Add local batch processor for offline PDF accessibility enhancement

[TenthEdict]

Summary

This PR adds a local batch processor module that complements the AWS-based PDF accessibility solution by providing offline batch processing capabilities.

Features

• OCR Enhancement: Adds invisible searchable text layers using Tesseract (via ocrmypdf)
• PDF/UA-1 Preparation: Adds compliance metadata and markers for accessibility
• Batch Processing: Process entire directory trees with folder structure preservation
• Parallel Processing: Multi-threaded processing with ThreadPoolExecutor
• Progress Tracking: Visual progress bar (tqdm) and JSON summary reports
• CLI Interface: User-friendly command-line interface with typer/rich

Use Cases

• Pre-processing PDFs before uploading to AWS S3
• Development and testing workflows
• Offline processing when AWS infrastructure is not available
• High-volume batch jobs with parallel workers

Quick Start

# Install dependencies
cd local_batch_processor
pip install -r requirements.txt

# Batch process a directory
python -m local_batch_processor.cli batch input_folder/ output_folder/ --workers 4

Test plan

• Install dependencies from local_batch_processor/requirements.txt
• Test single file processing with python -m local_batch_processor.cli process
• Test batch processing with python -m local_batch_processor.cli batch
• Verify JSON summary report generation
• Test parallel processing with --workers flag

🤖 Generated with Claude Code