ff7294e860
- 添加记忆提取异常处理机制，提升系统稳定性 - 实现记忆内容格式化功能，增强可读性和结构化输出 - 优化LLM响应解析逻辑，避免系统标识误写入记忆 - 改进向量存储批量嵌入生成，提升处理效率 - 为记忆系统添加机器人身份上下文注入，避免自身信息记录 - 增强记忆检索接口，支持额外上下文参数传递 - 添加控制台记忆预览功能，便于人工检查 - 优化记忆融合算法，正确处理单记忆组情况 - 改进流循环管理器，支持未读消息积压强制分发机制
426 lines
15 KiB
Python
426 lines
15 KiB
Python
"""
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流循环管理器
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为每个聊天流创建独立的无限循环任务，主动轮询处理消息
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"""
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import asyncio
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import time
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from typing import Dict, Optional, Any
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from src.common.logger import get_logger
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from src.config.config import global_config
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from src.chat.energy_system import energy_manager
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from src.chat.chatter_manager import ChatterManager
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from src.plugin_system.apis.chat_api import get_chat_manager
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logger = get_logger("stream_loop_manager")
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class StreamLoopManager:
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"""流循环管理器 - 每个流一个独立的无限循环任务"""
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def __init__(self, max_concurrent_streams: Optional[int] = None):
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# 流循环任务管理
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self.stream_loops: Dict[str, asyncio.Task] = {}
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self.loop_lock = asyncio.Lock()
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# 统计信息
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self.stats: Dict[str, Any] = {
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"active_streams": 0,
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"total_loops": 0,
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"total_process_cycles": 0,
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"total_failures": 0,
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"start_time": time.time(),
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}
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# 配置参数
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self.max_concurrent_streams = max_concurrent_streams or getattr(
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global_config.chat, "max_concurrent_distributions", 10
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)
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# 强制分发策略
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self.force_dispatch_unread_threshold: Optional[int] = getattr(
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global_config.chat, "force_dispatch_unread_threshold", 20
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)
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self.force_dispatch_min_interval: float = getattr(
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global_config.chat, "force_dispatch_min_interval", 0.1
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)
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# Chatter管理器
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self.chatter_manager: Optional[ChatterManager] = None
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# 状态控制
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self.is_running = False
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logger.info(f"流循环管理器初始化完成 (最大并发流数: {self.max_concurrent_streams})")
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async def start(self) -> None:
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"""启动流循环管理器"""
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if self.is_running:
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logger.warning("流循环管理器已经在运行")
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return
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self.is_running = True
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logger.info("流循环管理器已启动")
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async def stop(self) -> None:
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"""停止流循环管理器"""
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if not self.is_running:
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return
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self.is_running = False
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# 取消所有流循环
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async with self.loop_lock:
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for task in list(self.stream_loops.values()):
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if not task.done():
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task.cancel()
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try:
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await task
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except asyncio.CancelledError:
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pass
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self.stream_loops.clear()
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logger.info("流循环管理器已停止")
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async def start_stream_loop(self, stream_id: str, force: bool = False) -> bool:
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"""启动指定流的循环任务
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Args:
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stream_id: 流ID
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Returns:
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bool: 是否成功启动
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"""
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async with self.loop_lock:
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# 检查是否已有循环在运行
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if stream_id in self.stream_loops:
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logger.debug(f"流 {stream_id} 循环已在运行")
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return True
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# 判断是否需要强制分发
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force = force or self._should_force_dispatch_for_stream(stream_id)
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# 检查是否超过最大并发限制
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if len(self.stream_loops) >= self.max_concurrent_streams and not force:
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logger.warning(f"超过最大并发流数限制，无法启动流 {stream_id}")
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return False
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if force and len(self.stream_loops) >= self.max_concurrent_streams:
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logger.warning(
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"流 %s 未读消息积压严重(>%s)，突破并发限制强制启动分发", stream_id, self.force_dispatch_unread_threshold
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)
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# 创建流循环任务
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task = asyncio.create_task(self._stream_loop(stream_id))
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self.stream_loops[stream_id] = task
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self.stats["total_loops"] += 1
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logger.info(f"启动流循环: {stream_id}")
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return True
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async def stop_stream_loop(self, stream_id: str) -> bool:
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"""停止指定流的循环任务
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Args:
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stream_id: 流ID
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Returns:
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bool: 是否成功停止
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"""
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async with self.loop_lock:
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if stream_id in self.stream_loops:
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task = self.stream_loops[stream_id]
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if not task.done():
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task.cancel()
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try:
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await task
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except asyncio.CancelledError:
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pass
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del self.stream_loops[stream_id]
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logger.info(f"停止流循环: {stream_id}")
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return True
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return False
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async def _stream_loop(self, stream_id: str) -> None:
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"""单个流的无限循环
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Args:
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stream_id: 流ID
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"""
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logger.info(f"流循环开始: {stream_id}")
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try:
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while self.is_running:
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try:
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# 1. 获取流上下文
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context = await self._get_stream_context(stream_id)
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if not context:
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logger.warning(f"无法获取流上下文: {stream_id}")
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await asyncio.sleep(10.0)
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continue
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# 2. 检查是否有消息需要处理
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unread_count = self._get_unread_count(context)
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force_dispatch = self._needs_force_dispatch_for_context(context, unread_count)
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has_messages = force_dispatch or await self._has_messages_to_process(context)
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if has_messages:
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if force_dispatch:
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logger.info(
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"流 %s 未读消息 %d 条，触发强制分发", stream_id, unread_count
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)
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# 3. 激活chatter处理
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success = await self._process_stream_messages(stream_id, context)
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# 更新统计
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self.stats["total_process_cycles"] += 1
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if success:
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logger.debug(f"流处理成功: {stream_id}")
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else:
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self.stats["total_failures"] += 1
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logger.warning(f"流处理失败: {stream_id}")
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# 4. 计算下次检查间隔
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interval = await self._calculate_interval(stream_id, has_messages)
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if has_messages:
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updated_unread_count = self._get_unread_count(context)
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if self._needs_force_dispatch_for_context(context, updated_unread_count):
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interval = min(interval, max(self.force_dispatch_min_interval, 0.0))
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logger.debug(
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"流 %s 未读消息仍有 %d 条，使用加速分发间隔 %.2fs",
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stream_id,
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updated_unread_count,
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interval,
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)
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# 5. sleep等待下次检查
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logger.info(f"流 {stream_id} 等待 {interval:.2f}s")
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await asyncio.sleep(interval)
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except asyncio.CancelledError:
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logger.info(f"流循环被取消: {stream_id}")
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break
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except Exception as e:
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logger.error(f"流循环出错 {stream_id}: {e}", exc_info=True)
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self.stats["total_failures"] += 1
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await asyncio.sleep(5.0) # 错误时等待5秒再重试
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finally:
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# 清理循环标记
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async with self.loop_lock:
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if stream_id in self.stream_loops:
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del self.stream_loops[stream_id]
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logger.info(f"流循环结束: {stream_id}")
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async def _get_stream_context(self, stream_id: str) -> Optional[Any]:
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"""获取流上下文
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Args:
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stream_id: 流ID
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Returns:
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Optional[Any]: 流上下文，如果不存在返回None
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"""
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try:
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chat_manager = get_chat_manager()
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chat_stream = chat_manager.get_stream(stream_id)
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if chat_stream:
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return chat_stream.context_manager.context
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return None
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except Exception as e:
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logger.error(f"获取流上下文失败 {stream_id}: {e}")
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return None
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async def _has_messages_to_process(self, context: Any) -> bool:
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"""检查是否有消息需要处理
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Args:
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context: 流上下文
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Returns:
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bool: 是否有未读消息
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"""
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try:
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# 检查是否有未读消息
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if hasattr(context, "unread_messages") and context.unread_messages:
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return True
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# 检查其他需要处理的条件
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if hasattr(context, "has_pending_messages") and context.has_pending_messages:
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return True
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return False
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except Exception as e:
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logger.error(f"检查消息状态失败: {e}")
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return False
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async def _process_stream_messages(self, stream_id: str, context: Any) -> bool:
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"""处理流消息
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Args:
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stream_id: 流ID
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context: 流上下文
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Returns:
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bool: 是否处理成功
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"""
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if not self.chatter_manager:
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logger.warning(f"Chatter管理器未设置: {stream_id}")
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return False
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try:
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start_time = time.time()
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# 直接调用chatter_manager处理流上下文
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results = await self.chatter_manager.process_stream_context(stream_id, context)
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success = results.get("success", False)
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if success:
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await self._refresh_focus_energy(stream_id)
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process_time = time.time() - start_time
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logger.debug(f"流处理成功: {stream_id} (耗时: {process_time:.2f}s)")
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else:
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logger.warning(f"流处理失败: {stream_id} - {results.get('error_message', '未知错误')}")
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return success
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except Exception as e:
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logger.error(f"流处理异常: {stream_id} - {e}", exc_info=True)
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return False
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async def _calculate_interval(self, stream_id: str, has_messages: bool) -> float:
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"""计算下次检查间隔
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Args:
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stream_id: 流ID
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has_messages: 本次是否有消息处理
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Returns:
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float: 间隔时间（秒）
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"""
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# 基础间隔
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base_interval = getattr(global_config.chat, "distribution_interval", 5.0)
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# 如果没有消息，使用更长的间隔
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if not has_messages:
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return base_interval * 2.0 # 无消息时间隔加倍
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# 尝试使用能量管理器计算间隔
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try:
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# 获取当前focus_energy
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focus_energy = energy_manager.energy_cache.get(stream_id, (0.5, 0))[0]
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# 使用能量管理器计算间隔
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interval = energy_manager.get_distribution_interval(focus_energy)
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logger.debug(f"流 {stream_id} 动态间隔: {interval:.2f}s (能量: {focus_energy:.3f})")
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return interval
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except Exception as e:
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logger.debug(f"流 {stream_id} 使用默认间隔: {base_interval:.2f}s ({e})")
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return base_interval
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def get_queue_status(self) -> Dict[str, Any]:
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"""获取队列状态
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Returns:
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Dict[str, Any]: 队列状态信息
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"""
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current_time = time.time()
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uptime = current_time - self.stats["start_time"] if self.is_running else 0
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return {
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"active_streams": len(self.stream_loops),
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"total_loops": self.stats["total_loops"],
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"max_concurrent": self.max_concurrent_streams,
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"is_running": self.is_running,
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"uptime": uptime,
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"total_process_cycles": self.stats["total_process_cycles"],
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"total_failures": self.stats["total_failures"],
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"stats": self.stats.copy(),
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}
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def set_chatter_manager(self, chatter_manager: ChatterManager) -> None:
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"""设置chatter管理器
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Args:
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chatter_manager: chatter管理器实例
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"""
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self.chatter_manager = chatter_manager
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logger.info(f"设置chatter管理器: {chatter_manager.__class__.__name__}")
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def _should_force_dispatch_for_stream(self, stream_id: str) -> bool:
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if not self.force_dispatch_unread_threshold or self.force_dispatch_unread_threshold <= 0:
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return False
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try:
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chat_manager = get_chat_manager()
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chat_stream = chat_manager.get_stream(stream_id)
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if not chat_stream:
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return False
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unread = getattr(chat_stream.context_manager.context, "unread_messages", [])
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return len(unread) > self.force_dispatch_unread_threshold
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except Exception as e:
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logger.debug(f"检查流 {stream_id} 是否需要强制分发失败: {e}")
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return False
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def _get_unread_count(self, context: Any) -> int:
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try:
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unread_messages = getattr(context, "unread_messages", None)
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if unread_messages is None:
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return 0
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return len(unread_messages)
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except Exception:
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return 0
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def _needs_force_dispatch_for_context(self, context: Any, unread_count: Optional[int] = None) -> bool:
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if not self.force_dispatch_unread_threshold or self.force_dispatch_unread_threshold <= 0:
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return False
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count = unread_count if unread_count is not None else self._get_unread_count(context)
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return count > self.force_dispatch_unread_threshold
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def get_performance_summary(self) -> Dict[str, Any]:
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"""获取性能摘要
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Returns:
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Dict[str, Any]: 性能摘要
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"""
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current_time = time.time()
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uptime = current_time - self.stats["start_time"]
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# 计算吞吐量
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throughput = self.stats["total_process_cycles"] / max(1, uptime / 3600) # 每小时处理次数
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return {
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"uptime_hours": uptime / 3600,
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"active_streams": len(self.stream_loops),
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"total_process_cycles": self.stats["total_process_cycles"],
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"total_failures": self.stats["total_failures"],
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"throughput_per_hour": throughput,
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"max_concurrent_streams": self.max_concurrent_streams,
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}
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async def _refresh_focus_energy(self, stream_id: str) -> None:
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"""分发完成后基于历史消息刷新能量值"""
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try:
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chat_manager = get_chat_manager()
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chat_stream = chat_manager.get_stream(stream_id)
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if not chat_stream:
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logger.debug(f"刷新能量时未找到聊天流: {stream_id}")
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return
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await chat_stream.context_manager.refresh_focus_energy_from_history()
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logger.debug(f"已刷新聊天流 {stream_id} 的聚焦能量")
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except Exception as e:
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logger.warning(f"刷新聊天流 {stream_id} 能量失败: {e}")
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# 全局流循环管理器实例
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stream_loop_manager = StreamLoopManager()
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