691 lines
27 KiB
Python
691 lines
27 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 Any
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from src.chat.chatter_manager import ChatterManager
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from src.chat.energy_system import energy_manager
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from src.common.data_models.message_manager_data_model import StreamContext
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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.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: int | None = None):
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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 global_config.chat.max_concurrent_distributions
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# 强制分发策略
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self.force_dispatch_unread_threshold: int | None = 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(global_config.chat, "force_dispatch_min_interval", 0.1)
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# Chatter管理器
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self.chatter_manager: ChatterManager | None = None
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# 状态控制
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self.is_running = False
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# 每个流的上一次间隔值（用于日志去重）
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self._last_intervals: dict[str, float] = {}
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# 流循环启动锁：防止并发启动同一个流的多个循环任务
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self._stream_start_locks: dict[str, asyncio.Lock] = {}
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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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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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try:
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# 获取所有活跃的流
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from src.plugin_system.apis.chat_api import get_chat_manager
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chat_manager = get_chat_manager()
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all_streams = chat_manager.get_all_streams()
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# 创建任务列表以便并发取消
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cancel_tasks = []
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for chat_stream in all_streams.values():
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context = chat_stream.context_manager.context
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if context.stream_loop_task and not context.stream_loop_task.done():
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context.stream_loop_task.cancel()
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cancel_tasks.append((chat_stream.stream_id, context.stream_loop_task))
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# 并发等待所有任务取消
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if cancel_tasks:
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logger.info(f"正在取消 {len(cancel_tasks)} 个流循环任务...")
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await asyncio.gather(
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*[self._wait_for_task_cancel(stream_id, task) for stream_id, task in cancel_tasks],
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return_exceptions=True,
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)
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logger.info("所有流循环已清理")
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except Exception as e:
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logger.error(f"停止管理器时出错: {e}")
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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 - 优化版本使用自适应管理器
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Args:
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stream_id: 流ID
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force: 是否强制启动
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Returns:
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bool: 是否成功启动
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"""
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# 获取或创建该流的启动锁
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if stream_id not in self._stream_start_locks:
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self._stream_start_locks[stream_id] = asyncio.Lock()
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lock = self._stream_start_locks[stream_id]
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# 使用锁防止并发启动同一个流的多个循环任务
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async with lock:
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# 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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return False
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# 快速路径：如果流已存在且不是强制启动，无需处理
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if not force and context.stream_loop_task and not context.stream_loop_task.done():
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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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# 如果是强制启动且任务仍在运行，先取消旧任务
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if force and context.stream_loop_task and not context.stream_loop_task.done():
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logger.debug(f"强制启动模式：先取消现有流循环任务: {stream_id}")
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old_task = context.stream_loop_task
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old_task.cancel()
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try:
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await asyncio.wait_for(old_task, timeout=2.0)
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logger.debug(f"旧流循环任务已结束: {stream_id}")
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except (asyncio.TimeoutError, asyncio.CancelledError):
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logger.debug(f"旧流循环任务已取消或超时: {stream_id}")
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except Exception as e:
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logger.warning(f"等待旧任务结束时出错: {e}")
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# 创建流循环任务
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try:
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loop_task = asyncio.create_task(self._stream_loop_worker(stream_id), name=f"stream_loop_{stream_id}")
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# 将任务记录到 StreamContext 中
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context.stream_loop_task = loop_task
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# 更新统计信息
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self.stats["active_streams"] += 1
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self.stats["total_loops"] += 1
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logger.debug(f"启动流循环任务: {stream_id}")
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return True
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except Exception as e:
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logger.error(f"启动流循环任务失败 {stream_id}: {e}")
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return False
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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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# 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.debug(f"流 {stream_id} 上下文不存在，无需停止")
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return False
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# 检查是否有 stream_loop_task
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if not context.stream_loop_task or context.stream_loop_task.done():
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logger.debug(f"流 {stream_id} 循环不存在或已结束，无需停止")
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return False
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task = context.stream_loop_task
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if not task.done():
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task.cancel()
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try:
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# 设置取消超时，避免无限等待
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await asyncio.wait_for(task, timeout=5.0)
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except asyncio.CancelledError:
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logger.debug(f"流循环任务已取消: {stream_id}")
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except asyncio.TimeoutError:
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logger.warning(f"流循环任务取消超时: {stream_id}")
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except Exception as e:
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logger.error(f"等待流循环任务结束时出错: {stream_id} - {e}")
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# 清空 StreamContext 中的任务记录
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context.stream_loop_task = None
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logger.debug(f"停止流循环: {stream_id}")
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return True
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async def _stream_loop_worker(self, stream_id: str) -> None:
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"""单个流的工作循环 - 优化版本
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Args:
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stream_id: 流ID
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"""
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logger.debug(f"流循环工作器启动: {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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await self._flush_cached_messages_to_unread(stream_id)
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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("流 %s 未读消息 %d 条，触发强制分发", stream_id, unread_count)
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# 3. 在处理前更新能量值（用于下次间隔计算）
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try:
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await self._update_stream_energy(stream_id, context)
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except Exception as e:
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logger.debug(f"更新流能量失败 {stream_id}: {e}")
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# 4. 激活chatter处理
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success = await asyncio.wait_for(self._process_stream_messages(stream_id, context), global_config.chat.thinking_timeout)
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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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# 5. 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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# 6. sleep等待下次检查
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# 只在间隔发生变化时输出日志，避免刷屏
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last_interval = self._last_intervals.get(stream_id)
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if last_interval is None or abs(interval - last_interval) > 0.01:
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logger.info(f"流 {stream_id} 等待周期变化: {interval:.2f}s")
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self._last_intervals[stream_id] = interval
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await asyncio.sleep(interval)
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except asyncio.CancelledError:
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logger.debug(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 StreamContext 中的任务记录
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try:
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context = await self._get_stream_context(stream_id)
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if context and context.stream_loop_task:
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context.stream_loop_task = None
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logger.debug(f"清理 StreamContext 中的流循环任务: {stream_id}")
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except Exception as e:
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logger.debug(f"清理 StreamContext 任务记录失败: {e}")
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# 清理间隔记录
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self._last_intervals.pop(stream_id, None)
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logger.debug(f"流循环结束: {stream_id}")
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async def _get_stream_context(self, stream_id: str) -> StreamContext | None:
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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[StreamContext]: 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 = await 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: StreamContext) -> 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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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: StreamContext) -> bool:
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"""处理流消息 - 支持子任务管理
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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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# 设置处理状态为正在处理
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self._set_stream_processing_status(stream_id, True)
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# 子任务跟踪
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child_tasks = set()
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try:
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start_time = time.time()
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# 注意：缓存消息刷新已移至planner开始时执行（动作修改器之后），此处不再刷新
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# 设置触发用户ID，以实现回复保护
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last_message = context.get_last_message()
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if last_message:
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context.triggering_user_id = last_message.user_info.user_id
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# 创建子任务用于刷新能量（不阻塞主流程）
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energy_task = asyncio.create_task(self._refresh_focus_energy(stream_id))
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child_tasks.add(energy_task)
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energy_task.add_done_callback(lambda t: child_tasks.discard(t))
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# 设置 Chatter 正在处理的标志
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context.is_chatter_processing = True
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logger.debug(f"设置 Chatter 处理标志: {stream_id}")
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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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# 处理成功后，再次刷新缓存中可能的新消息
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additional_messages = await self._flush_cached_messages_to_unread(stream_id)
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if additional_messages:
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logger.debug(f"处理完成后刷新新消息: stream={stream_id}, 数量={len(additional_messages)}")
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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 asyncio.CancelledError:
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logger.debug(f"流处理被取消: {stream_id}")
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# 取消所有子任务
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for child_task in child_tasks:
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if not child_task.done():
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child_task.cancel()
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raise
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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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# 异常时也要清理子任务
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for child_task in child_tasks:
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if not child_task.done():
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child_task.cancel()
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return False
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finally:
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# 清除 Chatter 处理标志
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context.is_chatter_processing = False
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logger.debug(f"清除 Chatter 处理标志: {stream_id}")
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# 无论成功或失败，都要设置处理状态为未处理
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self._set_stream_processing_status(stream_id, False)
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def _set_stream_processing_status(self, stream_id: str, is_processing: bool) -> None:
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"""设置流的处理状态"""
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try:
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from .message_manager import message_manager
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if message_manager.is_running:
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message_manager.set_stream_processing_status(stream_id, is_processing)
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logger.debug(f"设置流处理状态: stream={stream_id}, processing={is_processing}")
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except ImportError:
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logger.debug("MessageManager不可用，跳过状态设置")
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except Exception as e:
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logger.warning(f"设置流处理状态失败: stream={stream_id}, error={e}")
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async def _flush_cached_messages_to_unread(self, stream_id: str) -> list:
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"""将缓存消息刷新到未读消息列表"""
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try:
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# 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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return []
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# 使用StreamContext的缓存刷新功能
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if hasattr(context, "flush_cached_messages"):
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cached_messages = context.flush_cached_messages()
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if cached_messages:
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logger.debug(f"从StreamContext刷新缓存消息: stream={stream_id}, 数量={len(cached_messages)}")
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return cached_messages
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else:
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logger.debug(f"StreamContext不支持缓存刷新: stream={stream_id}")
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return []
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except Exception as e:
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logger.warning(f"刷新StreamContext缓存失败: stream={stream_id}, error={e}")
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return []
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async def _update_stream_energy(self, stream_id: str, context: Any) -> None:
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"""更新流的能量值
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Args:
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stream_id: 流ID
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context: 流上下文 (StreamContext)
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"""
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try:
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from src.chat.message_receive.chat_stream import get_chat_manager
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# 获取聊天流
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chat_manager = get_chat_manager()
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chat_stream = await chat_manager.get_stream(stream_id)
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if not chat_stream:
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logger.debug(f"无法找到聊天流 {stream_id}，跳过能量更新")
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return
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# 从 context_manager 获取消息（包括未读和历史消息）
|
||
# 合并未读消息和历史消息
|
||
all_messages = []
|
||
|
||
# 添加历史消息
|
||
history_messages = context.get_history_messages(limit=global_config.chat.max_context_size)
|
||
all_messages.extend(history_messages)
|
||
|
||
# 添加未读消息
|
||
unread_messages = context.get_unread_messages()
|
||
all_messages.extend(unread_messages)
|
||
|
||
# 按时间排序并限制数量
|
||
all_messages.sort(key=lambda m: m.time)
|
||
messages = all_messages[-global_config.chat.max_context_size:]
|
||
|
||
# 获取用户ID
|
||
user_id = None
|
||
if context.triggering_user_id:
|
||
user_id = context.triggering_user_id
|
||
|
||
# 使用能量管理器计算并缓存能量值
|
||
energy = await energy_manager.calculate_focus_energy(
|
||
stream_id=stream_id,
|
||
messages=messages,
|
||
user_id=user_id
|
||
)
|
||
|
||
# 同步更新到 ChatStream
|
||
chat_stream._focus_energy = energy
|
||
|
||
logger.debug(f"已更新流 {stream_id} 的能量值: {energy:.3f}")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"更新流能量失败 {stream_id}: {e}", exc_info=False)
|
||
|
||
async def _calculate_interval(self, stream_id: str, has_messages: bool) -> float:
|
||
"""计算下次检查间隔
|
||
|
||
Args:
|
||
stream_id: 流ID
|
||
has_messages: 本次是否有消息处理
|
||
|
||
Returns:
|
||
float: 间隔时间（秒）
|
||
"""
|
||
# 基础间隔
|
||
base_interval = getattr(global_config.chat, "distribution_interval", 5.0)
|
||
|
||
# 如果没有消息，使用更长的间隔
|
||
if not has_messages:
|
||
return base_interval * 2.0 # 无消息时间隔加倍
|
||
|
||
# 尝试使用能量管理器计算间隔
|
||
try:
|
||
# 获取当前focus_energy
|
||
focus_energy = energy_manager.energy_cache.get(stream_id, (0.5, 0))[0]
|
||
|
||
# 使用能量管理器计算间隔
|
||
interval = energy_manager.get_distribution_interval(focus_energy)
|
||
|
||
logger.debug(f"流 {stream_id} 动态间隔: {interval:.2f}s (能量: {focus_energy:.3f})")
|
||
return interval
|
||
|
||
except Exception as e:
|
||
logger.debug(f"流 {stream_id} 使用默认间隔: {base_interval:.2f}s ({e})")
|
||
return base_interval
|
||
|
||
def get_queue_status(self) -> dict[str, Any]:
|
||
"""获取队列状态
|
||
|
||
Returns:
|
||
Dict[str, Any]: 队列状态信息
|
||
"""
|
||
current_time = time.time()
|
||
uptime = current_time - self.stats["start_time"] if self.is_running else 0
|
||
|
||
# 从统计信息中获取活跃流数量
|
||
active_streams = self.stats.get("active_streams", 0)
|
||
|
||
return {
|
||
"active_streams": active_streams,
|
||
"total_loops": self.stats["total_loops"],
|
||
"max_concurrent": self.max_concurrent_streams,
|
||
"is_running": self.is_running,
|
||
"uptime": uptime,
|
||
"total_process_cycles": self.stats["total_process_cycles"],
|
||
"total_failures": self.stats["total_failures"],
|
||
"stats": self.stats.copy(),
|
||
}
|
||
|
||
def set_chatter_manager(self, chatter_manager: ChatterManager) -> None:
|
||
"""设置chatter管理器
|
||
|
||
Args:
|
||
chatter_manager: chatter管理器实例
|
||
"""
|
||
self.chatter_manager = chatter_manager
|
||
logger.debug(f"设置chatter管理器: {chatter_manager.__class__.__name__}")
|
||
|
||
async def _should_force_dispatch_for_stream(self, stream_id: str) -> bool:
|
||
if not self.force_dispatch_unread_threshold or self.force_dispatch_unread_threshold <= 0:
|
||
return False
|
||
|
||
try:
|
||
chat_manager = get_chat_manager()
|
||
chat_stream = await chat_manager.get_stream(stream_id)
|
||
if not chat_stream:
|
||
return False
|
||
|
||
unread = getattr(chat_stream.context_manager.context, "unread_messages", [])
|
||
return len(unread) > self.force_dispatch_unread_threshold
|
||
except Exception as e:
|
||
logger.debug(f"检查流 {stream_id} 是否需要强制分发失败: {e}")
|
||
return False
|
||
|
||
def _get_unread_count(self, context: StreamContext) -> int:
|
||
try:
|
||
unread_messages = context.unread_messages
|
||
if unread_messages is None:
|
||
return 0
|
||
return len(unread_messages)
|
||
except Exception:
|
||
return 0
|
||
|
||
def _needs_force_dispatch_for_context(self, context: StreamContext, unread_count: int | None = None) -> bool:
|
||
if not self.force_dispatch_unread_threshold or self.force_dispatch_unread_threshold <= 0:
|
||
return False
|
||
|
||
count = unread_count if unread_count is not None else self._get_unread_count(context)
|
||
return count > self.force_dispatch_unread_threshold
|
||
|
||
def get_performance_summary(self) -> dict[str, Any]:
|
||
"""获取性能摘要
|
||
|
||
Returns:
|
||
Dict[str, Any]: 性能摘要
|
||
"""
|
||
current_time = time.time()
|
||
uptime = current_time - self.stats["start_time"]
|
||
|
||
# 计算吞吐量
|
||
throughput = self.stats["total_process_cycles"] / max(1, uptime / 3600) # 每小时处理次数
|
||
|
||
# 从统计信息中获取活跃流数量
|
||
active_streams = self.stats.get("active_streams", 0)
|
||
|
||
return {
|
||
"uptime_hours": uptime / 3600,
|
||
"active_streams": active_streams,
|
||
"total_process_cycles": self.stats["total_process_cycles"],
|
||
"total_failures": self.stats["total_failures"],
|
||
"throughput_per_hour": throughput,
|
||
"max_concurrent_streams": self.max_concurrent_streams,
|
||
}
|
||
|
||
async def _refresh_focus_energy(self, stream_id: str) -> None:
|
||
"""分发完成后基于历史消息刷新能量值"""
|
||
try:
|
||
chat_manager = get_chat_manager()
|
||
chat_stream = await chat_manager.get_stream(stream_id)
|
||
if not chat_stream:
|
||
logger.debug(f"刷新能量时未找到聊天流: {stream_id}")
|
||
return
|
||
|
||
await chat_stream.context_manager.refresh_focus_energy_from_history()
|
||
logger.debug(f"已刷新聊天流 {stream_id} 的聚焦能量")
|
||
except Exception as e:
|
||
logger.warning(f"刷新聊天流 {stream_id} 能量失败: {e}")
|
||
|
||
async def _wait_for_task_cancel(self, stream_id: str, task: asyncio.Task) -> None:
|
||
"""等待任务取消完成，带有超时控制
|
||
|
||
Args:
|
||
stream_id: 流ID
|
||
task: 要等待取消的任务
|
||
"""
|
||
try:
|
||
await asyncio.wait_for(task, timeout=5.0)
|
||
logger.debug(f"流循环任务已正常结束: {stream_id}")
|
||
except asyncio.CancelledError:
|
||
logger.debug(f"流循环任务已取消: {stream_id}")
|
||
except asyncio.TimeoutError:
|
||
logger.warning(f"流循环任务取消超时: {stream_id}")
|
||
except Exception as e:
|
||
logger.error(f"等待流循环任务结束时出错: {stream_id} - {e}")
|
||
|
||
async def _force_dispatch_stream(self, stream_id: str) -> None:
|
||
"""强制分发流处理
|
||
|
||
当流的未读消息超过阈值时，强制触发分发处理
|
||
这个方法主要用于突破并发限制时的紧急处理
|
||
|
||
注意：此方法目前未被使用，相关功能已集成到 start_stream_loop 方法中
|
||
|
||
Args:
|
||
stream_id: 流ID
|
||
"""
|
||
logger.debug(f"强制分发流处理: {stream_id}")
|
||
|
||
try:
|
||
# 获取流上下文
|
||
context = await self._get_stream_context(stream_id)
|
||
if not context:
|
||
logger.warning(f"强制分发时未找到流上下文: {stream_id}")
|
||
return
|
||
|
||
# 检查是否有现有的 stream_loop_task
|
||
if context.stream_loop_task and not context.stream_loop_task.done():
|
||
logger.debug(f"发现现有流循环 {stream_id}，将先取消再重新创建")
|
||
existing_task = context.stream_loop_task
|
||
existing_task.cancel()
|
||
# 创建异步任务来等待取消完成，并添加异常处理
|
||
cancel_task = asyncio.create_task(
|
||
self._wait_for_task_cancel(stream_id, existing_task), name=f"cancel_existing_loop_{stream_id}"
|
||
)
|
||
# 为取消任务添加异常处理，避免孤儿任务
|
||
cancel_task.add_done_callback(
|
||
lambda task: logger.debug(f"取消任务完成: {stream_id}")
|
||
if not task.exception()
|
||
else logger.error(f"取消任务异常: {stream_id} - {task.exception()}")
|
||
)
|
||
|
||
# 检查未读消息数量
|
||
unread_count = self._get_unread_count(context)
|
||
logger.info(f"流 {stream_id} 当前未读消息数: {unread_count}")
|
||
|
||
# 使用 start_stream_loop 重新创建流循环任务
|
||
success = await self.start_stream_loop(stream_id, force=True)
|
||
|
||
if success:
|
||
logger.info(f"已创建强制分发流循环: {stream_id}")
|
||
else:
|
||
logger.warning(f"创建强制分发流循环失败: {stream_id}")
|
||
|
||
except Exception as e:
|
||
logger.error(f"强制分发流处理失败 {stream_id}: {e}", exc_info=True)
|
||
|
||
|
||
# 全局流循环管理器实例
|
||
stream_loop_manager = StreamLoopManager() |