Add Wyoming voice stack to pyinfra + landscape doc

- Move piper-compose.yaml / whisper-compose.yaml from repo root into
  pyinfra/framework/compose/{piper,whisper}.yml; bind paths shifted to
  /srv/docker/{piper,whisper}/data on the box.
- deploy.py registers both stacks and provisions the data dirs.
- Homepage gets a "Voice" group with informational tiles (Wyoming has
  no web UI, so tiles show container status without click-through).
- New VoiceModels.md captures the May 2026 STT/TTS landscape, why the
  current Wyoming defaults aren't SOTA, and concrete upgrade paths
  (whisper-large-v3-turbo + faster-whisper-server, Kokoro, Sesame CSM,
  F5-TTS for cloning).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

README.md

@@ -30,7 +30,7 @@ Tailscale. Coding agents, monitoring, voice — all self-hosted.
 | [`Roadmap.md`](Roadmap.md) | What to build on top of the stack to narrow the gap with hosted Claude Code / Cowork / Skills / Design. |
 | [`TODO.md`](TODO.md) | Open questions and follow-ups. |
 | [`testing/qwen3-coder-30b/`](testing/qwen3-coder-30b/) | Small evaluation harness for Qwen3-Coder. |
-| `piper-compose.yaml`, `whisper-compose.yaml` | Voice (TTS / STT) compose files; not yet wired into the pyinfra deploy. |
+| [`VoiceModels.md`](VoiceModels.md) | STT / TTS landscape and upgrade paths from the Wyoming defaults. |
 
 ## Service ports (on `framework`)
 
@@ -46,6 +46,8 @@ Tailscale. Coding agents, monitoring, voice — all self-hosted.
 | `4317` | Phoenix OTLP/gRPC | Trace ingestion |
 | `6006` | Phoenix UI / OTLP/HTTP | Per-trace agent waterfall (also `:6006/v1/traces`) |
 | `8090` | Beszel | Host + container + AMD GPU dashboard |
+| `10200` | Piper | TTS (Wyoming protocol) — used by Home Assistant Assist |
+| `10300` | Whisper | STT (Wyoming protocol) — used by Home Assistant Assist |
 
 ## Quick start
 

VoiceModels.md

@@ -0,0 +1,174 @@
+# Voice models — landscape and upgrade paths
+
+State of the OSS speech stack as of May 2026, with concrete upgrade
+options for the Framework Desktop (Strix Halo iGPU, 64 GB UMA, 256 GB/s
+bandwidth — plenty of headroom alongside a 30 GB code model).
+
+## What's deployed today
+
+- **Whisper** (`tcp://framework:10300`) — `rhasspy/wyoming-whisper`,
+  Wyoming protocol, model `tiny-int8` (~75 MB). Picked for HA defaults,
+  not quality.
+- **Piper** (`tcp://framework:10200`) — `rhasspy/wyoming-piper`,
+  Wyoming protocol, voice `en_US-lessac-medium` (~63 MB, VITS-based).
+
+These are **convenient HA defaults**, not state-of-the-art. The Wyoming
+protocol is from the Rhasspy / Home Assistant ecosystem; it's good for
+HA Assist integration but doesn't expose an OpenAI-compatible HTTP API,
+so direct integration with OpenWebUI / OpenCode / agentic stacks
+requires a wrapper.
+
+## Speech-to-text (STT) landscape
+
+| Model | Provenance | Size | Quality (1–5) | Speed | License | Notes |
+|---|---|---|---|---|---|---|
+| **whisper tiny** | OpenAI (2022) | 75 MB | 2 | very fast | MIT | What we have. Commands OK; dictation rough. |
+| **whisper small** | OpenAI | 480 MB | 3 | fast | MIT | Reasonable middle ground. |
+| **whisper large-v3** | OpenAI (Nov 2023) | 3.1 GB | 5 | slow | MIT | Long the gold standard. |
+| **whisper large-v3-turbo** | OpenAI (Oct 2024) | 810 MB | 5 (≈v3) | ~6× v3 | MIT | **Best Whisper for this box.** Quality of large-v3 at small-model speeds. |
+| **faster-whisper** (any model) | SYSTRAN | same | same as base | ~4× faster | MIT | CTranslate2 reimpl. Drop-in via `fedirz/faster-whisper-server` (OpenAI-compatible). |
+| **distil-whisper** | HF (2024) | ~750 MB | 4 | fast | MIT | Distilled v2/v3. English-only. Lower latency than turbo. |
+| **WhisperX** | m-bain (2024) | + Whisper | 5 + alignment | slow | BSD | Whisper + word-level timestamps + speaker diarization. The right pick for meeting-transcription use cases. |
+| **Parakeet-TDT-0.6B** | NVIDIA (2024) | ~1.2 GB | 5 | fast | Apache 2.0 | Trades blows with Whisper-large on benchmarks. Smaller ecosystem. |
+| **Canary-1B** | NVIDIA (2024) | ~3.5 GB | 5 | medium | CC-BY-4.0 (non-commercial) | Multilingual; license is the catch. |
+| **Moonshine** | Useful Sensors (2024) | ~190 MB tiny / ~620 MB base | 4 | very fast | MIT | Optimized for edge/streaming. Newer, less mature ecosystem than Whisper. |
+
+**Recommendation for this box:** `whisper-large-v3-turbo` via
+`faster-whisper-server`. Best quality/speed/ecosystem balance, OpenAI
+API compat lets non-Wyoming clients use it directly.
+
+## Text-to-speech (TTS) landscape
+
+| Model | Provenance | Size | Quality (1–5) | Voices | License | Notes |
+|---|---|---|---|---|---|---|
+| **Piper** (current) | Rhasspy / Home Assistant | ~60–80 MB / voice | 3 | many pre-trained | MIT | Fast, CPU-friendly, prosody is okay but recognizably synthetic. Default in HA Assist. |
+| **Kokoro-82M** | hexgrad (Jan 2025) | ~340 MB | 4–5 | ~10 English | Apache 2.0 | **Sweet spot for this box.** Tiny model, surprisingly natural. OpenAI-API server: `Kokoro-FastAPI`. |
+| **Sesame CSM-1B** | Sesame AI Labs (open-sourced Mar 2025) | ~3 GB | 5 | conversational, context-aware | Apache 2.0 | Best emotional prosody in OSS. Designed for back-and-forth dialogue, not announcements. |
+| **F5-TTS** | F5-TTS group (2024) | ~1.4 GB | 5 | zero-shot voice cloning from 5–10 s reference | CC-BY-NC-4.0 | Voice cloning state-of-the-art for OSS. Non-commercial license. |
+| **XTTS-v2** | Coqui (2023) | ~1.8 GB | 4 | zero-shot voice cloning | Coqui PL (non-commercial) | Older but well-supported. Tortoise-TTS lineage. |
+| **MeloTTS** | MyShell (2024) | ~140 MB | 4 | multilingual | MIT | Strong multilingual support. |
+| **StyleTTS2** | Yinghao Aaron Li et al. (2023) | ~700 MB | 5 | many | MIT | Very natural; heavier inference path than Kokoro. |
+| **OpenVoice v2** | MyShell (2024) | ~1 GB | 4 | voice cloning + style transfer | MIT | Good cloning quality, more permissive license than F5/XTTS. |
+
+**Recommendation for this box:** **Kokoro** for general TTS (fast,
+high quality, permissive license), **Sesame CSM** layered alongside
+for conversational use cases.
+
+Commercial that nothing OSS reliably beats yet: **ElevenLabs** (general
+quality / voice cloning), **Cartesia Sonic** (real-time streaming
+latency).
+
+## Wyoming vs OpenAI-compatible servers
+
+The protocol choice matters depending on what you want to drive the
+voice stack with.
+
+| Consumer | Wyoming | OpenAI-compatible |
+|---|---|---|
+| Home Assistant Assist | ✅ native | possible via custom integration |
+| Wyoming satellite hardware (ESP32-S3-Box etc.) | ✅ native | ❌ |
+| OpenWebUI Voice (built-in) | ❌ | ✅ |
+| OpenCode / OpenHands voice add-ons | needs wrapper | ✅ direct |
+| Custom Python/Node scripts | possible | trivial |
+
+If you only ever want HA voice assistant, Wyoming is fine. If you also
+want voice in OpenWebUI or to script "hey local model, summarize this
+audio file" outside HA, **add OpenAI-compatible servers alongside** —
+they don't conflict (different ports).
+
+## Use cases for this stack
+
+In rough order of reach for a single-user homelab:
+
+1. **Home Assistant voice assistant.** Point HA's Assist pipeline at
+   Whisper:10300 and Piper:10200, add `wyoming-openwakeword`, plug a
+   Wyoming satellite (S3-Box, M5Stack Atom Echo, RPi). Self-hosted
+   Alexa replacement that talks to your local LLM.
+
+2. **Voice OpenWebUI.** With OpenAI-compatible STT/TTS servers, you can
+   speak to Qwen3-Coder in the browser and hear the response. OpenWebUI
+   has the hooks; Wyoming alone doesn't, hence the wrapper need.
+
+3. **Standalone transcription.** Drop a meeting recording on the box,
+   get a transcript out. Pair Whisper with WhisperX for diarization
+   ("who said what") and timestamps. Useful for podcast transcription,
+   interview indexing, lecture notes.
+
+4. **TTS notifications and announcements.** Pipe automation events
+   through Piper (or Kokoro). Voice notifications throughout the house
+   if you have HA + speakers.
+
+5. **Voice agent loops.** Mic input → Whisper → local LLM → Piper /
+   Kokoro → speakers. The "talk to your local assistant" loop that
+   neither Claude Code nor ChatGPT Code Interpreter natively does.
+   Roadmap.md item #8.
+
+6. **Meeting bots.** With Whisper + a custom integration, drop a bot
+   into Zoom/Google Meet, get a real-time transcript and post-meeting
+   summary from the local LLM.
+
+## Concrete upgrade paths
+
+### Path A — Stay Wyoming, bump model sizes (lowest effort)
+
+Edit the existing compose files to upgrade the models:
+
+- `compose/whisper.yml`: `--model tiny-int8` → `--model large-v3-turbo`
+  (or `medium-int8` for a middle step). Cost: ~810 MB / 1.5 GB on disk,
+  significant quality jump on dictation.
+- `compose/piper.yml`: `en_US-lessac-medium` → another voice. Browse at
+  <https://github.com/rhasspy/piper/blob/master/VOICES.md>.
+
+`./run.sh` from the Mac, recreate the containers on the box. Same
+Wyoming protocol, better quality.
+
+### Path B — Add OpenAI-compatible servers alongside (mid effort)
+
+Stand up `faster-whisper-server` + `Kokoro-FastAPI` as additional
+compose stacks (different ports). Wyoming stays for HA, OpenAI-API
+servers serve OpenWebUI / OpenCode / scripts. Both pull from the same
+model files if you want to avoid duplication.
+
+Sample compose entries to add:
+- `compose/faster-whisper.yml` — `fedirz/faster-whisper-server`,
+  port 8001 with `/v1/audio/transcriptions` endpoint.
+- `compose/kokoro.yml` — `ghcr.io/remsky/kokoro-fastapi-cpu` (or `-gpu`),
+  port 8002 with `/v1/audio/speech`.
+
+Then OpenWebUI Settings → Audio → STT URL `http://framework:8001/v1`,
+TTS URL `http://framework:8002/v1`, voice `af_bella` (Kokoro default).
+
+### Path C — Full SOTA conversational voice (higher effort)
+
+For "talk to my agent" with the best prosody available in OSS, run
+**Sesame CSM-1B** as the TTS instead of Kokoro/Piper. Heavier
+(~3-4 GB GPU at inference, ~5 GB on disk) but conversational quality
+is markedly better. No first-class OpenAI-API wrapper exists yet —
+expect a custom HTTP server or use the reference inference scripts.
+
+Pair with `whisper-large-v3-turbo` on STT for the matching jump in
+input quality.
+
+### Path D — Voice cloning (specialized)
+
+If you want a custom voice, **F5-TTS** or **OpenVoice v2** clone from
+a 5–10 second reference clip. F5 has the best quality, OpenVoice has
+the better license (MIT). Self-hosted; no first-party HTTP server —
+script-driven for now.
+
+## What I'd actually do
+
+Path A as the immediate quick win (5 minutes), Path B as the next
+weekend project (gives you voice in the existing browser UIs without
+forcing the Wyoming dependency on every consumer). Skip C/D until you
+have a concrete use case that demands them.
+
+## Reference catalogs
+
+- [Hugging Face TTS model leaderboard](https://huggingface.co/spaces/TTS-AGI/TTS-Arena) — blind preference scores across SOTA TTS
+- [Open ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard) — STT WER benchmarks
+- [Awesome STT / TTS](https://github.com/topics/text-to-speech) on GitHub
+- [Rhasspy / Wyoming](https://github.com/rhasspy) ecosystem — Home Assistant voice
+- [Kokoro repo](https://github.com/hexgrad/kokoro) and [Kokoro-FastAPI](https://github.com/remsky/Kokoro-FastAPI)
+- [Sesame CSM-1B](https://github.com/SesameAILabs/csm)
+- [faster-whisper-server](https://github.com/fedirz/faster-whisper-server)

piper-compose.yaml

@@ -1,12 +0,0 @@
-services:
-  piper:
-    image: rhasspy/wyoming-piper:latest
-    container_name: wyoming-piper
-    restart: unless-stopped
-    ports:
-      - "10200:10200"
-    volumes:
-      - ./piper-data:/data
-    command:
-      - --voice
-      - en_US-lessac-medium

pyinfra/framework/README.md

@@ -42,14 +42,15 @@ Or run it ephemerally without installing: `uvx pyinfra inventory.py deploy.py`.
   Requires a reboot to activate — pyinfra rewrites `/etc/default/grub`
   and runs `update-grub`, but won't reboot for you.
 - `/models/<vendor>/` layout
-- `/srv/docker/{llama,vllm,ollama,openwebui,beszel,openlit,phoenix,openhands,homepage}/docker-compose.yml`
+- `/srv/docker/{llama,vllm,ollama,openwebui,beszel,openlit,phoenix,openhands,homepage,whisper,piper}/docker-compose.yml`
   dropped in, not auto-started — you edit the model path then
   `docker compose up -d`
   (OpenWebUI needs no edits — it's pre-configured to find Ollama at
   `host.docker.internal:11434` and uses `searxng.n0n.io` for web search)
   (Beszel hub at :8090, OpenLIT UI at :3001, Phoenix UI at :6006,
-  OpenHands UI at :3030, Homepage at :7575 — see "Monitoring stack",
+  OpenHands UI at :3030, Homepage at :7575, Whisper STT at :10300,
-  "Agent harnesses", and "Front door" below)
+  Piper TTS at :10200 — see "Monitoring stack", "Agent harnesses",
+  "Front door", and "Voice" below)
 
 If a previous run installed the native llama.cpp build / full ROCm /
 native Ollama, those are auto-cleaned the next time `./run.sh` runs.
@@ -85,6 +86,31 @@ Compose images in
 (`services.yaml`, `settings.yaml`, etc.); edit there, `./run.sh`, restart
 the homepage container.
 
+## Voice
+
+Wyoming-protocol speech servers (Home Assistant's voice stack). No web
+UI — these are TCP protocol servers consumable by HA Assist, Wyoming
+satellites, or any Wyoming client.
+
+- **Whisper** (`/srv/docker/whisper`, `tcp://framework:10300`) —
+  speech-to-text. Default model is `tiny-int8` (~75 MB). Models
+  download into `/srv/docker/whisper/data/` on first run.
+
+- **Piper** (`/srv/docker/piper`, `tcp://framework:10200`) —
+  text-to-speech. Default voice is `en_US-lessac-medium` (~63 MB).
+  Browse alternatives at <https://github.com/rhasspy/piper/blob/master/VOICES.md>.
+
+Bring-up:
+```sh
+cd /srv/docker/whisper && docker compose up -d
+cd /srv/docker/piper && docker compose up -d
+```
+
+Both are conservative defaults sized for "small command-style usage";
+on Strix Halo's hardware budget you can run substantially better
+models. See [`localgenai/VoiceModels.md`](../../VoiceModels.md) for the
+landscape and upgrade options.
+
 ## Front door
 
 - **Homepage** (`/srv/docker/homepage`, http://framework:7575) — single

pyinfra/framework/compose/homepage/services.yaml

@@ -73,6 +73,21 @@
         server: localhost-docker
         container: phoenix
 
+- Voice:
+    # Wyoming-protocol services have no web UI; tiles are informational
+    # (container status + port). Click-through goes nowhere meaningful.
+    - Whisper:
+        icon: mdi-microphone-message
+        description: Speech-to-text (Wyoming :10300)
+        server: localhost-docker
+        container: wyoming-whisper
+
+    - Piper:
+        icon: mdi-account-voice
+        description: Text-to-speech (Wyoming :10200)
+        server: localhost-docker
+        container: wyoming-piper
+
 - External:
     - SearXNG:
         icon: searxng.svg

pyinfra/framework/compose/homepage/settings.yaml

@@ -21,6 +21,9 @@ layout:
   Observability:
     style: row
     columns: 3
+  Voice:
+    style: row
+    columns: 3
   External:
     style: row
     columns: 3

pyinfra/framework/compose/piper.yml

@@ -0,0 +1,22 @@
+# Wyoming Piper — text-to-speech over the Wyoming protocol.
+# https://github.com/rhasspy/wyoming-piper
+#
+# Wyoming is Home Assistant's voice protocol; it's also consumable by any
+# Wyoming client. No web UI — this is a protocol server on TCP :10200.
+#
+# Voice selection: en_US-lessac-medium is the most balanced English voice
+# (~63 MB, natural prosody). Browse alternatives at
+# https://github.com/rhasspy/piper/blob/master/VOICES.md — pulled into
+# /srv/docker/piper/data on first start.
+services:
+  piper:
+    image: rhasspy/wyoming-piper:latest
+    container_name: wyoming-piper
+    restart: unless-stopped
+    ports:
+      - "10200:10200"
+    volumes:
+      - /srv/docker/piper/data:/data
+    command:
+      - --voice
+      - en_US-lessac-medium

pyinfra/framework/compose/whisper.yml

@@ -0,0 +1,26 @@
+# Wyoming Whisper — speech-to-text over the Wyoming protocol.
+# https://github.com/rhasspy/wyoming-whisper
+#
+# Wyoming is Home Assistant's voice protocol; it's also consumable by any
+# Wyoming client. No web UI — this is a protocol server on TCP :10300.
+#
+# Model selection: `tiny-int8` is the smallest viable model (~75 MB),
+# fast and good enough for command-style transcription. Bump to
+# `base-int8` (140 MB) or `small-int8` (480 MB) for general dictation.
+# Models are downloaded into /srv/docker/whisper/data on first start.
+services:
+  whisper:
+    image: rhasspy/wyoming-whisper:latest
+    container_name: wyoming-whisper
+    restart: unless-stopped
+    ports:
+      - "10300:10300"
+    volumes:
+      - /srv/docker/whisper/data:/data
+    command:
+      - --model
+      - tiny-int8
+      - --language
+      - en
+      - --beam-size
+      - "1"

pyinfra/framework/deploy.py

@@ -339,6 +339,8 @@ for svc in (
     "phoenix",
     "openhands",
     "homepage",
+    "whisper",
+    "piper",
 ):
     files.directory(
         name=f"compose/{svc} dir",
@@ -470,6 +472,24 @@ for cfg in (
         _sudo=True,
     )
 
+# Voice stack — Wyoming-protocol Whisper (STT) and Piper (TTS). Models
+# are downloaded on first start; bind-mounting these dirs survives
+# container recreation.
+files.directory(
+    name="Whisper data dir",
+    path=f"{COMPOSE_DIR}/whisper/data",
+    group="docker",
+    mode="2775",
+    _sudo=True,
+)
+files.directory(
+    name="Piper data dir",
+    path=f"{COMPOSE_DIR}/piper/data",
+    group="docker",
+    mode="2775",
+    _sudo=True,
+)
+
 # --- Cleanup of artifacts from the prior native-build deploy ----------------
 # All idempotent — `present=False` is a no-op when the target is absent.
 

whisper-compose.yaml

@@ -1,16 +0,0 @@
-services:
-  whisper:
-    image: rhasspy/wyoming-whisper:latest
-    container_name: wyoming-whisper
-    restart: unless-stopped
-    ports:
-      - "10300:10300"
-    volumes:
-      - ./whisper-data:/data
-    command:
-      - --model
-      - tiny-int8
-      - --language
-      - en
-      - --beam-size
-      - "1"