Replaces 22 production eprintln! sites with structured tracing events
across 8 files. Closes Area B of the post-prognosis residuals plan
(docs/superpowers/plans/2026-05-12-engine-slop-residuals.md).
Files touched (22 sites):
- crates/hotkey/src/linux.rs (2) — hotplug watcher degraded-mode warnings
- crates/ai-formatting/src/pipeline.rs (1) — LLM cleanup fallback warning
- src-tauri/src/commands/transcription.rs (1) — chunking dispatch info
- src-tauri/src/commands/diagnostics.rs (1) — crashes-dir setup warning
- src-tauri/src/commands/tasks.rs (1) — malformed feedback row warning
- src-tauri/src/commands/power.rs (3) — App Nap acquire/release/fail
- src-tauri/src/commands/models.rs (5) — Whisper warmup lifecycle
- src-tauri/src/commands/live.rs (8) — session start, chunk dispatch,
per-chunk delivery, inference errors, worker disconnects, listener
loss, status-channel cascade
Levels: error for unrecoverable failures (inference disconnect, panic,
status cascade), warn for recoverable degradation (LLM fallback,
malformed rows, App Nap fail, hotplug watcher fail), info for lifecycle
(session start, chunk processed, App Nap acquire/release, warmup
complete, chunking dispatch), debug for per-chunk noise (speech-gate
skip, chunk dispatch).
Two new dependencies and two new filter targets:
- tracing = "0.1" added to crates/hotkey and crates/ai-formatting
- Default EnvFilter in src-tauri/src/lib.rs::init_tracing extended with
magnotia_hotkey=info,magnotia_ai_formatting=info so the new targets
emit at the default level
Out of scope (intentional, left as-is):
- crates/mcp/src/main.rs — CLI binary, stderr is the log contract
(module docstring) so the JSON-RPC stdout stream stays clean
- crates/*/tests/*.rs and crates/core/examples/tuning_log_demo.rs —
test/example diagnostic output relies on --nocapture stdio semantics
Discovery during sweep (not fixed — separate follow-up): hotkey crate
has 6 existing log:: calls (log::error/warn/info/debug) but the
workspace builds tracing-subscriber without the tracing-log feature, so
those events are currently silent. Worth a follow-up to either add the
tracing-log bridge or migrate hotkey's existing log:: calls to
tracing::.
Verification:
- cargo fmt --all
- cargo check --workspace --all-targets — clean
- cargo test --workspace — 330+ tests, zero failures
- rg eprintln! src-tauri/src/commands/ crates/hotkey/src/ crates/ai-formatting/src/ — zero hits
Pre-existing working-tree churn in crates/llm/, src/lib/pages/,
src/lib/utils/saveMarkdown.ts and the untracked phase10a dogfood notes
deliberately left unstaged per Jake's instruction.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Replace all instances of the legacy product names "Kon" and "Corbie" with
"Magnotia" across user-facing copy, code identifiers, package names, bundle
ids, file paths, and documentation. Preserves the unrelated "konsole" (KDE
terminal) reference and the parent CORBEL company name.
- Renames 10 Rust crates (kon-* → magnotia-*) and the tauri binary
- Updates package.json, tauri.conf.json (productName + identifier)
- Renames CSS classes (kon-rh-* → magnotia-rh-*) and animations
- Renames brand and roadmap docs
- Regenerates Cargo.lock and package-lock.json
Verified: svelte-check passes; pure-rust crates compile under new names.
2026-04-22 review MINORs and NITs:
- crates/core/src/providers.rs: delete entire module. SpeechToText /
TextProcessor / ProviderRegistry were forward-looking traits that
never got wired — the Transcriber trait in kon-transcription
(A.2 #13) has since superseded SpeechToText, and the Registry
pattern was redundant against LocalEngine. Keeping them as dead
public surface signalled future direction that is no longer
accurate.
- crates/core/src/types.rs: delete TranscriptMetadata. Forward-
looking struct with an unfulfilled TODO; storage has evolved
independently through v7/v8 migrations without adopting it.
- crates/ai-formatting/src/llm_client.rs: remove #[allow(dead_code)]
from CLEANUP_PROMPT and format_dictionary_suffix. Both are
actively called; the suppressions would hide future genuine
dead-code warnings in this regression-sensitive prompt file.
- src-tauri/src/commands/live.rs: remove #[allow(dead_code)] from
LiveStatusMessage. Every variant (Warning, Overload, Error,
Finished) is constructed in the module today.
- README.md: update kon-transcription row from "SpeechToText
trait" to "Transcriber trait" and mention the new streaming/
module.
Workspace test gate green (225 lib tests across all crates).
Review feedback (MINOR): char::is_whitespace returns false for
zero-width format codepoints (U+200B ZWSP, U+200C ZWNJ, U+200D ZWJ,
U+2060 WORD JOINER, U+FEFF ZWNBSP / BOM). The original normalise
pass let them through to the LLM where they waste tokens without
contributing any natural-language content.
Makes the decision explicit: these chars STRIP entirely rather than
collapse to a space. Collapsing would silently insert a word break
where the source had none ("hello<FEFF>world" → "hello world"
would merge two words into a space-separated pair that the original
author did not intend). Stripping preserves the original token
boundaries and drops the invisible noise.
Three new tests:
- zero_width_format_chars_strip_entirely — exhaustive coverage of
all five handled codepoints.
- zero_width_chars_do_not_break_adjacent_whitespace_collapsing —
"hello <FEFF> world" still collapses to "hello world" (the
strip does not leave behind an artefact that breaks the whitespace
collapse pass).
- leading_bom_is_stripped — a BOM at segment start, the common
artefact pattern when Whisper consumes an encoded file.
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>
ufal/whisper_streaming #161 documents the classic Whisper streaming
failure: on ambiguous audio the model falls into a prompt loop,
cascading a single token for 10+ words ("I I I I I I I I I I I…").
The chunk-boundary duplicate detector in live.rs doesn't catch
this — the repeat is within a single chunk, and the text is
technically novel so FTS is happy to keep it.
Fold the detection into is_hallucination as a third pass (after
HALLUCINATION_MARKERS substring-match and HALLUCINATION_TRAIL_PHRASES
exact-match). has_consecutive_repetition walks the token stream
(whitespace-split, lowercased) and returns true when any run of
≥REPETITION_RUN_THRESHOLD (4) identical tokens is found.
Threshold chosen deliberately: three consecutive matches appear in
normal speech ("no no no, that's wrong"), four almost never does.
Tests pin both sides — "I I I I I" detected, "no no no" allowed,
alternating patterns ("I am I am I am I am") allowed regardless of
length.
Phrase-level repetition ("thank you thank you thank you thank you")
is a documented companion failure mode but needs a sliding n-gram
matcher — deferred with a code comment flagging it.
No caller changes: post_process_segments already drops
is_hallucination hits when anti_hallucination is enabled.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Whisper was trained on subtitle corpora, so silence and room tone
trigger caption-style artefacts that the previous three-marker
blocklist ("[blank_audio]", "[music]", "[silence]") didn't catch:
"Thanks for watching!", "Please subscribe.", "ご視聴ありがとうござ
いました", "♪♪♪", etc. Documented in WhisperLive #185 / #246 and
ufal/whisper_streaming #121 as the top streaming-transcript-quality
issue after chunk-boundary repeats.
HALLUCINATION_MARKERS widens from 3 to 16 entries: all common
bracketed non-speech tags (applause / laughter / inaudible /
background noise / sounds), parens variants, and musical notation
(♪ / ♫). Still contains-match so the marker triggers even when
Whisper wraps it in other noise.
HALLUCINATION_TRAIL_PHRASES (renamed from AUTO_THANKS_PHRASES) jumps
from 4 to ~30 entries: YouTube sign-offs, subtitle-credit leakage,
and the two most common non-English variants (Japanese "thanks for
watching" + MBC Korean news sign-off). Stays exact-match so
legitimate dialogue containing "thanks" or "subscribe" mid-sentence
never gets dropped — a new regression test pins that invariant.
The <15-char length gate on trail phrases is removed; some of the
new entries (e.g. "please subscribe to our channel.") are longer.
Exact-match against a known list is safety enough.
No caller changes: post_process_segments already drops segments for
which is_hallucination returns true when anti_hallucination is on.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The previous prompt led with "You are a transcript cleanup assistant"
and listed cleanup rules. That framing quietly licenses the LLM to
treat cleanup as content editing — rephrasing for clarity, summarising
long sentences, "improving" phrasing. That's precisely the failure
mode OpenWhispr / Scriberr / Whispering users complain about ("the
LLM changed my meaning").
New framing lifts Whispering's published baseline: "translator from
spoken to written form — not an editor trying to improve the content."
Adds an explicit rule: do NOT improve, summarise, expand, or rephrase;
faithful written-form translation only, never content editing.
Both load-bearing concerns are now regression-tested — the existing
prompt-injection hardening assertions stay, and a new test pins the
translator framing + explicit no-editing rule against drift during
future refactors.
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>
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>
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>
Security fixes from code audit:
- CSP re-enabled in tauri.conf.json with strict directives
(was null — critical vulnerability)
- XSS fix in viewer highlightText(): HTML entities escaped before
inserting <mark> tags via {@html}
- Removed 3 unwrap() calls in rule_based.rs British English conversion
— replaced with safe let-else guards
- Removed unwrap() on main window lookup in lib.rs setup — now uses
if-let for graceful handling
- Wrapped JSON.parse in DictationPage transcription-result listener
with try/catch
Rebrand cleanup:
- Renamed all localStorage keys from ramble_* to kon_* across
7 files (stores, viewer, float, history)
12 tests passing, clippy clean.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
