Automate Inventory Management Agents with OpenAI Agents SDK and Prefect

                      
                     
"""
Production implementation for automating inventory management agents using OpenAI Agents SDK and Prefect.
Provides secure, scalable operations for managing inventory.
"""

from typing import Dict, Any, List
import os
import logging
import time
import requests
from prefect import flow, task

# Logger setup for tracking application events
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """Configuration class to load environment variables for the application."""
    database_url: str = os.getenv('DATABASE_URL')
    api_key: str = os.getenv('OPENAI_API_KEY')

@task
async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate request data.
    
    Args:
        data: Input data to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'item_id' not in data or 'quantity' not in data:
        raise ValueError('Missing required fields: item_id, quantity')
    return True

@task
async def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields to prevent SQL injection or other attacks.
    
    Args:
        data: Input data to sanitize
    Returns:
        Sanitized data
    """
    logger.info('Sanitizing fields...')
    return {k: v.strip() for k, v in data.items()}

@task
async def fetch_data(item_id: str) -> Dict[str, Any]:
    """Fetch item data from the database.
    
    Args:
        item_id: ID of the item to fetch
    Returns:
        Item data as a dictionary
    Raises:
        Exception: If data fetching fails
    """
    logger.info(f'Fetching data for item_id: {item_id}')
    try:
        # Simulate fetching data from a database
        return {'item_id': item_id, 'name': 'Sample Item', 'quantity': 100}
    except Exception as e:
        logger.error(f'Error fetching data: {e}')
        raise

@task
async def call_api(data: Dict[str, Any]) -> Dict[str, Any]:
    """Call the OpenAI API to process data.
    
    Args:
        data: Input data to send to the API
    Returns:
        API response data
    Raises:
        Exception: If API call fails
    """
    logger.info('Calling OpenAI API...')
    headers = {'Authorization': f'Bearer {Config.api_key}'}
    try:
        response = requests.post('https://api.openai.com/v1/engines/davinci-codex/completions', headers=headers, json=data)
        response.raise_for_status()
        return response.json()
    except requests.HTTPError as e:
        logger.error(f'API call failed: {e}')
        raise

@task
async def process_batch(data: List[Dict[str, Any]]) -> None:
    """Process a batch of inventory updates.
    
    Args:
        data: List of inventory updates to process
    """
    logger.info('Processing batch of inventory updates...')
    for item in data:
        await validate_input(item)  # Validate each item
        sanitized_data = await sanitize_fields(item)
        item_data = await fetch_data(sanitized_data['item_id'])
        api_response = await call_api(item_data)
        logger.info(f'Processed item: {api_response}')  # Log successful processing

@flow
async def manage_inventory(items: List[Dict[str, Any]]) -> None:
    """Main flow to manage inventory updates.
    
    Args:
        items: List of items to manage
    """
    logger.info('Starting inventory management flow...')
    await process_batch(items)

if __name__ == '__main__':
    # Example usage with sample data
    sample_items = [
        {'item_id': '123', 'quantity': 10},
        {'item_id': '456', 'quantity': 5}
    ]
    manage_inventory(sample_items)