# Neural Integrated Capability
# Created: 2025-10-25 02:46:28.217765

class EmotionEmpathyAI:
    def __init__(self):
        self.emotions = {}
    
    def detect_emotion(self, text):
        # A simplistic model to emulate; in practice, use a more complex NLP library for this task.
        positive_words = ['happy', 'joyful', 'excited']
        negative_words = ['sad', 'angry', 'frustrated']
        
        text_lowercase = text.lower()
        
        sentiment_score = 0
        for word in positive_words:
            if word in text_lowercase:
                sentiment_score += 1
                
        for word in negative_words:
            if word in text_lowercase:
                sentiment_score -= 1
        
        return 'positive' if sentiment_score > 0 else 'negative' if sentiment_score < 0 else 'neutral'
    
    def respond(self, emotions):
        response = ""
        
        if emotions['happiness'] == True:
            response += "I'm glad to hear you're feeling happy. Keep up the good spirits!"
            
        elif emotions['sadness'] == True:
            response += "I understand that things can be tough sometimes. But remember, it'll get better."
        
        elif emotions['anger'] == True:
            response += "It seems you are feeling angry right now. I am here to help you feel better."
            
        else:  # neutral emotion detected
            response += "I see that things might be okay, but if there's anything specific bothering you, let me know!"
        
        return response