Fine-Tune GR00T Robot Policies for Industrial Grasping with Isaac

                      
                     
"""
Production implementation for Fine-Tuning GR00T Robot Policies.
Provides secure, scalable operations for industrial grasping.
"""

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

# Setting up logging for the application
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class for environment variables.
    """
    database_url: str = os.getenv('DATABASE_URL')
    api_url: str = os.getenv('API_URL')
    retry_attempts: int = int(os.getenv('RETRY_ATTEMPTS', 3))

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate input data for the robot policies.
    
    Args:
        data: Input data to validate
    Returns:
        True if valid, otherwise raises ValueError
    Raises:
        ValueError: If validation fails
    """
    if 'policy_id' not in data:
        raise ValueError('Missing policy_id')
    if not isinstance(data['policy_id'], str):
        raise ValueError('Invalid policy_id type')
    return True

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

async def normalize_data(data: Dict[str, Any]) -> Dict[str, Any]:
    """Normalize data to maintain consistency.
    
    Args:
        data: Input data to normalize
    Returns:
        Normalized data
    """
    # Example normalization
    return {key: value.lower() for key, value in data.items()}

async def transform_records(records: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform records for processing.
    
    Args:
        records: List of records to transform
    Returns:
        Transformed records
    """
    return [await normalize_data(record) for record in records]

async def fetch_data() -> List[Dict[str, Any]]:
    """Fetch data from external API.
    
    Returns:
        List of data records
    Raises:
        Exception: If fetching fails
    """
    try:
        response = requests.get(Config.api_url)
        response.raise_for_status()  # Raises HTTPError for bad responses
        return response.json()
    except Exception as e:
        logger.error(f'Failed to fetch data: {e}')
        raise

async def save_to_db(data: List[Dict[str, Any]]) -> None:
    """Save processed data to the database.
    
    Args:
        data: Data to save
    Raises:
        Exception: If saving fails
    """
    # Simulated DB save operation
    logger.info('Saving data to the database...')
    # Placeholder for actual DB logic

async def process_batch(data: List[Dict[str, Any]]) -> None:
    """Process a batch of data for the robot policies.
    
    Args:
        data: Batch of data to process
    Raises:
        Exception: If processing fails
    """
    try:
        # Example processing logic
        transformed_data = await transform_records(data)
        await save_to_db(transformed_data)
    except Exception as e:
        logger.error(f'Error processing batch: {e}')
        raise

async def aggregate_metrics(data: List[Dict[str, Any]]) -> Dict[str, Any]:
    """Aggregate metrics from processed data.
    
    Args:
        data: List of processed records
    Returns:
        Aggregated metrics
    """
    # Placeholder for metric aggregation logic
    return {'total_records': len(data)}

class GR00TPolicyOrchestrator:
    """Main orchestrator for GR00T robot policy management.
    """

    async def run(self) -> None:
        """Main workflow for fine-tuning policies.
        """
        try:
            raw_data = await fetch_data()
            await validate_input(raw_data)
            sanitized_data = await sanitize_fields(raw_data)
            await process_batch(sanitized_data)
            metrics = await aggregate_metrics(sanitized_data)
            logger.info(f'Metrics: {metrics}')
        except Exception as e:
            logger.error(f'Workflow error: {e}')

if __name__ == '__main__':
    # Example usage of the orchestrator
    orchestrator = GR00TPolicyOrchestrator()
    orchestrator.run()  # Note: This should be awaited in an async context