Lumotia

jake/Lumotia

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Author	SHA1	Message	Date
Jake	36efcf2320	feat(onboarding): parakeet-as-default pinned by test; FirstRunPage handles distil ids Parakeet-TDT scores 85 on any GPU-equipped English-capable system (Instant speed + Great accuracy + GPU boost + headroom) vs ~75 for the best distilled Whisper. A new test in recommendation.rs locks this in so future scoring tweaks don't silently regress it. FirstRunPage previously stored settings.modelSize by title-casing a lowercased alias — which worked for Tiny/Base/Small/Medium but produced "Whisper-distil-small-en" for the new distil ids. Swap to an id→label map and pass the raw model id through to download_model/load_model; the backend already accepts full ids via the whisper_model_id fallback. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-04-21 07:41:22 +01:00
jake	95c8d490c3	fix(kon): harden core crate — shared System instance, accurate CPU field, serialisable errors - Share single System::new_all() in probe_system() instead of calling it twice - Rename CpuInfo::core_count to logical_processors (sys.cpus().len() returns logical, not physical) - Add fallback arm to probe_os() for unsupported cfg targets - Add serde::Serialize to KonError for structured frontend error reporting - Annotate dead code (ProviderRegistry, TranscriptMetadata) with #[allow(dead_code)] + TODO comments - Update downstream references in recommendation tests and tauri hardware command Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-03-17 00:19:04 +00:00
jake	6588130e36	feat(kon): add core crate — types, traits, hardware, model registry, recommendation - Value objects: ModelId, EngineName, Megabytes, AudioSamples, Segment, Transcript - KonError enum with thiserror - Constants centralised: audio pipeline, VAD, RAM thresholds, inference threading - SpeechToText and TextProcessor provider traits with ProviderRegistry - Unified model registry (Whisper tiny/base/small/medium + Parakeet CTC int8) - Hardware detection: probe_ram, probe_cpu, probe_gpu (stub), probe_os - Recommendation engine: score_model (pure function), rank_recommendations (sorted) - 5 tests passing, clippy clean Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-03-16 20:27:27 +00:00

Author

SHA1

Message

Date

Jake

36efcf2320

feat(onboarding): parakeet-as-default pinned by test; FirstRunPage handles distil ids

Parakeet-TDT scores 85 on any GPU-equipped English-capable system (Instant
speed + Great accuracy + GPU boost + headroom) vs ~75 for the best distilled
Whisper. A new test in recommendation.rs locks this in so future scoring
tweaks don't silently regress it.

FirstRunPage previously stored settings.modelSize by title-casing a lowercased
alias — which worked for Tiny/Base/Small/Medium but produced
"Whisper-distil-small-en" for the new distil ids. Swap to an id→label map
and pass the raw model id through to download_model/load_model; the backend
already accepts full ids via the whisper_model_id fallback.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-04-21 07:41:22 +01:00

jake

95c8d490c3

fix(kon): harden core crate — shared System instance, accurate CPU field, serialisable errors

- Share single System::new_all() in probe_system() instead of calling it twice
- Rename CpuInfo::core_count to logical_processors (sys.cpus().len() returns logical, not physical)
- Add fallback arm to probe_os() for unsupported cfg targets
- Add serde::Serialize to KonError for structured frontend error reporting
- Annotate dead code (ProviderRegistry, TranscriptMetadata) with #[allow(dead_code)] + TODO comments
- Update downstream references in recommendation tests and tauri hardware command

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-03-17 00:19:04 +00:00

jake

6588130e36

feat(kon): add core crate — types, traits, hardware, model registry, recommendation

- Value objects: ModelId, EngineName, Megabytes, AudioSamples, Segment, Transcript
- KonError enum with thiserror
- Constants centralised: audio pipeline, VAD, RAM thresholds, inference threading
- SpeechToText and TextProcessor provider traits with ProviderRegistry
- Unified model registry (Whisper tiny/base/small/medium + Parakeet CTC int8)
- Hardware detection: probe_ram, probe_cpu, probe_gpu (stub), probe_os
- Recommendation engine: score_model (pure function), rank_recommendations (sorted)
- 5 tests passing, clippy clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-03-16 20:27:27 +00:00

3 Commits