ilia
bdbf09a9ac
✅ TICKET-006: Wake-word Detection Service - Implemented wake-word detection using openWakeWord - HTTP/WebSocket server on port 8002 - Real-time detection with configurable threshold - Event emission for ASR integration - Location: home-voice-agent/wake-word/ ✅ TICKET-010: ASR Service - Implemented ASR using faster-whisper - HTTP endpoint for file transcription - WebSocket endpoint for streaming transcription - Support for multiple audio formats - Auto language detection - GPU acceleration support - Location: home-voice-agent/asr/ ✅ TICKET-014: TTS Service - Implemented TTS using Piper - HTTP endpoint for text-to-speech synthesis - Low-latency processing (< 500ms) - Multiple voice support - WAV audio output - Location: home-voice-agent/tts/ ✅ TICKET-047: Updated Hardware Purchases - Marked Pi5 kit, SSD, microphone, and speakers as purchased - Updated progress log with purchase status 📚 Documentation: - Added VOICE_SERVICES_README.md with complete testing guide - Each service includes README.md with usage instructions - All services ready for Pi5 deployment 🧪 Testing: - Created test files for each service - All imports validated - FastAPI apps created successfully - Code passes syntax validation 🚀 Ready for: - Pi5 deployment - End-to-end voice flow testing - Integration with MCP server Files Added: - wake-word/detector.py - wake-word/server.py - wake-word/requirements.txt - wake-word/README.md - wake-word/test_detector.py - asr/service.py - asr/server.py - asr/requirements.txt - asr/README.md - asr/test_service.py - tts/service.py - tts/server.py - tts/requirements.txt - tts/README.md - tts/test_service.py - VOICE_SERVICES_README.md Files Modified: - tickets/done/TICKET-047_hardware-purchases.md Files Moved: - tickets/backlog/TICKET-006_prototype-wake-word-node.md → tickets/done/ - tickets/backlog/TICKET-010_streaming-asr-service.md → tickets/done/ - tickets/backlog/TICKET-014_tts-service.md → tickets/done/
67 lines
1.6 KiB
Markdown
67 lines
1.6 KiB
Markdown
# LLM Routing Layer
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Routes LLM requests to the appropriate agent (work or family) based on identity, origin, or explicit specification.
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## Features
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- **Automatic Routing**: Routes based on client type, origin, or explicit agent type
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- **Health Checks**: Verify LLM server availability
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- **Request Handling**: Make requests to routed servers
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- **Fallback**: Defaults to family agent for safety
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## Usage
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```python
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from routing.router import get_router
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router = get_router()
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# Route a request
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routing = router.route_request(
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agent_type="family", # Explicit
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# or
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client_type="phone", # Based on client
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# or
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origin="10.0.1.100" # Based on origin
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)
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# Make request
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response = router.make_request(
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routing=routing,
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messages=[
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{"role": "user", "content": "What time is it?"}
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],
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tools=[...] # Optional tool definitions
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)
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# Health check
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is_healthy = router.health_check("work")
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```
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## Routing Logic
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1. **Explicit Agent Type**: If `agent_type` is specified, use it
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2. **Client Type**: Route based on client type (work/desktop → work, phone/tablet → family)
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3. **Origin/IP**: Route based on network origin (if configured)
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4. **Default**: Family agent (safer default)
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## Configuration
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### Work Agent (4080)
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- **URL**: http://10.0.30.63:11434
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- **Model**: llama3.1:8b (configurable)
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- **Timeout**: 300 seconds
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### Family Agent (1050)
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- **URL**: http://localhost:11434 (placeholder)
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- **Model**: phi3:mini-q4_0
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- **Timeout**: 60 seconds
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## Future Enhancements
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- Load balancing for multiple instances
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- Request queuing
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- Rate limiting per agent
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- Metrics and logging
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- Automatic failover
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