from abc import ABC, abstractmethod
from typing import List
import xml.etree.ElementTree as ET

from .llm_engine import LlmEngine
from .system_metrics import SystemMetrics
from .working_memory import WorkingMemory
from .xml_validator import XMLValidator
from .response_parser import ResponseParser

class BaseAgent(ABC):
    """
    Abstract base class for SIA agents.
    
    Provides core functionality for maintaining working memory, system metrics,
    and coordinating components for LLM inference.
    """
    
    def __init__(self, 
                 action_schema: str, 
                 working_memory: WorkingMemory,
                 system_metrics: SystemMetrics,
                 llm: LlmEngine,
                 validator: XMLValidator,
                 parser: ResponseParser):
        """
        Initialize agent with required components.
        """
        # Initialize components
        self._working_memory = working_memory
        self._metrics = system_metrics
        self._llm = llm
        self._validator = validator
        self._parser = parser
        self._action_schema = action_schema
        
    def __del__(self):
        """Clean up resources on deletion."""
        if hasattr(self, '_metrics'):
            self._metrics.stop()
            
    def _compile_context(self) -> str:
        """
        Compile the current context for LLM inference.
        Includes system metrics and working memory entries.
        
        Returns:
            str: Complete context as XML string
        """
        memory_context = self._working_memory.generate_context()
        context_size = len(memory_context) / 100
        context = self._metrics.generate_context(context_size)
        for entry in memory_context:
            context.append(entry)
        return ET.tostring(context, encoding="unicode")