New crates/ai-formatting/src/to_plain_text.rs module with one public
function: to_plain_text(&[Segment]) -> String.
Rules the function enforces:
- each segment's text is whitespace-normalised (any run of unicode
whitespace collapses to a single ASCII space, so tabs, newlines,
and NBSPs never reach the LLM),
- empty and whitespace-only segments are dropped,
- remaining segments are joined with a single ASCII space,
- the joined string is normalised again (so a segment ending in a
space followed by one starting in a space does not produce a double
space) and trimmed end-to-end.
pipeline.rs's inline join is replaced with this call. Whisper's
timestamp fields (Segment.start / .end) are carried separately and
never reach the LLM by construction — the "timestamps stripped"
half of brief item #29's acceptance falls out of using Segment.text
alone. The work the module actually adds is whitespace discipline
and the tested boundary (empty input, empty-only input, NBSPs,
pathological whitespace runs, idempotence, double-space at join
boundaries).
Source: Scriberr PR #288 — feeding raw Whisper JSON (with timestamps
and per-segment structure) degraded cleanup quality; plain-text
input raised it back.
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>
kon-llm now owns a real LlamaBackend + LlamaModel, with three Qwen3 tiers
(1.7B Q4, 4B-Instruct-2507 Q4, 14B Q5) selectable per hardware. Downloads
are resumable with SHA-256 verification and stored under ~/.kon/models/llm.
Engine exposes three high-level surfaces — all greedy/temp-0, GBNF-constrained
where output shape matters:
- cleanup_text (prompt-injection-hardened system prompt; profile terms
appended as "preserve these spellings" suffix)
- decompose_task (3–7 micro-steps, constrained JSON array)
- extract_tasks (optional-array; empty when no explicit commitments)
post_process_segments now takes an Option<&LlmEngine> and, when loaded and
format_mode != Raw, joins segments → cleanup → replaces segments with the
cleaned text (first segment span). Rule-based path still runs first; LLM
errors log and keep rule-based output.
Tauri commands: recommend_llm_tier, check_llm_model, download_llm_model,
load_llm_model, unload_llm_model, delete_llm_model, get_llm_status,
cleanup_transcript_text_cmd, extract_tasks_from_transcript_cmd,
decompose_and_store (LLM-backed subtasks).
Settings: AI tier toggle (off / cleanup / tasks), model picker with
downloaded/loaded status, download progress events via
kon:llm-download-progress.
Dictation: ensureLlmModelLoaded on mount, cleanupTranscriptIfEnabled after
stop when tier != off and format_mode != Raw, LLM task extraction when
tier=tasks (regex fallback on failure).
Interim: both llama-cpp-sys-2 and whisper-rs-sys statically link their own
ggml, so src-tauri/build.rs emits -Wl,--allow-multiple-definition on Linux.
Replace with a system-ggml shared-lib setup as a follow-up.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ai-formatting:
- rule_based.rs: collapse_repetitions() merges adjacent duplicate
tokens like 'I I can' -> 'I can' and 'think think that' -> 'think
that'. Normalises case and punctuation before comparison.
- pipeline.rs: post_process now calls collapse_repetitions when
format_mode is Clean or Smart. Added unit coverage.
audio:
- capture.rs: replace the seven deprecated cpal DeviceTrait::name()
call sites with a device_display_name() helper that uses the
non-deprecated description() path. Keeps identical behaviour,
silences compile warnings, ready for cpal upgrade.
Addresses the 'Christ. Christ.' live-transcription boundary duplicate
Jake saw during Group 1 dogfooding. Does not fix all cross-chunk
overlap cases (see live.rs OVERLAP_SAMPLES for the root cause) but
catches the common stutter pattern at post-processing.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- Normalise BRITISH_REPLACEMENTS: remove baked-in \b from entries so all
entries are plain base words; the function adds boundaries uniformly
- Replace O(n*m) while-loop double-space removal with single-pass collapse
- Add debug_assert! documenting ASCII assumption for byte-indexed suffix slicing
- Expand llm_client.rs module-level doc comment
- Run cargo fmt on ai-formatting crate
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
