"""
Abstract base class for all LLM implementations.
"""

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


class BaseLLM(ABC):
    """Abstract interface for LLM models."""
    
    def __init__(self, name: str, model_id: str):
        self.name = name
        self.model_id = model_id
        self._initialized = False
    
    @property
    def is_initialized(self) -> bool:
        return self._initialized
    
    @abstractmethod
    async def initialize(self) -> None:
        """Initialize the model. Must be called before generate()."""
        pass
    
    @abstractmethod
    async def generate(
        self,
        prompt: str = None,
        chat_messages: List[Dict[str, str]] = None,
        max_new_tokens: int = 150,
        temperature: float = 0.7,
        top_p: float = 0.9,
        **kwargs
    ) -> str:
        """
        Generate text from prompt or chat messages.
        
        Args:
            prompt: Raw text prompt
            chat_messages: List of {"role": "...", "content": "..."} messages
            max_new_tokens: Maximum tokens to generate
            temperature: Sampling temperature
            top_p: Nucleus sampling parameter
            
        Returns:
            Generated text string
        """
        pass
    
    @abstractmethod
    def get_info(self) -> Dict[str, Any]:
        """Return model information for /models endpoint."""
        pass