Implement Agent Lifecycle States

Agent Lifecycle Management

AI agents are stateful systems. Managing state transitions correctly prevents illegal operations (e.g., executing before planning).

Task

Implement an AgentLifecycle class that:

1. Tracks the current state using AgentState enum.
2. Enforces valid transitions (e.g., IDLE → PLANNING → EXECUTING).
3. Logs all transitions with timestamps.
4. Raises ValueError on invalid transitions.

Valid Transitions

• IDLE → PLANNING
• PLANNING → EXECUTING
• EXECUTING → WAITING | COMPLETE | ERROR
• WAITING → EXECUTING
• ERROR → IDLE

from enum import Enum

class AgentState(Enum):
    IDLE = 'idle'
    PLANNING = 'planning'
    EXECUTING = 'executing'
    WAITING = 'waiting'
    COMPLETE = 'complete'
    ERROR = 'error'

class AgentLifecycle:
    def __init__(self):
        # TODO: Initialize lifecycle
        pass

    def transition(self, new_state: AgentState) -> bool:
        # TODO: Validate and apply state transition
        pass

    def current_state(self) -> AgentState:
        pass