337 lines
14 KiB
Python
337 lines
14 KiB
Python
# Copyright 2023
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""分片助手管理器 - 减少锁竞争的高并发agent缓存系统"""
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import hashlib
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import time
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import json
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import asyncio
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from typing import Dict, List, Optional
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import threading
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import logging
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logger = logging.getLogger('app')
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from agent.deep_assistant import init_agent
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from agent.prompt_loader import load_system_prompt_async, load_mcp_settings_async
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class ShardedAgentManager:
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"""分片助手管理器
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使用分片技术减少锁竞争，支持高并发访问
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"""
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def __init__(self, max_cached_agents: int = 20, shard_count: int = 16):
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self.max_cached_agents = max_cached_agents
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self.shard_count = shard_count
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# 创建分片
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self.shards = []
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for i in range(shard_count):
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shard = {
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'agents': {}, # {cache_key: assistant_instance}
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'unique_ids': {}, # {cache_key: unique_id}
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'access_times': {}, # LRU 访问时间管理
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'creation_times': {}, # 创建时间记录
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'lock': asyncio.Lock(), # 每个分片独立锁
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'creation_locks': {}, # 防止并发创建相同agent的锁
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}
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self.shards.append(shard)
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# 用于统计的全局锁（读写分离）
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self._stats_lock = threading.RLock()
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self._global_stats = {
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'total_requests': 0,
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'cache_hits': 0,
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'cache_misses': 0,
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'agent_creations': 0
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}
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def _get_shard_index(self, cache_key: str) -> int:
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"""根据缓存键获取分片索引"""
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hash_value = int(hashlib.md5(cache_key.encode('utf-8')).hexdigest(), 16)
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return hash_value % self.shard_count
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def _get_cache_key(self, bot_id: str, model_name: str = None, api_key: str = None,
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model_server: str = None, generate_cfg: Dict = None,
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system_prompt: str = None, mcp_settings: List[Dict] = None) -> str:
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"""获取包含所有相关参数的哈希值作为缓存键"""
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cache_data = {
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'bot_id': bot_id,
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'model_name': model_name or '',
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'api_key': api_key or '',
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'model_server': model_server or '',
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'generate_cfg': json.dumps(generate_cfg or {}, sort_keys=True),
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'system_prompt': system_prompt or '',
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'mcp_settings': json.dumps(mcp_settings or [], sort_keys=True)
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}
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cache_str = json.dumps(cache_data, sort_keys=True)
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return hashlib.md5(cache_str.encode('utf-8')).hexdigest()[:16]
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def _update_access_time(self, shard: dict, cache_key: str):
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"""更新访问时间（LRU 管理）"""
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shard['access_times'][cache_key] = time.time()
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def _cleanup_old_agents(self, shard: dict):
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"""清理分片中的旧助手实例，基于 LRU 策略"""
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# 计算每个分片的最大容量
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shard_max_capacity = max(1, self.max_cached_agents // self.shard_count)
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if len(shard['agents']) <= shard_max_capacity:
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return
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# 按 LRU 顺序排序，删除最久未访问的实例
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sorted_keys = sorted(shard['access_times'].keys(),
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key=lambda k: shard['access_times'][k])
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keys_to_remove = sorted_keys[:-shard_max_capacity]
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removed_count = 0
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for cache_key in keys_to_remove:
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try:
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del shard['agents'][cache_key]
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del shard['unique_ids'][cache_key]
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del shard['access_times'][cache_key]
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del shard['creation_times'][cache_key]
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shard['creation_locks'].pop(cache_key, None)
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removed_count += 1
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logger.info(f"分片清理过期的助手实例缓存: {cache_key}")
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except KeyError:
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continue
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if removed_count > 0:
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logger.info(f"分片已清理 {removed_count} 个过期的助手实例缓存")
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async def get_or_create_agent(self,
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bot_id: str,
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project_dir: Optional[str],
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model_name: str = "qwen3-next",
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api_key: Optional[str] = None,
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model_server: Optional[str] = None,
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generate_cfg: Optional[Dict] = None,
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language: Optional[str] = None,
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system_prompt: Optional[str] = None,
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mcp_settings: Optional[List[Dict]] = None,
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robot_type: Optional[str] = "general_agent",
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user_identifier: Optional[str] = None):
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"""获取或创建文件预加载的助手实例"""
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# 更新请求统计
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with self._stats_lock:
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self._global_stats['total_requests'] += 1
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# 异步加载配置文件（带缓存）
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final_system_prompt = await load_system_prompt_async(
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project_dir, language, system_prompt, robot_type, bot_id, user_identifier
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)
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final_mcp_settings = await load_mcp_settings_async(
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project_dir, mcp_settings, bot_id, robot_type
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)
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cache_key = self._get_cache_key(bot_id, model_name, api_key, model_server,
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generate_cfg, final_system_prompt, final_mcp_settings)
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# 获取分片
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shard_index = self._get_shard_index(cache_key)
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shard = self.shards[shard_index]
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# 使用分片级异步锁防止并发创建相同的agent
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async with shard['lock']:
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# 检查是否已存在该助手实例
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if cache_key in shard['agents']:
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self._update_access_time(shard, cache_key)
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agent = shard['agents'][cache_key]
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# 更新缓存命中统计
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with self._stats_lock:
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self._global_stats['cache_hits'] += 1
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logger.info(f"分片复用现有的助手实例缓存: {cache_key} (bot_id: {bot_id}, shard: {shard_index})")
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return agent
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# 更新缓存未命中统计
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with self._stats_lock:
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self._global_stats['cache_misses'] += 1
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# 使用更细粒度的创建锁
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creation_lock = shard['creation_locks'].setdefault(cache_key, asyncio.Lock())
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# 在分片锁外创建agent，减少锁持有时间
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async with creation_lock:
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# 再次检查是否已存在（获取锁后可能有其他请求已创建）
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async with shard['lock']:
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if cache_key in shard['agents']:
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self._update_access_time(shard, cache_key)
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agent = shard['agents'][cache_key]
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with self._stats_lock:
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self._global_stats['cache_hits'] += 1
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return agent
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# 清理过期实例
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async with shard['lock']:
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self._cleanup_old_agents(shard)
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# 创建新的助手实例
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logger.info(f"分片创建新的助手实例缓存: {cache_key}, bot_id: {bot_id}, shard: {shard_index}")
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current_time = time.time()
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agent = await init_agent(
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bot_id=bot_id,
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model_name=model_name,
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api_key=api_key,
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model_server=model_server,
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generate_cfg=generate_cfg,
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system_prompt=final_system_prompt,
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mcp=final_mcp_settings,
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robot_type=robot_type,
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language=language,
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user_identifier=user_identifier,
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)
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# 缓存实例
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async with shard['lock']:
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shard['agents'][cache_key] = agent
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shard['unique_ids'][cache_key] = bot_id
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shard['access_times'][cache_key] = current_time
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shard['creation_times'][cache_key] = current_time
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# 清理创建锁
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shard['creation_locks'].pop(cache_key, None)
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# 更新创建统计
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with self._stats_lock:
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self._global_stats['agent_creations'] += 1
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logger.info(f"分片助手实例缓存创建完成: {cache_key}, shard: {shard_index}")
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return agent
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def get_cache_stats(self) -> Dict:
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"""获取缓存统计信息"""
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current_time = time.time()
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total_agents = 0
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agents_info = []
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for i, shard in enumerate(self.shards):
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for cache_key, agent in shard['agents'].items():
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total_agents += 1
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agents_info.append({
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"cache_key": cache_key,
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"unique_id": shard['unique_ids'].get(cache_key, "unknown"),
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"shard": i,
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"created_at": shard['creation_times'].get(cache_key, 0),
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"last_accessed": shard['access_times'].get(cache_key, 0),
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"age_seconds": int(current_time - shard['creation_times'].get(cache_key, current_time)),
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"idle_seconds": int(current_time - shard['access_times'].get(cache_key, current_time))
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})
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stats = {
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"total_cached_agents": total_agents,
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"max_cached_agents": self.max_cached_agents,
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"shard_count": self.shard_count,
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"agents": agents_info
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}
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# 添加全局统计
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with self._stats_lock:
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stats.update({
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"total_requests": self._global_stats['total_requests'],
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"cache_hits": self._global_stats['cache_hits'],
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"cache_misses": self._global_stats['cache_misses'],
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"cache_hit_rate": (
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self._global_stats['cache_hits'] / max(1, self._global_stats['total_requests']) * 100
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),
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"agent_creations": self._global_stats['agent_creations']
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})
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return stats
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def clear_cache(self) -> int:
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"""清空所有缓存"""
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cache_count = 0
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for shard in self.shards:
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cache_count += len(shard['agents'])
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shard['agents'].clear()
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shard['unique_ids'].clear()
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shard['access_times'].clear()
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shard['creation_times'].clear()
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shard['creation_locks'].clear()
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# 重置统计
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with self._stats_lock:
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self._global_stats = {
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'total_requests': 0,
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'cache_hits': 0,
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'cache_misses': 0,
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'agent_creations': 0
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}
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logger.info(f"分片管理器已清空所有助手实例缓存，共清理 {cache_count} 个实例")
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return cache_count
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def remove_cache_by_unique_id(self, unique_id: str) -> int:
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"""根据 unique_id 移除所有相关的缓存"""
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removed_count = 0
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for i, shard in enumerate(self.shards):
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keys_to_remove = []
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# 找到所有匹配的 unique_id 的缓存键
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for cache_key, stored_unique_id in shard['unique_ids'].items():
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if stored_unique_id == unique_id:
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keys_to_remove.append(cache_key)
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# 移除找到的缓存
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for cache_key in keys_to_remove:
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try:
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del shard['agents'][cache_key]
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del shard['unique_ids'][cache_key]
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del shard['access_times'][cache_key]
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del shard['creation_times'][cache_key]
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shard['creation_locks'].pop(cache_key, None)
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removed_count += 1
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logger.info(f"分片 {i} 已移除助手实例缓存: {cache_key} (unique_id: {unique_id})")
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except KeyError:
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continue
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if removed_count > 0:
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logger.info(f"分片管理器已移除 unique_id={unique_id} 的 {removed_count} 个助手实例缓存")
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else:
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logger.warning(f"分片管理器未找到 unique_id={unique_id} 的缓存实例")
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return removed_count
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# 全局分片助手管理器实例
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_global_sharded_agent_manager: Optional[ShardedAgentManager] = None
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def get_global_sharded_agent_manager() -> ShardedAgentManager:
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"""获取全局分片助手管理器实例"""
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global _global_sharded_agent_manager
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if _global_sharded_agent_manager is None:
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_global_sharded_agent_manager = ShardedAgentManager()
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return _global_sharded_agent_manager
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def init_global_sharded_agent_manager(max_cached_agents: int = 20, shard_count: int = 16):
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"""初始化全局分片助手管理器"""
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global _global_sharded_agent_manager
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_global_sharded_agent_manager = ShardedAgentManager(max_cached_agents, shard_count)
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return _global_sharded_agent_manager
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