Spaces:
Running
Running
| import logging | |
| import time | |
| import threading | |
| """ | |
| modules/autonomy_executor.py — F.R.I.D.A.Y OMEGA Background Task Executor | |
| Manages autonomous, long-running multi-step goals without blocking the main event loop. | |
| """ | |
| _running_goals = {} | |
| def start_goal(goal_id: str, description: str, steps: list): | |
| """ | |
| Start tracking a new long-term goal. | |
| """ | |
| _running_goals[goal_id] = { | |
| 'description': description, | |
| 'steps': steps, | |
| 'status': 'started', | |
| 'start_time': time.time(), | |
| 'completed_steps': [] | |
| } | |
| logging.getLogger(__name__).info(f"[AUTONOMY] Started goal {goal_id}: {description}") | |
| # In a real implementation, this would spin up a background thread or async task | |
| # to execute the steps sequentially. For now, we mock the execution. | |
| def _execute(): | |
| for i, step in enumerate(steps): | |
| time.sleep(2) # Simulate work | |
| _running_goals[goal_id]['completed_steps'].append(step) | |
| logging.getLogger(__name__).info(f"[AUTONOMY] Completed step {i+1} for goal {goal_id}") | |
| _running_goals[goal_id]['status'] = 'completed' | |
| logging.getLogger(__name__).info(f"[AUTONOMY] Goal {goal_id} completed.") | |
| t = threading.Thread(target=_execute, daemon=True) | |
| t.start() | |
| def get_goal_status(goal_id: str) -> dict: | |
| """Return current status of a tracked goal.""" | |
| return _running_goals.get(goal_id, {}) | |
| def get_all_goals() -> dict: | |
| """Return all tracked goals.""" | |
| return _running_goals | |