Monitor Assembly Line Health with Evidently and YOLO26

                      
                     
"""
Production implementation for monitoring assembly line health with Evidently and YOLO26.
Provides secure, scalable operations leveraging advanced AI for anomaly detection.
"""

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

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

class Config:
    # Load configuration from environment variables
    DATABASE_URL: str = os.getenv('DATABASE_URL')
    YOLO_MODEL_URL: str = os.getenv('YOLO_MODEL_URL')
    EVIDENTLY_API_URL: str = os.getenv('EVIDENTLY_API_URL')

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

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

def fetch_data(api_url: str) -> Dict[str, Any]:
    """Fetch data from external API.
    
    Args:
        api_url: The URL to fetch data from
    Returns:
        Response data as dict
    Raises:
        RuntimeError: If the request fails
    """
    try:
        response = requests.get(api_url)
        response.raise_for_status()  # Raise an error for bad responses
        return response.json()
    except requests.RequestException as e:
        logger.error(f'Error fetching data: {e}')
        raise RuntimeError('Failed to fetch data')

def process_batch(batch: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Process a batch of assembly line data.
    
    Args:
        batch: List of data records to process
    Returns:
        Processed records
    """
    processed_records = []
    for record in batch:
        try:
            validate_input(record)  # Validate each record
            sanitized = sanitize_fields(record)  # Sanitize fields
            processed_records.append(sanitized)  # Add to processed list
        except ValueError as e:
            logger.warning(f'Validation error: {e}')  # Log validation errors
    return processed_records

def aggregate_metrics(records: List[Dict[str, Any]]) -> Dict[str, float]:
    """Aggregate metrics from processed records.
    
    Args:
        records: List of processed records
    Returns:
        Aggregated metrics as dict
    """
    aggregated = {'average_value': 0.0}
    if records:
        total_value = sum(record['metrics']['value'] for record in records)
        aggregated['average_value'] = total_value / len(records)
    return aggregated

class AssemblyLineMonitor:
    """Main orchestrator for monitoring assembly line health.
    
    Attributes:
        config: Configuration details
    """
    def __init__(self, config: Config):
        self.config = config

    def run_monitoring(self):
        """Execute the monitoring workflow.
        
        This method orchestrates the fetching, processing, and reporting of assembly line health data.
        """
        while True:
            try:
                raw_data = fetch_data(self.config.YOLO_MODEL_URL)  # Fetch raw data from YOLO model
                processed_data = process_batch(raw_data)  # Process raw data
                metrics = aggregate_metrics(processed_data)  # Aggregate metrics
                self.report_metrics(metrics)  # Report metrics
                time.sleep(60)  # Wait before the next iteration
            except RuntimeError as e:
                logger.error(f'Monitoring error: {e}')  # Handle monitoring errors gracefully
                time.sleep(10)  # Wait before retrying

    def report_metrics(self, metrics: Dict[str, float]):
        """Report aggregated metrics to Evidently API.
        
        Args:
            metrics: Aggregated metrics to report
        Raises:
            RuntimeError: If the reporting fails
        """
        try:
            response = requests.post(self.config.EVIDENTLY_API_URL, json=metrics)
            response.raise_for_status()  # Ensure successful response
            logger.info('Metrics reported successfully')
        except requests.RequestException as e:
            logger.error(f'Error reporting metrics: {e}')
            raise RuntimeError('Failed to report metrics')

if __name__ == '__main__':
    config = Config()  # Load configuration
    monitor = AssemblyLineMonitor(config)  # Create monitor instance
    monitor.run_monitoring()  # Start monitoring workflow