v0.1.0

Offline English SQLite word prediction for embedded applications and CLI use.

• Model en-aac-oanc-v1: 21,674 words and 539,151 n-grams, including the evaluated AAC/OANC corpus mixture.
• Contextual word completion, separate local personal learning, transactional imports/reset, and explicit production model validation.
• Native macOS Apple Silicon, Windows x64 and Linux x64 CLI ZIPs; platform-independent model ZIP with provenance, evaluation reports and corpus attribution.
• All release CI checks and downloaded-package smoke tests pass on macOS, Windows and Linux. Release assets and their internal checksums were verified before publication.

Download the English model ZIP and the CLI ZIP for your platform into separate directories. Check each outer .sha256, then run the included verify_bundle.py against the extracted files. Applications can consume the Rust library directly at this release commit.

CLI executables are unsigned. Linux binaries require compatible GNU libc. Personal databases are unencrypted and must stay local. Corpus terms are separate from MIT code licensing; retain the included attribution and notices, including the documented distinction between OANC's current publisher grant and historical notice. Scores and AAC test results are not clinical suitability claims.

See README and docs/production.md for usage, limitations and integration guidance.