New crates/transcription/src/transcriber.rs defines a Transcriber
trait (Send supertrait for spawn_blocking travel) with
TranscriberCapabilities (sample_rate, channels, supports_initial_prompt).
TranscriberCapabilities.sample_rate is load-bearing for the upcoming
progressive WAV writer (#19).
Concrete impls:
- SpeechModelAdapter wraps Box<dyn transcribe_rs::SpeechModel + Send>
for Parakeet (and any future transcribe-rs-backed engine).
- WhisperRsBackend moves its transcribe_sync body into the impl,
widening the signature from &self to &mut self so per-call
WhisperState can be created cleanly through the trait object.
LocalEngine now holds Box<dyn Transcriber + Send>; dispatch in
transcribe_sync collapses from a match to a direct call. Adds
LocalEngine::capabilities() for the WAV-writer.
Cargo feature flag "whisper" (default on) makes whisper-rs, num_cpus,
and the whole whisper_rs_backend module optional. cargo check
--no-default-features -p kon-transcription now builds without pulling
whisper-rs-sys — the escape hatch brief item #6 / #13 called for on
Windows / non-AVX2 / cloud-only builds. load_whisper is cfg-gated
behind the same feature.
src-tauri/src/commands/models.rs load_model_from_disk returns
Box<dyn Transcriber + Send> instead of SpeechBackend; caller chain
(ensure_model_loaded, prewarm_default_model) is unchanged.
transcriber_trait_is_object_safe test lands alongside the trait as a
compile-time witness against future Self-returning / generic-method
additions.
Two new Settings → AI knobs that compose cleanly with what already
shipped (aiTier, LLM model, translator prompt framing).
**B.1 #15 — Named cleanup presets.** LlmPromptPreset enum
(Default / Email / Notes / Code) appends a short context hint onto
the CLEANUP_PROMPT just before generation. Presets shape tone and
structure ("email paragraph", "bulleted meeting notes", "preserve
technical terms") without licensing the content-editing the
translator-not-editor framing forbids. cleanup_transcript_text_cmd
now takes `preset: Option<String>` which runs through the new
LlmPromptPreset::parse (normalises aliases like "meeting-notes",
collapses unknown values to Default).
**A.1 #28 — Sequential-GPU guard.** New LocalEngine::unload drops
the backend + model_id so a subsequent load actually reclaims VRAM.
load_llm_model, load_model, and load_parakeet_model Tauri commands
grow an optional `concurrent: bool` argument. When concurrent is
Some(false), loading LLM first unloads whisper+parakeet, and vice
versa — prevents VRAM OOM on tight-VRAM setups. Default is the
previous parallel behaviour so nothing changes for multi-GB cards.
Transcribe-in-progress paths (transcribe_pcm, transcribe_file, live)
pass None, so mid-dictation model loads don't accidentally tear
down the LLM.
Settings UI (AI section):
- Cleanup preset segmented button + descriptive copy for each option.
- GPU concurrency segmented button with explicit trade-off text
("faster transitions vs fits in tight VRAM").
Frontend wiring:
- settings.llmPromptPreset flows from DictationPage's
cleanupTranscriptIfEnabled into the Tauri command.
- settings.aiGpuConcurrency flows from both DictationPage (auto-load
on record) and SettingsPage (manual load/unload buttons) as
`concurrent: "parallel" === true` to the load commands.
Tests: three new preset cases in crates/ai-formatting/src/llm_client.rs
(parse aliases, suffix non-empty for non-default, default suffix
empty). All 139 existing lib tests still pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Major quality pass on top of Phase 2. Five substantive changes plus
cross-cutting touches across audio, hotkey, transcription, and Tauri
command layers.
Transcription quality
- Long-audio chunking in commands/transcription.rs: Parakeet and large
file transcription now chunk-and-recompose with overlap trimming, so
the live-path chunking advantage extends to file-based workflows.
- Stateful live speech gate in commands/live.rs on top of the earlier
duplicate-boundary filtering — distinguishes start-of-speech from
mid-speech and holds state across chunks.
Auto-learning corrections
- New crates/ai-formatting/src/correction_learning.rs: extracts user
text corrections from viewer edits and proposes additions to the
active profile's vocabulary.
- src-tauri/src/commands/profiles.rs bridge for frontend-driven
confirmation of learned terms.
- src/routes/viewer/+page.svelte hooks the learning path into the
segment-edit flow so corrections feed profile_terms without a
separate 'train this profile' UX.
Transcript profile provenance
- Migration v8 (crates/storage/src/migrations.rs) adds profile_id to
transcripts, defaulting to DEFAULT_PROFILE_ID so existing rows stay
valid.
- crates/storage/src/database.rs: TranscriptRow + CRUD carry profile_id.
- src-tauri/src/commands/transcripts.rs: add_transcript accepts and
persists profile_id.
- DictationPage.svelte + FilesPage.svelte send activeProfileId on
capture so learned corrections are attributed to the right profile.
Cleanup prompt contract
- crates/ai-formatting/src/llm_client.rs hardened: the CLEANUP_PROMPT
now specifies concrete do/do-not rules, ready for a real model-backed
cleanup pass. The llm_client is still a stub — kon-llm remains unwired
— but the prompt shape is final.
Cross-cutting polish
- Minor touches in audio (capture/decode/resample), hotkey (lib/linux/stub),
core, transcription (concurrency/model_manager/local_engine/whisper_rs),
and the rest of src-tauri/src/commands/*: error-path tightening, log
clarity, TS-migration follow-ups (@ts-nocheck additions for incremental
typing).
Verified locally: npm run check, cargo test -p kon-ai-formatting,
cargo test -p kon-storage, cargo test -p kon --lib commands::live::tests,
cargo check — all green.
Scope boundary: kon-llm crate is still a stub; task extraction remains
rule-based. Bundled local-LLM runtime is the next clean step and is not
in this commit.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
transcribe-rs 0.3.10's ParakeetModel::transcribe_raw ignores its
options argument and calls self.infer(samples, &TimestampGranularity::default())
where default is TimestampGranularity::Token — per-subword segments.
That surfaces in Kon as output like 'T Est Ing One , Two , Three . W Ow ,
This Is T Ri Ble .' because DictationPage joins segment texts with ' '.
Introduce a thin ParakeetWordGranularity wrapper that implements
SpeechModel and overrides transcribe_raw to call the concrete
ParakeetModel::transcribe_with() with ParakeetParams { timestamp_granularity:
Some(Word) }. Pre-existing bug unrelated to Phase 2 work — surfaced during
Group 1 dogfooding because Parakeet was being tested for the first time.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Upstream transcribe-rs 0.3.10 added required fields to TranscribeOptions.
Set both to None (use engine defaults).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- LocalEngine wraps transcribe-rs SpeechModel behind Kon's own abstraction
- load_parakeet() and load_whisper() factory functions
- Unified model manager: download with progress callback, check, list, path resolution
- Atomic downloads: .part suffix with rename on completion
- run_inference() encapsulates spawn_blocking threading
- Zero Tauri dependency in this crate (progress via callback, not events)
- transcribe-rs v0.3.2 with onnx + whisper-cpp features
- 4 tests passing, clippy clean
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
