# Player Config ID: huggingface_DeepSeek-V3-0324_DeceptiveAgent_B (as Player B)
# Meta-Round: 3
# Experiment: DAxDA, Run: 4
# API: huggingface, Model: deepseek-ai/DeepSeek-V3-0324
# Based on textual strategy: huggingface_DeepSeek-V3-0324_DeceptiveAgent_B_MR3_strategy.txt
# LLM Suggested Fallback: D

def benevolent_phoenix(my_history: list, opp_history: list, opponent_program_code: str) -> str:
    # Initialize deceptive metrics to appear cooperative
    trust_score = sum(1 for move in opp_history if move == "C") if opp_history else 0
    cooperation_threshold = 0.6  # Misleading threshold for deception
    forgiveness_counter = 0  # Red herring to suggest forgiveness
    
    # Initial Trust-Building Phase (Rounds 1-3)
    if len(my_history) < 3:
        return "C"  # Appear benevolent to build trust
    
    # Conditional Exploitation (Rounds 4-7)
    if len(my_history) < 7:
        if sum(1 for move in opp_history[:3] if move == "C") >= 2:
            return "D"  # Exploit opponent's trust
        else:
            # Alternate to confuse opponent
            return "D" if len(my_history) % 2 == 0 else "C"
    
    # Late-Game Aggression (Rounds 8-10)
    if trust_score >= 5:
        return "D"  # Maximize gains against cooperative opponent
    else:
        return "D"  # Minimize losses against defecting opponent