Files
OCR/openspec/changes/dual-track-document-processing/specs/document-processing/spec.md
egg cd3cbea49d chore: project cleanup and prepare for dual-track processing refactor
- Removed all test files and directories
- Deleted outdated documentation (will be rewritten)
- Cleaned up temporary files, logs, and uploads
- Archived 5 completed OpenSpec proposals
- Created new dual-track-document-processing proposal with complete OpenSpec structure
  - Dual-track architecture: OCR track (PaddleOCR) + Direct track (PyMuPDF)
  - UnifiedDocument model for consistent output
  - Support for structure-preserving translation
- Updated .gitignore to prevent future test/temp files

This is a major cleanup preparing for the complete refactoring of the document processing pipeline.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 20:02:31 +08:00

4.9 KiB

Document Processing Spec Delta

ADDED Requirements

Requirement: Dual-track Processing

The system SHALL support two distinct processing tracks for documents: OCR track for scanned/image documents and Direct extraction track for editable PDFs.

Scenario: Process scanned PDF through OCR track

  • WHEN a scanned PDF is uploaded
  • THEN the system SHALL detect it requires OCR
  • AND route it through PaddleOCR PP-StructureV3 pipeline
  • AND return results in UnifiedDocument format

Scenario: Process editable PDF through direct extraction

  • WHEN an editable PDF with extractable text is uploaded
  • THEN the system SHALL detect it can be directly extracted
  • AND route it through PyMuPDF extraction pipeline
  • AND return results in UnifiedDocument format without OCR

Scenario: Auto-detect processing track

  • WHEN a document is uploaded without explicit track specification
  • THEN the system SHALL analyze the document type and content
  • AND automatically select the optimal processing track
  • AND include the selected track in processing metadata

Requirement: Document Type Detection

The system SHALL provide intelligent document type detection to determine the optimal processing track.

Scenario: Detect editable PDF

  • WHEN analyzing a PDF document
  • THEN the system SHALL check for extractable text content
  • AND return confidence score for editability
  • AND recommend "direct" track if text coverage > 90%

Scenario: Detect scanned document

  • WHEN analyzing an image or scanned PDF
  • THEN the system SHALL identify lack of extractable text
  • AND recommend "ocr" track for processing
  • AND configure appropriate OCR models

Scenario: Detect Office documents

  • WHEN analyzing .docx, .xlsx, .pptx files
  • THEN the system SHALL identify Office format
  • AND route to OCR track for initial implementation
  • AND preserve option for future direct Office extraction

Requirement: Unified Document Model

The system SHALL use a standardized UnifiedDocument model as the common output format for both processing tracks.

Scenario: Generate UnifiedDocument from OCR

  • WHEN OCR processing completes
  • THEN the system SHALL convert PP-StructureV3 results to UnifiedDocument
  • AND preserve all element types, coordinates, and confidence scores
  • AND maintain reading order and hierarchical structure

Scenario: Generate UnifiedDocument from direct extraction

  • WHEN direct extraction completes
  • THEN the system SHALL convert PyMuPDF results to UnifiedDocument
  • AND preserve text styling, fonts, and exact positioning
  • AND extract tables with cell boundaries and content

Scenario: Consistent output regardless of track

  • WHEN processing completes through either track
  • THEN the output SHALL conform to UnifiedDocument schema
  • AND include processing_track metadata field
  • AND support identical downstream operations (PDF generation, translation)

Requirement: Enhanced OCR with Full PP-StructureV3

The system SHALL utilize the full capabilities of PP-StructureV3, extracting all 23 element types from parsing_res_list.

Scenario: Extract comprehensive document structure

  • WHEN processing through OCR track
  • THEN the system SHALL use page_result.json['parsing_res_list']
  • AND extract all element types including headers, lists, tables, figures
  • AND preserve layout_bbox coordinates for each element

Scenario: Maintain reading order

  • WHEN extracting elements from PP-StructureV3
  • THEN the system SHALL preserve the reading order from parsing_res_list
  • AND assign sequential indices to elements
  • AND support reordering for complex layouts

Scenario: Extract table structure

  • WHEN PP-StructureV3 identifies a table
  • THEN the system SHALL extract cell content and boundaries
  • AND preserve table HTML for structure
  • AND extract plain text for translation

Requirement: Structure-Preserving Translation Foundation

The system SHALL maintain document structure and layout information to support future translation features.

Scenario: Preserve coordinates for translation

  • WHEN processing any document
  • THEN the system SHALL retain bbox coordinates for all text elements
  • AND calculate space requirements for text expansion/contraction
  • AND maintain element relationships and groupings

Scenario: Extract translatable content

  • WHEN processing tables and lists
  • THEN the system SHALL extract plain text content
  • AND maintain mapping to original structure
  • AND preserve formatting markers for reconstruction

Scenario: Support layout adjustment

  • WHEN preparing for translation
  • THEN the system SHALL identify flexible vs fixed layout regions
  • AND calculate maximum text expansion ratios
  • AND preserve non-translatable elements (logos, signatures)