Run Multi-Task Visual Inspection Queries with PaliGemma and Supervision

"""
Production implementation for running multi-task visual inspection queries.
Provides secure, scalable operations suitable for real-time processing.
"""
from typing import Dict, Any, List
import os
import logging
import asyncio
import httpx
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, Session

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

# Database configuration
DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///./test.db')
Base = declarative_base()

# SQLAlchemy model definition
class InspectionResult(Base):
    __tablename__ = 'inspection_results'
    id = Column(Integer, primary_key=True, index=True)
    status = Column(String, index=True)
    details = Column(String)

# Create the database engine and session
engine = create_engine(DATABASE_URL)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# Configuration class
class Config:
    max_retries: int = 3
    timeout: int = 5

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
    """
    if 'task_id' not in data:
        logger.error('Missing task_id')
        raise ValueError('Missing task_id')
    return True

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

async def fetch_data(url: str) -> Dict[str, Any]:
    """Fetch data from the given URL with retries.
    
    Args:
        url: URL to fetch data from
    Returns:
        JSON response data
    Raises:
        Exception: If fetching fails after retries
    """
    async with httpx.AsyncClient() as client:
        for attempt in range(Config.max_retries):
            try:
                response = await client.get(url, timeout=Config.timeout)
                response.raise_for_status()  # Raise exception for HTTP errors
                return response.json()
            except httpx.HTTPStatusError as e:
                logger.warning(f'HTTP error: {e}, retrying...')
            except Exception as e:
                logger.error(f'Error fetching data: {e}')
                if attempt == Config.max_retries - 1:
                    raise Exception('Max retries exceeded')
    return {}

async def save_to_db(data: Dict[str, Any], db: Session) -> None:
    """Save inspection result to the database.
    
    Args:
        data: Data to save
        db: Database session
    """
    result = InspectionResult(**data)
    db.add(result)
    db.commit()
    db.refresh(result)
    logger.info(f'Saved result with ID: {result.id}')  # Log successful save

async def process_batch(batch: List[Dict[str, Any]]) -> None:
    """Process a batch of inspection tasks.
    
    Args:
        batch: List of tasks to process
    """
    async with SessionLocal() as db:
        for task in batch:
            try:
                await validate_input(task)  # Validate input
                sanitized_data = await sanitize_fields(task)  # Sanitize data
                # Simulate processing task
                logger.info(f'Processing task: {sanitized_data}')
                await save_to_db(sanitized_data, db)  # Save to DB
            except Exception as e:
                logger.error(f'Error processing task {task}: {e}')  # Log error

async def main(url: str) -> None:
    """Main orchestration function.
    
    Args:
        url: URL to fetch tasks from
    """
    data = await fetch_data(url)  # Fetch data
    await process_batch(data['tasks'])  # Process fetched tasks

if __name__ == '__main__':
    # Example usage
    url = 'http://example.com/api/tasks'
    asyncio.run(main(url))  # Run the main function asynchronously