from typing import Optional, cast, TYPE_CHECKING, Literal, Dict, List, Tuple, Any
from langchain_core.language_models.chat_models import BaseChatModel
from langchain_openai import ChatOpenAI
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_core.callbacks import BaseCallbackHandler
from ea_chatbot.config import LLMConfig

def get_llm_model(config: LLMConfig, callbacks: Optional[List[BaseCallbackHandler]] = None) -> BaseChatModel:
    """
    Factory function to get a LangChain chat model based on configuration.
    
    Args:
        config: LLMConfig object containing model settings.
        callbacks: Optional list of LangChain callback handlers.
        
    Returns:
        Initialized BaseChatModel instance.
        
    Raises:
        ValueError: If the provider is not supported.
    """
    params = {
        "temperature": config.temperature,
        "max_tokens": config.max_tokens,
        **config.provider_specific
    }
    
    # Filter out None values to allow defaults to take over if not specified
    params = {k: v for k, v in params.items() if v is not None}

    if config.provider.lower() == "openai":
        return ChatOpenAI(model=config.model, callbacks=callbacks, **params)
    elif config.provider.lower() == "google" or config.provider.lower() == "google_genai":
        return ChatGoogleGenerativeAI(model=config.model, callbacks=callbacks, **params)
    else:
        raise ValueError(f"Unsupported LLM provider: {config.provider}")