Clouda PDF v0.2.0

Clouda PDF v0.2.0

First public release of Clouda PDF, an Arabic-first, model-agnostic PDF-to-DOCX runtime with isolated data, training, and model subsystems, aimed at open, self-hostable, independently evaluated Arabic Document AI infrastructure.

Highlights

• Arabic-first PDF-to-DOCX runtime for Arabic, English, and mixed-language documents.
• Trusted born-digital PDF text extraction — embedded text must pass the canonical digital-text trust gate before direct extraction is authorized.
• RTL-aware DOCX generation — valid, editable, text-only DOCX output preserving page order, Arabic Unicode, RTL paragraph direction, footers, and page boundaries.
• Explicit page routing states — pages are classified as digital_text, blank_page, near_blank, pending_ocr_model, or review_required; scanned, image-only, or uncertain pages are kept in explicit review states instead of being presented as OCR output.
• Integrated Clouda Data Factory (clouda_data.factory) — deterministic synthetic Arabic OCR data generation (ingest, Arabic RTL rendering, atomic + composite distortions, QC, exports, JSONL/CSV manifests, seeds, resume, multiprocessing) with factory-* commands in the canonical CLI, a lossless factory-to-canonical-manifest adapter, SIL OFL 1.1 bundled fonts, and Training Experiment Framework dry-run integration. The standalone clouda-data-factory repository is superseded.
• Supporting data and training infrastructure — pre-training dataset preparation (provenance-preserving manifests, conservative Arabic normalization, validation, exact deduplication, leakage-safe splitting, JSONL export), training planning, Results Store, the loopback-only Clouda Lab dashboard, and a published metadata-only 177-page Arabic OCR benchmark (v0.1.0).

Important limitations

• No final trained OCR model is bundled. Image-only scanned pages remain in pending_ocr_model unless a licensed, validated OCR model is actually integrated.
• OCR inference remains disabled by default unless a suitable validated model is integrated.
• A larger 462-page held-out evaluation is in progress and currently paused pending additional compute capacity; production model selection remains open. This release makes no claims about that evaluation.
• Production application accuracy is not claimed.

License

Apache-2.0 applies to original Clouda OCR source code and project materials in this public repository. Third-party datasets, models, and benchmark source materials remain governed by their respective licenses — see LICENSE, NOTICE, and DATA_LICENSES.md.