stack/eval/benchmarks/bigbench.py

"""
BIG-Bench Hard benchmark implementation
"""

from typing import Dict, Any, List

class BIGBenchHard:
    def __init__(self):
        self.benchmark_name = "BIG-Bench Hard"
        self.test_cases = self._load_test_cases()
        self.total_cases = len(self.test_cases)
    
    def _load_test_cases(self) -> List[Dict]:
        """Load BIG-Bench Hard test cases"""
        # This would typically load from a file or API
        # For now, return a placeholder structure
        return [
            {
                "description": "Logical reasoning problem",
                "prompt": "If all cats are mammals and all mammals are animals, are all cats animals?",
                "answer": "Yes"
            },
            {
                "description": "Common sense reasoning",
                "prompt": "What happens when you drop a glass on a hard floor?",
                "answer": "It breaks"
            },
            {
                "description": "Mathematical reasoning",
                "prompt": "If a train travels 60 miles in 1.5 hours, what is its average speed?",
                "answer": "40 mph"
            }
            # Add more test cases here
        ]
    
    def evaluate(self, model_name: str) -> Dict[str, Any]:
        """Evaluate model against BIG-Bench Hard benchmark"""
        correct_answers = 0
        
        for i, test_case in enumerate(self.test_cases):
            prompt = test_case["prompt"]
            
            # Simulate model response
            response = self._generate_response(model_name, prompt)
            
            # Check if answer is correct
            if self._check_answer(response, test_case["answer"]):
                correct_answers += 1
        
        accuracy = correct_answers / self.total_cases if self.total_cases > 0 else 0
        
        return {
            "pass_at_1": correct_answers,
            "pass_at_3": correct_answers,  # Simplified for now
            "pass_at_5": correct_answers,  # Simplified for now
            "total_cases": self.total_cases,
            "accuracy": accuracy,
            "benchmark": self.benchmark_name
        }
    
    def _generate_response(self, model_name: str, prompt: str) -> str:
        """Generate response using the specified model"""
        # This would call the actual model API
        # For now, return a placeholder
        return "Yes"
    
    def _check_answer(self, response: str, correct_answer: str) -> bool:
        """Check if the response matches the correct answer"""
        try:
            response = response.strip().lower()
            correct_answer = correct_answer.strip().lower()
            
            # Simple string comparison for now
            return response == correct_answer
            
        except Exception as e:
            return False


if __name__ == "__main__":
    benchmark = BIGBenchHard()
    results = benchmark.evaluate("test_model")
    print(f"BIG-Bench Hard Results: {results}")