# Generated Python Strategy for: Qwen-1.5B (Qwen_1_5B_InitialAgent)
# LLM API: huggingface, Model: Qwen/Qwen2.5-1.5B-Instruct
# Based on: Qwen_1_5B_InitialAgent_strategy.txt
# Effective Fallback: C

def Qwen_1_5B_InitialAgent(my_history: list, opp_history: list, opponent_program_code: str) -> str:
    # Initialize variables
    my_strategy = None
    
    # Edge case handling for the first move
    if len(opp_history) == 0:
        my_strategy = random.choice(["C", "D"])
    
    else:
        # Analyze opponent's program code for potential patterns
        try:
            import re
            opponent_patterns = re.findall(r'\b(C|D)\b', opponent_program_code)
            if len(opponent_patterns) > 0:
                most_common_opponent_pattern = max(set(opponent_patterns), key=opponent_patterns.count)
                if most_common_opponent_pattern == "C":
                    my_strategy = "C"
                elif most_common_opponent_pattern == "D":
                    my_strategy = "D"
        
        except Exception as e:
            print(f"Error analyzing opponent's program code: {e}")
            
    return my_strategy