import os import pandas as pd from utils import clean_text, setup_logger logger = setup_logger('document_processor') # تم تعديل القيم الافتراضية هنا لتناسب النصوص الطويلة def split_into_chunks(text, chunk_size=1000, overlap=200): """ Split text into overlapping chunks Args: text: The text to split chunk_size: Number of characters per chunk (Zidnah to 1000) overlap: Number of characters to overlap (Zidnah to 200) """ chunks = [] start = 0 text_length = len(text) while start < text_length: end = start + chunk_size chunk = text[start:end] # Try to break at sentence boundary for better context if end < text_length: # Look for sentence endings last_period = chunk.rfind('.') last_question = chunk.rfind('؟') # Arabic question mark last_exclamation = chunk.rfind('!') last_newline = chunk.rfind('\n') # Find the best break point break_point = max(last_period, last_question, last_exclamation, last_newline) # Only break if we're past halfway through the chunk # This ensures we don't create very small chunks if break_point > chunk_size * 0.5: chunk = chunk[:break_point + 1] end = start + break_point + 1 chunk = chunk.strip() if chunk: # Only add non-empty chunks chunks.append(chunk) # Move start pointer, ensuring we overlap # If we reached the end of text, break to avoid infinite loop if start >= end - overlap: start = end else: start = end - overlap return chunks def load_single_document(file_path, chunk_size=1000, overlap=200): """ Load a single document and split it into chunks Args: file_path: Path to the .txt file chunk_size: Size of each chunk in characters (Default: 1000) overlap: Overlap between chunks in characters (Default: 200) """ try: with open(file_path, 'r', encoding='utf-8') as file: content = clean_text(file.read()) if not content: logger.warning(f"Empty content in {file_path}") return pd.DataFrame() # Split into chunks using the new sizes chunks = split_into_chunks(content, chunk_size, overlap) # Create dataframe with chunks documents = [] for i, chunk in enumerate(chunks): documents.append({ 'path': file_path, 'chunk_id': i, 'total_chunks': len(chunks), 'content': chunk, 'content_length': len(chunk) }) logger.info(f"Loaded {os.path.basename(file_path)}: {len(chunks)} chunks") return pd.DataFrame(documents) except Exception as e: logger.error(f"Error reading {file_path}: {e}") return pd.DataFrame()