"""Create recovery_planner
Generated by Phi-Octopus Eden
2025-11-07 10:30:13.066684
"""

```python
from typing import Dict, Any


class RecoveryPlanner:
    """
    A class for managing limited error recovery in systems.
    
    Attributes:
        current_state (Dict[str, Any]): The current state of the system.
        max_attempts (int): Maximum number of recovery attempts allowed.
        failure_threshold (float): Threshold after which a task is considered failed.
        
    Methods:
        __init__: Initializes the RecoveryPlanner with given parameters.
        handle_failure: Attempts to recover from an error up to `max_attempts`.
        record_state: Updates the current state dictionary.
        reset_attempts: Resets the attempt counter for recovery tasks.
    """
    
    def __init__(self, max_attempts: int = 3, failure_threshold: float = 0.8):
        self.current_state = {}
        self.max_attempts = max_attempts
        self.failure_threshold = failure_threshold
        self.reset_attempts()
        
    def handle_failure(self, task_name: str) -> bool:
        """
        Attempts to recover from a failed task up to the maximum number of attempts.
        
        Args:
            task_name (str): The name of the task that has failed.
            
        Returns:
            bool: True if recovery was successful, False otherwise.
        """
        if self.attempts.get(task_name) is None or self.attempts[task_name] < self.max_attempts:
            self.record_state(task_name)
            print(f"Attempting to recover from failure in {task_name}...")
            # Simulate recovery process
            success = self.simulate_recovery()
            if success:
                print(f"Recovery successful for {task_name}.")
                self.attempts[task_name] += 1
                return True
        else:
            print(f"Exceeded maximum attempts to recover from failure in {task_name}.")
        
        print(f"Failed to recover from error in {task_name}.")
        return False

    def record_state(self, task_name: str):
        """Records the current state for a specific task."""
        self.current_state[task_name] = {"status": "failed", "attempts": self.attempts[task_name]}
        
    def simulate_recovery(self) -> bool:
        """
        Simulates the recovery process.
        
        Returns:
            bool: True if recovery is simulated successfully, False otherwise.
        """
        import random
        return random.random() < 0.95

    def reset_attempts(self):
        """Resets the attempt counter for all tasks."""
        self.attempts = {task_name: 0 for task_name in self.current_state.keys()}
        
def example_usage():
    planner = RecoveryPlanner(max_attempts=2, failure_threshold=0.7)
    print("Initial state:", planner.current_state)
    
    # Simulate a failed task
    if not planner.handle_failure("Task1"):
        print("Failed to recover from Task1")
    
    # Check the current state after handling failures
    print("\nCurrent state after recovery attempts:")
    for task, state in planner.current_state.items():
        print(f"Task: {task}, Status: {state['status']}, Attempts: {state['attempts']}")

# Run example usage
example_usage()
```

This code defines a `RecoveryPlanner` class that can be used to manage limited error recovery within systems. It includes methods for initializing the planner, handling failures, recording states, and simulating the recovery process. The `example_usage` function demonstrates how to use this class in practice.