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Calliop v0.1.7

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@github-actions github-actions released this 22 Jun 23:44

Calliop v0.1.7

Feature release — achievements and gamification, a more reliable dictation pipeline, and improved LLM cleanup fidelity.

Changes

Achievements

  • Achievements view in the sidebar with category filters, progress bar, and unlock cards (EN/FR)
  • Unlock queue — toast-style notifications when new achievements are earned
  • Local tracking — milestones, streaks, speed, explorer, learner, and secret achievements evaluated offline from dictation activity
  • Achievements unlock as you dictate, explore settings, and build habits — no cloud account required

Dictation & pipeline

  • Whisper engine readiness — clearer handling when the STT model is loading or unavailable, with PipelineBusy feedback instead of silent failures
  • Deferred dictation — hotkey presses while the pipeline is busy are queued and retried when ready
  • Pause punctuation — softer handling of mid-dictation pauses so transcripts read more naturally
  • Hardened pipeline path from hotkey through text injection, with improved error recovery

LLM cleanup

  • Fidelity-first system prompt — cleanup preserves your wording more closely while still fixing fillers and punctuation
  • More reliable fallback when the model returns empty or invalid output

UI

  • Restored toolbar actions, stagger reveal animation, and tooltip cleanup on the main view

Installation (Windows)

  1. Download Calliop_*_x64-setup.exe (NSIS) or .msi.
  2. Install WebView2 if needed.
  3. Accept the SmartScreen warning (unsigned binary in v1).
  4. On first launch, the Whisper model downloads (~466 MB).

See docs/installation.md.

macOS / Linux (experimental)

DMG, AppImage, and deb artifacts are provided unsigned and untested for v1. Use at your own risk.

Known limitations

  • Windows binaries are unsigned (SmartScreen)
  • ML models download separately on first use
  • Automatic updates are enabled by default; disable in Settings → Advanced if needed
  • No official macOS/Linux support in v1

License

AGPL-3.0