"""
Utilities for safely accessing configuration values regardless of whether they're stored 
in dictionaries or objects.
"""

def safe_get_config(config_obj, key, default=None):
    """
    Safely get a configuration value regardless of whether the config object is a dictionary or object.
    
    Args:
        config_obj: Configuration object (dict or object with attributes)
        key: Key or attribute name to access
        default: Default value to return if key/attribute doesn't exist
        
    Returns:
        The value of the key/attribute, or default if not found
    """
    if config_obj is None:
        return default
        
    if isinstance(config_obj, dict):
        return config_obj.get(key, default)
    
    return getattr(config_obj, key, default)

def get_model_name(config_obj):
    """
    Gets model name from config with proper fallbacks.
    
    Args:
        config_obj: Configuration object
        
    Returns:
        Model name string
    """
    transformer_config = safe_get_config(config_obj, "TRANSFORMER_CONFIG", {})
    return safe_get_config(transformer_config, "MODEL_NAME", "bert-base-uncased")

def get_embedding_model(config_obj):
    """
    Creates or retrieves an embedding model based on configuration.
    
    Args:
        config_obj: Configuration object
        
    Returns:
        Embedding model instance
    """
    from utils.transformer_utils import get_sentence_transformer
    model_name = get_model_name(config_obj)
    return get_sentence_transformer(model_name)

"""Utilities for configuration validation and fixes"""
import os
import logging
from typing import Dict, Any

logger = logging.getLogger(__name__)

def validate_config(config: Any) -> None:
    """Validate and fix configuration objects to prevent errors"""
    
    # Fix TRANSFORMER_CONFIG if it exists
    if hasattr(config, 'TRANSFORMER_CONFIG'):
        tc = config.TRANSFORMER_CONFIG
        
        # If it's a dict, make sure it has necessary values
        if isinstance(tc, dict):
            # Ensure required keys have default values
            defaults = {
                "MAX_SEQ_LENGTH": 512,
                "MODEL_NAME": "bert-base-uncased",
                "NUM_LAYERS": 6,
                "EMBEDDING_DIM": 768,
                "NUM_HEADS": 12,
                "HIDDEN_DIM": 768,
                "DROPOUT": 0.1,
                "POOLING_MODE": "mean"
            }
            
            # Add any missing defaults
            for key, value in defaults.items():
                if key not in tc:
                    tc[key] = value
                    logger.info(f"Added default {key}={value} to TRANSFORMER_CONFIG")
    
    # Check data directories
    data_dir = getattr(config, "DATA_DIR", os.environ.get("TLM_DATA_DIR", "/tmp/tlm_data"))
    os.makedirs(data_dir, exist_ok=True)
    
    # Check model directory
    model_dir = getattr(config, "MODEL_DIR", os.path.join(data_dir, "models"))
    os.makedirs(model_dir, exist_ok=True)
    
    logger.info("Configuration validated and fixed")