from typing import Dict, Any
from pathlib import Path
from dotenv import load_dotenv
from huggingface_hub import login
import os

def validate_model_path(model_path: Path) -> bool:
    """Validate that a model path exists and contains necessary files"""
    if not model_path.exists():
        return False
    required_files = ['config.json', 'pytorch_model.bin']
    return all((model_path / file).exists() for file in required_files)

def validate_generation_params(params: Dict[str, Any]) -> Dict[str, Any]:
    """Validate and normalize generation parameters"""
    validated = params.copy()

    # Ensure temperature is within bounds
    if 'temperature' in validated:
        validated['temperature'] = max(0.0, min(2.0, validated['temperature']))

    # Ensure max_new_tokens is reasonable
    if 'max_new_tokens' in validated:
        validated['max_new_tokens'] = max(1, min(4096, validated['max_new_tokens']))

    return validated

def validate_hf(setup_logger, config):
    """
    Validate Hugging Face authentication.
    Checks for .env file, loads environment variables, and attempts HF login if token exists.
    """
    logger = setup_logger(config, "hf_validation")

    # Check for .env file
    env_path = Path('.env')
    if env_path.exists():
        logger.info("Found .env file, loading environment variables")
        load_dotenv()
    else:
        logger.warning("No .env file found. Fine if you're on Huggingface, but you need one to run locally on your PC.")

    # Check for HF token
    hf_token = os.getenv('HF_TOKEN')
    if not hf_token:
        logger.error("No HF_TOKEN found in environment variables")
        return False

    try:
        # Attempt login
        login(token=hf_token)
        logger.info("Successfully authenticated with Hugging Face")
        return True
    except Exception as e:
        logger.error(f"Failed to authenticate with Hugging Face: {str(e)}")
        return False