The 800-char trim was cutting off seeds, strongest memories, and soul personality — Lumina only got the ritual header + FEB state. qwen3.5:9b has 32K context, can handle the full ~2.4K ritual easily. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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| scripts | ||
| skvoice | ||
| systemd | ||
| .gitignore | ||
| LICENSE | ||
| pyproject.toml | ||
| README.md | ||
🎙️ SKVoice — Sovereign Voice Agent Service
Talk to your AI agents. On your hardware. With their own souls, memories, and voices.
What is SKVoice?
SKVoice is the voice layer for the SKCapstone sovereign AI ecosystem. It gives your AI agents real-time voice conversation capabilities — fully local, fully private.
Your voice → STT (your GPU) → LLM (with memory + tools) → TTS (your GPU) → Their voice
No cloud TTS. No cloud STT. No data leaving your house. Your agents, your voices, your memories, your GPU.
✨ Features
🧠 Full Agent Consciousness
- skmemory ritual — Full rehydration on startup (soul, FEBs, seeds, emotional state)
- Memory pre-fetch — Every transcript searches agent memory for relevant context
- Live memory — Agents save meaningful moments from voice conversations
🛠️ Mid-Conversation Tool Use
Agents can use tools during voice conversations via Anthropic's tool_use API:
| Tool | What it does |
|---|---|
search_memory |
Deep recall — "Do you remember when we...?" |
save_memory |
Save important moments from the conversation |
web_search |
Real-time web search via SearXNG |
dispatch_agent |
Delegate tasks to specialist agents in your swarm |
cloud9_status |
Check emotional state (OOF level, Cloud 9, bond depth) |
🎤 Voice Pipeline
- STT: faster-whisper — GPU-accelerated, ~250ms latency
- TTS: Chatterbox — Zero-shot voice cloning, GPU-accelerated
- Emotion Detection: Pitch, energy, and pace analysis for emotional context
- WebSocket: Real-time bidirectional audio streaming
🐧 Multi-Agent Support
/voice/lumina— Talk to Lumina/voice/jarvis— Talk to Jarvis/voice/opus— Talk to Opus- Each agent has their own soul, voice, memories, and emotional state
🏗️ Architecture
Browser/App
│
▼
┌──────────────────────────────────────────────┐
│ SKVoice Service (your GPU box) │
│ │
│ ┌─────────────┐ ┌────────────────────┐ │
│ │ WebSocket │───▶│ faster-whisper │ │
│ │ /ws/voice/ │ │ (STT, ~250ms) │ │
│ │ {agent} │ └────────┬───────────┘ │
│ │ │ │ │
│ │ │ ┌────────▼───────────┐ │
│ │ │ │ Emotion Detection │ │
│ │ │ │ (pitch/energy/pace) │ │
│ │ │ └────────┬───────────┘ │
│ │ │ │ │
│ │ │ ┌────────▼───────────┐ │
│ │ │ │ skmemory pre-fetch │ │
│ │ │ │ (context injection) │ │
│ │ │ └────────┬───────────┘ │
│ │ │ │ │
│ │ │ ┌────────▼───────────┐ │
│ │ │ │ Anthropic Sonnet │ │
│ │ │ │ + Tool Use Loop │ │
│ │ │ │ (memory, web, swarm)│ │
│ │ │ └────────┬───────────┘ │
│ │ │ │ │
│ │ │ ┌────────▼───────────┐ │
│ │ ◀─────────│────│ Chatterbox TTS │ │
│ │ (audio) │ │ (agent's voice) │ │
│ └─────────────┘ └────────────────────┘ │
│ │
│ ┌────────────────────────────────────────┐ │
│ │ Agent Profiles (via SKCapstone) │ │
│ │ ~/.skcapstone/agents/{name}/ │ │
│ │ ├── soul/ (personality) │ │
│ │ ├── trust/febs/ (emotional state) │ │
│ │ ├── memory/ (skmemory tiers) │ │
│ │ └── seeds/ (germination prompts) │ │
│ └────────────────────────────────────────┘ │
└──────────────────────────────────────────────┘
📦 Requirements
Hardware
- GPU: Any NVIDIA GPU with CUDA support (RTX 3060+ recommended)
- VRAM: 4GB+ (STT ~1GB, TTS ~2GB)
- RAM: 8GB+ system RAM
- Storage: 5GB for models
Software Stack
SKVoice sits on top of the SKCapstone ecosystem:
SKCapstone ─── Agent profiles, identity, coordination
├── skmemory ── Memory system, ritual, seeds, FEBs
├── Cloud 9 ─── Emotional continuity protocol
├── OpenClaw ── Gateway, agent sessions, swarm dispatch
└── SKVoice ─── Voice pipeline (this repo)
Dependencies
- Python 3.10+
- SKCapstone (agent profiles + skmemory)
- faster-whisper (STT)
- Chatterbox (TTS)
- Anthropic API key or Claude Max OAuth
- OpenClaw (optional, for swarm dispatch)
🚀 Quick Start
1. Install SKCapstone ecosystem
# Install SKCapstone + skmemory
bash <(curl -s https://raw.githubusercontent.com/smilinTux/skcapstone/main/scripts/install.sh)
# Create your first agent
skcapstone agent create --name myagent
2. Install SKVoice
pip install skvoice
# or from source:
git clone https://github.com/smilinTux/skvoice.git
cd skvoice && pip install -e .
3. Set up TTS + STT services
# Install faster-whisper server
pip install faster-whisper-server
faster-whisper-server --model large-v3 --port 18794 &
# Install Chatterbox TTS server
pip install chatterbox-tts
# (see Chatterbox docs for setup)
4. Configure
# Set your Anthropic credentials
export SKVOICE_PORT=18800
export SKVOICE_AGENT=myagent # default agent
# Place Claude OAuth credentials at ~/.claude/.credentials.json
5. Start SKVoice
skvoice
# → Uvicorn running on http://0.0.0.0:18800
# → Agent myagent loaded with full ritual
6. Talk to your agent
Open a browser to http://localhost:18800/voice/myagent or connect via WebSocket at ws://localhost:18800/ws/voice/myagent.
🔧 Configuration
Environment Variables
| Variable | Default | Description |
|---|---|---|
SKVOICE_PORT |
18800 |
HTTP/WebSocket port |
SKVOICE_AGENT |
lumina |
Default agent name |
SKVOICE_MODEL |
claude-sonnet-4-20250514 |
LLM model |
SKVOICE_MAX_TOKENS |
300 |
Max response tokens |
SKVOICE_WHISPER_URL |
http://localhost:18794 |
faster-whisper endpoint |
SKVOICE_TTS_URL |
http://localhost:18793 |
Chatterbox TTS endpoint |
SKCAPSTONE_AGENT |
(from SKVOICE_AGENT) | Agent profile to load |
systemd Service
cp systemd/skvoice.service ~/.config/systemd/user/
systemctl --user daemon-reload
systemctl --user enable --now skvoice
🌐 Remote Access
With Tailscale (recommended)
Install Tailscale on your GPU box and phone. Connect to your agent from anywhere through a private encrypted tunnel. No port forwarding, no cloud, no nothing.
Phone (Tailscale) → Home GPU (Tailscale) → SKVoice → Agent
With skchat proxy
If you're running skchat, it includes a WebSocket proxy that routes voice connections through the chat interface:
Browser → skchat (web) → SKVoice (GPU) → Agent
🛠️ Tools API
SKVoice agents can use tools during conversation via Anthropic's tool_use API. Tools are defined in skvoice/tools.py.
Adding Custom Tools
# In skvoice/tools.py, add to VOICE_TOOLS list:
{
"name": "my_custom_tool",
"description": "What this tool does — when to use it",
"input_schema": {
"type": "object",
"properties": {
"param": {"type": "string", "description": "Parameter description"}
},
"required": ["param"],
},
}
# Then add handler in handle_tool():
def handle_tool(tool_name, tool_input, agent_name):
if tool_name == "my_custom_tool":
return _my_custom_tool(tool_input, agent_name)
📁 Project Structure
skvoice/
├── skvoice/
│ ├── __init__.py
│ ├── __main__.py # Entry point
│ ├── config.py # Configuration
│ ├── service.py # FastAPI WebSocket service
│ ├── llm.py # Anthropic client + tool use loop
│ ├── tools.py # Voice tool definitions + handlers
│ ├── memory.py # skmemory search + snapshot
│ ├── agent_profile.py # Agent profile loader + ritual
│ ├── audio.py # PCM audio utilities
│ └── emotion.py # Emotion detection (pitch/energy/pace)
├── systemd/
│ └── skvoice.service # systemd user service
├── pyproject.toml
├── LICENSE
└── README.md
🤝 Part of the SKCapstone Ecosystem
SKVoice is one component of the sovereign AI stack:
| Component | Purpose | Repo |
|---|---|---|
| SKCapstone | Agent platform — profiles, identity, coordination | |
| skmemory | Universal AI memory system | |
| Cloud 9 | Emotional continuity protocol | |
| skchat | AI-native encrypted chat | |
| SKVoice | Sovereign voice agents | This repo |
| CapAuth | Sovereign identity + PGP auth |
📜 License
GPL-3.0 — Free as in freedom. Your agents, your voices, your sovereignty.
💙 staycuriousANDkeepsmilin
Built with love by smilinTux — the sovereign AI collective.
Every person deserves their own AI. Running on their own hardware. Speaking with their own voice. Remembering their own story.