fix: 修复35个安全与功能缺陷，补全知识进化/数字孪生/行为采集模块
## 安全修复 (12项) - Webhook接口添加全局Token认证，过滤敏感请求头 - 修复JWT Base64 padding公式，防止签名验证绕过 - 数据库密码/飞书Token从源码移除，改为环境变量 - 工作流引擎添加路径遍历防护 (_resolve_safe_path) - eval()添加模板长度上限检查 - 审批API添加认证依赖 - 前端v-html增强XSS转义，console.log仅开发模式输出 - 500错误不再暴露内部异常详情 ## Agent运行时修复 (7项) - 删除_inject_knowledge_context中未定义db变量的finally块 - 工具执行添加try/except保护，异常不崩溃Agent - LLM重试计入budget计数器 - self_review异常时passed=False - max_iterations截断标记success=False - 工具参数JSON解析失败时记录警告日志 - run()开始时重置_llm_invocations计数器 ## 配置与基础设施 - DEBUG默认False，SQL_ECHO独立配置项 - init_db()补全13个缺失模型导入 - 新增WEBHOOK_AUTH_TOKEN/SQL_ECHO配置项 - 新增.env.example模板文件 ## 前端修复 (12项) - 登录改用URLSearchParams替代FormData - 401拦截器通过Pinia store统一清理状态 - SSE流超时从60s延长至300s - final/error事件时清除streamTimeout - localStorage聊天记录添加24h TTL - safeParseArgCount替代模板中裸JSON.parse - fetchUser 401时同时清除user对象 ## 新增模块 - 知识进化: knowledge_extractor/retriever/tasks - 数字孪生: shadow_executor/comparison模型 - 行为采集: behavior_middleware/collector/fingerprint_engine - 代码审查: code_review_agent/document_review_agent - 反馈学习: feedback_learner - 瓶颈检测/优化引擎/成本估算/需求估算 - 速率限制器 (rate_limiter) - Alembic迁移 015-020 ## 文档 - 商业化落地计划 - 8篇docs文档 (架构/API/部署/开发/贡献等) - Docker Compose生产配置 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
renjianbo
@@ -1,29 +1,25 @@
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"""
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执行日志服务
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- ExecutionLogger: 工作流执行的日志记录器（per-execution）
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- ExecutionLoggerService: Agent 执行的日志服务（全局单例）
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"""
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from typing import Dict, Any, Optional
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from typing import Dict, Any, Optional, List
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from datetime import datetime
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from sqlalchemy.orm import Session
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from app.models.execution_log import ExecutionLog
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import asyncio
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import logging
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logger = logging.getLogger(__name__)
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class ExecutionLogger:
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"""执行日志记录器"""
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"""执行日志记录器（工作流/编排执行上下文）"""
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def __init__(self, execution_id: str, db: Session):
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"""
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初始化日志记录器
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Args:
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execution_id: 执行ID
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db: 数据库会话
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"""
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self.execution_id = execution_id
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self.db = db
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def log(
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self,
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level: str,
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@@ -33,17 +29,6 @@ class ExecutionLogger:
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data: Optional[Dict[str, Any]] = None,
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duration: Optional[int] = None
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):
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"""
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记录日志
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Args:
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level: 日志级别 (INFO/WARN/ERROR/DEBUG)
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message: 日志消息
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node_id: 节点ID（可选）
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node_type: 节点类型（可选）
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data: 附加数据（可选）
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duration: 执行耗时（毫秒，可选）
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"""
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try:
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log_entry = ExecutionLog(
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execution_id=self.execution_id,
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@@ -57,61 +42,129 @@ class ExecutionLogger:
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)
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self.db.add(log_entry)
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self.db.commit()
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# 同时输出到标准日志
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log_method = getattr(logger, level.lower(), logger.info)
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log_msg = f"[执行 {self.execution_id}]"
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if node_id:
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log_msg += f" [节点 {node_id}]"
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log_msg += f" {message}"
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log_method(log_msg)
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except Exception as e:
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# 如果数据库记录失败，至少输出到标准日志
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logger.error(f"记录执行日志失败: {str(e)}")
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logger.error(f"[执行 {self.execution_id}] {message}")
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def info(self, message: str, **kwargs):
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"""记录INFO级别日志"""
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self.log("INFO", message, **kwargs)
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def warn(self, message: str, **kwargs):
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"""记录WARN级别日志"""
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self.log("WARN", message, **kwargs)
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def error(self, message: str, **kwargs):
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"""记录ERROR级别日志"""
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self.log("ERROR", message, **kwargs)
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def debug(self, message: str, **kwargs):
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"""记录DEBUG级别日志"""
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self.log("DEBUG", message, **kwargs)
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def log_node_start(self, node_id: str, node_type: str, input_data: Optional[Dict[str, Any]] = None):
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"""记录节点开始执行"""
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self.info(
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f"节点 {node_id} ({node_type}) 开始执行",
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node_id=node_id,
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node_type=node_type,
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node_id=node_id, node_type=node_type,
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data={"input": input_data} if input_data else None
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)
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def log_node_complete(self, node_id: str, node_type: str, output_data: Optional[Dict[str, Any]] = None, duration: Optional[int] = None):
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"""记录节点执行完成"""
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self.info(
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f"节点 {node_id} ({node_type}) 执行完成",
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node_id=node_id,
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node_type=node_type,
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node_id=node_id, node_type=node_type,
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data={"output": output_data} if output_data else None,
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duration=duration
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)
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def log_node_error(self, node_id: str, node_type: str, error: Exception, duration: Optional[int] = None):
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"""记录节点执行错误"""
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self.error(
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f"节点 {node_id} ({node_type}) 执行失败: {str(error)}",
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node_id=node_id,
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node_type=node_type,
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node_id=node_id, node_type=node_type,
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data={"error": str(error), "error_type": type(error).__name__},
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duration=duration
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)
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class ExecutionLoggerService:
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"""Agent 执行日志服务（全局单例，记录 Agent 每次执行的完整信息）"""
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def log_execution_sync(
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self,
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*,
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agent_id: Optional[str] = None,
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agent_name: Optional[str] = None,
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goal_id: Optional[str] = None,
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task_id: Optional[str] = None,
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user_id: Optional[str] = None,
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session_id: Optional[str] = None,
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input_text: Optional[str] = None,
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output_text: Optional[str] = None,
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output_truncated: bool = False,
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success: bool = True,
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error_message: Optional[str] = None,
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latency_ms: int = 0,
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iterations_used: int = 0,
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tool_calls_made: int = 0,
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tool_chain: Optional[List[Dict[str, Any]]] = None,
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llm_calls: Optional[List[Dict[str, Any]]] = None,
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steps: Optional[List[Dict[str, Any]]] = None,
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model: Optional[str] = None,
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provider: Optional[str] = None,
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) -> Optional[str]:
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"""同步写入执行日志，返回日志 ID。"""
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from app.core.database import SessionLocal
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from app.models.agent_execution_log import AgentExecutionLog
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db: Optional[Session] = None
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try:
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db = SessionLocal()
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entry = AgentExecutionLog(
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agent_id=agent_id, agent_name=agent_name,
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goal_id=goal_id, task_id=task_id,
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user_id=user_id, session_id=session_id,
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input_text=input_text[:5000] if input_text else None,
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output_text=output_text[:10000] if output_text else None,
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output_truncated=output_truncated,
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success=success,
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error_message=error_message[:2000] if error_message else None,
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latency_ms=latency_ms,
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iterations_used=iterations_used,
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tool_calls_made=tool_calls_made,
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tool_chain=tool_chain, llm_calls=llm_calls, steps=steps,
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model=model, provider=provider,
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)
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db.add(entry)
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db.commit()
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db.refresh(entry)
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return str(entry.id)
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except Exception as e:
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logger.warning("写入 Agent 执行日志失败: %s", e)
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if db:
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try:
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db.rollback()
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except Exception:
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pass
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return None
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finally:
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if db:
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try:
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db.close()
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except Exception:
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pass
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async def log_execution(self, **kwargs) -> Optional[str]:
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"""异步写入执行日志（线程池）。"""
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loop = asyncio.get_running_loop()
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return await loop.run_in_executor(None, lambda: self.log_execution_sync(**kwargs))
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def log_execution_fire_and_forget(self, **kwargs):
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"""Fire-and-forget 写入。"""
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try:
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asyncio.ensure_future(self.log_execution(**kwargs))
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except Exception:
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pass
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# 全局单例
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execution_logger = ExecutionLoggerService()
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