548 lines
21 KiB
Python
548 lines
21 KiB
Python
"""
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Zep图谱记忆更新服务
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将模拟中的Agent活动动态更新到Zep图谱中
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"""
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import os
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import time
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import threading
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import json
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from typing import Dict, Any, List, Optional, Callable
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from dataclasses import dataclass
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from datetime import datetime
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from queue import Queue, Empty
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from zep_cloud.client import Zep
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from ..config import Config
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from ..utils.logger import get_logger
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logger = get_logger('mirofish.zep_graph_memory_updater')
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@dataclass
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class AgentActivity:
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"""Agent活动记录"""
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platform: str # twitter / reddit
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agent_id: int
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agent_name: str
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action_type: str # CREATE_POST, LIKE_POST, etc.
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action_args: Dict[str, Any]
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round_num: int
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timestamp: str
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def to_episode_text(self) -> str:
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"""
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将活动转换为可以发送给Zep的文本描述
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采用自然语言描述格式，让Zep能够从中提取实体和关系
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不添加模拟相关的前缀，避免误导图谱更新
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"""
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# 根据不同的动作类型生成不同的描述
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action_descriptions = {
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"CREATE_POST": self._describe_create_post,
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"LIKE_POST": self._describe_like_post,
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"DISLIKE_POST": self._describe_dislike_post,
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"REPOST": self._describe_repost,
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"QUOTE_POST": self._describe_quote_post,
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"FOLLOW": self._describe_follow,
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"CREATE_COMMENT": self._describe_create_comment,
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"LIKE_COMMENT": self._describe_like_comment,
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"DISLIKE_COMMENT": self._describe_dislike_comment,
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"SEARCH_POSTS": self._describe_search,
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"SEARCH_USER": self._describe_search_user,
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"MUTE": self._describe_mute,
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}
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describe_func = action_descriptions.get(self.action_type, self._describe_generic)
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description = describe_func()
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# 直接返回 "agent名称: 活动描述" 格式，不添加模拟前缀
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return f"{self.agent_name}: {description}"
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def _describe_create_post(self) -> str:
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content = self.action_args.get("content", "")
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if content:
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return f"published a post: \"{content}\""
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return "published a post"
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def _describe_like_post(self) -> str:
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"""Like post - includes post content and author info"""
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post_content = self.action_args.get("post_content", "")
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post_author = self.action_args.get("post_author_name", "")
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if post_content and post_author:
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return f"liked {post_author}'s post: \"{post_content}\""
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elif post_content:
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return f"liked a post: \"{post_content}\""
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elif post_author:
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return f"liked a post by {post_author}"
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return "liked a post"
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def _describe_dislike_post(self) -> str:
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"""Dislike post - includes post content and author info"""
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post_content = self.action_args.get("post_content", "")
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post_author = self.action_args.get("post_author_name", "")
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if post_content and post_author:
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return f"disliked {post_author}'s post: \"{post_content}\""
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elif post_content:
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return f"disliked a post: \"{post_content}\""
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elif post_author:
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return f"disliked a post by {post_author}"
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return "disliked a post"
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def _describe_repost(self) -> str:
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"""Repost - includes original post content and author info"""
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original_content = self.action_args.get("original_content", "")
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original_author = self.action_args.get("original_author_name", "")
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if original_content and original_author:
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return f"reposted {original_author}'s post: \"{original_content}\""
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elif original_content:
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return f"reposted a post: \"{original_content}\""
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elif original_author:
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return f"reposted a post by {original_author}"
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return "reposted a post"
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def _describe_quote_post(self) -> str:
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"""Quote post - includes original content, author info, and quote comment"""
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original_content = self.action_args.get("original_content", "")
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original_author = self.action_args.get("original_author_name", "")
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quote_content = self.action_args.get("quote_content", "") or self.action_args.get("content", "")
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base = ""
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if original_content and original_author:
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base = f"quoted {original_author}'s post \"{original_content}\""
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elif original_content:
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base = f"quoted a post \"{original_content}\""
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elif original_author:
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base = f"quoted a post by {original_author}"
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else:
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base = "quoted a post"
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if quote_content:
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base += f", commenting: \"{quote_content}\""
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return base
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def _describe_follow(self) -> str:
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"""Follow user - includes followed user's name"""
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target_user_name = self.action_args.get("target_user_name", "")
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if target_user_name:
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return f"followed user \"{target_user_name}\""
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return "followed a user"
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def _describe_create_comment(self) -> str:
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"""Create comment - includes comment content and post info"""
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content = self.action_args.get("content", "")
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post_content = self.action_args.get("post_content", "")
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post_author = self.action_args.get("post_author_name", "")
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if content:
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if post_content and post_author:
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return f"commented on {post_author}'s post \"{post_content}\": \"{content}\""
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elif post_content:
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return f"commented on post \"{post_content}\": \"{content}\""
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elif post_author:
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return f"commented on {post_author}'s post: \"{content}\""
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return f"commented: \"{content}\""
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return "posted a comment"
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def _describe_like_comment(self) -> str:
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"""Like comment - includes comment content and author info"""
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comment_content = self.action_args.get("comment_content", "")
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comment_author = self.action_args.get("comment_author_name", "")
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if comment_content and comment_author:
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return f"liked {comment_author}'s comment: \"{comment_content}\""
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elif comment_content:
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return f"liked a comment: \"{comment_content}\""
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elif comment_author:
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return f"liked a comment by {comment_author}"
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return "liked a comment"
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def _describe_dislike_comment(self) -> str:
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"""Dislike comment - includes comment content and author info"""
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comment_content = self.action_args.get("comment_content", "")
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comment_author = self.action_args.get("comment_author_name", "")
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if comment_content and comment_author:
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return f"disliked {comment_author}'s comment: \"{comment_content}\""
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elif comment_content:
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return f"disliked a comment: \"{comment_content}\""
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elif comment_author:
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return f"disliked a comment by {comment_author}"
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return "disliked a comment"
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def _describe_search(self) -> str:
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"""Search posts - includes search keywords"""
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query = self.action_args.get("query", "") or self.action_args.get("keyword", "")
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return f"searched for \"{query}\"" if query else "performed a search"
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def _describe_search_user(self) -> str:
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"""Search user - includes search keywords"""
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query = self.action_args.get("query", "") or self.action_args.get("username", "")
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return f"searched for user \"{query}\"" if query else "searched for a user"
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def _describe_mute(self) -> str:
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"""Mute user - includes muted user's name"""
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target_user_name = self.action_args.get("target_user_name", "")
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if target_user_name:
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return f"muted user \"{target_user_name}\""
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return "muted a user"
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def _describe_generic(self) -> str:
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# Generic description for unknown action types
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return f"performed {self.action_type} action"
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class ZepGraphMemoryUpdater:
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"""
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Zep图谱记忆更新器
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监控模拟的actions日志文件，将新的agent活动实时更新到Zep图谱中。
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按平台分组，每累积BATCH_SIZE条活动后批量发送到Zep。
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所有有意义的行为都会被更新到Zep，action_args中会包含完整的上下文信息：
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- 点赞/踩的帖子原文
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- 转发/引用的帖子原文
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- 关注/屏蔽的用户名
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- 点赞/踩的评论原文
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"""
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# 批量发送大小（每个平台累积多少条后发送）
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BATCH_SIZE = 5
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# 平台名称映射（用于控制台显示）
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PLATFORM_DISPLAY_NAMES = {
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'twitter': '世界1',
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'reddit': '世界2',
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}
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# 发送间隔（秒），避免请求过快
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SEND_INTERVAL = 0.5
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# 重试配置
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MAX_RETRIES = 3
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RETRY_DELAY = 2 # 秒
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def __init__(self, graph_id: str, api_key: Optional[str] = None):
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"""
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初始化更新器
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Args:
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graph_id: Zep图谱ID
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api_key: Zep API Key（可选，默认从配置读取）
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"""
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self.graph_id = graph_id
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self.api_key = api_key or Config.ZEP_API_KEY
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if not self.api_key:
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raise ValueError("ZEP_API_KEY is not configured")
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self.client = Zep(api_key=self.api_key)
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# 活动队列
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self._activity_queue: Queue = Queue()
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# 按平台分组的活动缓冲区（每个平台各自累积到BATCH_SIZE后批量发送）
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self._platform_buffers: Dict[str, List[AgentActivity]] = {
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'twitter': [],
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'reddit': [],
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}
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self._buffer_lock = threading.Lock()
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# 控制标志
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self._running = False
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self._worker_thread: Optional[threading.Thread] = None
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# 统计
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self._total_activities = 0 # 实际添加到队列的活动数
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self._total_sent = 0 # 成功发送到Zep的批次数
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self._total_items_sent = 0 # 成功发送到Zep的活动条数
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self._failed_count = 0 # 发送失败的批次数
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self._skipped_count = 0 # 被过滤跳过的活动数（DO_NOTHING）
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logger.info(f"ZepGraphMemoryUpdater 初始化完成: graph_id={graph_id}, batch_size={self.BATCH_SIZE}")
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def _get_platform_display_name(self, platform: str) -> str:
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"""获取平台的显示名称"""
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return self.PLATFORM_DISPLAY_NAMES.get(platform.lower(), platform)
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def start(self):
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"""启动后台工作线程"""
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if self._running:
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return
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self._running = True
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self._worker_thread = threading.Thread(
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target=self._worker_loop,
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daemon=True,
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name=f"ZepMemoryUpdater-{self.graph_id[:8]}"
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)
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self._worker_thread.start()
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logger.info(f"ZepGraphMemoryUpdater 已启动: graph_id={self.graph_id}")
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def stop(self):
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"""停止后台工作线程"""
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self._running = False
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# 发送剩余的活动
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self._flush_remaining()
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if self._worker_thread and self._worker_thread.is_alive():
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self._worker_thread.join(timeout=10)
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logger.info(f"ZepGraphMemoryUpdater 已停止: graph_id={self.graph_id}, "
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f"total_activities={self._total_activities}, "
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f"batches_sent={self._total_sent}, "
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f"items_sent={self._total_items_sent}, "
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f"failed={self._failed_count}, "
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f"skipped={self._skipped_count}")
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def add_activity(self, activity: AgentActivity):
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"""
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添加一个agent活动到队列
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所有有意义的行为都会被添加到队列，包括：
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- CREATE_POST（发帖）
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- CREATE_COMMENT（评论）
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- QUOTE_POST（引用帖子）
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- SEARCH_POSTS（搜索帖子）
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- SEARCH_USER（搜索用户）
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- LIKE_POST/DISLIKE_POST（点赞/踩帖子）
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- REPOST（转发）
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- FOLLOW（关注）
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- MUTE（屏蔽）
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- LIKE_COMMENT/DISLIKE_COMMENT（点赞/踩评论）
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action_args中会包含完整的上下文信息（如帖子原文、用户名等）。
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Args:
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activity: Agent活动记录
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"""
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# 跳过DO_NOTHING类型的活动
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if activity.action_type == "DO_NOTHING":
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self._skipped_count += 1
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return
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self._activity_queue.put(activity)
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self._total_activities += 1
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logger.debug(f"添加活动到Zep队列: {activity.agent_name} - {activity.action_type}")
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def add_activity_from_dict(self, data: Dict[str, Any], platform: str):
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"""
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从字典数据添加活动
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Args:
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data: 从actions.jsonl解析的字典数据
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platform: 平台名称 (twitter/reddit)
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"""
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# 跳过事件类型的条目
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if "event_type" in data:
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return
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activity = AgentActivity(
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platform=platform,
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agent_id=data.get("agent_id", 0),
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agent_name=data.get("agent_name", ""),
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action_type=data.get("action_type", ""),
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action_args=data.get("action_args", {}),
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round_num=data.get("round", 0),
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timestamp=data.get("timestamp", datetime.now().isoformat()),
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)
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self.add_activity(activity)
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def _worker_loop(self):
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"""后台工作循环 - 按平台批量发送活动到Zep"""
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while self._running or not self._activity_queue.empty():
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try:
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# 尝试从队列获取活动（超时1秒）
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try:
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activity = self._activity_queue.get(timeout=1)
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# 将活动添加到对应平台的缓冲区
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platform = activity.platform.lower()
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with self._buffer_lock:
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if platform not in self._platform_buffers:
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self._platform_buffers[platform] = []
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self._platform_buffers[platform].append(activity)
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# 检查该平台是否达到批量大小
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if len(self._platform_buffers[platform]) >= self.BATCH_SIZE:
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batch = self._platform_buffers[platform][:self.BATCH_SIZE]
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self._platform_buffers[platform] = self._platform_buffers[platform][self.BATCH_SIZE:]
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# 释放锁后再发送
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self._send_batch_activities(batch, platform)
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# 发送间隔，避免请求过快
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time.sleep(self.SEND_INTERVAL)
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except Empty:
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pass
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except Exception as e:
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logger.error(f"工作循环异常: {e}")
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time.sleep(1)
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def _send_batch_activities(self, activities: List[AgentActivity], platform: str):
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"""
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批量发送活动到Zep图谱（合并为一条文本）
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Args:
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activities: Agent活动列表
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platform: 平台名称
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"""
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if not activities:
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return
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# 将多条活动合并为一条文本，用换行分隔
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episode_texts = [activity.to_episode_text() for activity in activities]
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combined_text = "\n".join(episode_texts)
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# 带重试的发送
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for attempt in range(self.MAX_RETRIES):
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try:
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self.client.graph.add(
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graph_id=self.graph_id,
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type="text",
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data=combined_text
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)
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self._total_sent += 1
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self._total_items_sent += len(activities)
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display_name = self._get_platform_display_name(platform)
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logger.info(f"成功批量发送 {len(activities)} 条{display_name}活动到图谱 {self.graph_id}")
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logger.debug(f"批量内容预览: {combined_text[:200]}...")
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return
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except Exception as e:
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if attempt < self.MAX_RETRIES - 1:
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logger.warning(f"批量发送到Zep失败 (尝试 {attempt + 1}/{self.MAX_RETRIES}): {e}")
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time.sleep(self.RETRY_DELAY * (attempt + 1))
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else:
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logger.error(f"批量发送到Zep失败，已重试{self.MAX_RETRIES}次: {e}")
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self._failed_count += 1
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def _flush_remaining(self):
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"""发送队列和缓冲区中剩余的活动"""
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# 首先处理队列中剩余的活动，添加到缓冲区
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while not self._activity_queue.empty():
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try:
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activity = self._activity_queue.get_nowait()
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platform = activity.platform.lower()
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with self._buffer_lock:
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if platform not in self._platform_buffers:
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self._platform_buffers[platform] = []
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self._platform_buffers[platform].append(activity)
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except Empty:
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break
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# 然后发送各平台缓冲区中剩余的活动（即使不足BATCH_SIZE条）
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with self._buffer_lock:
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for platform, buffer in self._platform_buffers.items():
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if buffer:
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display_name = self._get_platform_display_name(platform)
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logger.info(f"发送{display_name}平台剩余的 {len(buffer)} 条活动")
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self._send_batch_activities(buffer, platform)
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# 清空所有缓冲区
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for platform in self._platform_buffers:
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self._platform_buffers[platform] = []
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def get_stats(self) -> Dict[str, Any]:
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"""获取统计信息"""
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with self._buffer_lock:
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buffer_sizes = {p: len(b) for p, b in self._platform_buffers.items()}
|
||
|
||
return {
|
||
"graph_id": self.graph_id,
|
||
"batch_size": self.BATCH_SIZE,
|
||
"total_activities": self._total_activities, # 添加到队列的活动总数
|
||
"batches_sent": self._total_sent, # 成功发送的批次数
|
||
"items_sent": self._total_items_sent, # 成功发送的活动条数
|
||
"failed_count": self._failed_count, # 发送失败的批次数
|
||
"skipped_count": self._skipped_count, # 被过滤跳过的活动数（DO_NOTHING）
|
||
"queue_size": self._activity_queue.qsize(),
|
||
"buffer_sizes": buffer_sizes, # 各平台缓冲区大小
|
||
"running": self._running,
|
||
}
|
||
|
||
|
||
class ZepGraphMemoryManager:
|
||
"""
|
||
管理多个模拟的Zep图谱记忆更新器
|
||
|
||
每个模拟可以有自己的更新器实例
|
||
"""
|
||
|
||
_updaters: Dict[str, ZepGraphMemoryUpdater] = {}
|
||
_lock = threading.Lock()
|
||
|
||
@classmethod
|
||
def create_updater(cls, simulation_id: str, graph_id: str) -> ZepGraphMemoryUpdater:
|
||
"""
|
||
为模拟创建图谱记忆更新器
|
||
|
||
Args:
|
||
simulation_id: 模拟ID
|
||
graph_id: Zep图谱ID
|
||
|
||
Returns:
|
||
ZepGraphMemoryUpdater实例
|
||
"""
|
||
with cls._lock:
|
||
# 如果已存在，先停止旧的
|
||
if simulation_id in cls._updaters:
|
||
cls._updaters[simulation_id].stop()
|
||
|
||
updater = ZepGraphMemoryUpdater(graph_id)
|
||
updater.start()
|
||
cls._updaters[simulation_id] = updater
|
||
|
||
logger.info(f"创建图谱记忆更新器: simulation_id={simulation_id}, graph_id={graph_id}")
|
||
return updater
|
||
|
||
@classmethod
|
||
def get_updater(cls, simulation_id: str) -> Optional[ZepGraphMemoryUpdater]:
|
||
"""获取模拟的更新器"""
|
||
return cls._updaters.get(simulation_id)
|
||
|
||
@classmethod
|
||
def stop_updater(cls, simulation_id: str):
|
||
"""停止并移除模拟的更新器"""
|
||
with cls._lock:
|
||
if simulation_id in cls._updaters:
|
||
cls._updaters[simulation_id].stop()
|
||
del cls._updaters[simulation_id]
|
||
logger.info(f"已停止图谱记忆更新器: simulation_id={simulation_id}")
|
||
|
||
# 防止 stop_all 重复调用的标志
|
||
_stop_all_done = False
|
||
|
||
@classmethod
|
||
def stop_all(cls):
|
||
"""停止所有更新器"""
|
||
# 防止重复调用
|
||
if cls._stop_all_done:
|
||
return
|
||
cls._stop_all_done = True
|
||
|
||
with cls._lock:
|
||
if cls._updaters:
|
||
for simulation_id, updater in list(cls._updaters.items()):
|
||
try:
|
||
updater.stop()
|
||
except Exception as e:
|
||
logger.error(f"停止更新器失败: simulation_id={simulation_id}, error={e}")
|
||
cls._updaters.clear()
|
||
logger.info("已停止所有图谱记忆更新器")
|
||
|
||
@classmethod
|
||
def get_all_stats(cls) -> Dict[str, Dict[str, Any]]:
|
||
"""获取所有更新器的统计信息"""
|
||
return {
|
||
sim_id: updater.get_stats()
|
||
for sim_id, updater in cls._updaters.items()
|
||
}
|