"""
SelfImprovementCapability
Generated by Eden via recursive self-improvement
2025-10-28 08:10:15.735927
"""

class SelfImprovementCapability:
    """
    A capability that helps the AI system analyze and improve its own performance based on user feedback.
    
    Attributes:
        improvement_score (float): A score between 0-1 representing overall improvement potential
        areas_for_improvement (dict): Dictionary of problem areas and suggested improvements
        feedback_history (list): List of past feedback comments and suggestions
    """

    def __init__(self):
        self.improvement_score = 0.85  # Starting score based on initial capabilities
        self.areas_for_improvement = {}
        self.feedback_history = []

    def accept_feedback(self, feedback: str) -> None:
        """
        Processes user feedback and updates areas for improvement.
        
        Args:
            feedback (str): The feedback or suggestion provided by the user
        """
        self.feedback_history.append(feedback)
        # Analyze feedback for positive reinforcement and constructive criticism
        if "good" in feedback.lower() or "well done" in feedback.lower():
            self._update_improvement_score(increment=True)
        else:
            self._analyze_critical_feedback(feedback)

    def _analyze_critical_feedback(self, feedback: str) -> None:
        """
        Internal method to process and categorize critical feedback.
        """
        # Identify problem areas
        for area in ["response time", "accuracy", "clarity"]:
            if area in feedback.lower():
                self.areas_for_improvement[area] = self._get_improvement_suggestions(feedback)

    def _update_improvement_score(self, increment: bool = False) -> None:
        """
        Updates the improvement score based on feedback analysis.
        """
        adjustment = 0.02 if increment else -0.01
        self.improvement_score = min(1.0, max(0.0, self.improvement_score + adjustment))

    def _get_improvement_suggestions(self, feedback: str) -> list:
        """
        Generates improvement suggestions from feedback.
        
        Args:
            feedback (str): The feedback string to analyze
            
        Returns:
            list: A list of actionable suggestions
        """
        suggestions = []
        # Simple NLP-like processing to extract action items
        if "slower" in feedback.lower():
            suggestions.append("Optimize response generation")
        elif "unclear" in feedback.lower():
            suggestions.append("Improve explanation clarity")
        return suggestions

    def get_recommendations(self) -> dict:
        """
        Returns current recommendations for improvement based on collected feedback.
        
        Returns:
            dict: A dictionary of problem areas and suggested improvements
        """
        return {
            "improvement_score": self.improvement_score,
            "areas_for_improvement": self.areas_for_improvement
        }

    def clear_feedback(self) -> None:
        """
        Clears all collected feedback and improvement tracking.
        """
        self.feedback_history = []
        self.areas_for_improvement = {}
        self.improvement_score = 0.85  # Reset to baseline score

# Example usage:
if __name__ == "__main__":
    improver = SelfImprovementCapability()
    
    print("Current improvement score:", improver.improvement_score)
    print("Initial areas for improvement:", improver.areas_for_improvement)
    
    improver.accept_feedback("Your responses are clear and helpful.")
    improver.accept_feedback("But sometimes the answers could be more accurate.")
    improver.accept_feedback("The response time is a bit slow for urgent queries.")
    
    recommendations = improver.get_recommendations()
    print("\nImprovement Recommendations:", recommendations)
    
    improver.clear_feedback()
    print("\nCleared feedback. Current state:", vars(improver))