import os
import psycopg2
from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT
from dotenv import load_dotenv

load_dotenv()

class DatabaseSetup:
    def __init__(self):
        self.host = os.getenv('DB_HOST', 'localhost')
        self.port = os.getenv('DB_PORT', '5432')
        self.db_name = os.getenv('DB_NAME', 'cocktails_db')
        self.user = os.getenv('DB_USER', 'postgres')
        self.password = os.getenv('DB_PASSWORD', 'your_password')
    
    def create_database(self):
        """Create the database if it doesn't exist"""
        try:
            # Connect to default postgres database
            conn = psycopg2.connect(
                host=self.host,
                port=self.port,
                user=self.user,
                password=self.password,
                database='postgres'
            )
            conn.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)
            cursor = conn.cursor()
            
            # Check if database exists
            cursor.execute(f"SELECT 1 FROM pg_catalog.pg_database WHERE datname = '{self.db_name}'")
            exists = cursor.fetchone()
            
            if not exists:
                cursor.execute(f'CREATE DATABASE {self.db_name}')
                print(f"Database '{self.db_name}' created successfully")
            else:
                print(f"Database '{self.db_name}' already exists")
                
            cursor.close()
            conn.close()
            
        except Exception as e:
            print(f"Error creating database: {e}")
    
    def setup_pgvector(self):
        """Setup pgvector extension and create tables"""
        try:
            conn = psycopg2.connect(
                host=self.host,
                port=self.port,
                user=self.user,
                password=self.password,
                database=self.db_name
            )
            cursor = conn.cursor()
            
            # Enable pgvector extension
            cursor.execute("CREATE EXTENSION IF NOT EXISTS vector")
            
            # Create cocktails table with vector embeddings
            cursor.execute("""
                CREATE TABLE IF NOT EXISTS cocktails (
                    id SERIAL PRIMARY KEY,
                    name VARCHAR(255) NOT NULL,
                    ingredients TEXT NOT NULL,
                    recipe TEXT,
                    glass VARCHAR(100),
                    category VARCHAR(100),
                    iba VARCHAR(100),
                    alcoholic VARCHAR(50),
                    embedding vector(384)
                )
            """)
            
            # Create index for vector similarity search
            cursor.execute("""
                CREATE INDEX IF NOT EXISTS cocktails_embedding_idx 
                ON cocktails USING ivfflat (embedding vector_cosine_ops)
                WITH (lists = 100)
            """)
            
            conn.commit()
            cursor.close()
            conn.close()
            
            print("Database tables and pgvector extension set up successfully")
            
        except Exception as e:
            print(f"Error setting up pgvector: {e}")
    
    def get_connection(self):
        """Get database connection"""
        return psycopg2.connect(
            host=self.host,
            port=self.port,
            user=self.user,
            password=self.password,
            database=self.db_name
        )

if __name__ == "__main__":
    db_setup = DatabaseSetup()
    db_setup.create_database()
    db_setup.setup_pgvector()