Build Intelligent Equipment Log Search Pipelines with DeepSeek-OCR-2 and LlamaIndex

"""
Production implementation for building intelligent equipment log search pipelines with DeepSeek-OCR-2 and LlamaIndex.
Provides secure, scalable operations for processing logs and extracting insights.
"""
from typing import Dict, Any, List, Tuple
import os
import logging
import asyncio
import httpx
import psycopg2
from contextlib import asynccontextmanager

# Logger setup for tracking information and errors
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class to handle environment variables.
    """
    database_url: str = os.getenv('DATABASE_URL')
    ocr_service_url: str = os.getenv('OCR_SERVICE_URL')

@asynccontextmanager
async def get_db_connection() -> None:
    """
    Context manager for database connection pooling.
    
    Yields:
        A connection object to the database.
    """
    conn = psycopg2.connect(Config.database_url)
    try:
        yield conn
    finally:
        conn.close()  # Ensure connection is closed after use

async def validate_input(data: Dict[str, Any]) -> bool:
    """
    Validate incoming data for the log search pipeline.
    
    Args:
        data: Input data dictionary to validate.
    Returns:
        True if valid.
    Raises:
        ValueError: If validation fails.
    """
    if 'log_id' not in data:
        raise ValueError('Missing log_id')
    return True

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

async def fetch_data(log_id: str) -> Dict[str, Any]:
    """
    Fetch log data from the database by log_id.
    
    Args:
        log_id: The ID of the log to fetch.
    Returns:
        Log data as a dictionary.
    Raises:
        Exception: If data fetching fails.
    """
    async with get_db_connection() as conn:
        with conn.cursor() as cursor:
            cursor.execute('SELECT * FROM logs WHERE id = %s', (log_id,))
            result = cursor.fetchone()
            if not result:
                raise Exception('Log not found')
            return dict(result)

async def transform_records(data: Dict[str, Any]) -> Dict[str, Any]:
    """
    Transform log data for processing.
    
    Args:
        data: The log data to transform.
    Returns:
        Transformed data dictionary.
    """
    # Here, implement any transformation logic needed
    return data

async def call_ocr_service(data: Dict[str, Any]) -> Dict[str, Any]:
    """
    Call the OCR service to extract text from images in the log.
    
    Args:
        data: The data containing image URLs.
    Returns:
        Extracted text data.
    Raises:
        Exception: If OCR service call fails.
    """
    async with httpx.AsyncClient() as client:
        response = await client.post(Config.ocr_service_url, json=data)
        response.raise_for_status()  # Raises an HTTPError for bad responses
        return response.json()

async def save_to_db(log_data: Dict[str, Any]) -> None:
    """
    Save processed log data back to the database.
    
    Args:
        log_data: Processed log data to save.
    Raises:
        Exception: If saving fails.
    """
    async with get_db_connection() as conn:
        with conn.cursor() as cursor:
            cursor.execute('INSERT INTO processed_logs (data) VALUES (%s)', (log_data,))
            conn.commit()

async def handle_errors(error: Exception) -> None:
    """
    Handle errors gracefully and log them.
    
    Args:
        error: The error to handle.
    """
    logger.error(f'An error occurred: {error}')  # Log the error

async def process_batch(log_ids: List[str]) -> None:
    """
    Process a batch of logs by their IDs.
    
    Args:
        log_ids: List of log IDs to process.
    """
    for log_id in log_ids:
        try:
            logger.info(f'Processing log ID: {log_id}')
            data = await fetch_data(log_id)
            validated_data = await validate_input(data)
            sanitized_data = await sanitize_fields(validated_data)
            transformed_data = await transform_records(sanitized_data)
            ocr_result = await call_ocr_service(transformed_data)
            await save_to_db(ocr_result)
        except Exception as e:
            await handle_errors(e)  # Handle any errors that occur

if __name__ == '__main__':
    # Example usage
    log_ids_to_process = ['log1', 'log2', 'log3']
    asyncio.run(process_batch(log_ids_to_process))