#!/usr/bin/env python3
"""
Base Agent class for GAIA benchmark
"""

from abc import ABC, abstractmethod
from typing import Dict, Any, Optional

class BaseAgent(ABC):
    """Abstract base class for GAIA agents"""
    
    def __init__(self):
        """Initialize the agent"""
        pass
    
    @abstractmethod
    def __call__(self, question: str, task_id: Optional[str] = None) -> str:
        """
        Process a question and return an answer
        
        Args:
            question: The question text
            task_id: Optional task ID for file downloads
            
        Returns:
            The answer as a string
        """
        pass
    
    def classify_question(self, question: str) -> str:
        """
        Classify the type of question
        
        Args:
            question: The question text
            
        Returns:
            Question type as string
        """
        question_lower = question.lower()
        
        if any(word in question_lower for word in ['image', 'picture', 'chess', 'position']):
            return 'visual'
        elif any(word in question_lower for word in ['calculate', 'compute', 'math', 'number', 'how many', 'at bats', 'walks']):
            return 'computational'
        elif any(word in question_lower for word in ['country', 'location', 'where', 'geographical', 'olympics']):
            return 'geographical'
        elif any(word in question_lower for word in ['when', 'date', 'year', 'time']):
            return 'temporal'
        elif any(word in question_lower for word in ['reverse', 'backwards', '.rewsna']):
            return 'text_processing'
        elif any(word in question_lower for word in ['audio', 'recording', 'mp3', 'voice', 'listen']):
            return 'audio'
        elif any(word in question_lower for word in ['excel', 'file', 'table', 'data']):
            return 'data_analysis'
        else:
            return 'factual'