class FECController:
    def __init__(self):
        pass

    def generate_prompt(self, final_uesp):
        # Validate required keys
        required_keys = [
            'emotion_family',
            'primary_emotion_code',
            'emotion_arc_trajectory',
            'resonance_pattern'
        ]

        for key in required_keys:
            if key not in final_uesp:
                raise KeyError(f"Missing required key: {key}")

        # Map human-readable emotion label from code
        emotion_code = final_uesp['primary_emotion_code']
        if emotion_code.startswith("VAR-"):
            emotion_label = emotion_code.replace("VAR-", "").split('-')[0].title()
        elif emotion_code.startswith("FAM-"):
            emotion_label = emotion_code.replace("FAM-", "").title()
        else:
            emotion_label = "Unknown"

        # Base fields
        arc = final_uesp['emotion_arc_trajectory']
        resonance = final_uesp['resonance_pattern']

        # Optional fields with fallbacks
        blend_states = final_uesp.get('blend_states', 'None detected')
        response_strategy = final_uesp.get('response_strategy', 'RSM-DEFAULT')
        tone_classification = final_uesp.get('tone_classification', 'TBD')

        # Build Fusion Prompt
        fusion_prompt = f"""
Contextual Emotional State:

- Primary Emotion: {emotion_label}
- Emotional Arc: {arc}
- Resonance: {resonance}
- Tone: {tone_classification}
- Blend States: {blend_states}
- Intervention Strategy: {response_strategy}

Empathic Objective:
Align your response tone and content with the above emotional context. Prioritize emotional authenticity, HEART-compliant care, and safety. Do not merely reflect emotion — respond in an emotionally aligned and supportive manner that honors the user’s lived experience.

HEART Compliance: Response must align with HEART™ ethical principles — transparency, alignment, contextuality, traceability, and emotional safety.
""".strip()

        return fusion_prompt