def clean_answer(answer: any) -> str:
        """
        Clean up the answer to remove common prefixes and formatting
        that models often add but that can cause exact match failures.
        
        Args:
            answer: The raw answer from the model
            
        Returns:
            The cleaned answer as a string
        """
        # Convert non-string types to strings
        if not isinstance(answer, str):
            # Handle numeric types (float, int)
            if isinstance(answer, float):
                # Format floating point numbers properly
                # Check if it's an integer value in float form (e.g., 12.0)
                if answer.is_integer():
                    formatted_answer = str(int(answer))
                else:
                    # For currency values that might need formatting
                    if abs(answer) >= 1000:
                        formatted_answer = f"${answer:,.2f}"
                    else:
                        formatted_answer = str(answer)
                return formatted_answer
            elif isinstance(answer, int):
                return str(answer)
            else:
                # For any other type
                return str(answer)
        
        # Now we know answer is a string, so we can safely use string methods
        # Normalize whitespace
        answer = answer.strip()
        
        # Remove common prefixes and formatting that models add
        prefixes_to_remove = [
            "The answer is ", 
            "Answer: ",
            "Final answer: ",
            "The result is ",
            "To answer this question: ",
            "Based on the information provided, ",
            "According to the information: ",
        ]
        
        for prefix in prefixes_to_remove:
            if answer.startswith(prefix):
                answer = answer[len(prefix):].strip()
        
        # Remove quotes if they wrap the entire answer
        if (answer.startswith('"') and answer.endswith('"')) or (answer.startswith("'") and answer.endswith("'")):
            answer = answer[1:-1].strip()
        
        return answer



# Clean the answer
        clean_text = clean_answer(llm_response.content)