Parse Scientific Datasheets and Material Specs from Industrial PDFs with Nougat and LlamaIndex

"""
Production implementation for parsing scientific datasheets and material specs from industrial PDFs.
Provides secure, scalable operations using Nougat and LlamaIndex for data extraction.
"""
import os
import logging
from typing import List, Dict, Any
import pdfplumber
import requests

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

class Config:
    """Configuration class for environment variables."""
    pdf_storage_url: str = os.getenv('PDF_STORAGE_URL')
    database_url: str = os.getenv('DATABASE_URL')

def validate_input_data(data: Dict[str, Any]) -> bool:
    """Validate input data for required fields.
    
    Args:
        data: Dictionary containing input data to validate.
    Returns:
        bool: True if data is valid.
    Raises:
        ValueError: If validation fails.
    """  
    if 'url' not in data:
        raise ValueError('Missing required field: url')
    return True

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

def fetch_pdf_data(url: str) -> str:
    """Fetch PDF data from a given URL.
    
    Args:
        url: URL of the PDF to fetch.
    Returns:
        str: PDF data as text.
    Raises:
        Exception: If fetching fails.
    """  
    try:
        response = requests.get(url)
        response.raise_for_status()
        logger.info('PDF fetched successfully.')
        return response.content
    except requests.RequestException as e:
        logger.error(f'Error fetching PDF: {e}')
        raise Exception(f'Failed to fetch PDF: {e}')

def parse_pdf(content: bytes) -> List[str]:
    """Parse PDF content to extract text.
    
    Args:
        content: Binary content of the PDF file.
    Returns:
        List[str]: Extracted text from the PDF.
    Raises:
        Exception: If parsing fails.
    """  
    try:
        with pdfplumber.open(content) as pdf:
            text = []
            for page in pdf.pages:
                text.append(page.extract_text())
            logger.info('PDF parsed successfully.')
            return text
    except Exception as e:
        logger.error(f'Error parsing PDF: {e}')
        raise Exception('Failed to parse PDF')

def transform_records(raw_data: List[str]) -> List[Dict[str, Any]]:
    """Transform raw text data into structured records.
    
    Args:
        raw_data: List of raw text data from the PDF.
    Returns:
        List[Dict[str, Any]]: List of structured records.
    """  
    records = []
    for data in raw_data:
        # Logic to transform raw data to structured format
        records.append({'spec': data})
    logger.info('Data transformed into records.')
    return records

def save_to_db(records: List[Dict[str, Any]]) -> None:
    """Save structured records to the database.
    
    Args:
        records: List of records to save.
    Raises:
        Exception: If saving fails.
    """  
    # Placeholder for database connection logic
    for record in records:
        # Simulate saving record to DB
        logger.info(f'Saving record: {record}')

def process_batch(data: Dict[str, Any]) -> None:
    """Process a batch of data.
    
    Args:
        data: Dictionary containing input data for processing.
    Raises:
        Exception: If processing fails.
    """  
    try:
        validated_data = validate_input_data(data)
        sanitized_data = sanitize_fields(validated_data)
        content = fetch_pdf_data(sanitized_data['url'])
        raw_data = parse_pdf(content)
        records = transform_records(raw_data)
        save_to_db(records)
    except ValueError as ve:
        logger.error(f'Validation error: {ve}')
        raise
    except Exception as e:
        logger.error(f'Processing error: {e}')
        raise

class DatasheetParser:
    """Main class for orchestrating the parsing workflow."""

    def __init__(self, config: Config):
        self.config = config

    def run(self, data: Dict[str, Any]) -> None:
        """Run the data parsing workflow.
        
        Args:
            data: Input data for parsing.
        """  
        process_batch(data)

if __name__ == '__main__':
    # Example usage of the DatasheetParser
    config = Config()
    parser = DatasheetParser(config)
    input_data = {'url': 'http://example.com/sample.pdf'}
    try:
        parser.run(input_data)
    except Exception as e:
        logger.error(f'Error during parsing: {e}')