592bca4f39
- 4.1 Fallback chain: LLM fallback_llm config in AgentLLMConfig, retry with alternate model on API failure; Agent fallback_agent in DAG nodes - 4.2 Knowledge sharing: GlobalKnowledge model with embedding-based semantic search, auto-extraction of tool names as tags after execution - 4.3 Async execution: execute_agent_task fully implemented with AgentRuntime, scheduler dual-path for workflow/non-workflow agents Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
148 lines
4.7 KiB
Python
148 lines
4.7 KiB
Python
"""Agent 定时任务服务：cron 解析、执行触发、下次执行时间计算"""
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from __future__ import annotations
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import logging
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from datetime import datetime, timezone, timedelta
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from typing import Optional
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from croniter import croniter
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from sqlalchemy.orm import Session
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from app.core.database import SessionLocal
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logger = logging.getLogger(__name__)
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def compute_next_run(cron_expression: str, after: Optional[datetime] = None) -> datetime:
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"""根据 cron 表达式计算下一次执行时间。
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Args:
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cron_expression: 标准 5 位 cron 表达式，如 "0 9 * * *"
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after: 从哪个时间点开始计算，默认为当前 UTC 时间
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Returns:
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下次执行的 UTC datetime
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"""
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base = after or datetime.now(timezone.utc)
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# croniter 需要以 datetime 对象作为基准
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base_naive = base.replace(tzinfo=None) if base.tzinfo else base
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cron = croniter(cron_expression, base_naive)
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next_dt = cron.get_next(datetime)
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return next_dt
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def create_execution_for_schedule(db: Session, schedule) -> Optional[str]:
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"""为定时任务创建 Execution 记录并投递 Celery 任务。
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Args:
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db: 数据库会话
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schedule: AgentSchedule ORM 对象
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Returns:
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创建的 execution_id，失败返回 None
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"""
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from app.models.execution import Execution
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from app.models.agent import Agent
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agent = db.query(Agent).filter(Agent.id == schedule.agent_id).first()
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if not agent:
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logger.warning("定时任务 %s 关联的 Agent %s 不存在", schedule.id, schedule.agent_id)
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return None
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# 创建执行记录（关联 schedule_id）
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execution = Execution(
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agent_id=schedule.agent_id,
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schedule_id=schedule.id,
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input_data={"message": schedule.input_message},
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status="pending",
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)
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db.add(execution)
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db.flush() # 获取 id
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try:
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if agent.workflow_config and agent.workflow_config.get("nodes"):
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# 有工作流配置：走完整工作流引擎
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from app.tasks.workflow_tasks import execute_workflow_task
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task = execute_workflow_task.delay(
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str(execution.id),
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f"agent_{schedule.agent_id}",
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agent.workflow_config,
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{"message": schedule.input_message},
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)
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else:
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# 无工作流配置：走简单 Agent 异步执行
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from app.tasks.agent_tasks import execute_agent_task
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task = execute_agent_task.delay(
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str(schedule.agent_id),
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{"message": schedule.input_message},
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)
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execution.task_id = task.id
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execution.status = "running"
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db.commit()
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logger.info(
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"定时任务 %s 已投递执行: execution=%s task=%s",
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schedule.id, execution.id, task.id,
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)
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return str(execution.id)
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except Exception as e:
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execution.status = "failed"
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execution.error_message = f"定时任务投递失败: {e!s}"
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db.commit()
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logger.warning("定时任务 %s 投递失败: %s", schedule.id, e)
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return str(execution.id)
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def check_and_run_due_schedules() -> int:
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"""检查所有启用的定时任务，执行到期的任务。
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被 Celery Beat 每分钟调用一次。
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Returns:
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本次触发的任务数
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"""
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from app.models.agent_schedule import AgentSchedule
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db: Optional[Session] = None
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try:
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db = SessionLocal()
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now = datetime.utcnow()
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due_schedules = (
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db.query(AgentSchedule)
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.filter(
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AgentSchedule.enabled == True, # noqa: E712
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AgentSchedule.next_run_at <= now,
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)
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.all()
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)
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triggered = 0
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for sched in due_schedules:
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try:
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# 创建执行记录
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create_execution_for_schedule(db, sched)
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# 更新定时任务状态
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sched.last_run_at = now
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sched.last_run_status = "success"
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# 计算下次执行时间
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sched.next_run_at = compute_next_run(sched.cron_expression, after=now)
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db.commit()
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triggered += 1
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logger.info(
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"定时任务触发完成: name=%s next_run=%s",
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sched.name, sched.next_run_at,
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)
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except Exception as e:
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logger.error("定时任务 %s 执行失败: %s", sched.id, e)
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sched.last_run_at = now
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sched.last_run_status = "failed"
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db.commit()
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return triggered
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except Exception as e:
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logger.error("检查定时任务失败: %s", e)
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return 0
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finally:
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if db:
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db.close()
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