Update server instructions and tool docstring to explicitly tell clients
to call speak() in parallel with other tools rather than blocking on it
alone. Expand CLAUDE.md concurrency section with progress notification
details (ticker interval, message fields, annotation semantics).
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).
Chunked synthesis splits long texts into sentences and pipelines
synthesis with playback — first audio plays within ~1-2s instead of
waiting for full synthesis. Queue supports suppress_exit_tone between
chunks for seamless playback.
Tool annotations (ToolAnnotations) signal behavioral hints to MCP
clients: speak() is openWorldHint=True (physical speakers),
cancel_speech() is destructiveHint=True, read-only tools marked
accordingly.
Progress notifications now include message= strings that tell LLM
clients they can continue working during playback. Server instructions
corrected from "returns immediately" to accurately describe blocking
behavior with parallel-safe guidance. speak() docstring updated to
encourage concurrent tool calls.
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()'s CancelledError handler was calling queue.cancel() which killed
pw-play mid-sentence during container restarts. Now it just re-raises,
letting the consumer finish naturally. Explicit cancel_speech() still
kills playback immediately.
Also override FastMCP's timeout_graceful_shutdown=0 in uvicorn config
so request handlers get shutdown_timeout seconds before cancellation.
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)
Queue-aware exit tones: descending roger beep when queue empties
("over"), ascending standby blip when more items are queued ("standby,
more coming"). Includes quindar-out (2475 Hz) as Apollo-themed
alternative. Configurable via TTS_EXIT_TONE env var.
Also adds CLAUDE.md documenting the full tone system.
Generate 48kHz WAV tones at startup (chirp and apollo/quindar) using
numpy. The queue consumer plays the selected tone before each speech
item via pw-play. Configurable via TTS_ENTRY_TONE env var: chirp
(default), apollo, none, or path to a custom WAV file.
SNAC's convolutional decoder has a receptive field spanning multiple
frames. Batched decode (28 tokens at a time) created boundary
discontinuities that produced muddled audio. Since pw-play waits for
the full WAV anyway, single-pass decode costs only ~2s extra and
produces clean audio.
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.
FastMCP 3.0 Streamable HTTP server exposing Piper (Wyoming/Docker),
Kokoro (ONNX), and Orpheus (Ollama+SNAC) as MCP tools. Includes a
FIFO speech queue so concurrent agents don't talk over each other —
waiting callers get queue position updates via ctx.info().
Tools: speak, generate_audio, list_voices, list_engines
Resource: audio://recent
