OCR/openspec/changes/dual-track-document-processing/tasks.md

Implementation Tasks: Dual-track Document Processing

1. Core Infrastructure

• 1.1 Add PyMuPDF and other dependencies to requirements.txt
  • 1.1.1 Add PyMuPDF>=1.23.0
  • 1.1.2 Add pdfplumber>=0.10.0
  • 1.1.3 Add python-magic-bin>=0.4.14
  • 1.1.4 Test dependency installation
• 1.2 Create UnifiedDocument model in backend/app/models/
  • 1.2.1 Define UnifiedDocument dataclass
  • 1.2.2 Add DocumentElement model
  • 1.2.3 Add DocumentMetadata model
  • 1.2.4 Create converters for both OCR and direct extraction outputs
    • Note: OCR converter complete; DirectExtractionEngine returns UnifiedDocument directly
• 1.3 Create DocumentTypeDetector service
  • 1.3.1 Implement file type detection using python-magic
  • 1.3.2 Add PDF editability checking logic
  • 1.3.3 Add Office document detection
  • 1.3.4 Create routing logic to determine processing track
  • 1.3.5 Add unit tests for detector

2. Direct Extraction Track

• 2.1 Create DirectExtractionEngine service
  • 2.1.1 Implement PyMuPDF-based text extraction
  • 2.1.2 Add structure preservation logic
  • 2.1.3 Extract tables with coordinates
  • 2.1.4 Extract images and their positions
  • 2.1.5 Maintain reading order
  • 2.1.6 Handle multi-column layouts
• 2.2 Implement layout analysis for editable PDFs
  • 2.2.1 Detect headers and footers
  • 2.2.2 Identify sections and subsections
  • 2.2.3 Parse lists and nested structures
  • 2.2.4 Extract font and style information
• 2.3 Create direct extraction to UnifiedDocument converter
  • 2.3.1 Map PyMuPDF structures to UnifiedDocument
  • 2.3.2 Preserve coordinate information
  • 2.3.3 Maintain element relationships
• 2.4 Add Office document direct extraction support
  • 2.4.1 Update DocumentTypeDetector._analyze_office to convert to PDF first
  • 2.4.2 Analyze converted PDF for text extractability
  • 2.4.3 Route to direct track if PDF is text-based
  • 2.4.4 Update OCR service to use DirectExtractionEngine for Office files
  • 2.4.5 Add unit tests for Office → PDF → Direct flow
  • Note: This optimization significantly improves Office document processing time (from >300s to ~2-5s)

3. OCR Track Enhancement

• 3.1 Upgrade PP-StructureV3 configuration
  • 3.1.1 Update config for RTX 4060 8GB optimization
  • 3.1.2 Enable batch processing for GPU efficiency
  • 3.1.3 Configure memory management settings
  • 3.1.4 Set up model caching
• 3.2 Enhance OCR service to use parsing_res_list
  • 3.2.1 Replace markdown extraction with parsing_res_list
  • 3.2.2 Extract all 23 element types
  • 3.2.3 Preserve bbox coordinates from PP-StructureV3
  • 3.2.4 Maintain reading order information
• 3.3 Create OCR to UnifiedDocument converter
  • 3.3.1 Map PP-StructureV3 elements to UnifiedDocument
  • 3.3.2 Handle complex nested structures
  • 3.3.3 Preserve all metadata

4. Unified Processing Pipeline

• 4.1 Update main OCR service for dual-track processing
  • 4.1.1 Integrate DocumentTypeDetector
  • 4.1.2 Route to appropriate processing engine
  • 4.1.3 Return UnifiedDocument from both tracks
  • 4.1.4 Maintain backward compatibility
• 4.2 Create unified JSON export
  • 4.2.1 Define standardized JSON schema
  • 4.2.2 Include processing metadata
  • 4.2.3 Support both track outputs
• 4.3 Update PDF generator for UnifiedDocument
  • 4.3.1 Adapt PDF generation to use UnifiedDocument
  • 4.3.2 Preserve layout from both tracks
  • 4.3.3 Handle coordinate transformations

5. Translation System Foundation

• 5.1 Create TranslationEngine interface
  • 5.1.1 Define translation API contract
  • 5.1.2 Support element-level translation
  • 5.1.3 Preserve formatting markers
• 5.2 Implement structure-preserving translation
  • 5.2.1 Translate text while maintaining coordinates
  • 5.2.2 Handle table cell translations
  • 5.2.3 Preserve list structures
  • 5.2.4 Maintain header hierarchies
• 5.3 Create translated document renderer
  • 5.3.1 Generate PDF with translated text
  • 5.3.2 Adjust layouts for text expansion/contraction
  • 5.3.3 Handle font substitution for target languages

6. API Updates

• 6.1 Update OCR endpoints
  • 6.1.1 Add processing_track parameter
  • 6.1.2 Support track auto-detection
  • 6.1.3 Return processing metadata
• 6.2 Add document type detection endpoint
  • 6.2.1 Create /analyze endpoint
  • 6.2.2 Return recommended processing track
  • 6.2.3 Provide confidence scores
• 6.3 Update result export endpoints
  • 6.3.1 Support UnifiedDocument format
  • 6.3.2 Add format conversion options
  • 6.3.3 Include processing track information

7. Frontend Updates

• 7.1 Update task detail view
  • 7.1.1 Display processing track information
  • 7.1.2 Show track-specific metadata
  • 7.1.3 Add track selection UI (if manual override needed)
    • Note: Track display implemented; manual override via API query params
• 7.2 Update results preview
  • 7.2.1 Handle UnifiedDocument format
  • 7.2.2 Display enhanced structure information
  • 7.2.3 Show coordinate overlays (debug mode)
    • Note: Future enhancement, not critical for initial release
• 7.3 Add translation UI preparation
  • 7.3.1 Add translation toggle/button
  • 7.3.2 Language selection dropdown
  • 7.3.3 Translation progress indicator
    • Note: UI prepared with disabled state; awaiting Section 5 implementation

8. Testing

• 8.1 Unit tests for DocumentTypeDetector
  • 8.1.1 Test various file types
  • 8.1.2 Test editability detection
  • 8.1.3 Test edge cases
• 8.2 Unit tests for DirectExtractionEngine
  • 8.2.1 Test text extraction accuracy
  • 8.2.2 Test structure preservation
  • 8.2.3 Test coordinate extraction
• 8.3 Integration tests for dual-track processing
  • 8.3.1 Test routing logic
  • 8.3.2 Test UnifiedDocument generation
  • 8.3.3 Test backward compatibility
• 8.4 End-to-end tests
  • 8.4.1 Test scanned PDF processing (OCR track)
  • 8.4.2 Test editable PDF processing (direct track)
  • 8.4.3 Test Office document processing
  • 8.4.4 Test image file processing
• 8.5 Performance testing
  • 8.5.1 Benchmark both processing tracks
  • 8.5.2 Test GPU memory usage
  • 8.5.3 Compare processing times

9. Documentation

• 9.1 Update API documentation
  • 9.1.1 Document new endpoints
  • 9.1.2 Update existing endpoint docs
  • 9.1.3 Add processing track information
• 9.2 Create architecture documentation
  • 9.2.1 Document dual-track flow
  • 9.2.2 Explain UnifiedDocument structure
  • 9.2.3 Add decision trees for track selection
• 9.3 Add deployment guide
  • 9.3.1 Document GPU requirements
  • 9.3.2 Add environment configuration
  • 9.3.3 Include troubleshooting guide

10. Deployment Preparation

• 10.1 Update Docker configuration
  • 10.1.1 Add new dependencies to Dockerfile
  • 10.1.2 Configure GPU support
  • 10.1.3 Update volume mappings
• 10.2 Update environment variables
  • 10.2.1 Add processing track settings
  • 10.2.2 Configure GPU memory limits
  • 10.2.3 Add feature flags
• 10.3 Create migration plan
  • 10.3.1 Plan for existing data migration
  • 10.3.2 Create rollback procedures
  • 10.3.3 Document breaking changes

Completion Checklist

• All unit tests passing
• Integration tests passing
• Performance benchmarks acceptable
• Documentation complete
• Code reviewed
• Deployment tested in staging

Future Improvements

The following improvements are identified but not part of this change proposal:

Batch Processing Enhancement

• Related to: Section 3.1.2 (Enable batch processing for GPU efficiency)
• Description: Implement true batch inference by sending multiple pages or documents to PaddleOCR simultaneously
• Benefits: Better GPU utilization, reduced overhead from model switching
• Requirements: Queue management, memory-aware batching, result aggregation
• Recommendation: Create a separate change proposal when ready to implement