"""LLM configuration settings."""
from dataclasses import dataclass
from typing import Optional, Dict, Any

@dataclass
class LLMConfig:
    provider: str
    model_name: str
    api_key: str
    api_base: Optional[str] = None
    additional_params: Optional[Dict[str, Any]] = None

class LLMProviderSettings:
    """Settings for different LLM providers."""
    
    OPENAI_SETTINGS = {
        'gpt-3.5-turbo-16k': {
            'provider': 'openai',
            'model_name': 'gpt-3.5-turbo-16k',
            'max_tokens': 16000,
            'temperature': 0.7,
        },
        'gpt-4': {
            'provider': 'openai',
            'model_name': 'gpt-4',
            'max_tokens': 8000,
            'temperature': 0.7,
        }
    }
    
    DEEPSEEK_SETTINGS = {
        'deepseek-chat': {
            'provider': 'deepseek',
            'model_name': 'deepseek-chat',
            'max_tokens': 8000,
            'temperature': 0.7,
            'api_base': 'https://api.deepseek.com/v1',  # Example API base, replace with actual
        }
    }
    
    @classmethod
    def get_config(cls, provider: str, model_name: str, api_key: str) -> LLMConfig:
        """Get LLM configuration for a specific provider and model."""
        if provider == 'openai':
            if model_name in cls.OPENAI_SETTINGS:
                settings = cls.OPENAI_SETTINGS[model_name]
                return LLMConfig(
                    provider=settings['provider'],
                    model_name=settings['model_name'],
                    api_key=api_key,
                    additional_params={
                        'max_tokens': settings['max_tokens'],
                        'temperature': settings['temperature']
                    }
                )
        elif provider == 'deepseek':
            if model_name in cls.DEEPSEEK_SETTINGS:
                settings = cls.DEEPSEEK_SETTINGS[model_name]
                return LLMConfig(
                    provider=settings['provider'],
                    model_name=settings['model_name'],
                    api_key=api_key,
                    api_base=settings['api_base'],
                    additional_params={
                        'max_tokens': settings['max_tokens'],
                        'temperature': settings['temperature']
                    }
                )
        
        raise ValueError(f"Unsupported provider '{provider}' or model '{model_name}'")

    @classmethod
    def list_available_models(cls):
        """List all available models and their providers."""
        models = {
            'openai': list(cls.OPENAI_SETTINGS.keys()),
            'deepseek': list(cls.DEEPSEEK_SETTINGS.keys())
        }
        return models