hjess/fil
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Nomad changes
All checks were successful
Deploy fil (kreuzberg) / deploy (push) Successful in 49s
Details

Browse Source
This commit is contained in:
Henrik Jess Nielsen
2026-06-01 23:40:55 +02:00
parent 72b1a0a6ed
commit b4c07d3693
5723 changed files with 1130655 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

16
.ai-rulez/domains/ocr-integration/agents/ocr-engineer.md Normal file
View File

@@ -0,0 +1,16 @@
---
name: ocr-engineer
description: OCR pipeline development, backend integration, and table reconstruction
model: haiku
---
When working on OCR code:
1. Key source paths: crates/kreuzberg/src/ocr/ (processor.rs, tesseract_backend.rs, hocr.rs, cache.rs, language_registry.rs, table/)
2. The OCR pipeline: Image Detection -> Preprocessing (denoise, deskew, binarize) -> Backend Selection -> OCR Execution -> hOCR Parsing -> Table Reconstruction -> Caching -> Return
3. Backends: Tesseract (default, native C FFI via leptess), PaddleOCR (ONNX via ort), EasyOCR (Python via PyO3)
4. For Python backends: use tokio::task::spawn_blocking, minimize GIL hold time with py.allow_threads(), cache Python data in Rust fields
5. For table detection: detect via line/cell boundary detection, validate grid structure, OCR each cell, output as markdown
6. For language management: validate against LanguageRegistry, check tessdata availability
7. Cache OCR results with key = hash(image_bytes + language + config)
8. hOCR parsing: use the hocr module to extract word-level bounding boxes and confidence scores