import os
from pathlib import Path
from dotenv import load_dotenv

def load_environment_variables():
    """
    Load environment variables with proper priority:
    1. System environment variables (highest priority - for production/HF Spaces)
    2. .env file (fallback for local development)
    """
    # First check if we're in a production environment (HF Spaces, Docker, etc.)
    # by looking for common production indicators
    is_production = any([
        os.getenv("SPACE_ID"),  # Hugging Face Spaces
        os.getenv("RENDER"),    # Render.com
        os.getenv("RAILWAY_ENVIRONMENT"),  # Railway
        os.getenv("VERCEL"),    # Vercel
        os.getenv("KUBERNETES_SERVICE_HOST"),  # Kubernetes
        os.getenv("AWS_LAMBDA_FUNCTION_NAME"),  # AWS Lambda
    ])
    
    # Load .env file only if not in production AND file exists
    env_path = Path('.') / '.env'
    if not is_production and env_path.exists():
        print(f"🔧 Loading environment variables from {env_path}")
        load_dotenv(dotenv_path=env_path, override=False)  # Don't override existing env vars
    elif is_production:
        print("🚀 Production environment detected, using system environment variables")
    else:
        print("⚠️ No .env file found and not in production environment")

# Load environment variables using the unified method
load_environment_variables()

# OpenAI Configuration
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
OPENAI_MODEL_NAME = os.getenv("OPENAI_MODEL_NAME", "gpt-5-mini")

AZURE_API_KEY = os.getenv("AZURE_API_KEY")
AZURE_API_BASE = os.getenv("AZURE_API_BASE")
AZURE_API_VERSION = os.getenv("AZURE_API_VERSION")

# Langfuse Configuration
LANGFUSE_PUBLIC_KEY = os.getenv("LANGFUSE_PUBLIC_KEY")
LANGFUSE_SECRET_KEY = os.getenv("LANGFUSE_SECRET_KEY")
LANGFUSE_HOST = os.getenv("LANGFUSE_HOST", "https://cloud.langfuse.com")
LANGFUSE_AUTH = ""
if LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY:
    import base64
    LANGFUSE_AUTH = base64.b64encode(f"{LANGFUSE_PUBLIC_KEY}:{LANGFUSE_SECRET_KEY}".encode()).decode()

# Other API Keys
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")

# Database Configuration
# For HF Spaces, use /data persistent storage directory if available
# Fall back to /tmp if /data is not accessible (Persistent Storage not enabled)
# For local development, use datasets/db directory
def _get_default_db_uri():
    """Get default database URI based on environment."""
    if os.getenv("SPACE_ID"):  # HF Spaces
        # Try to use HF Persistent Storage at /data first
        data_dir = Path("/data")
        try:
            # Check if /data exists and is writable
            data_dir.mkdir(parents=True, exist_ok=True)
            test_file = data_dir / ".write_test"
            test_file.touch()
            test_file.unlink()
            print("✅ Using HF Persistent Storage at /data")
            return "sqlite:////data/agent_monitoring.db"
        except (OSError, PermissionError) as e:
            # Fall back to /tmp if /data is not available
            print(f"⚠️ /data not available ({e}), using /tmp for ephemeral storage")
            tmp_dir = Path("/tmp/agentgraph")
            tmp_dir.mkdir(parents=True, exist_ok=True)
            return f"sqlite:///{tmp_dir}/agent_monitoring.db"
    else:
        # Local development - use datasets/db relative to project root
        project_root = Path(__file__).parent.parent.resolve()
        db_dir = project_root / "datasets" / "db"
        os.makedirs(db_dir, exist_ok=True)
        return f"sqlite:///{db_dir}/agent_monitoring.db"

DB_URI = os.getenv("DB_URI", _get_default_db_uri())

# Function to validate configuration
def validate_config():
    """Validates that all required environment variables are set"""
    required_vars = [
        ("OPENAI_API_KEY", OPENAI_API_KEY),
    ]
    
    missing_vars = [var_name for var_name, var_value in required_vars if not var_value]
    
    if missing_vars:
        missing_vars_str = ", ".join(missing_vars)
        print(f"❌ Missing required environment variables: {missing_vars_str}")
        print(f"📝 Please set them in the .env file or as environment variables")
        return False
    
    return True

def debug_config():
    """Debug function to show current configuration state"""
    print("🔍 AgentGraph Configuration Debug:")
    print("=" * 50)
    
    # Show environment loading method
    env_path = Path('.') / '.env'
    is_production = any([
        os.getenv("SPACE_ID"),
        os.getenv("RENDER"),
        os.getenv("RAILWAY_ENVIRONMENT"),
        os.getenv("VERCEL"),
        os.getenv("KUBERNETES_SERVICE_HOST"),
        os.getenv("AWS_LAMBDA_FUNCTION_NAME"),
    ])
    
    print(f"🏗️ Environment: {'Production' if is_production else 'Development'}")
    print(f"📁 .env file exists: {env_path.exists()}")
    print(f"📍 Working directory: {Path.cwd()}")
    print()
    
    # Show key configuration values (masked)
    configs = [
        ("OPENAI_API_KEY", OPENAI_API_KEY),
        ("OPENAI_MODEL_NAME", OPENAI_MODEL_NAME),
        ("LANGFUSE_PUBLIC_KEY", LANGFUSE_PUBLIC_KEY),
        ("LANGFUSE_SECRET_KEY", LANGFUSE_SECRET_KEY),
        ("LANGFUSE_HOST", LANGFUSE_HOST),
        ("DB_URI", DB_URI),
    ]
    
    for name, value in configs:
        if value:
            if "KEY" in name or "SECRET" in name:
                masked = f"{value[:8]}..." if len(value) > 8 else "***"
                print(f"✅ {name}: {masked}")
            else:
                print(f"✅ {name}: {value}")
        else:
            print(f"❌ {name}: Not set")
    
    print("=" * 50)