Recursive AI
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Changelog

OneOcr 1.0.0CHANGELOG.md at 8db430f Markdown

All oneocr docs

All notable changes are listed here. The format follows Keep a Changelog and versions follow Semantic Versioning.

[1.0.0] - 2026-10-31

First release.

Added

  • Local OCR (RecursiveAI.OneOcr): a pure-managed reader for scans, born-digital renders, screenshots and phone photos of flat documents, with no dependency beyond the base class library and RecursiveAI.OneImage. Latin (including the EU languages, Turkish and Vietnamese), Greek and Cyrillic in one recognizer. Page orientation (0/90/180/270) and deskew are on by default.
  • Deterministic output. Text, boxes and confidences are bit-identical on AVX-512, AVX2, 128-bit vectors (SSE and NEON) and the scalar path, and at every degree of parallelism. The numeric rules are specified in docs/spec/numerics.md.
  • The page model (OcrPage, blocks, lines, words, characters, tables, key-value pairs, a Source and a calibrated Confidence on every element) and its versioned oneocr.page JSON, which shares member names with OnePDF's onepdf.extraction.
  • Calibrated confidence. A word's confidence is the probability that the word is exactly right, calibrated per script on held-out data.
  • Local Markdown from the page model: headings, lists, pipe tables, with headers and footers dropped.
  • Document extraction: ExtractInvoice(), ExtractReceipt() and Extract<T>() over a small local model that labels words on the page, so a value always carries the words and boxes it was read from. Invoice fields carry their EN 16931 business-term ids. The model ships in RecursiveAI.OneOcr.Models.Documents.
  • LLM vision (RecursiveAI.OneOcr.Llm): Anthropic, OpenAI, OpenAI-compatible servers, Gemini and Azure OpenAI over a plain HttpClient. Every returned value is checked against the words on the page and comes back Grounded, GroundedNormalized, Derived or Ungrounded. Cost estimates and caps, routing between local models and the LLM, an Offline switch, a redaction hook and no-retention flags. Nothing leaves the machine unless you configure a provider.
  • Fine-tuning (RecursiveAI.OneOcr.Training): recognition and extraction fine-tuning on your own documents, on the CPU, deterministic and resumable, with a review queue for lines the reader and the LLM disagree on.
  • PDF pages (RecursiveAI.OneOcr.Pdf): text-layer words where a page has them, local OCR for scanned regions and image-only pages, one page model.
  • The oneocr command-line tool (RecursiveAI.OneOcr.Tool): ocr, train, eval and review.
  • The model container, a versioned binary format for weights, specified in docs/spec/model-container-v1.md; the bundled recognizer, page detector and language models are embedded in RecursiveAI.OneOcr.Models and checked against their SHA-256 pins on every load.
  • Parsers for model files, images, page JSON, PDFs, review files and LLM responses are bounds-checked, run under limits checked before anything large is allocated, and have fuzz targets. NativeAOT and trimming are supported.

Known limits

  • Not supported: CJK, Arabic and Indic scripts, handwriting, curved-page dewarping and scene text.
  • The README's benchmark tables list every category where a competing engine reads better than OneOcr.
  • A NativeAOT build for x64 needs an instruction-set level of at least x86-64-v3; the package sets it by default. Below it the reader runs its exact scalar path, about a hundred times slower, with the same text.