Meet2Notes 0.9.0

Nemotron 3 becomes the default diarization engine for fresh installations.
This release adds cached voice matching, Bonsai 8B for smaller GPUs, remote
model presets, and flexible context with provider-aware prompt caching.

AI models, context and caching

• Add automatic context sizing for local and remote AI engines, with separate
  output limits and full remote attachments validated by the provider. Share
  stable notes/chat prefixes across engines, enable supported provider cache
  hints, and retain larger resident local windows for follow-up cache reuse.
  See docs/automatic-context-cache.md for limits and validation.

• Add shared OpenAI, Anthropic and Gemini model presets to AI Engine and Live
  Assistant LiteLLM settings, retaining Custom model IDs and manual endpoints.
  Update the minimum LiteLLM version to 1.103.1 for the current model catalog.

Installation and speaker recognition

• Default fresh installations to Nemotron 3 diarization, including its private
  runtime and saved-voice embedding model. Preserve existing user selections.

• Automatically choose Bonsai 8B 1-bit with 8K initial context on compatible
  NVIDIA GPUs with 3–7 GB VRAM; retain LFM below 3 GB and existing 27B tiers.

• Save bounded voice identity samples from separate long interventions, skipping
  their first three seconds and detected overlaps. Use centered shorter speech
  only when needed, retain complete speaker audio exports, and invalidate previous
  matching caches when the sampling policy changes.

• Add optional Bonsai 8B 1-bit (1.16 GB), with pinned native runtime installation,
  an 8K starting context and a separate 65,536-token model ceiling for notes and
  assistant requests.

• Cache saved-voice and meeting-speaker embeddings locally, invalidating them when
  source audio, diarization or the embedding model changes. Compare cached vectors
  without loading the embedding model on repeat runs.

• Sample up to 30 seconds of distributed voice fragments per speaker, excluding
  overlap, with up to 60 seconds for uncertain matches. Keep ambiguous speakers
  unnamed and expose matching progress, cancellation and phase timings.

• Add optional NVIDIA Nemotron 3 Diarization with CPU/CUDA selection, automatic
  detection of up to eight speakers, bounded audio windows and a speaker cache
  that persists across windows and resets for each recording.

• Install its pinned Transformers preview in a private runtime; reuse the
  existing saved-voice embedding/cosine matcher, model unloading, and cancellation.

• Report analyzed audio duration throughout diarization and expose the engine
  in Settings and meet2notes-models --models nvidia-nemotron-3-diarization.

Validation and practical limits

• Real API cache checks succeeded with OpenAI GPT-6 Luna, Claude Sonnet 5.5 and
  Gemini 3.5 Flash-Lite. Native Bonsai reuse was also verified. Gemini reused only
  part of the prefix; no provider cache hit or latency is guaranteed. See
  context and cache validation.
• The latest ITV Nemotron run matched all eight saved voices in 7.873 seconds;
  a cached repeat took 0.098 seconds. Profiles came from the same recording,
  so this does not establish recognition accuracy on new recordings.
• Bonsai 8B memory checks include a constrained Linux environment, not a physical
  RTX 3050 Mobile benchmark. Long-context answer-quality limitations are recorded
  in the validation report.

Updating to 0.9.0

• Stop the application before updating and restart afterwards. Windows users can
  run update.bat or install-update.bat; Pinokio users can select Update.
  Source installations should pull the release and rerun ./install.sh with
  their existing storage/backend options.
• Meetings, recordings, saved voices, custom storage and existing model choices
  are preserved. New defaults do not automatically replace a saved engine.
• To adopt Nemotron 3 or Bonsai 8B, select/install it in Settings, or apply the
  recommended audio profile explicitly. Initial downloads include the private
  runtime and required model assets; LLM installation does not generate a test answer.
• Automatic context is enabled by default unless a previous manual/Bonsai
  preference disabled it. Disable it in AI Engine or Live Assistant to retain
  a fixed budget. Provider limits and available memory still apply.
• Voice embedding caches are rebuilt when source audio, model or sampling policy
  changes. Existing saved voice WAVs are retained; re-save a noisy voice sample
  to apply the new interior selection to its audio.
• LiteLLM is upgraded to at least 1.103.1 by the normal dependency update.
  No manual database migration is required. See
  safe updates.