Build RAG Systems for Equipment Manuals with torchtune and LlamaIndex

"""
Production implementation for Building RAG Systems for Equipment Manuals.
This system integrates torchtune for tuning models and LlamaIndex for indexing.
"""

from typing import Dict, Any, List
import os
import logging
import time
import torchtune
from llama_index import LlamaIndex

# Configure logging for tracking events and errors
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class to load environment variables.
    """  
    database_url: str = os.getenv('DATABASE_URL')
    model_tuning_params: Dict[str, Any] = {
        'param1': os.getenv('PARAM1'),
        'param2': os.getenv('PARAM2'),
    }

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate request data for RAG system.
    
    Args:
        data: Input to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'manual_id' not in data:
        raise ValueError('Missing manual_id')  # Ensure manual_id is present
    return True

async def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields for safety.
    
    Args:
        data: Input data to sanitize
    Returns:
        Sanitized data
    Raises:
        ValueError: If sanitization fails
    """
    # Example of sanitizing fields, this can be expanded as needed
    return {key: str(value).strip() for key, value in data.items()}

async def normalize_data(raw_data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Normalize raw data from manuals.
    
    Args:
        raw_data: List of raw data dictionaries
    Returns:
        List of normalized data dictionaries
    """
    return [{
        'id': item['manual_id'],
        'content': item.get('content', '')
    } for item in raw_data]

async def transform_records(data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Transform records for processing.
    
    Args:
        data: List of records to transform
    Returns:
        Transformed records
    """
    # Placeholder for transformation logic
    return data

async def fetch_data(manual_ids: List[str]) -> List[Dict[str, Any]]:
    """Fetch equipment manuals from the database.
    
    Args:
        manual_ids: List of manual IDs to fetch
    Returns:
        List of fetched manuals
    """
    # Simulated fetching data, replace with actual DB fetch logic
    logger.info(f'Fetching manuals for IDs: {manual_ids}')
    return [{'manual_id': manual_id, 'content': 'Sample Content'} for manual_id in manual_ids]

async def save_to_db(records: List[Dict[str, Any]]) -> None:
    """Save processed records to the database.
    
    Args:
        records: List of records to save
    """
    # Placeholder for database saving logic
    logger.info(f'Saving records: {records}')

async def call_api(endpoint: str, payload: Dict[str, Any]) -> Any:
    """Call external API with payload.
    
    Args:
        endpoint: API endpoint URL
        payload: Data to send in the request
    Returns:
        Response from the API
    Raises:
        Exception: If API call fails
    """
    logger.info(f'Calling API {endpoint} with payload: {payload}')
    # Simulated API call, replace with actual logic
    time.sleep(1)  # Simulate network delay
    return {'status': 'success'}

async def process_batch(manual_ids: List[str]) -> None:
    """Process a batch of manuals.
    
    Args:
        manual_ids: List of manual IDs to process
    """
    try:
        raw_data = await fetch_data(manual_ids)  # Fetch manuals
        validated = await validate_input(raw_data)  # Validate input
        sanitized = await sanitize_fields(raw_data)  # Sanitize fields
        normalized = await normalize_data(sanitized)  # Normalize data
        transformed = await transform_records(normalized)  # Transform records
        await save_to_db(transformed)  # Save to DB
    except Exception as e:
        logger.error(f'Error processing batch: {e}')  # Log error

class RagSystem:
    """Main class for the RAG system.
    Integrates all components for processing manuals.
    """
    def __init__(self):
        self.config = Config()  # Load config

    async def run(self, manual_ids: List[str]) -> None:
        """Run the RAG system for given manual IDs.
        
        Args:
            manual_ids: List of manual IDs to process
        """
        logger.info(f'Starting RAG system for IDs: {manual_ids}')  # Log start
        await process_batch(manual_ids)  # Process the batch

if __name__ == '__main__':
    import asyncio
    rag_system = RagSystem()  # Initialize RAG system
    asyncio.run(rag_system.run(['id1', 'id2', 'id3']))  # Run with example IDs