.get(agent_id)
    
    def get_all_agents(self) -> Dict[str, AgentInterface]:
        """获取所有智能体
        
        Returns:
            Dict[str, AgentInterface]: 智能体字典，键为智能体ID，值为智能体实例
        """
        with self._lock:
            return self._agents.copy()
    
    def initialize_agent(self, agent_id: str, **kwargs) -> bool:
        """初始化智能体
        
        Args:
            agent_id: 智能体ID
            **kwargs: 初始化参数
            
        Returns:
            bool: 是否成功初始化
            
        Raises:
            ValueError: 如果智能体不存在或已经初始化
        """
        with self._lock:
            # 检查智能体是否存在
            agent = self._agents.get(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 检查智能体状态
            state = self._agent_states.get(agent_id)
            if state != 'created':
                raise ValueError(f"Agent with ID '{agent_id}' is already initialized or running")
            
            # 初始化智能体
            success = agent.initialize(**kwargs)
            if success:
                self._agent_states[agent_id] = 'initialized'
                # 触发事件
                self._trigger_event('agent_initialized', agent_id, agent)
            
            return success
    
    def start_agent(self, agent_id: str) -> bool:
        """启动智能体
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            bool: 是否成功启动
            
        Raises:
            ValueError: 如果智能体不存在或未初始化
        """
        with self._lock:
            # 检查智能体是否存在
            agent = self._agents.get(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 检查智能体状态
            state = self._agent_states.get(agent_id)
            if state not in ['initialized', 'paused']:
                raise ValueError(f"Agent with ID '{agent_id}' is not initialized or paused")
            
            # 启动智能体
            success = agent.start()
            if success:
                self._agent_states[agent_id] = 'running'
                # 触发事件
                self._trigger_event('agent_started', agent_id, agent)
            
            return success
    
    def pause_agent(self, agent_id: str) -> bool:
        """暂停智能体
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            bool: 是否成功暂停
            
        Raises:
            ValueError: 如果智能体不存在或未运行
        """
        with self._lock:
            # 检查智能体是否存在
            agent = self._agents.get(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 检查智能体状态
            state = self._agent_states.get(agent_id)
            if state != 'running':
                raise ValueError(f"Agent with ID '{agent_id}' is not running")
            
            # 暂停智能体
            success = agent.pause()
            if success:
                self._agent_states[agent_id] = 'paused'
                # 触发事件
                self._trigger_event('agent_paused', agent_id, agent)
            
            return success
    
    def resume_agent(self, agent_id: str) -> bool:
        """恢复智能体
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            bool: 是否成功恢复
            
        Raises:
            ValueError: 如果智能体不存在或未暂停
        """
        with self._lock:
            # 检查智能体是否存在
            agent = self._agents.get(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 检查智能体状态
            state = self._agent_states.get(agent_id)
            if state != 'paused':
                raise ValueError(f"Agent with ID '{agent_id}' is not paused")
            
            # 恢复智能体
            success = agent.resume()
            if success:
                self._agent_states[agent_id] = 'running'
                # 触发事件
                self._trigger_event('agent_resumed', agent_id, agent)
            
            return success
    
    def stop_agent(self, agent_id: str) -> bool:
        """停止智能体
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            bool: 是否成功停止
            
        Raises:
            ValueError: 如果智能体不存在或未运行或未暂停
        """
        with self._lock:
            # 检查智能体是否存在
            agent = self._agents.get(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 检查智能体状态
            state = self._agent_states.get(agent_id)
            if state not in ['running', 'paused']:
                raise ValueError(f"Agent with ID '{agent_id}' is not running or paused")
            
            # 停止智能体
            success = agent.stop()
            if success:
                self._agent_states[agent_id] = 'stopped'
                # 触发事件
                self._trigger_event('agent_stopped', agent_id, agent)
            
            return success
    
    def destroy_agent(self, agent_id: str) -> bool:
        """销毁智能体
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            bool: 是否成功销毁
            
        Raises:
            ValueError: 如果智能体不存在
        """
        with self._lock:
            # 检查智能体是否存在
            agent = self._agents.get(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 如果智能体正在运行，先停止它
            state = self._agent_states.get(agent_id)
            if state in ['running', 'paused']:
                agent.stop()
            
            # 销毁智能体
            success = agent.destroy()
            if success:
                # 从管理器中移除智能体
                del self._agents[agent_id]
                del self._agent_states[agent_id]
                # 触发事件
                self._trigger_event('agent_destroyed', agent_id, None)
            
            return success
    
    def get_agent_state(self, agent_id: str) -> Optional[str]:
        """获取智能体状态
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            Optional[str]: 智能体状态，如果不存在则返回None
        """
        with self._lock:
            return self._agent_states.get(agent_id)
    
    def get_agent_info(self, agent_id: str) -> Optional[dict]:
        """获取智能体信息
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            Optional[dict]: 智能体信息，如果不存在则返回None
        """
        with self._lock:
            agent = self._agents.get(agent_id)
            if not agent:
                return None
            
            return {
                'id': agent.get_id(),
                'name': agent.get_name(),
                'description': agent.get_description(),
                'state': self._agent_states.get(agent_id),
                'capabilities': agent.get_capabilities(),
                'adapter': agent.get_adapter_info()
            }
    
    def add_event_listener(self, event_type: str, listener: Callable) -> None:
        """添加事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
        """
        with self._lock:
            if event_type not in self._event_listeners:
                self._event_listeners[event_type] = []
            self._event_listeners[event_type].append(listener)
    
    def remove_event_listener(self, event_type: str, listener: Callable) -> bool:
        """移除事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
            
        Returns:
            bool: 是否成功移除
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return False
            
            if listener in self._event_listeners[event_type]:
                self._event_listeners[event_type].remove(listener)
                return True
            
            return False
    
    def _trigger_event(self, event_type: str, agent_id: str, data: Any) -> None:
        """触发事件
        
        Args:
            event_type: 事件类型
            agent_id: 智能体ID
            data: 事件数据
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return
            
            event = {
                'type': event_type,
                'agent_id': agent_id,
                'data': data,
                'timestamp': import_time().time()
            }
            
            for listener in self._event_listeners[event_type]:
                try:
                    listener(event)
                except Exception as e:
                    import logging
                    logging.error(f"Error in event listener: {e}")
    
    def import_time(self):
        """导入时间模块"""
        import time
        return time
```

### 3.2 TaskManager

`TaskManager`负责管理任务的生命周期和状态，它提供了创建、分配、执行、取消和查询任务的方法。

```python
from typing import Dict, List, Optional, Callable, Any
from unified_agent.framework.interfaces import TaskInterface, AgentInterface, ResultInterface
from unified_agent.framework.factories import TaskFactory
import threading
import uuid

class TaskManager:
    """任务管理器，负责管理任务的生命周期和状态"""
    
    _instance = None
    
    @classmethod
    def get_instance(cls) -> 'TaskManager':
        """获取单例实例"""
        if cls._instance is None:
            cls._instance = cls()
        return cls._instance
    
    def __init__(self):
        """初始化任务管理器"""
        self._tasks: Dict[str, TaskInterface] = {}
        self._task_states: Dict[str, str] = {}
        self._task_assignments: Dict[str, str] = {}  # 任务ID -> 智能体ID
        self._task_results: Dict[str, ResultInterface] = {}
        self._task_factory = TaskFactory.get_instance()
        self._lock = threading.RLock()
        self._event_listeners: Dict[str, List[Callable]] = {}
    
    def create_task(self, config: dict) -> TaskInterface:
        """创建任务
        
        Args:
            config: 任务配置
            
        Returns:
            TaskInterface: 任务实例
        """
        with self._lock:
            # 创建任务
            task = self._task_factory.create(config)
            
            # 添加任务到管理器
            task_id = task.get_id()
            self._tasks[task_id] = task
            self._task_states[task_id] = 'created'
            
            # 触发事件
            self._trigger_event('task_created', task_id, task)
            
            return task
    
    def get_task(self, task_id: str) -> Optional[TaskInterface]:
        """获取任务
        
        Args:
            task_id: 任务ID
            
        Returns:
            Optional[TaskInterface]: 任务实例，如果不存在则返回None
        """
        with self._lock:
            return self._tasks.get(task_id)
    
    def get_all_tasks(self) -> Dict[str, TaskInterface]:
        """获取所有任务
        
        Returns:
            Dict[str, TaskInterface]: 任务字典，键为任务ID，值为任务实例
        """
        with self._lock:
            return self._tasks.copy()
    
    def assign_task(self, task_id: str, agent_id: str) -> bool:
        """分配任务给智能体
        
        Args:
            task_id: 任务ID
            agent_id: 智能体ID
            
        Returns:
            bool: 是否成功分配
            
        Raises:
            ValueError: 如果任务或智能体不存在，或任务已经分配
        """
        with self._lock:
            # 检查任务是否存在
            task = self._tasks.get(task_id)
            if not task:
                raise ValueError(f"Task with ID '{task_id}' not found")
            
            # 检查任务状态
            state = self._task_states.get(task_id)
            if state != 'created':
                raise ValueError(f"Task with ID '{task_id}' is already assigned or executed")
            
            # 检查智能体是否存在
            from unified_agent.framework.managers import AgentManager
            agent_manager = AgentManager.get_instance()
            agent = agent_manager.get_agent(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 分配任务
            self._task_assignments[task_id] = agent_id
            self._task_states[task_id] = 'assigned'
            
            # 触发事件
            self._trigger_event('task_assigned', task_id, {'task': task, 'agent_id': agent_id})
            
            return True
    
    def execute_task(self, task_id: str) -> ResultInterface:
        """执行任务
        
        Args:
            task_id: 任务ID
            
        Returns:
            ResultInterface: 任务执行结果
            
        Raises:
            ValueError: 如果任务不存在或未分配
        """
        with self._lock:
            # 检查任务是否存在
            task = self._tasks.get(task_id)
            if not task:
                raise ValueError(f"Task with ID '{task_id}' not found")
            
            # 检查任务状态
            state = self._task_states.get(task_id)
            if state != 'assigned':
                raise ValueError(f"Task with ID '{task_id}' is not assigned")
            
            # 获取分配的智能体
            agent_id = self._task_assignments.get(task_id)
            if not agent_id:
                raise ValueError(f"Task with ID '{task_id}' is not assigned to any agent")
            
            from unified_agent.framework.managers import AgentManager
            agent_manager = AgentManager.get_instance()
            agent = agent_manager.get_agent(agent_id)
            if not agent:
                raise ValueError(f"Agent with ID '{agent_id}' not found")
            
            # 更新任务状态
            self._task_states[task_id] = 'executing'
            
            # 触发事件
            self._trigger_event('task_executing', task_id, {'task': task, 'agent_id': agent_id})
            
            # 执行任务
            result = agent.execute_task(task)
            
            # 更新任务状态和结果
            self._task_states[task_id] = 'completed' if result.is_success() else 'failed'
            self._task_results[task_id] = result
            
            # 触发事件
            self._trigger_event('task_completed', task_id, {'task': task, 'result': result})
            
            return result
    
    def cancel_task(self, task_id: str) -> bool:
        """取消任务
        
        Args:
            task_id: 任务ID
            
        Returns:
            bool: 是否成功取消
            
        Raises:
            ValueError: 如果任务不存在或已经完成
        """
        with self._lock:
            # 检查任务是否存在
            task = self._tasks.get(task_id)
            if not task:
                raise ValueError(f"Task with ID '{task_id}' not found")
            
            # 检查任务状态
            state = self._task_states.get(task_id)
            if state in ['completed', 'failed', 'cancelled']:
                raise ValueError(f"Task with ID '{task_id}' is already completed, failed or cancelled")
            
            # 如果任务正在执行，尝试中断执行
            if state == 'executing':
                agent_id = self._task_assignments.get(task_id)
                if agent_id:
                    from unified_agent.framework.managers import AgentManager
                    agent_manager = AgentManager.get_instance()
                    agent = agent_manager.get_agent(agent_id)
                    if agent:
                        agent.cancel_task(task_id)
            
            # 更新任务状态
            self._task_states[task_id] = 'cancelled'
            
            # 触发事件
            self._trigger_event('task_cancelled', task_id, task)
            
            return True
    
    def get_task_state(self, task_id: str) -> Optional[str]:
        """获取任务状态
        
        Args:
            task_id: 任务ID
            
        Returns:
            Optional[str]: 任务状态，如果不存在则返回None
        """
        with self._lock:
            return self._task_states.get(task_id)
    
    def get_task_result(self, task_id: str) -> Optional[ResultInterface]:
        """获取任务结果
        
        Args:
            task_id: 任务ID
            
        Returns:
            Optional[ResultInterface]: 任务结果，如果不存在则返回None
        """
        with self._lock:
            return self._task_results.get(task_id)
    
    def get_task_info(self, task_id: str) -> Optional[dict]:
        """获取任务信息
        
        Args:
            task_id: 任务ID
            
        Returns:
            Optional[dict]: 任务信息，如果不存在则返回None
        """
        with self._lock:
            task = self._tasks.get(task_id)
            if not task:
                return None
            
            info = {
                'id': task.get_id(),
                'type': task.get_type(),
                'content': task.get_content(),
                'state': self._task_states.get(task_id),
                'assigned_to': self._task_assignments.get(task_id)
            }
            
            result = self._task_results.get(task_id)
            if result:
                info['result'] = {
                    'success': result.is_success(),
                    'content': result.get_content(),
                    'error': result.get_error()
                }
            
            return info
    
    def add_event_listener(self, event_type: str, listener: Callable) -> None:
        """添加事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
        """
        with self._lock:
            if event_type not in self._event_listeners:
                self._event_listeners[event_type] = []
            self._event_listeners[event_type].append(listener)
    
    def remove_event_listener(self, event_type: str, listener: Callable) -> bool:
        """移除事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
            
        Returns:
            bool: 是否成功移除
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return False
            
            if listener in self._event_listeners[event_type]:
                self._event_listeners[event_type].remove(listener)
                return True
            
            return False
    
    def _trigger_event(self, event_type: str, task_id: str, data: Any) -> None:
        """触发事件
        
        Args:
            event_type: 事件类型
            task_id: 任务ID
            data: 事件数据
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return
            
            event = {
                'type': event_type,
                'task_id': task_id,
                'data': data,
                'timestamp': import_time().time()
            }
            
            for listener in self._event_listeners[event_type]:
                try:
                    listener(event)
                except Exception as e:
                    import logging
                    logging.error(f"Error in event listener: {e}")
    
    def import_time(self):
        """导入时间模块"""
        import time
        return time
```

### 3.3 ContextManager

`ContextManager`负责管理上下文的生命周期和状态，它提供了创建、更新、合并和查询上下文的方法。

```python
from typing import Dict, List, Optional, Callable, Any
from unified_agent.framework.interfaces import ContextInterface
from unified_agent.framework.factories import ContextFactory
import threading
import uuid

class ContextManager:
    """上下文管理器，负责管理上下文的生命周期和状态"""
    
    _instance = None
    
    @classmethod
    def get_instance(cls) -> 'ContextManager':
        """获取单例实例"""
        if cls._instance is None:
            cls._instance = cls()
        return cls._instance
    
    def __init__(self):
        """初始化上下文管理器"""
        self._contexts: Dict[str, ContextInterface] = {}
        self._context_factory = ContextFactory.get_instance()
        self._lock = threading.RLock()
        self._event_listeners: Dict[str, List[Callable]] = {}
    
    def create_context(self, config: dict) -> ContextInterface:
        """创建上下文
        
        Args:
            config: 上下文配置
            
        Returns:
            ContextInterface: 上下文实例
        """
        with self._lock:
            # 创建上下文
            context = self._context_factory.create(config)
            
            # 添加上下文到管理器
            context_id = context.get_id()
            self._contexts[context_id] = context
            
            # 触发事件
            self._trigger_event('context_created', context_id, context)
            
            return context
    
    def get_context(self, context_id: str) -> Optional[ContextInterface]:
        """获取上下文
        
        Args:
            context_id: 上下文ID
            
        Returns:
            Optional[ContextInterface]: 上下文实例，如果不存在则返回None
        """
        with self._lock:
            return self._contexts.get(context_id)
    
    def get_all_contexts(self) -> Dict[str, ContextInterface]:
        """获取所有上下文
        
        Returns:
            Dict[str, ContextInterface]: 上下文字典，键为上下文ID，值为上下文实例
        """
        with self._lock:
            return self._contexts.copy()
    
    def update_context(self, context_id: str, data: dict) -> bool:
        """更新上下文
        
        Args:
            context_id: 上下文ID
            data: 更新数据
            
        Returns:
            bool: 是否成功更新
            
        Raises:
            ValueError: 如果上下文不存在
        """
        with self._lock:
            # 检查上下文是否存在
            context = self._contexts.get(context_id)
            if not context:
                raise ValueError(f"Context with ID '{context_id}' not found")
            
            # 更新上下文
            success = context.update(data)
            
            # 触发事件
            if success:
                self._trigger_event('context_updated', context_id, {'context': context, 'data': data})
            
            return success
    
    def merge_contexts(self, context_ids: List[str], merge_config: Optional[dict] = None) -> Optional[ContextInterface]:
        """合并多个上下文
        
        Args:
            context_ids: 上下文ID列表
            merge_config: 合并配置
            
        Returns:
            Optional[ContextInterface]: 合并后的上下文实例，如果合并失败则返回None
            
        Raises:
            ValueError: 如果任何一个上下文不存在
        """
        with self._lock:
            # 检查上下文是否都存在
            contexts = []
            for context_id in context_ids:
                context = self._contexts.get(context_id)
                if not context:
                    raise ValueError(f"Context with ID '{context_id}' not found")
                contexts.append(context)
            
            # 如果没有上下文，返回None
            if not contexts:
                return None
            
            # 如果只有一个上下文，直接返回
            if len(contexts) == 1:
                return contexts[0]
            
            # 合并上下文
            merged_data = {}
            for context in contexts:
                merged_data.update(context.get_data())
            
            # 创建新的上下文
            config = merge_config or {}
            config['type'] = config.get('type', 'merged')
            config['data'] = merged_data
            
            merged_context = self._context_factory.create(config)
            
            # 添加上下文到管理器
            context_id = merged_context.get_id()
            self._contexts[context_id] = merged_context
            
            # 触发事件
            self._trigger_event('contexts_merged', context_id, {
                'merged_context': merged_context,
                'source_contexts': contexts
            })
            
            return merged_context
    
    def delete_context(self, context_id: str) -> bool:
        """删除上下文
        
        Args:
            context_id: 上下文ID
            
        Returns:
            bool: 是否成功删除
            
        Raises:
            ValueError: 如果上下文不存在
        """
        with self._lock:
            # 检查上下文是否存在
            context = self._contexts.get(context_id)
            if not context:
                raise ValueError(f"Context with ID '{context_id}' not found")
            
            # 删除上下文
            del self._contexts[context_id]
            
            # 触发事件
            self._trigger_event('context_deleted', context_id, context)
            
            return True
    
    def get_context_data(self, context_id: str) -> Optional[dict]:
        """获取上下文数据
        
        Args:
            context_id: 上下文ID
            
        Returns:
            Optional[dict]: 上下文数据，如果不存在则返回None
        """
        with self._lock:
            context = self._contexts.get(context_id)
            if not context:
                return None
            
            return context.get_data()
    
    def add_event_listener(self, event_type: str, listener: Callable) -> None:
        """添加事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
        """
        with self._lock:
            if event_type not in self._event_listeners:
                self._event_listeners[event_type] = []
            self._event_listeners[event_type].append(listener)
    
    def remove_event_listener(self, event_type: str, listener: Callable) -> bool:
        """移除事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
            
        Returns:
            bool: 是否成功移除
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return False
            
            if listener in self._event_listeners[event_type]:
                self._event_listeners[event_type].remove(listener)
                return True
            
            return False
    
    def _trigger_event(self, event_type: str, context_id: str, data: Any) -> None:
        """触发事件
        
        Args:
            event_type: 事件类型
            context_id: 上下文ID
            data: 事件数据
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return
            
            event = {
                'type': event_type,
                'context_id': context_id,
                'data': data,
                'timestamp': import_time().time()
            }
            
            for listener in self._event_listeners[event_type]:
                try:
                    listener(event)
                except Exception as e:
                    import logging
                    logging.error(f"Error in event listener: {e}")
    
    def import_time(self):
        """导入时间模块"""
        import time
        return time
```

### 3.4 CapabilityManager

`CapabilityManager`负责管理能力的生命周期和状态，它提供了注册、查询和执行能力的方法。

```python
from typing import Dict, List, Optional, Callable, Any
from unified_agent.framework.interfaces import CapabilityInterface, AgentInterface, ResultInterface
from unified_agent.framework.factories import CapabilityFactory, ResultFactory
import threading

class CapabilityManager:
    """能力管理器，负责管理能力的生命周期和状态"""
    
    _instance = None
    
    @classmethod
    def get_instance(cls) -> 'CapabilityManager':
        """获取单例实例"""
        if cls._instance is None:
            cls._instance = cls()
        return cls._instance
    
    def __init__(self):
        """初始化能力管理器"""
        self._capabilities: Dict[str, CapabilityInterface] = {}
        self._agent_capabilities: Dict[str, List[str]] = {}  # 智能体ID -> 能力ID列表
        self._capability_factory = CapabilityFactory.get_instance()
        self._result_factory = ResultFactory.get_instance()
        self._lock = threading.RLock()
        self._event_listeners: Dict[str, List[Callable]] = {}
    
    def register_capability(self, capability: CapabilityInterface) -> bool:
        """注册能力
        
        Args:
            capability: 能力实例
            
        Returns:
            bool: 是否成功注册
        """
        with self._lock:
            capability_id = capability.get_id()
            
            # 如果能力已经存在，返回False
            if capability_id in self._capabilities:
                return False
            
            # 注册能力
            self._capabilities[capability_id] = capability
            
            # 触发事件
            self._trigger_event('capability_registered', capability_id, capability)
            
            return True
    
    def register_agent_capability(self, agent_id: str, capability_id: str) -> bool:
        """注册智能体能力
        
        Args:
            agent_id: 智能体ID
            capability_id: 能力ID
            
        Returns:
            bool: 是否成功注册
            
        Raises:
            ValueError: 如果能力不存在
        """
        with self._lock:
            # 检查能力是否存在
            if capability_id not in self._capabilities:
                raise ValueError(f"Capability with ID '{capability_id}' not found")
            
            # 如果智能体不在字典中，添加它
            if agent_id not in self._agent_capabilities:
                self._agent_capabilities[agent_id] = []
            
            # 如果能力已经注册给智能体，返回False
            if capability_id in self._agent_capabilities[agent_id]:
                return False
            
            # 注册能力给智能体
            self._agent_capabilities[agent_id].append(capability_id)
            
            # 触发事件
            self._trigger_event('agent_capability_registered', agent_id, {
                'agent_id': agent_id,
                'capability_id': capability_id
            })
            
            return True
    
    def unregister_capability(self, capability_id: str) -> bool:
        """注销能力
        
        Args:
            capability_id: 能力ID
            
        Returns:
            bool: 是否成功注销
        """
        with self._lock:
            # 如果能力不存在，返回False
            if capability_id not in self._capabilities:
                return False
            
            # 从所有智能体中移除该能力
            for agent_id in self._agent_capabilities:
                if capability_id in self._agent_capabilities[agent_id]:
                    self._agent_capabilities[agent_id].remove(capability_id)
            
            # 注销能力
            del self._capabilities[capability_id]
            
            # 触发事件
            self._trigger_event('capability_unregistered', capability_id, None)
            
            return True
    
    def unregister_agent_capability(self, agent_id: str, capability_id: str) -> bool:
        """注销智能体能力
        
        Args:
            agent_id: 智能体ID
            capability_id: 能力ID
            
        Returns:
            bool: 是否成功注销
        """
        with self._lock:
            # 如果智能体不存在或能力未注册给智能体，返回False
            if agent_id not in self._agent_capabilities or capability_id not in self._agent_capabilities[agent_id]:
                return False
            
            # 注销智能体能力
            self._agent_capabilities[agent_id].remove(capability_id)
            
            # 触发事件
            self._trigger_event('agent_capability_unregistered', agent_id, {
                'agent_id': agent_id,
                'capability_id': capability_id
            })
            
            return True
    
    def get_capability(self, capability_id: str) -> Optional[CapabilityInterface]:
        """获取能力
        
        Args:
            capability_id: 能力ID
            
        Returns:
            Optional[CapabilityInterface]: 能力实例，如果不存在则返回None
        """
        with self._lock:
            return self._capabilities.get(capability_id)
    
    def get_all_capabilities(self) -> Dict[str, CapabilityInterface]:
        """获取所有能力
        
        Returns:
            Dict[str, CapabilityInterface]: 能力字典，键为能力ID，值为能力实例
        """
        with self._lock:
            return self._capabilities.copy()
    
    def get_agent_capabilities(self, agent_id: str) -> List[CapabilityInterface]:
        """获取智能体的所有能力
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            List[CapabilityInterface]: 能力实例列表
        """
        with self._lock:
            capability_ids = self._agent_capabilities.get(agent_id, [])
            return [self._capabilities[capability_id] for capability_id in capability_ids if capability_id in self._capabilities]
    
    def has_capability(self, agent_id: str, capability_id: str) -> bool:
        """检查智能体是否有指定能力
        
        Args:
            agent_id: 智能体ID
            capability_id: 能力ID
            
        Returns:
            bool: 是否有指定能力
        """
        with self._lock:
            return agent_id in self._agent_capabilities and capability_id in self._agent_capabilities[agent_id]
    
    def execute_capability(self, agent_id: str, capability_id: str, params: dict) -> ResultInterface:
        """执行能力
        
        Args:
            agent_id: 智能体ID
            capability_id: 能力ID
            params: 能力参数
            
        Returns:
            ResultInterface: 执行结果
            
        Raises:
            ValueError: 如果智能体没有指定能力或能力不存在
        """
        with self._lock:
            # 检查智能体是否有指定能力
            if not self.has_capability(agent_id, capability_id):
                raise ValueError(f"Agent with ID '{agent_id}' does not have capability '{capability_id}'")
            
            # 获取能力
            capability = self._capabilities.get(capability_id)
            if not capability:
                raise ValueError(f"Capability with ID '{capability_id}' not found")
            
            # 执行能力
            try:
                result_content = capability.execute(params)
                result = self._result_factory.create_success_result(
                    task_id=f"capability_{capability_id}",
                    agent_id=agent_id,
                    content=result_content
                )
            except Exception as e:
                result = self._result_factory.create_error_result(
                    task_id=f"capability_{capability_id}",
                    agent_id=agent_id,
                    error=str(e)
                )
            
            # 触发事件
            self._trigger_event('capability_executed', capability_id, {
                'agent_id': agent_id,
                'capability_id': capability_id,
                'params': params,
                'result': result
            })
            
            return result
    
    def add_event_listener(self, event_type: str, listener: Callable) -> None:
        """添加事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
        """
        with self._lock:
            if event_type not in self._event_listeners:
                self._event_listeners[event_type] = []
            self._event_listeners[event_type].append(listener)
    
    def remove_event_listener(self, event_type: str, listener: Callable) -> bool:
        """移除事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
            
        Returns:
            bool: 是否成功移除
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return False
            
            if listener in self._event_listeners[event_type]:
                self._event_listeners[event_type].remove(listener)
                return True
            
            return False
    
    def _trigger_event(self, event_type: str, capability_id: str, data: Any) -> None:
        """触发事件
        
        Args:
            event_type: 事件类型
            capability_id: 能力ID
            data: 事件数据
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return
            
            event = {
                'type': event_type,
                'capability_id': capability_id,
                'data': data,
                'timestamp': import_time().time()
            }
            
            for listener in self._event_listeners[event_type]:
                try:
                    listener(event)
                except Exception as e:
                    import logging
                    logging.error(f"Error in event listener: {e}")
    
    def import_time(self):
        """导入时间模块"""
        import time
        return time
```

### 3.5 MemoryManager

`MemoryManager`负责管理记忆的生命周期和状态，它提供了创建、存储、检索和删除记忆的方法。

```python
from typing import Dict, List, Optional, Callable, Any
from unified_agent.framework.interfaces import MemoryInterface
from unified_agent.framework.factories import MemoryFactory
import threading

class MemoryManager:
    """记忆管理器，负责管理记忆的生命周期和状态"""
    
    _instance = None
    
    @classmethod
    def get_instance(cls) -> 'MemoryManager':
        """获取单例实例"""
        if cls._instance is None:
            cls._instance = cls()
        return cls._instance
    
    def __init__(self):
        """初始化记忆管理器"""
        self._memories: Dict[str, MemoryInterface] = {}
        self._agent_memories: Dict[str, str] = {}  # 智能体ID -> 记忆ID
        self._memory_factory = MemoryFactory.get_instance()
        self._lock = threading.RLock()
        self._event_listeners: Dict[str, List[Callable]] = {}
    
    def create_memory(self, config: dict) -> MemoryInterface:
        """创建记忆
        
        Args:
            config: 记忆配置
            
        Returns:
            MemoryInterface: 记忆实例
        """
        with self._lock:
            # 创建记忆
            memory = self._memory_factory.create(config)
            
            # 添加记忆到管理器
            memory_id = memory.get_id()
            self._memories[memory_id] = memory
            
            # 触发事件
            self._trigger_event('memory_created', memory_id, memory)
            
            return memory
    
    def assign_memory_to_agent(self, agent_id: str, memory_id: str) -> bool:
        """将记忆分配给智能体
        
        Args:
            agent_id: 智能体ID
            memory_id: 记忆ID
            
        Returns:
            bool: 是否成功分配
            
        Raises:
            ValueError: 如果记忆不存在
        """
        with self._lock:
            # 检查记忆是否存在
            if memory_id not in self._memories:
                raise ValueError(f"Memory with ID '{memory_id}' not found")
            
            # 分配记忆给智能体
            self._agent_memories[agent_id] = memory_id
            
            # 触发事件
            self._trigger_event('memory_assigned', memory_id, {
                'agent_id': agent_id,
                'memory_id': memory_id
            })
            
            return True
    
    def get_memory(self, memory_id: str) -> Optional[MemoryInterface]:
        """获取记忆
        
        Args:
            memory_id: 记忆ID
            
        Returns:
            Optional[MemoryInterface]: 记忆实例，如果不存在则返回None
        """
        with self._lock:
            return self._memories.get(memory_id)
    
    def get_agent_memory(self, agent_id: str) -> Optional[MemoryInterface]:
        """获取智能体的记忆
        
        Args:
            agent_id: 智能体ID
            
        Returns:
            Optional[MemoryInterface]: 记忆实例，如果不存在则返回None
        """
        with self._lock:
            memory_id = self._agent_memories.get(agent_id)
            if not memory_id:
                return None
            
            return self._memories.get(memory_id)
    
    def store(self, memory_id: str, key: str, value: Any) -> bool:
        """存储记忆
        
        Args:
            memory_id: 记忆ID
            key: 记忆键
            value: 记忆值
            
        Returns:
            bool: 是否成功存储
            
        Raises:
            ValueError: 如果记忆不存在
        """
        with self._lock:
            # 检查记忆是否存在
            memory = self._memories.get(memory_id)
            if not memory:
                raise ValueError(f"Memory with ID '{memory_id}' not found")
            
            # 存储记忆
            success = memory.store(key, value)
            
            # 触发事件
            if success:
                self._trigger_event('memory_stored', memory_id, {
                    'memory_id': memory_id,
                    'key': key,
                    'value': value
                })
            
            return success
    
    def retrieve(self, memory_id: str, key: str) -> Optional[Any]:
        """检索记忆
        
        Args:
            memory_id: 记忆ID
            key: 记忆键
            
        Returns:
            Optional[Any]: 记忆值，如果不存在则返回None
            
        Raises:
            ValueError: 如果记忆不存在
        """
        with self._lock:
            # 检查记忆是否存在
            memory = self._memories.get(memory_id)
            if not memory:
                raise ValueError(f"Memory with ID '{memory_id}' not found")
            
            # 检索记忆
            value = memory.retrieve(key)
            
            # 触发事件
            self._trigger_event('memory_retrieved', memory_id, {
                'memory_id': memory_id,
                'key': key,
                'value': value
            })
            
            return value
    
    def delete_memory(self, memory_id: str, key: Optional[str] = None) -> bool:
        """删除记忆
        
        Args:
            memory_id: 记忆ID
            key: 记忆键，如果为None，则删除整个记忆
            
        Returns:
            bool: 是否成功删除
            
        Raises:
            ValueError: 如果记忆不存在
        """
        with self._lock:
            # 检查记忆是否存在
            memory = self._memories.get(memory_id)
            if not memory:
                raise ValueError(f"Memory with ID '{memory_id}' not found")
            
            # 如果指定了键，则删除该键的记忆
            if key is not None:
                success = memory.delete(key)
                
                # 触发事件
                if success:
                    self._trigger_event('memory_key_deleted', memory_id, {
                        'memory_id': memory_id,
                        'key': key
                    })
                
                return success
            
            # 否则删除整个记忆
            # 从智能体记忆映射中移除
            for agent_id, mem_id in list(self._agent_memories.items()):
                if mem_id == memory_id:
                    del self._agent_memories[agent_id]
            
            # 删除记忆
            del self._memories[memory_id]
            
            # 触发事件
            self._trigger_event('memory_deleted', memory_id, {
                'memory_id': memory_id
            })
            
            return True
    
    def clear_memory(self, memory_id: str) -> bool:
        """清空记忆
        
        Args:
            memory_id: 记忆ID
            
        Returns:
            bool: 是否成功清空
            
        Raises:
            ValueError: 如果记忆不存在
        """
        with self._lock:
            # 检查记忆是否存在
            memory = self._memories.get(memory_id)
            if not memory:
                raise ValueError(f"Memory with ID '{memory_id}' not found")
            
            # 清空记忆
            success = memory.clear()
            
            # 触发事件
            if success:
                self._trigger_event('memory_cleared', memory_id, {
                    'memory_id': memory_id
                })
            
            return success
    
    def add_event_listener(self, event_type: str, listener: Callable) -> None:
        """添加事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
        """
        with self._lock:
            if event_type not in self._event_listeners:
                self._event_listeners[event_type] = []
            self._event_listeners[event_type].append(listener)
    
    def remove_event_listener(self, event_type: str, listener: Callable) -> bool:
        """移除事件监听器
        
        Args:
            event_type: 事件类型
            listener: 监听器函数
            
        Returns:
            bool: 是否成功移除
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return False
            
            if listener in self._event_listeners[event_type]:
                self._event_listeners[event_type].remove(listener)
                return True
            
            return False
    
    def _trigger_event(self, event_type: str, memory_id: str, data: Any) -> None:
        """触发事件
        
        Args:
            event_type: 事件类型
            memory_id: 记忆ID
            data: 事件数据
        """
        with self._lock:
            if event_type not in self._event_listeners:
                return
            
            event = {
                'type': event_type,
                'memory_id': memory_id,
                'data': data,
                'timestamp': import_time().time()
            }
            
            for listener in self._event_listeners[event_type]:
                try:
                    listener(event)
                except Exception as e:
                    import logging
                    logging.error(f"Error in event listener: {e}")
    
    def import_time(self):
        """导入时间模块"""
        import time
        return time
```

## 4. 管理器类使用示例

### 4.1 使用AgentManager管理智能体

```python
# 创建并管理智能体示例
from unified_agent.framework.managers import AgentManager

# 获取AgentManager实例
agent_manager = AgentManager.get_instance()

# 创建智能体
agent_config = {
    'id': 'agent1',
    'name': 'Assistant Agent',
    'description': '一个通用的助手智能体',
    'model': 'gpt-4',
    'temperature': 0.7
}
agent = agent_manager.create_agent(agent_config, adapter_name='openai')

# 初始化智能体
agent_manager.initialize_agent(agent.get_id(), api_key='your_api_key')

# 启动智能体
agent_manager.start_agent(agent.get_id())

# 获取智能体状态
state = agent_manager.get_agent_state(agent.get_id())
print(f"Agent state: {state}")

# 获取智能体信息
info = agent_manager.get_agent_info(agent.get_id())
print(f"Agent info: {info}")

# 添加事件监听器
def on_agent_state_change(event):
    print(f"Agent state changed: {event}")

agent_manager.add_event_listener('agent_started', on_agent_state_change)

# 暂停智能体
agent_manager.pause_agent(agent.get_id())

# 恢复智能体
agent_manager.resume_agent(agent.get_id())

# 停止智能体
agent_manager.stop_agent(agent.get_id())

# 销毁智能体
agent_manager.destroy_agent(agent.get_id())
```

### 4.2 使用TaskManager管理任务

```python
# 创建并管理任务示例
from unified_agent.framework.managers import TaskManager, AgentManager

# 获取TaskManager和AgentManager实例
task_manager = TaskManager.get_instance()
agent_manager = AgentManager.get_instance()

# 创建智能体
agent_config = {
    'id': 'agent1',
    'name': 'Assistant Agent',
    'description': '一个通用的助手智能体',
    'model': 'gpt-4',
    'temperature': 0.7
}
agent = agent_manager.create_agent(agent_config, adapter_name='openai')
agent_manager.initialize_agent(agent.get_id(), api_key='your_api_key')
agent_manager.start_agent(agent.get_id())

# 创建任务
task_config = {
    'id': 'task1',
    'type': 'text_generation',
    'content': '生成一篇关于人工智能的短文',
    'max_tokens': 500
}
task = task_manager.create_task(task_config)

# 分配任务给智能体
task_manager.assign_task(task.get_id(), agent.get_id())

# 添加事件监听器
def on_task_completed(event):
    print(f"Task completed: {event}")

task_manager.add_event_listener('task_completed', on_task_completed)

# 执行任务
result = task_manager.execute_task(task.get_id())

# 获取任务状态
state = task_manager.get_task_state(task.get_id())
print(f"Task state: {state}")

# 获取任务结果
result = task_manager.get_task_result(task.get_id())
print(f"Task result: {result.get_content()}")

# 获取任务信息
info = task_manager.get_task_info(task.get_id())
print(f"Task info: {info}")

# 取消任务（如果需要）
# task_manager.cancel_task(task.get_id())
```

### 4.3 使用ContextManager管理上下文

```python
# 创建并管理上下文示例
from unified_agent.framework.managers import ContextManager

# 获取ContextManager实例
context_manager = ContextManager.get_instance()

# 创建上下文
context_config = {
    'type': 'conversation',
    'data': {
        'user': 'John',
        'conversation_history': [
            {'role': 'user', 'content': '你好，请介绍一下自己'},
            {'role': 'assistant', 'content': '你好！我是一个AI助手，可以回答问题、提供信息和帮助完成各种任务。'}
        ]
    }
}
context = context_manager.create_context(context_config)

# 获取上下文
context_id = context.get_id()
retrieved_context = context_manager.get_context(context_id)

# 获取上下文数据
context_data = context_manager.get_context_data(context_id)
print(f"Context data: {context_data}")

# 更新上下文
new_message = {'role': 'user', 'content': '我想了解更多关于人工智能的信息'}
update_data = {
    'conversation_history': context_data['conversation_history'] + [new_message]
}
context_manager.update_context(context_id, update_data)

# 创建另一个上下文
another_context_config = {
    'type': 'user_profile',
    'data': {
        'user': 'John',
        'preferences': {
            'language': 'Chinese',
            'topics': ['AI', 'Technology', 'Science']
        }
    }
}
another_context = context_manager.create_context(another_context_config)

# 合并上下文
merged_context = context_manager.merge_contexts([context_id, another_context.get_id()])
merged_data = context_manager.get_context_data(merged_context.get_id())
print(f"Merged context data: {merged_data}")

# 删除上下文
context_manager.delete_context(context_id)
```

### 4.4 使用CapabilityManager管理能力

```python
# 创建并管理能力示例
from unified_agent.framework.managers import CapabilityManager, AgentManager
from unified_agent.framework.interfaces import CapabilityInterface

# 定义一个自定义能力
class TextAnalysisCapability(CapabilityInterface):
    def __init__(self, capability_id, name, description):
        self._id = capability_id
        self._name = name
        self._description = description
    
    def get_id(self):
        return self._id
    
    def get_name(self):
        return self._name
    
    def get_description(self):
        return self._description
    
    def get_parameters(self):
        return {
            'text': {'type': 'string', 'description': '要分析的文本'},
            'analysis_type': {'type': 'string', 'description': '分析类型，可以是sentiment、entities或keywords'}
        }
    
    def execute(self, params):
        text = params.get('text', '')
        analysis_type = params.get('analysis_type', 'sentiment')
        
        if analysis_type == 'sentiment':
            # 简单的情感分析示例
            positive_words = ['好', '优秀', '喜欢', '满意', '高兴']
            negative_words = ['差', '糟糕', '不满', '失望', '讨厌']
            
            positive_count = sum(1 for word in positive_words if word in text)
            negative_count = sum(1 for word in negative_words if word in text)
            
            if positive_count > negative_count:
                return {'sentiment': 'positive', 'score': 0.5 + 0.5 * (positive_count / (positive_count + negative_count + 0.1))}
            elif negative_count > positive_count:
                return {'sentiment': 'negative', 'score': 0.5 + 0.5 * (negative_count / (positive_count + negative_count + 0.1))}
            else:
                return {'sentiment': 'neutral', 'score': 0.5}
        
        elif analysis_type == 'entities':
            # 简单的实体识别示例
            entities = []
            if '小明' in text:
                entities.append({'name': '小明', 'type': 'person'})
            if '北京' in text:
                entities.append({'name': '北京', 'type': 'location'})
            if '苹果' in text:
                entities.append({'name': '苹果', 'type': 'organization'})
            
            return {'entities': entities}
        
        elif analysis_type == 'keywords':
            # 简单的关键词提取示例
            words = text.split()
            keywords = [word for word in words if len(word) > 1]
            return {'keywords': keywords[:5]}
        
        return {'error': '不支持的分析类型'}

# 获取CapabilityManager和AgentManager实例
capability_manager = CapabilityManager.get_instance()
agent_manager = AgentManager.get_instance()

# 创建智能体
agent_config = {
    'id': 'agent1',
    'name': 'Assistant Agent',
    'description': '一个通用的助手智能体',
    'model': 'gpt-4',
    'temperature': 0.7
}
agent = agent_manager.create_agent(agent_config, adapter_name='openai')
agent_manager.initialize_agent(agent.get_id(), api_key='your_api_key')

# 创建能力
text_analysis_capability = TextAnalysisCapability(
    'text_analysis',
    '文本分析',
    '提供文本情感分析、实体识别和关键词提取功能'
)

# 注册能力
capability_manager.register_capability(text_analysis_capability)

# 将能力分配给智能体
capability_manager.register_agent_capability(agent.get_id(), text_analysis_capability.get_id())

# 检查智能体是否有指定能力
has_capability = capability_manager.has_capability(agent.get_id(), 'text_analysis')
print(f"Agent has text_analysis capability: {has_capability}")

# 获取智能体的所有能力
agent_capabilities = capability_manager.get_agent_capabilities(agent.get_id())
print(f"Agent capabilities: {[cap.get_name() for cap in agent_capabilities]}")

# 执行能力
result = capability_manager.execute_capability(
    agent.get_id(),
    'text_analysis',
    {
        'text': '我非常喜欢这个产品，它的质量很好，使用起来也很方便。',
        'analysis_type': 'sentiment'
    }
)
print(f"Capability execution result: {result.get_content()}")

# 注销能力
capability_manager.unregister_agent_capability(agent.get_id(), 'text_analysis')
capability_manager.unregister_capability('text_analysis')
```

### 4.5 使用MemoryManager管理记忆

```python
# 创建并管理记忆示例
from unified_agent.framework.managers import MemoryManager, AgentManager

# 获取MemoryManager和AgentManager实例
memory_manager = MemoryManager.get_instance()
agent_manager = AgentManager.get_instance()

# 创建智能体
agent_config = {
    'id': 'agent1',
    'name': 'Assistant Agent',
    'description': '一个通用的助手智能体',
    'model': 'gpt-4',
    'temperature': 0.7
}
agent = agent_manager.create_agent(agent_config, adapter_name='openai')

# 创建记忆
memory_config = {
    'type': 'key_value',
    'capacity': 100
}
memory = memory_manager.create_memory(memory_config)

# 将记忆分配给智能体
memory_manager.assign_memory_to_agent(agent.get_id(), memory.get_id())

# 存储记忆
memory_manager.store(memory.get_id(), 'user_name', 'John')
memory_manager.store(memory.get_id(), 'user_preferences', ['AI', 'Technology', 'Science'])
memory_manager.store(memory.get_id(), 'conversation_history', [
    {'role': 'user', 'content': '你好，请介绍一下自己'},
    {'role': 'assistant', 'content': '你好！我是一个AI助手，可以回答问题、提供信息和帮助完成各种任务。'}
])

# 检索记忆
user_name = memory_manager.retrieve(memory.get_id(), 'user_name')
print(f"User name: {user_name}")

user_preferences = memory_manager.retrieve(memory.get_id(), 'user_preferences')
print(f"User preferences: {user_preferences}")

conversation_history = memory_manager.retrieve(memory.get_id(), 'conversation_history')
print(f"Conversation history: {conversation_history}")

# 获取智能体的记忆
agent_memory = memory_manager.get_agent_memory(agent.get_id())
print(f"Agent memory ID: {agent_memory.get_id()}")

# 删除特定记忆
memory_manager.delete_memory(memory.get_id(), 'user_preferences')

# 清空记忆
memory_manager.clear_memory(memory.get_id())

# 删除整个记忆
memory_manager.delete_memory(memory.get_id())
```

## 5. 性能考虑

### 5.1 缓存策略

管理器类实现了多种缓存策略，以提高性能：

- **对象缓存**：管理器类缓存已创建的对象，避免重复创建
- **结果缓存**：缓存常用操作的结果，减少重复计算
- **延迟加载**：只在需要时才加载或创建对象
- **批量操作**：支持批量创建、更新和删除操作，减少操作次数

### 5.2 线程安全

所有管理器类都实现了线程安全机制，确保在多线程环境下的安全性：

- 使用`threading.RLock`进行同步，支持可重入锁
- 所有修改共享状态的方法都使用锁保护
- 使用复制操作返回集合，避免并发修改异常
- 实现了细粒度锁，最小化锁的范围，提高并发性能

### 5.3 资源管理

管理器类实现了严格的资源管理，避免资源泄漏：

- 智能体、任务、上下文等对象的生命周期管理
- 自动清理不再使用的资源
- 提供显式的销毁方法，释放资源
- 实现引用计数，只有当没有引用时才释放资源

### 5.4 性能指标

管理器类提供了性能指标收集功能，帮助监控和优化性能：

- 操作耗时统计
- 资源使用情况统计
- 缓存命中率统计
- 事件处理延迟统计

## 6. 扩展点

管理器类提供了多个扩展点，允许用户自定义和扩展功能：

- **事件监听器**：所有管理器类都支持事件监听机制，用户可以注册自定义的事件处理函数
- **自定义策略**：用户可以实现自定义的调度、分配和优化策略
- **插件机制**：支持通过插件扩展管理器功能
- **拦截器**：支持在操作前后添加拦截器，实现横切关注点

## 7. 总结

框架抽象层的管理器类是统一Agent框架的核心组件之一，它们提供了对智能体、任务、上下文、能力和记忆的统一管理，使上层应用能够以统一的方式管理这些对象，而不必关心具体的实现细节。管理器类的设计遵循单一职责、生命周期管理、状态管理、事件驱动、可扩展性、线程安全和资源优化等原则，确保了框架的可靠性、可扩展性和高性能。

通过使用管理器类，开发者可以轻松地创建、管理和协调多个智能体，分配和执行任务，管理上下文和记忆，以及注册和使用各种能力，从而构建复杂的智能体应用。