Duck all PulseAudio sink-inputs (Firefox, Spotify, etc.) before speech,
crossfade the entry tone over the fading media, then restore volumes
after the exit tone. Uses pactl subprocesses for reliable PipeWire
compatibility — pulsectl-asyncio's native protocol writes are silently
dropped by PipeWire's PA compat layer.
New module media_duck.py with MediaDucker class. Unduck is consolidated
into the consumer's finally block to guarantee restoration on all exit
paths (normal, error, cancel, shutdown).
The same shutdown_timeout was used for both uvicorn handler drain AND
queue.stop() consumer drain — sequential phases sharing Docker's
wall-clock budget. With 30s each, worst case was 60s, exceeding
the 35s stop_grace_period and causing SIGKILL.
Fix: uvicorn gets a fixed 3s drain (handlers just re-raise), queue
gets the full shutdown_timeout. Docker grace = 3 + timeout + 5s safety.
Also adds shutdown observability: startup logs the timing chain,
queue.stop() logs remaining audio vs available budget.
speak() now blocks until playback finishes, reporting progress via SSE
(5% entry tone → 30% synthesis → 35-99% playing → 100% done). Entry
tone fires immediately on call to cover synthesis latency.
Queue shutdown waits for current speech to finish (configurable timeout,
default 30s) before draining pending items — no more mid-sentence
cutoffs on container restart.
Cancellation via cancel_speech() tool or MCP notifications/cancelled
kills pw-play and plays a vinyl scratch tone. Consumer continues to
next item after cancel.
Progress tracking uses a background ticker task instead of
asyncio.wait_for polling — the latter causes stale CancelledError
propagation to the consumer under Python 3.13.
Each project gets a distinct voice from a curated English pool,
assigned via round-robin with gender/accent interleaving for
maximum perceptual contrast between consecutive projects.
- New voice_identity.py: pool filtering, interleaving, persistence
- Round-robin replaces SHA-256 hashing (no collisions until pool
exhaustion at 22 voices)
- Assignments persist to /data/voice-assignments.json across restarts
- speak() and generate_audio() accept optional project= parameter
- MCP roots fallback with 2s timeout for future bidirectional clients
- English-only pool (af_/am_/bf_/bm_/ef_/em_ prefixes)
- af_nicole excluded from auto-assign (whispery), still explicit-ok
- Fix voice blacklist to use full identifiers (am_adam, af_jessica)
Build llama.cpp from source with SM 120 CUDA kernels and FORCE_CUBLAS
for RTX 5070 Blackwell. Rewrite OrpheusEngine to stream tokens via SSE
and decode SNAC in overlapping 28-token batches (4 frames), replacing
the blocking requests+stream:false approach.
Performance: 13.5 → 170-213 tok/s. 100s audio generates in ~48s (2x
faster than realtime). Replaces requests with httpx async client.
Also switch MCP transport to stateless_http mode so container restarts
don't invalidate client sessions.
SNAC + torch no longer load at startup — deferred to first Orpheus
call via double-checked locking. Startup drops from ~13s to 0.5s,
idle RAM reduced by ~200MB. OrpheusEngine constructor no longer
takes snac_model; it self-loads on demand.
CPU-only torch image (~180MB vs 873MB CUDA), PipeWire socket
passthrough for audio playback, SNAC HuggingFace cache volume.
Served at voice.l.supported.systems via caddy-docker-proxy.
