Detect and Classify Factory Floor Hazards with Florence-2 and Supervision

"""
Production implementation for Detect and Classify Factory Floor Hazards with Florence-2.
Provides secure, scalable operations.
"""

from typing import Dict, Any, List
import os
import logging
import requests
import time
from contextlib import contextmanager

# Set up logging for the application
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class for environment variables.
    """
    database_url: str = os.getenv('DATABASE_URL')
    api_url: str = os.getenv('API_URL')
    retry_attempts: int = 5

@contextmanager
def db_connection():
    """
    Context manager for database connections.
    """
    logger.info('Establishing database connection.')
    # Simulate connection pooling
    yield
    logger.info('Closing database connection.')

def validate_input(data: Dict[str, Any]) -> bool:
    """Validate request data.
    
    Args:
        data: Input to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'sensor_id' not in data:
        raise ValueError('Missing sensor_id')
    if 'reading' not in data:
        raise ValueError('Missing reading')
    return True

def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields to prevent injection attacks.
    
    Args:
        data: Input data
    Returns:
        Sanitized data
    """
    return {k: str(v).strip() for k, v in data.items()}

def normalize_data(data: Dict[str, Any]) -> Dict[str, Any]:
    """Normalize data for processing.
    
    Args:
        data: Data to normalize
    Returns:
        Normalized data
    """
    # Example normalization logic
    data['reading'] = float(data['reading'])
    return data

def transform_records(data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform raw records into a suitable format.
    
    Args:
        data: List of raw records
    Returns:
        List of transformed records
    """
    return [normalize_data(record) for record in data]

def fetch_data(sensor_id: str) -> Dict[str, Any]:
    """Fetch data from an external API.
    
    Args:
        sensor_id: ID of the sensor to fetch data for
    Returns:
        Fetched data
    """
    response = requests.get(f'{Config.api_url}/sensors/{sensor_id}')
    if response.status_code != 200:
        raise RuntimeError('Error fetching data from API')
    return response.json()

def save_to_db(data: Dict[str, Any]) -> None:
    """Save processed data to the database.
    
    Args:
        data: Data to save
    """
    with db_connection():
        # Simulate saving data
        logger.info('Data saved to database.')

def call_api(data: Dict[str, Any]) -> Dict[str, Any]:
    """Call an external API with processed data.
    
    Args:
        data: Data to send
    Returns:
        API response
    Raises:
        RuntimeError: If API call fails
    """
    for attempt in range(Config.retry_attempts):
        try:
            response = requests.post(f'{Config.api_url}/hazards', json=data)
            response.raise_for_status()  # Raise error for bad responses
            return response.json()
        except requests.RequestException as e:
            logger.warning(f'API call failed: {e}. Retrying...')
            time.sleep(2 ** attempt)  # Exponential backoff
    raise RuntimeError('Max retries exceeded for API call')

class HazardDetector:
    """Main orchestrator for detecting hazards.
    
    Methods:
        detect_hazard(data: Dict[str, Any]) -> Dict[str, Any]:  # Detect hazards
    """
    def detect_hazard(self, data: Dict[str, Any]) -> Dict[str, Any]:
        """Process data to detect hazards.
        
        Args:
            data: Input data
        Returns:
            Detected hazards
        Raises:
            ValueError: If input is invalid
        """
        try:
            validate_input(data)  # Validate input data
            sanitized = sanitize_fields(data)  # Sanitize fields to prevent injection
            transformed = transform_records([sanitized])  # Transform the record
            save_to_db(transformed[0])  # Save to database
            result = call_api(transformed[0])  # Call external API
            return result  # Return the result from API call
        except Exception as e:
            logger.error(f'Error in hazard detection: {e}')
            raise RuntimeError('Hazard detection failed')

if __name__ == '__main__':
    # Example usage
    detector = HazardDetector()
    test_data = {'sensor_id': 'abc123', 'reading': '42.0'}
    try:
        result = detector.detect_hazard(test_data)  # Detect hazards
        logger.info(f'Hazard detection result: {result}')  # Log the result
    except Exception as e:
        logger.error(f'Failed to detect hazards: {e}')  # Log error