# HomeAI — Master TODO

> Track progress across all sub-projects. See each sub-project `PLAN.md` for detailed implementation notes.
> Status: `[ ]` pending · `[~]` in progress · `[x]` done

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## Phase 1 — Foundation

### P1 · homeai-infra

- [x] Install Docker Desktop for Mac, enable launch at login
- [x] Create shared `homeai` Docker network
- [x] Create `~/server/docker/` directory structure
- [x] Write compose files: Uptime Kuma, code-server, n8n (HA, Portainer, Gitea are pre-existing on 10.0.0.199)
- [x] `docker compose up -d` — bring all services up
- [x] Home Assistant onboarding — long-lived access token generated, stored in `.env`
- [ ] Install Tailscale, verify all services reachable on Tailnet
- [ ] Uptime Kuma: add monitors for all services, configure mobile alerts
- [ ] Verify all containers survive a cold reboot

### P2 · homeai-llm

- [x] Install Ollama natively via brew
- [x] Write and load launchd plist (`com.homeai.ollama.plist`) — `/opt/homebrew/bin/ollama`
- [x] Register local GGUF models via Modelfiles (no download): llama3.3:70b, qwen3:32b, codestral:22b, qwen2.5:7b
- [x] Register additional models: EVA-LLaMA-3.33-70B, Midnight-Miqu-70B, QwQ-32B, Qwen3.5-35B, Qwen3-Coder-30B, Qwen3-VL-30B, GLM-4.6V-Flash, DeepSeek-R1-8B, gemma-3-27b
- [x] Deploy Open WebUI via Docker compose (port 3030)
- [x] Verify Open WebUI connected to Ollama, all models available
- [ ] Run `scripts/benchmark.sh` — record results in `benchmark-results.md`
- [ ] Add Ollama + Open WebUI to Uptime Kuma monitors

---

## Phase 2 — Voice Pipeline

### P3 · homeai-voice

- [x] Install `wyoming-faster-whisper` — model: faster-whisper-large-v3 (auto-downloaded)
- [x] Install Kokoro ONNX TTS — models at `~/models/kokoro/`
- [x] Write Wyoming-Kokoro adapter server (`homeai-voice/tts/wyoming_kokoro_server.py`)
- [x] Write + load launchd plists for Wyoming STT (10300) and TTS (10301)
- [x] Install openWakeWord + pyaudio — model: hey_jarvis
- [x] Write + load openWakeWord launchd plist (`com.homeai.wakeword`) — DISABLED, replaced by Wyoming satellite
- [x] Write `wyoming/test-pipeline.sh` — smoke test (3/3 passing)
- [x] Install Wyoming satellite — handles wake word via HA voice pipeline
- [x] Install Wyoming satellite for Mac Mini (port 10700)
- [x] Write OpenClaw conversation custom component for Home Assistant
- [x] Connect Home Assistant Wyoming integration (STT + TTS + Satellite) — ready to configure in HA UI
- [x] Create HA Voice Assistant pipeline with OpenClaw conversation agent — component ready, needs HA UI setup
- [x] Test HA Assist via browser: type query → hear spoken response
- [x] Test full voice loop: wake word → STT → OpenClaw → TTS → audio playback
- [ ] Install Chatterbox TTS (MPS build), test with sample `.wav`
- [ ] Install Qwen3-TTS via MLX (fallback)
- [ ] Train custom wake word using character name
- [ ] Add Wyoming STT/TTS to Uptime Kuma monitors

---

## Phase 3 — Agent & Character

### P4 · homeai-agent

- [x] Install OpenClaw (npm global, v2026.3.2)
- [x] Configure Ollama provider (native API, `http://localhost:11434`)
- [x] Write + load launchd plist (`com.homeai.openclaw`) — gateway on port 8080
- [x] Fix context window: set `contextWindow=32768` for llama3.3:70b in `openclaw.json`
- [x] Fix Llama 3.3 Modelfile: add tool-calling TEMPLATE block
- [x] Verify `openclaw agent --message "..." --agent main` → completed
- [x] Write `skills/home-assistant` SKILL.md — HA REST API control
- [x] Write `skills/voice-assistant` SKILL.md — voice response style guide
- [x] Wire HASS_TOKEN — create `~/.homeai/hass_token` or set env in launchd plist
- [x] Test home-assistant skill: "turn on/off the reading lamp"
- [x] Set up mem0 with Chroma backend, test semantic recall
- [x] Write memory backup launchd job
- [x] Build morning briefing n8n workflow
- [x] Build notification router n8n workflow
- [x] Verify full voice → agent → HA action flow
- [x] Add OpenClaw to Uptime Kuma monitors (Manual user action required)

### P5 · homeai-character *(can start alongside P4)*

- [x] Define and write `schema/character.schema.json` (v1)
- [x] Write `characters/aria.json` — default character
- [x] Set up Vite project in `src/`, install deps
- [x] Integrate existing `character-manager.jsx` into Vite project
- [x] Add schema validation on export (ajv)
- [x] Add expression mapping UI section
- [x] Add custom rules editor
- [x] Test full edit → export → validate → load cycle
- [x] Wire character system prompt into OpenClaw agent config
- [x] Record or source voice reference audio for Aria (`~/voices/aria.wav`)
- [x] Pre-process audio with ffmpeg, test with Chatterbox
- [x] Update `aria.json` with voice clone path if quality is good
- [x] Build unified HomeAI dashboard — dark-themed frontend showing live service status + links to individual UIs
- [x] Add character profile management to dashboard — store/switch character configs with attached profile images
- [x] Add TTS voice preview in character editor — Kokoro preview via OpenClaw bridge with loading state, custom text, stop control
- [ ] Deploy dashboard as Docker container or static site on Mac Mini

---

## Phase 4 — Hardware Satellites

### P6 · homeai-esp32

- [ ] Install ESPHome: `pip install esphome`
- [ ] Write `esphome/secrets.yaml` (gitignored)
- [ ] Write `base.yaml`, `voice.yaml`, `display.yaml`, `animations.yaml`
- [ ] Write `s3-box-living-room.yaml` for first unit
- [ ] Flash first unit via USB
- [ ] Verify unit appears in HA device list
- [ ] Assign Wyoming voice pipeline to unit in HA
- [ ] Test full wake → STT → LLM → TTS → audio playback cycle
- [ ] Test LVGL face: idle → listening → thinking → speaking → error
- [ ] Verify OTA firmware update works wirelessly
- [ ] Flash remaining units (bedroom, kitchen, etc.)
- [ ] Document MAC address → room name mapping

---

## Phase 5 — Visual Layer

### P7 · homeai-visual

- [ ] Install VTube Studio (Mac App Store)
- [ ] Enable WebSocket API on port 8001
- [ ] Source/purchase a Live2D model (nizima.com or booth.pm)
- [ ] Load model in VTube Studio
- [ ] Create hotkeys for all 8 expression states
- [ ] Write `skills/vtube_studio` SKILL.md + implementation
- [ ] Run auth flow — click Allow in VTube Studio, save token
- [ ] Test all 8 expressions via test script
- [ ] Update `aria.json` with real VTube Studio hotkey IDs
- [ ] Write `lipsync.py` amplitude-based helper
- [ ] Integrate lip sync into OpenClaw TTS dispatch
- [ ] Test full pipeline: voice → thinking expression → speaking with lip sync
- [ ] Set up VTube Studio mobile (iPhone/iPad) on Tailnet

---

## Phase 6 — Image Generation

### P8 · homeai-images

- [ ] Clone ComfyUI to `~/ComfyUI/`, install deps in venv
- [ ] Verify MPS is detected at launch
- [ ] Write and load launchd plist (`com.homeai.comfyui.plist`)
- [ ] Download SDXL base model
- [ ] Download Flux.1-schnell
- [ ] Download ControlNet models (canny, depth)
- [ ] Test generation via ComfyUI web UI (port 8188)
- [ ] Build and export `quick.json`, `portrait.json`, `scene.json`, `upscale.json` workflows
- [ ] Write `skills/comfyui` SKILL.md + implementation
- [ ] Test skill: "Generate a portrait of Aria looking happy"
- [ ] Collect character reference images for LoRA training
- [ ] Train SDXL LoRA with kohya_ss, verify character consistency
- [ ] Add ComfyUI to Uptime Kuma monitors

---

## Phase 7 — Extended Integrations & Polish

- [ ] Deploy Music Assistant (Docker), integrate with Home Assistant
- [ ] Write `skills/music` SKILL.md for OpenClaw
- [ ] Deploy Snapcast server on Mac Mini
- [ ] Configure Snapcast clients on ESP32 units for multi-room audio
- [ ] Configure Authelia as 2FA layer in front of web UIs
- [ ] Build advanced n8n workflows (calendar reminders, daily briefing v2)
- [ ] Create iOS Shortcuts to trigger OpenClaw from iPhone widget
- [ ] Configure ntfy/Pushover alerts in Uptime Kuma for all services
- [ ] Automate mem0 + character config backup to Gitea (daily)
- [ ] Train custom wake word using character's name
- [ ] Document all service URLs, ports, and credentials in a private Gitea wiki
- [ ] Tailscale ACL hardening — restrict which devices can reach which services
- [ ] Stress test: reboot Mac Mini, verify all services recover in <2 minutes

---

## Open Decisions

- [ ] Confirm character name (determines wake word training)
- [ ] Live2D model: purchase off-the-shelf or commission custom?
- [ ] mem0 backend: Chroma (simple) vs Qdrant Docker (better semantic search)?
- [ ] Snapcast output: ESP32 built-in speakers or dedicated audio hardware per room?
- [ ] Authelia user store: local file vs LDAP?