MCP Document Processor

from typing import Dict, Any, Optional import os import logging import PyPDF2 from datetime import datetime import pytesseract import cv2 import numpy as np logger = logging.getLogger(__name__) class DocumentParser: """Utility for parsing different document formats.""" def __init__(self, ocr_enabled: bool = True): self.ocr_enabled = ocr_enabled def parse(self, file_path: str) -> str: """Parse a document and return the text content.""" if not os.path.exists(file_path): logger.error(f"File not found: {file_path}") return "" file_ext = os.path.splitext(file_path)[1].lower() if file_ext == '.pdf': return self._parse_pdf(file_path) elif file_ext in ['.jpg', '.jpeg', '.png', '.tiff', '.tif', '.bmp']: return self._parse_image(file_path) elif file_ext in ['.txt', '.md', '.csv']: return self._parse_text_file(file_path) else: logger.warning(f"Unsupported file format: {file_ext}") return "" def get_metadata(self, file_path: str) -> Dict[str, Any]: """Extract metadata from the document.""" if not os.path.exists(file_path): logger.error(f"File not found: {file_path}") return {} file_ext = os.path.splitext(file_path)[1].lower() file_stat = os.stat(file_path) # Common metadata for all file types metadata = { "filename": os.path.basename(file_path), "file_size": file_stat.st_size, "last_modified": datetime.fromtimestamp(file_stat.st_mtime).isoformat(), "file_type": file_ext[1:] if file_ext.startswith('.') else file_ext } # Add format-specific metadata if file_ext == '.pdf': pdf_metadata = self._get_pdf_metadata(file_path) metadata.update(pdf_metadata) return metadata def _parse_pdf(self, file_path: str) -> str: """Parse a PDF file and extract text.""" try: with open(file_path, 'rb') as file: reader = PyPDF2.PdfReader(file) # Check if PDF has text first_page = reader.pages[0] text = first_page.extract_text() # If no text is found and OCR is enabled, use OCR if not text.strip() and self.ocr_enabled: logger.info(f"No text found in PDF, attempting OCR: {file_path}") return self._ocr_pdf(file_path) # Extract text from all pages full_text = [] for page in reader.pages: full_text.append(page.extract_text()) return "\n".join(full_text) except Exception as e: logger.error(f"Error parsing PDF {file_path}: {str(e)}") return "" def _ocr_pdf(self, file_path: str) -> str: """Perform OCR on a PDF file.""" # This would require converting PDF to images first # This is a simplified implementation return "OCR result would be here" def _parse_image(self, file_path: str) -> str: """Parse an image file using OCR.""" if not self.ocr_enabled: logger.warning("OCR is not enabled, cannot extract text from image") return "" try: # Read the image image = cv2.imread(file_path) # Convert to grayscale gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # Apply thresholding to improve OCR _, threshold = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY) # Perform OCR text = pytesseract.image_to_string(threshold) return text except Exception as e: logger.error(f"Error parsing image {file_path}: {str(e)}") return "" def _parse_text_file(self, file_path: str) -> str: """Parse a plain text file.""" try: with open(file_path, 'r', encoding='utf-8') as file: return file.read() except UnicodeDecodeError: # Try with a different encoding try: with open(file_path, 'r', encoding='latin-1') as file: return file.read() except Exception as e: logger.error(f"Error parsing text file {file_path}: {str(e)}") return "" except Exception as e: logger.error(f"Error parsing text file {file_path}: {str(e)}") return "" def _get_pdf_metadata(self, file_path: str) -> Dict[str, Any]: """Extract metadata from a PDF file.""" try: with open(file_path, 'rb') as file: reader = PyPDF2.PdfReader(file) metadata = { "num_pages": len(reader.pages) } # Extract document info if reader.metadata: for key, value in reader.metadata.items(): if key.startswith('/'): key = key[1:] # Remove the leading slash metadata[key.lower()] = value return metadata except Exception as e: logger.error(f"Error extracting PDF metadata {file_path}: {str(e)}") return {}