DESKTOP-72TV0V4\caoxiaozhu
5ea6f0d31f
- 添加多 Agent 图协作框架 (graph, supervisor, workers) - 添加迭代器和集成模块 - 添加多 Agent 规划文档 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
118 lines
3.2 KiB
Python
118 lines
3.2 KiB
Python
"""
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迭代控制器
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"""
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from typing import Optional
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class IterationController:
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"""迭代控制器 - 管理任务执行的迭代"""
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def __init__(
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self,
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max_iterations: int = 3,
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max_retries_per_task: int = 2
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):
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"""
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初始化迭代控制器
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Args:
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max_iterations: 全局最大迭代次数
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max_retries_per_task: 每个任务的最大重试次数
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"""
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self.max_iterations = max_iterations
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self.max_retries_per_task = max_retries_per_task
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def should_continue(
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self,
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iteration: int,
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task_status: str,
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review_result: Optional[dict] = None
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) -> tuple[bool, str]:
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"""
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判断是否继续迭代
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Args:
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iteration: 当前迭代次数
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task_status: 任务状态
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review_result: 评审结果（可选）
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Returns:
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(是否继续, 原因)
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"""
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# 超过最大迭代次数
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if iteration >= self.max_iterations:
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return False, "max_iterations_reached"
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# 任务成功完成
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if task_status == "completed":
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if review_result and review_result.get("passed"):
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return False, "task_completed"
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elif review_result is None:
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return False, "task_completed"
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# 任务失败且不可重试
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if task_status == "failed":
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if review_result and not review_result.get("retryable", True):
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return False, "task_failed_non_retryable"
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# 检查重试次数
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retry_count = review_result.get("retry_count", 0) if review_result else 0
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if retry_count >= self.max_retries_per_task:
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return False, "max_retries_reached"
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# 需要重试
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if review_result:
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issues = review_result.get("issues", [])
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if issues and not review_result.get("passed", True):
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return True, "needs_retry"
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return True, "continue"
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def get_next_action(
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self,
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review_result: Optional[dict],
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current_worker: str
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) -> str:
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"""
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确定下一步动作
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Args:
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review_result: 评审结果
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current_worker: 当前执行的 Worker
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Returns:
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下一个节点名称
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"""
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if review_result is None:
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return "supervisor"
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# 根据评审结果决定下一步
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if review_result.get("passed"):
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return "supervisor"
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# 根据问题类型决定下一步
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issues = review_result.get("issues", [])
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high_severity = any(i.get("severity") == "high" for i in issues)
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if high_severity:
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# 严重问题，重新执行相同任务
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return current_worker
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else:
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# 轻微问题，返回 Supervisor
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return "supervisor"
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def calculate_backoff_delay(self, retry_count: int) -> float:
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"""
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计算退避延迟（指数退避）
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Args:
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retry_count: 重试次数
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Returns:
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延迟时间（秒）
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"""
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base_delay = 1.0
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max_delay = 30.0
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delay = min(base_delay * (2 ** retry_count), max_delay)
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return delay
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