conversations come back as conversations

A probe on the torch stage worker (~/dockers/torch-worker) runs beside every
transcription and decides what the recording is: solo dictation returns as
paragraphs exactly as before, several voices return speaker-labeled with
conversation: true. Nobody declares which — the caller cannot know.

Transcription and the worker each get a serial FIFO queue on their own
resource, so the probe costs a solo memo nothing and multi-user traffic
stays fair. The worker is optional and best-effort throughout: unreachable
or failing, everything still transcribes, just never labeled.

Speaker attribution is segment-granularity by maximal turn overlap —
whisper.cpp's own timestamps, no alignment stage. If boundaries prove
sloppy, wav2vec2 alignment returns as a worker endpoint.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

skills/transcribe/SKILL.md

@@ -42,11 +42,18 @@ multipart/form-data:
   file             — the audio file (mp3, wav, m4a, whatever whisper.cpp accepts)
   spokenLanguages  — zero or more, e.g. spokenLanguages=en&spokenLanguages=pt
 
-→ { "text": "…", "detectedLanguage": "en" }
+→ { "text": "…", "detectedLanguage": "en", "conversation": false }
+→ { "text": "Speaker 1: …\n\nSpeaker 2: …", "detectedLanguage": "en", "conversation": true, "speakers": 2 }
 → 400 { "error": "Whisper not configured — PUT /api/transcribe/config first" }
 → 502 { "error": "…" }   — the whisper.cpp server rejected or failed the request
 ```
 
+Nobody declares whether a recording is a conversation — the pipeline finds out. A probe on the
+diarization worker runs alongside transcription; solo dictation comes back as paragraphs exactly as
+before, and a recording with several voices comes back speaker-labeled with `conversation: true`.
+Expect diarized recordings to take longer (roughly half realtime on top of transcription). If the
+worker is down or not configured, everything still transcribes — just never labeled.
+
 `spokenLanguages` only matters when Whisper's own detection is genuinely unsure — it breaks the tie
 toward a language you already know the speaker uses. Pass what you know; pass nothing and detection still
 works, it is just less informed on an ambiguous clip.