Orchestrate Autonomous Supply Chain Audit Agents with Strands Agents and Prefect

"""
Production implementation for orchestrating autonomous supply chain audit agents using Strands Agents and Prefect.
Provides secure, scalable operations with robust error handling and logging.
"""
from typing import Dict, Any, List
import os
import logging
import time
import json
import requests
from sqlalchemy import create_engine, Column, Integer, String, Sequence
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, scoped_session

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Load configuration from environment variables
class Config:
    database_url: str = os.getenv('DATABASE_URL', 'sqlite:///audit_agents.db')

# Setup database connection pooling
Base = declarative_base()
engine = create_engine(Config.database_url, pool_size=5, max_overflow=10)
Session = scoped_session(sessionmaker(bind=engine))

# Define data model
class AuditAgent(Base):
    """
    Represents an audit agent in the database.
    """
    __tablename__ = 'audit_agents'
    id = Column(Integer, Sequence('agent_id_seq'), primary_key=True)
    name = Column(String(50))
    status = Column(String(20))

Base.metadata.create_all(engine)

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate input data for the audit agent.
    
    Args:
        data: Input data to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'name' not in data:
        raise ValueError('Missing name in input data')
    if 'status' not in data:
        raise ValueError('Missing status in input data')
    return True

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

async def transform_records(records: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform raw records into a format suitable for processing.
    
    Args:
        records: Raw records from input
    Returns:
        List of transformed records
    """
    transformed = [{'name': rec['name'], 'status': rec['status']} for rec in records]
    logger.info('Transformed records for processing')
    return transformed

async def process_batch(batch: List[Dict[str, Any]]) -> None:
    """Process a batch of audit agents, saving to the database.
    
    Args:
        batch: List of audit agents to process
    """
    session = Session()
    try:
        for item in batch:
            agent = AuditAgent(name=item['name'], status=item['status'])
            session.add(agent)
            logger.info(f'Added agent {item['name']} to the session')
        session.commit()
        logger.info('Batch processed successfully')
    except Exception as e:
        session.rollback()
        logger.error(f'Error processing batch: {e}')
        raise
    finally:
        session.close()

async def fetch_data(api_url: str) -> List[Dict[str, Any]]:
    """Fetch data from an external API.
    
    Args:
        api_url: URL of the API endpoint
    Returns:
        List of records fetched from the API
    Raises:
        ConnectionError: If the API call fails
    """
    try:
        response = requests.get(api_url)
        response.raise_for_status()
        logger.info('Fetched data from API')
        return response.json()
    except requests.RequestException as e:
        logger.error(f'Failed to fetch data: {e}')
        raise ConnectionError('Could not fetch data from API')

async def save_to_db(data: List[Dict[str, Any]]) -> None:
    """Save transformed data to the database.
    
    Args:
        data: List of data to save
    """
    await process_batch(data)

async def call_api(api_url: str) -> None:
    """Main function to orchestrate API calls and database operations.
    
    Args:
        api_url: URL of the API endpoint
    """
    try:
        raw_data = await fetch_data(api_url)
        validated_data = await sanitize_fields(raw_data)
        transformed_data = await transform_records(validated_data)
        await save_to_db(transformed_data)
    except ValueError as ve:
        logger.error(f'Validation error: {ve}')
    except ConnectionError as ce:
        logger.error(f'Connection error: {ce}')
    except Exception as e:
        logger.error(f'Unexpected error: {e}')

if __name__ == '__main__':
    # Example usage of the orchestrator
    api_url = 'https://api.example.com/audit_agents'
    run(call_api(api_url))