Ruby bindings for the redact-ner Rust crate. Provides Named Entity Recognition (NER) for PII detection backed by the ONNX Runtime.

Early MVP. Wraps the upstream NerRecognizer API surface: from_file, analyze, available?, supports_language?, supported_entities, plus configuration accessors.

The gem ships a native Rust extension built via rb_sys. You need:

• Ruby >= 3.0
• A working Rust toolchain (rustc and cargo, stable)
• The ONNX Runtime shared library available at runtime (see below)

bundle install
bin/rake compile   # or: bundle exec rake compile

Note: invoke rake via bin/rake (a bundler binstub) or bundle exec rake. Running plain rake will fail because the globally installed rake conflicts with the bundle-locked version.

The precompiled x86_64-linux-musl and aarch64-linux-musl gems link the C++ runtime libstdc++ dynamically, so it must be present at load time. Bare Alpine/distroless images do not ship it — install it first, e.g. apk add --no-cache libstdc++ on Alpine. glibc images (e.g. Debian slim) already include it.

redact-ner uses the ort crate with the load-dynamic feature, which means the ONNX Runtime shared library is looked up at runtime, not at link time. You must point ORT_DYLIB_PATH to a libonnxruntime.so / .dylib / .dll compatible with the upstream crate.

Example (Linux):

export ORT_DYLIB_PATH=/path/to/onnxruntime-linux-x64-1.20.0/lib/libonnxruntime.so.1.20.0

Upstream redact-ner does not raise when a model or tokenizer cannot be loaded. Recognizer.from_file always returns a recognizer object; if the ONNX session or tokenizer fails to initialize (model file missing, ORT_DYLIB_PATH unset, etc.), the recognizer is left in an "unavailable" state and #analyze quietly returns an empty array.

If you want a hard failure instead, check #available? immediately:

rec = RedactNer::Recognizer.from_file("model.onnx")
raise "NER model failed to load" unless rec.available?

require "redact_ner"

recognizer = RedactNer::Recognizer.from_file("path/to/model.onnx")

results = recognizer.analyze("John Doe works at Acme Corp in New York", "en")
results.each do |r|
  puts "#{r.entity_type}\t#{r.start}..#{r.end}\t#{r.score.round(3)}\t#{r.text}"
end

analyze returns an array of RedactNer::Result, which is a Struct with the following attributes:

Other methods:

recognizer.available?              # => true if a model + tokenizer were loaded
recognizer.supports_language?("ja") # => true / false
recognizer.supported_entities      # => ["PERSON", "LOCATION", ...]
recognizer.name                    # => "NerRecognizer"
recognizer.min_confidence          # => 0.7
recognizer.max_seq_length          # => 512
recognizer.model_path              # => the path you passed in

This gem does not bundle models. Use the scripts/export_ner_model.py helper from the upstream censgate/redact repository to export a HuggingFace NER model to ONNX. Place the resulting model.onnx, tokenizer.json, and config.json in a single directory and pass the .onnx path to Recognizer.from_file.

bundle install
bin/rake compile
bin/rake test

Releases are automated. To cut a release:

1. Run the Release Prep workflow (Actions → Release Prep → Run workflow), choosing the bump level (patch/minor/major). It bumps lib/redact_ner/version.rb, rolls CHANGELOG.md from GitHub-generated notes, opens a Release PR, and creates a draft GitHub Release.
2. Review/edit the Release PR (and the draft Release notes) and merge it. Merging auto-creates and pushes the vX.Y.Z tag.
3. The tag triggers the Release workflow: it builds the 5 precompiled gems + source gem, then the publish job waits for approval on the rubygems GitHub Environment. Approve it to publish to RubyGems and un-draft the GitHub Release with the gem assets attached.

To abort before publishing, close the Release PR without merging and delete the release/vX.Y.Z branch and the draft Release.

Licensed under either of

• Apache License, Version 2.0 (LICENSE-APACHE)
• MIT license (LICENSE-MIT)

at your option. The upstream redact-ner crate is Apache-2.0.