Implement Agent Memory and Recall for Factory Operations with smolagents and PydanticAI

"""
Production implementation for Agent Memory and Recall for Factory Operations.
This module provides secure and scalable operations using smolagents and PydanticAI.
"""
from typing import Dict, Any, List, Optional
import os
import logging
import asyncio
import httpx
from pydantic import BaseModel, ValidationError

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

class Config:
    """Configuration class to manage environment variables."""
    database_url: str = os.getenv('DATABASE_URL', 'sqlite:///./test.db')  # Default to SQLite
    retry_attempts: int = 5
    retry_delay: float = 1.0

class Record(BaseModel):
    """Data model for storing factory operations records."""
    id: int
    operation: str
    status: str
    timestamp: str

async 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
    """
    try:
        Record(**data)  # Validate data against Record model
    except ValidationError as e:
        logger.error(f'Validation error: {e}')
        raise ValueError('Invalid input data')  # Raise error on validation failure
    return True

async def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize fields to prevent injection attacks.
    
    Args:
        data: Input data to sanitize
    Returns:
        Sanitized data
    """
    return {key: str(value).strip() for key, value in data.items()}  # Strip whitespace from fields

async def fetch_data(api_url: str) -> List[Dict[str, Any]]:
    """Fetch data from an API.
    
    Args:
        api_url: URL to fetch data from
    Returns:
        List of records fetched
    Raises:
        Exception: If HTTP request fails
    """
    async with httpx.AsyncClient() as client:
        response = await client.get(api_url)
        response.raise_for_status()  # Raise error for bad responses
        return response.json()

async def save_to_db(records: List[Dict[str, Any]]) -> None:
    """Save records to the database.
    
    Args:
        records: List of records to save
    Raises:
        Exception: If database operation fails
    """
    # Placeholder for actual DB save logic
    logger.info(f'Saving {len(records)} records to the database.')  # Log number of records being saved

async def process_batch(batch: List[Dict[str, Any]]) -> None:
    """Process a batch of records.
    
    Args:
        batch: List of records to process
    """
    # Log processing of batch
    logger.info(f'Processing batch of {len(batch)} records.')  # Log batch processing
    await save_to_db(batch)  # Save processed batch

async def call_api_and_process(api_url: str) -> None:
    """Fetch data from API and process it.
    
    Args:
        api_url: URL of the API to call
    """
    try:
        data = await fetch_data(api_url)  # Fetch data
        await process_batch(data)  # Process fetched data
    except Exception as e:
        logger.error(f'Error during API call and processing: {e}')  # Log error

class FactoryOperations:
    """Orchestrator class for managing factory operations."""

    def __init__(self, config: Config):
        self.config = config  # Store configuration

    async def execute(self, api_url: str) -> None:
        """Execute the factory operations.
        
        Args:
            api_url: URL for fetching data
        """
        try:
            await call_api_and_process(api_url)  # Call API and process data
        except Exception as e:
            logger.error(f'Execution error: {e}')  # Log execution errors

if __name__ == '__main__':
    # Example usage
    config = Config()  # Instantiate configuration
    factory_ops = FactoryOperations(config)  # Create orchestrator
    asyncio.run(factory_ops.execute('https://api.example.com/factory'))  # Run operations