Adds a 'Regenerate recap' action so corrected speaker names flow into freshly
written summaries/extras (not just find-replaced). regenerate() commits the
corrections (rewrite speakers.json + reconcile voiceprints), re-runs RecapAnalyzer
on the corrected transcript via the gateway LLM, and rewrites recap.json +
transcript.md + recap.html. save() and regenerate() share commitCorrections();
both rebaseline the speaker set afterward so further edits map cleanly. Editor view
gains the button + progress spinner; RecapEditModel takes the gateway baseURL/skipTLS.
52/52 XCTest; builds clean.
Native editor to fix speaker-ID errors after transcription (modeled on recap-relay's
correction UX): rename a speaker in the legend, merge two speakers, or reassign an
individual transcript line. Saving rewrites speakers.json, re-renders transcript.md +
recap.html, and updates the voiceprint memory — so a correction compounds: naming an
"Unknown" speaker teaches that voice for future calls.
- SpeakerEditing (pure, tested): replaceSpeaker (rename = merge-onto-existing),
reassign, netNameMap (compose ops), and remap (apply a name map to a recap's
structured fields + whole-word free text, so summaries/extras update without re-LLM).
- RecapEditModel (@MainActor): loads speakers.json (+ optional recap.json +
cluster_fingerprints.json); on save writes the resolved speakers.json, re-renders,
and reconciles voiceprints — merge keeps the survivor's print; rename/name-an-Unknown
enrolls the cluster's fingerprint under the new name.
- TranscriptEditorView (SwiftUI) + EditorWindow (AppKit window for the LSUIElement app);
menu gains "Edit speakers".
- Pipeline now persists cluster_fingerprints.json (every cluster incl. Unknown) and
recap.json (RecapFile) so the editor can learn voices + re-render offline.
- RecapModels made Codable; TranscriptAssembler exposes allFingerprints;
VoiceprintStore gains enroll() + merge().
52/52 XCTest (6 new, incl. a full rename→artifacts→voiceprint round-trip on disk).
New 'Recap' phase — turns speakers.json into a human-readable recap, leveraging
recap-relay's proven logic/prompts but calling the Spark gateway's OpenAI-compatible
/v1/chat/completions directly (same host/TLS as label-merge; Qwen3-35B). We start
from already-named speakers (label-merge), so recap-relay's speaker clustering +
name-inference are skipped entirely.
- GatewayLLMClient: /v1/chat/completions (JSON mode), model discovery via
/api/endpoints, TLS-skip reuse, 503 retry, sequential.
- RecapAnalyzer: speakers.json → numbered [N] (MM:SS) Name: text transcript →
time-windowed analyze (single window for short calls, 18min/2min overlap for long)
→ stitch/dedup topic sections → meeting extras (TLDR/decisions/action_items/
open_questions/key_quotes). Defensive JSON parsing of LLM output.
- RecapRenderer: writes transcript.md + a self-contained dark-theme recap.html
(topic sections w/ collapsible transcripts, extras panels, speaker color chips,
full timestamped speaker-attributed transcript, print styles).
- SessionController.buildRecap: best-effort after speakers.json (gated by
settings.recapEnabled); surfaces recapURL → menu 'Open recap'. Skips silently if
the gateway has no LLM. Settings toggle added.
Validated END-TO-END on the real Meet session against the live gateway: dual-channel
transcription → 3 topic sections + accurate TLDR + key quotes; 'Go Bitcoin'
correctly attributed to the remote speaker. 46/46 XCTest (10 new).
The backend shipped dual-channel mode; wire the client to it. We already capture
mic (you) and system (others) separately, so send them as two files instead of the
mono mix — fixing the misattribution at the source.
- SparkControlClient: labelMergeDual(mic_file, system_file, self_name, self_vad);
multipart generalized to N files; shared POST/retry/decode extracted.
- SessionPackager.rebasedSelfVadData: chunk-local [{start,end}] for self_vad;
sliceAudio reused for both tracks.
- TranscriptPipeline.process: dual-channel chunking (slice mic+system, rebase
timeline + self_vad per chunk) when system audio is healthy; mono mixed-file
fallback (self folded into the timeline) otherwise.
- VisualCapture.finish: write the full visual_timeline.json (remote + self merged)
but return REMOTE (vision) segments only — self travels via the mic channel.
- TranscriptAssembler: rank mic_channel highest (the user's own track wins).
- VoiceprintStore: store the clean mic_channel self voiceprint.
- SessionController: pass mic/system URLs + remote timeline + channel self-spans +
self_name + systemHealthy; self_vad.json now reflects the channel-verified spans.
Validated END-TO-END against the live backend on the real misattributing session:
'Go Bitcoin' (remote) is now attributed to Unknown_0, NOT the user; the user's own
lines come back source=mic_channel; per-channel ASR recovered fuller remote text.
36/36 XCTest (4 new: self_vad rebase, mic_channel ranking + voiceprint storage).
Grant's insight + proven on real session audio: we capture self (mic) and others
(system) as separate tracks, then throw the separation away by mixing to mono — so
the backend has to re-guess who's who. Analysis of a real call showed the channels
are cleanly separated (envelope corr 0.015, NO echo); Caitlyn's 'Go Bitcoin' was
11.8x louder in system than mic, yet the mono mix + noisy visual named it 'Grant'.
ChannelSelfVAD marks self-speech as windows where the mic is active AND louder than
system (mic > system x1.5). Benefits: (1) self is identified by CHANNEL, not by the
on-screen name — set one name in Settings, no per-platform matching; (2) a remote
speaker (or room echo) can never be mislabeled as self. Computed at finalize from
the two finished WAVs; the live capture path is untouched. Falls back to mic-VAD if
tracks can't be read. SessionController feeds these spans to the backend timeline.
Validated on the real session: 16 self spans; 'Go Bitcoin' (72-74s) correctly
EXCLUDED, Grant's 49.9-53.3s / 62.6-64s correctly INCLUDED. 33/33 XCTest (5 new).
Visual capture falls back to audio-only silently, so the user couldn't tell if
it attached on a real call. SessionInfo now carries visualSegmentCount (nil =
audio-only; a count = visual ran, with that many vision-detected speaker
segments), shown in the menu as '… · N visual segments' or '… · audio-only'.
Makes the pending live-call validation unambiguous.
Visual capture now runs alongside audio: on call start the session picks the
app's adapter, captures the call window on the SAME monotonic clock as the audio
(AudioRecorder.sharedT0Host), and on stop writes visual_timeline.json and hands
the backend the visual segments with mic-VAD self-spans merged. Any visual
failure (no adapter, no window, Screen Recording denied) leaves the session
recording audio-only — the proven path is never blocked or broken.
- CallDetector now emits DetectedCall{app, bundleID, windowID}: the exact
CGWindowID of the matched Meet browser window (native apps → nil → largest).
- VisualCapture wraps VisualObserver + AdapterRegistry, writes visual_timeline.json.
- AudioRecorder.sharedT0Host() exposes the shared t0 for frame alignment.
Hardened per a 3-lens adversarial review (concurrency / failure-isolation /
data-flow), all 6 confirmed findings fixed:
- P0 (critical): startVisual could adopt a stale capture into a DIFFERENT session
(cross-session SCStream leak + visual_timeline.json written to the wrong
folder). Now gated on session identity — generation + recorder ===, still
.recording — with fail-closed adoption; otherwise the stream is cancelled.
- P1: observer captured the browser's largest window, not the detected Meet
window. Now targets the exact CGWindowID (pickWindowIndex, unit-tested),
largest-area only as fallback.
- P2: a startVisual orphaned by a concurrent stop could leak a stream on quit.
inFlightVisual is registered before the await and drained in prepareForTermination.
- P3: trailing visual gap/segment ends could exceed duration_sec. Clamped in
VisualCapture (clampSegments/clampGaps, unit-tested).
- P4: capture pixel size used NSScreen.main scale; now uses the scale of the
display actually hosting the window (OCR clarity on secondary displays).
- VisualObserver.stop() bounds stopCapture() with a 3s timeout (mirrors audio) so
a wedged stream can't hang finalization.
25/25 XCTest pass. Live validation on real calls still pending.
AudioRecorder captures system audio (ScreenCaptureKit) + mic (AVAudioEngine) on a
single serial ioQueue, one shared monotonic t0, time-driven writers (pad gaps /
trim overlaps) so tracks stay aligned, and an energy mic-VAD for 'self' spans.
AudioMixer sums the aligned tracks into mixed_mono_16k.wav. SessionController
drives a serialized start/stop state machine, writes the session folder +
self_vad.json, exposes live level meters, and finalizes on quit.
Hardening from review: ioQueue single-domain (no races), stop() never hangs
(mic-first teardown + bounded stopCapture), layout-agnostic mic deep-copy,
discard-only video output to keep SCStream alive, VAD lockstep on committed
frames, stable signing team in project.yml, single-instance enforcement.
Grant Gilliam