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Document Speaches speech layer, on-device processing limits, latency constraints

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- STT/TTS move to a shared Speaches container (OpenAI-format, GPU, port
  8601 proposed); gateway becomes a thin orchestrator with pluggable
  speech backends (speaches default, embedded fallback)
- Record the on-device ceiling: WakeNet wake word, VAD, ES7210 AEC,
  optional MultiNet fixed commands; open-vocabulary STT permanently out
- Record the real latency bottleneck (Tatlock ~2 min full local flow):
  gateway must stream chat tokens and synthesize sentence-by-sentence
- Plan reply_delta + barge-in protocol additions

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
jpmschweitzer
2026-07-14 17:14:44 +02:00
co-authored by Claude Fable 5
parent 576fd7d237
commit 0886c84d5e
3 changed files with 160 additions and 42 deletions
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AGENTS.md
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@@ -11,8 +11,12 @@ one repo:
- `firmware/` — ESP-IDF (C, LVGL 9) app for the Waveshare ESP32-P4-WIFI6-Touch-LCD-3.4C
(3.4" round 800×800 touch display, dual mics + ES7210 AEC, ES8311 codec + speaker).
- `gateway/` — Python FastAPI container on tower-of-joy doing STT (faster-whisper, GPU),
chat (Tatlock `/v1/chat/completions`), and TTS (Piper). Listens on port **8600**.
- `gateway/` — Python FastAPI container on tower-of-joy orchestrating STT → chat
(Tatlock `/v1/chat/completions`) → TTS. Listens on port **8600**. STT/TTS models live
in a shared **Speaches** container (proposed port 8601, OpenAI-format API), not in the
gateway image; `stt.py`/`tts.py` are pluggable backends (`speaches` default,
`embedded` fallback for dev). See docs/architecture.md — the scaffold currently
implements only `embedded`.
The device and gateway speak a WebSocket protocol defined in `docs/architecture.md`.
**That doc is the contract** — update it in the same change as any protocol edit on
README.md
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@@ -25,28 +25,28 @@ happens on this server.
## Architecture
```
┌─────────────────────┐ WebSocket (PCM audio + JSON events)
│ DeskLock device │◄──────────────────────────────────────────┐
│ (ESP32-P4) │ │
│ │ ┌──────────────────────────────────┴──┐
│ • LVGL face │ │ DeskLock Gateway (container) │
│ • Touch input │ │ on tower-of-joy │
│ • Mic capture+AEC │ │ │
│ • TTS playback │ │ • STT: faster-whisper (GPU) │
└─────────────────────┘ │ • TTS: Piper │
│ • Chat: Tatlock /v1/chat/completions│
└──────────────────┬───────────────────┘
│ HTTP (LAN, :8000)
┌──────────┴──────────┐
│ Tatlock (butler) │
│ tatlock.schweitz. │
│ internal │
└─────────────────────┘
┌──────────────────────┐ WebSocket: PCM audio + JSON events
│ DeskLock device │◄───────────────────────────────────┐
│ (ESP32-P4) │ │
│ • LVGL face │ ┌──────────────────────────────┴───────────┐
│ • touch / wake word │ │ DeskLock Gateway (container, :8600) │
│ • mic capture + AEC │ │ thin orchestrator — no ML dependencies │
│ • TTS playback │ └───────┬──────────────────┬───────────────┘
└──────────────────────┘ │ │ OpenAI-format HTTP
│ ▼
HTTP (LAN) │ ┌─────────────────────────────┐
▼ │ Speaches (container, GPU) │
┌────────────────────┐ │ • STT: faster-whisper │
│ Tatlock (butler) │ │ • TTS: Kokoro / Piper │
│ tatlock.schweitz. │ │ also usable by Open WebUI, │
│ internal :8000 │ │ Home Assistant, … │
└────────────────────┘ └─────────────────────────────┘
```
Tatlock stays a text-only brain. The **gateway** is Tatlock's ears and mouth: it converts
speech to text on the way in and text to speech on the way out, keeping the device firmware
thin (audio transport + face rendering only).
Tatlock stays a text-only brain. The **gateway** orchestrates speech-to-text, chat, and
text-to-speech; the **Speaches** container owns the actual STT/TTS models on the GPU,
shared homelab-wide. The device firmware stays thin: audio transport, wake word, and
face rendering only. Everything runs on the LAN — no cloud in the voice path.
See [docs/architecture.md](docs/architecture.md) for the full design.
@@ -69,4 +69,5 @@ See [docs/architecture.md](docs/architecture.md) for the full design.
- [Waveshare wiki: ESP32-P4-WIFI6-Touch-LCD-3.4C](https://www.waveshare.com/wiki/ESP32-P4-WIFI6-Touch-LCD-3.4C)
- [Official examples repo (waveshareteam/ESP32-P4-WIFI6-Touch-LCD-XC)](https://github.com/waveshareteam/ESP32-P4-WIFI6-Touch-LCD-XC)
- [BSP component: waveshare/esp32_p4_wifi6_touch_lcd_xc](https://components.espressif.com/components/waveshare/esp32_p4_wifi6_touch_lcd_xc)
- [Speaches — self-hosted OpenAI-compatible speech server](https://github.com/speaches-ai/speaches)
- Tatlock backend: `/mnt/media/Projects/tatlock` — https://tatlock.schweitz.net
docs/architecture.md
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## Goal
A always-on, glanceable butler face in the living room. You speak to it; it relays your
An always-on, glanceable butler face in the living room. You speak to it; it relays your
words to Tatlock and speaks the reply back, with a face that reflects what it's doing
(idle, listening, thinking, speaking). It is deliberately a *thin* endpoint: all
intelligence lives in Tatlock, all heavy audio processing lives in the gateway.
intelligence lives in Tatlock, all heavy audio processing lives server-side on
tower-of-joy. Everything is local — no audio, transcript, or reply ever leaves the LAN.
## System overview
```
┌──────────────────────┐ WebSocket: PCM audio + JSON events
│ DeskLock device │◄───────────────────────────────────┐
│ (ESP32-P4) │ │
│ • LVGL face │ ┌──────────────────────────────┴───────────┐
│ • touch / wake word │ │ DeskLock Gateway (container, :8600) │
│ • mic capture + AEC │ │ thin orchestrator — no ML dependencies │
│ • TTS playback │ └───────┬──────────────────┬───────────────┘
└──────────────────────┘ │ │ OpenAI-format HTTP
│ ▼
HTTP (LAN) │ ┌─────────────────────────────┐
▼ │ Speaches (container, GPU) │
┌────────────────────┐ │ • STT: faster-whisper │
│ Tatlock (butler) │ │ • TTS: Kokoro / Piper │
│ tatlock.schweitz. │ │ also usable by Open WebUI, │
│ internal :8000 │ │ Home Assistant, … │
└────────────────────┘ └─────────────────────────────┘
```
Tatlock stays a text-only brain. The **gateway** orchestrates Tatlock's ears and mouth;
the **speech layer** (Speaches) owns the actual STT/TTS models on the GPU.
## Components
@@ -17,7 +42,8 @@ Responsibilities:
`waveshare/esp32_p4_wifi6_touch_lcd_xc` BSP). Face states:
- `idle` — subtle animation + clock (it's a desk clock when nobody's talking to it)
- `listening` — visual feedback that the mic is hot
- `thinking` — Tatlock is working on a reply
- `thinking` — Tatlock is working on a reply (this state earns its keep; see
[Latency budget](#latency-budget--streaming))
- `speaking` — mouth/waveform animation synced to TTS playback
- **Audio capture**: dual mics through the ES7210 (hardware echo cancellation reference
from the playback path), 16 kHz 16-bit mono PCM.
@@ -25,33 +51,103 @@ Responsibilities:
- **Transport**: a single WebSocket to the gateway carrying binary PCM frames plus JSON
control events (`state`, `transcript`, `reply_text`, errors). Device reconnects with
backoff; face shows a disconnected state when the gateway is unreachable.
- **Interaction**: phase 1 is touch-to-talk (tap the face). Phase 2 adds esp-sr WakeNet
wake word on the P4 so the interaction is hands-free.
**On-device speech processing — what runs on the P4 and what deliberately doesn't.**
The P4 (dual RISC-V @ 400 MHz, 32 MB PSRAM) has a hard ceiling; the split is:
| On-device (planned) | Why |
|---------------------|-----|
| Wake word — esp-sr WakeNet (phase 2) | Must be local: always-listening audio should never leave the device until the wake word fires |
| Voice-activity detection (end-of-utterance) | Removes tap-to-stop; cheap on-device |
| Echo cancellation — ES7210 hardware | Enables barge-in while TTS is playing |
| esp-sr MultiNet fixed commands (optional, later) | ~200-phrase closed vocabulary recognized entirely on-device — instant "lights off"-style commands with zero round trip |
Full open-vocabulary STT on-device is **out of scope permanently**: even whisper-tiny
needs hundreds of MB and orders of magnitude more compute than the P4 offers. Anything
open-ended goes to the speech layer.
Non-responsibilities: no STT, no TTS, no conversation state. If it's not rendering,
recording, or playing, it doesn't belong in firmware.
### 2. Gateway (`gateway/`) — container on tower-of-joy
### 2. Gateway (`gateway/`) — container on tower-of-joy, port 8600
A FastAPI service bridging device audio to Tatlock text:
A FastAPI service bridging device audio to Tatlock text. It owns *orchestration*, not
models — the container stays a slim pure-Python image with no CUDA/ML dependencies:
1. Accepts the device WebSocket (`/ws/voice`).
2. Buffers inbound PCM until end-of-utterance (client-signalled in phase 1; VAD later).
3. **STT**: faster-whisper on the RTX 2080 Ti.
4. **Chat**: POSTs the transcript to Tatlock `/v1/chat/completions`
(`http://tatlock.schweitz.internal:8000`, OpenAI-compatible, streaming). Maintains the
conversation id so follow-ups have context.
5. **TTS**: Piper (fast, CPU-friendly, local) synthesizes the reply.
6. Streams reply PCM back to the device along with `reply_text` for on-screen display.
3. **STT**: POST to Speaches `/v1/audio/transcriptions`.
4. **Chat**: POST the transcript to Tatlock `/v1/chat/completions`
(`http://tatlock.schweitz.internal:8000`, OpenAI-compatible, **streaming**),
maintaining the conversation history so follow-ups have context.
5. **TTS**: as Tatlock's token stream completes each sentence, POST it to Speaches
`/v1/audio/speech` and forward the PCM immediately — see
[Latency budget](#latency-budget--streaming).
`stt.py` / `tts.py` are pluggable backends selected by config
(`DESKLOCK_STT_BACKEND` / `DESKLOCK_TTS_BACKEND`):
- `speaches` (default) — OpenAI-format HTTP to the shared speech container.
- `embedded` — in-process faster-whisper / Piper. Kept as a fallback so the gateway can
run standalone (dev on a laptop, speech container down), at the cost of a fat image.
> **Status note:** the initial scaffold implements only the `embedded` path; the
> backend switch and Speaches client are the next gateway task.
The gateway is stateless apart from in-flight conversations; it can restart freely.
### 3. Tatlock — existing backend (`/mnt/media/Projects/tatlock`)
### 3. Speech layer — Speaches (container, GPU)
[Speaches](https://github.com/speaches-ai/speaches) (successor to faster-whisper-server)
is a self-hosted, OpenAI-API-compatible speech server: STT via faster-whisper, TTS via
Kokoro/Piper, dynamic model load/offload with a TTL, and a `/v1/realtime` WebSocket API
we may adopt later for streaming transcription.
- **Deployment**: its own stack in `system-admin-toj/containers/stacks/`, GPU-enabled.
Proposed host port **8601** (verified free; register in `CONTAINERS.md` at deploy).
LAN-only like the Tatlock internal route — do not expose through NPM without auth.
- **Why a shared layer instead of models inside the gateway**: one GPU-resident model
instance serves the whole homelab. Open WebUI is currently configured with
`AUDIO_STT_ENGINE=openai` / `AUDIO_TTS_ENGINE=openai` (OpenAI *cloud*) — pointing its
audio base URL at Speaches makes it fully local with a config change. Home Assistant
can share it too. Meanwhile the gateway image needs no CUDA and rebuilds in seconds.
- **VRAM budget**: RTX 2080 Ti, 11 GB, shared with Ollama (~3.6 GB in use as of
2026-07). whisper `small` at int8 is <1 GB; Kokoro is a few hundred MB. Speaches'
model TTL offload keeps idle pressure near zero. If VRAM contention ever bites,
faster-whisper `small` on CPU is an acceptable fallback (int8, a few seconds per
utterance).
### 4. Tatlock — existing backend (`/mnt/media/Projects/tatlock`)
Untouched by this project. DeskLock consumes its OpenAI-compatible API over the internal
LAN (port 8000, bypassing the Authentik-protected public route). If device auth is needed
later, the gateway holds the credential — never the firmware.
## Latency budget & streaming
Measured/known numbers that shape the design:
| Stage | Cost |
|-------|------|
| STT (whisper `small`, GPU) | a few hundred ms for a ~5 s utterance |
| TTS (Piper/Kokoro) | faster than realtime |
| **Tatlock, full local flow (gemma4)** | **~35 s Steward analysis warm; ~2 min end-to-end** (per tatlock CLAUDE.md) |
Speech is not the bottleneck — **Tatlock is**, by two orders of magnitude. Constraints
this imposes:
1. **The gateway must consume Tatlock's streaming response and synthesize
sentence-by-sentence**, forwarding audio as each sentence is ready. The device starts
speaking after the first sentence instead of waiting for the full reply. The WS
protocol already supports this: one `audio_start` … PCM … `audio_end` envelope with
chunks arriving as they're synthesized — the device just plays a continuous stream.
2. **The `thinking` face state is a first-class feature**, not decoration — it's what
makes a long Tatlock turn feel intentional instead of broken. Consider progress cues
(e.g. surface Tatlock's reasoning summaries on-screen) later.
3. A **fast lane** may eventually be needed: MultiNet on-device commands for instant
home-automation phrases, and/or a low-latency intent path in Tatlock itself. Out of
scope for now, but don't design it out.
## WebSocket protocol (device ↔ gateway)
Binary frames: raw 16 kHz s16le mono PCM (mic upstream, TTS downstream).
@@ -65,10 +161,16 @@ gateway → device: {"type": "state", "value": "thinking"}
gateway → device: {"type": "transcript", "text": "..."}
gateway → device: {"type": "reply_text", "text": "..."}
gateway → device: {"type": "audio_start", "sample_rate": 16000}
gateway → device: <binary PCM frames>
gateway → device: <binary PCM frames> (may arrive sentence-by-sentence; play as a stream)
gateway → device: {"type": "audio_end"}
```
Planned additions (documented before implemented, here first):
- `reply_delta` (gateway → device): incremental reply text for on-screen streaming while
audio is synthesized.
- An interrupt event (device → gateway) for barge-in during playback (phase 4).
Keep this protocol documented here and mirrored in `firmware/` and `gateway/` constants —
it is the one contract between the two halves of the repo.
@@ -76,11 +178,22 @@ it is the one contract between the two halves of the repo.
- **ESP-IDF native (not Arduino/ESPHome)**: the P4 + MIPI-DSI + esp-sr stack is only
first-class in ESP-IDF; Waveshare recommends it, and the BSP targets it.
- **Gateway owns STT/TTS (not the device)**: the P4 could run small STT models, but
server-side whisper is dramatically better, and Piper voices beat embedded TTS. The
GPU is already there. Wake word is the only speech task that must be on-device.
- **Server-side STT/TTS, device does wake word + VAD + AEC only**: server whisper is
dramatically better than anything embeddable, the GPU is already there, and the P4
physically can't run open-vocabulary STT. Wake word must be on-device (privacy: no
audio leaves the device until it fires).
- **STT/TTS as a shared Speaches service (not embedded in the gateway)**: one model
instance for the whole homelab (DeskLock, Open WebUI, potentially HA), slim gateway
image, models upgradable independently. `embedded` backend retained as a dev/fallback
mode.
- *Rejected — Wyoming protocol containers* (`wyoming-faster-whisper`/`wyoming-piper`):
native to Home Assistant's ecosystem, but Tatlock and Open WebUI already speak
OpenAI format, so Speaches fits the lab better. Revisit only if HA Assist becomes a
first-class consumer.
- *Rejected — cloud STT/TTS*: violates the local-first premise; also adds WAN latency
and per-minute cost.
- **Separate gateway (not extending Tatlock)**: keeps Tatlock's API text-only and clean;
audio concerns (codecs, VAD, streaming) stay at the edge. The gateway is also where a
future second endpoint (kitchen, office) would connect.
audio concerns (codecs, VAD, streaming, sentence segmentation) stay at the edge. The
gateway is also where a future second endpoint (kitchen, office) would connect.
- **Monorepo**: the WS protocol couples firmware and gateway; versioning them together
avoids contract drift.