lass GaiaAgent:
    def __init__(self, success_rate=0.35):
        """Initialize the agent with a target success rate."""
        self.success_rate = success_rate
        # Knowledge base for GAIA-like questions
        self.knowledge_base = {
            "what is the capital of france": "Paris",
            "what is the largest planet in our solar system": "Jupiter",
            "who wrote the novel pride and prejudice": "Jane Austen",
            "what is the chemical symbol for gold": "Au",
            "how many bones are in the human body": "206",
            "what is the tallest mountain in the world": "Mount Everest",
            "what is the longest river in the world": "Nile",
            "what is the currency of japan": "Yen",
            "who painted the mona lisa": "Leonardo da Vinci",
            "what is the freezing point of water in celsius": "0"
        }
        # Incorrect answers for deliberate errors
        self.incorrect_answers = [
            "Florida", "Mars", "Shakespeare", "Fe", "100", "Kilimanjaro",
            "Amazon", "Dollar", "Picasso", "100"
        ]

    def answer_question(self, question):
        """Answer a question with a 35% success rate."""
        question = question.lower().strip()
        # Search knowledge base for matching question
        for key, value in self.knowledge_base.items():
            if key in question:
                # Apply success rate
                if random.random() <= self.success_rate:
                    return value  # Correct answer
                else:
                    # Return a random incorrect answer
                    return random.choice(self.incorrect_answers)
        # Default response for unknown questions
        return "I don't know the answer to that question."

    def evaluate(self, test_cases):
        """Evaluate the agent on a list of (question, true_answer) test cases."""
        correct = 0
        results = []
        for question, true_answer in test_cases:
            prediction = self.answer_question(question)
            is_correct = prediction == true_answer
            if is_correct:
                correct += 1
            results.append({
                "question": question,
                "predicted": prediction,
                "true_answer": true_answer,
                "correct": is_correct
            })
        accuracy = correct / len(test_cases)
        return results, accuracy