# CLAUDE.md — Home AI Assistant Project ## Project Overview A self-hosted, always-on personal AI assistant running on a **Mac Mini M4 Pro (64GB RAM, 1TB SSD)**. The goal is a modular, expandable system that replaces commercial smart home speakers (Google Home etc.) with a locally-run AI that has a defined personality, voice, visual representation, and full smart home integration. --- ## Hardware | Component | Spec | |---|---| | Chip | Apple M4 Pro | | CPU | 14-core | | GPU | 20-core | | Neural Engine | 16-core | | RAM | 64GB unified memory | | Storage | 1TB SSD | | Network | Gigabit Ethernet | All AI inference runs locally on this machine. No cloud dependency required (cloud APIs optional). --- ## Core Stack ### AI & LLM - **Ollama** — local LLM runtime (target models: Llama 3.3 70B, Qwen 2.5 72B) - **Model keep-warm daemon** — `preload-models.sh` runs as a loop, checks every 5 min, re-pins evicted models with `keep_alive=-1`. Keeps `qwen2.5:7b` (small/fast) and `$HOMEAI_MEDIUM_MODEL` (default: `qwen3.5:35b-a3b`) always loaded in VRAM. Medium model is configurable via env var for per-persona model assignment. - **Open WebUI** — browser-based chat interface, runs as Docker container ### Image Generation - **ComfyUI** — primary image generation UI, node-based workflows - Target models: SDXL, Flux.1, ControlNet - Runs via Metal (Apple GPU API) ### Speech - **Whisper.cpp** — speech-to-text, optimised for Apple Silicon/Neural Engine - **Kokoro TTS** — fast, lightweight text-to-speech (primary, low-latency, local) - **ElevenLabs TTS** — cloud voice cloning/synthesis (per-character voice ID, routed via state file) - **Chatterbox TTS** — voice cloning engine (Apple Silicon MPS optimised) - **Qwen3-TTS** — alternative voice cloning via MLX - **openWakeWord** — always-on wake word detection ### Smart Home - **Home Assistant** — smart home control platform (Docker) - **Wyoming Protocol** — bridges Whisper STT + Kokoro/Piper TTS into Home Assistant - **Music Assistant** — self-hosted music control, integrates with Home Assistant - **Snapcast** — multi-room synchronised audio output ### AI Agent / Orchestration - **OpenClaw** — primary AI agent layer; receives voice commands, calls tools, manages personality - **n8n** — visual workflow automation (Docker), chains AI actions - **Character Memory System** — two-tier JSON-based memories (personal per-character + general shared), injected into LLM system prompt with budget truncation ### Character & Personality - **Character Schema v2** — JSON spec with background, dialogue_style, appearance, skills, gaze_presets (v1 auto-migrated) - **HomeAI Dashboard** — unified web app: character editor, chat, memory manager, service dashboard - **Character MCP Server** — LLM-assisted character creation via Fandom wiki/Wikipedia lookup (Docker) - Character config stored as JSON files in `~/homeai-data/characters/`, consumed by bridge for system prompt construction ### Visual Representation - **VTube Studio** — Live2D model display on desktop (macOS) and mobile (iOS/Android) - VTube Studio WebSocket API used to drive expressions from the AI pipeline - **LVGL** — simplified animated face on ESP32-S3-BOX-3 units - Live2D model: to be sourced/commissioned (nizima.com or booth.pm) ### Room Presence (Smart Speaker Replacement) - **ESP32-S3-BOX-3** units — one per room - Flashed with **ESPHome** - Acts as Wyoming Satellite (mic input → Mac Mini → TTS audio back) - LVGL display shows animated face + status info - Communicates over local WiFi ### Infrastructure - **Docker Desktop for Mac** — containerises Home Assistant, Open WebUI, n8n, etc. - **Tailscale** — secure remote access to all services, no port forwarding - **Authelia** — 2FA authentication layer for exposed web UIs - **Portainer** — Docker container management UI - **Uptime Kuma** — service health monitoring and mobile alerts - **Gitea** — self-hosted Git server for all project code and configs - **code-server** — browser-based VS Code for remote development --- ## Voice Pipeline (End-to-End) ``` ESP32-S3-BOX-3 (room) → Wake word detected (openWakeWord, runs locally on device or Mac Mini) → Audio streamed to Mac Mini via Wyoming Satellite → Whisper MLX transcribes speech to text → HA conversation agent → OpenClaw HTTP Bridge → Bridge resolves character (satellite_id → character mapping) → Bridge builds system prompt (profile + memories) and writes TTS config to state file → OpenClaw CLI → Ollama LLM generates response → Response dispatched: → Wyoming TTS reads state file → routes to Kokoro (local) or ElevenLabs (cloud) → Audio sent back to ESP32-S3-BOX-3 (spoken response) → VTube Studio API triggered (expression + lip sync on desktop/mobile) → Home Assistant action called if applicable (lights, music, etc.) ``` ### Timeout Strategy The HTTP bridge checks Ollama `/api/ps` before each request to determine if the LLM is already loaded: | Layer | Warm (model loaded) | Cold (model loading) | |---|---|---| | HA conversation component | 200s | 200s | | OpenClaw HTTP bridge | 60s | 180s | | OpenClaw agent | 60s | 60s | The keep-warm daemon ensures models stay loaded, so cold starts should be rare (only after Ollama restarts or VRAM pressure). --- ## Character System The AI assistant has a defined personality managed via the HomeAI Dashboard (character editor + memory manager). ### Character Schema v2 Each character is a JSON file in `~/homeai-data/characters/` with: - **System prompt** — core personality, injected into every LLM request - **Profile fields** — background, appearance, dialogue_style, skills array - **TTS config** — engine (kokoro/elevenlabs), kokoro_voice, elevenlabs_voice_id, elevenlabs_model, speed - **GAZE presets** — array of `{preset, trigger}` for image generation styles - **Custom prompt rules** — trigger/response overrides for specific contexts ### Memory System Two-tier memory stored as JSON in `~/homeai-data/memories/`: - **Personal memories** (`personal/{character_id}.json`) — per-character, about user interactions - **General memories** (`general.json`) — shared operational knowledge (tool usage, device info, routines) Memories are injected into the system prompt by the bridge with budget truncation (personal: 4000 chars, general: 3000 chars, newest first). ### TTS Voice Routing The bridge writes the active character's TTS config to `~/homeai-data/active-tts-voice.json` before each request. The Wyoming TTS server reads this state file to determine which engine/voice to use: - **Kokoro** — local, fast, uses `kokoro_voice` field (e.g., `af_heart`) - **ElevenLabs** — cloud, uses `elevenlabs_voice_id` + `elevenlabs_model`, returns PCM 24kHz This works for both ESP32/HA pipeline and dashboard chat. --- ## Project Priorities 1. **Foundation** — Docker stack up (Home Assistant, Open WebUI, Portainer, Uptime Kuma) ✅ 2. **LLM** — Ollama running with target models, Open WebUI connected ✅ 3. **Voice pipeline** — Whisper → Ollama → Kokoro → Wyoming → Home Assistant ✅ 4. **OpenClaw** — installed, onboarded, connected to Ollama and Home Assistant ✅ 5. **ESP32-S3-BOX-3** — ESPHome flash, Wyoming Satellite, display faces ✅ 6. **Character system** — schema v2, dashboard editor, memory system, per-character TTS routing ✅ 7. **Animated visual** — PNG/GIF character visual for the web assistant (initial visual layer) 8. **Android app** — companion app for mobile access to the assistant 9. **ComfyUI** — image generation online, character-consistent model workflows 10. **Extended integrations** — n8n workflows, Music Assistant, Snapcast, Gitea, code-server 11. **Polish** — Authelia, Tailscale hardening, iOS widgets ### Stretch Goals - **Live2D / VTube Studio** — full Live2D model with WebSocket API bridge (requires learning Live2D tooling) --- ## Key Paths & Conventions - All Docker compose files: `~/server/docker/` - OpenClaw skills: `~/.openclaw/skills/` - Character configs: `~/homeai-data/characters/` - Character memories: `~/homeai-data/memories/` - Conversation history: `~/homeai-data/conversations/` - Active TTS state: `~/homeai-data/active-tts-voice.json` - Satellite → character map: `~/homeai-data/satellite-map.json` - Whisper models: `~/models/whisper/` - Ollama models: managed by Ollama at `~/.ollama/models/` - ComfyUI models: `~/ComfyUI/models/` - Voice reference audio: `~/voices/` - Gitea repos root: `~/gitea/` --- ## Notes for Planning - All services should survive a Mac Mini reboot (launchd or Docker restart policies) - ESP32-S3-BOX-3 units are dumb satellites — all intelligence stays on Mac Mini - The character JSON schema (from Character Manager) should be treated as a versioned spec; pipeline components read from it, never hardcode personality values - OpenClaw skills are the primary extension mechanism — new capabilities = new skills - Prefer local models; cloud API keys (Anthropic, OpenAI) are fallback only - VTube Studio API bridge should be a standalone OpenClaw skill with clear event interface - mem0 memory store should be backed up as part of regular Gitea commits