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/
87 lines
1.7 KiB
Markdown
87 lines
1.7 KiB
Markdown
# 4080 LLM Server (Work Agent)
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LLM server for work agent running on remote GPU VM.
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## Server Information
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- **Host**: 10.0.30.63
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- **Port**: 11434
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- **Endpoint**: http://10.0.30.63:11434
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- **Service**: Ollama
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## Available Models
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The server has the following models available:
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- `deepseek-r1:70b` - 70B model (currently configured)
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- `deepseek-r1:671b` - 671B model
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- `llama3.1:8b` - Llama 3.1 8B
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- `qwen2.5:14b` - Qwen 2.5 14B
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- And others (see `test_connection.py`)
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## Configuration
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Edit `config.py` to change the model:
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```python
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MODEL_NAME = "deepseek-r1:70b" # or your preferred model
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```
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## Testing Connection
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```bash
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cd home-voice-agent/llm-servers/4080
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python3 test_connection.py
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```
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This will:
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1. Test server connectivity
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2. List available models
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3. Test chat endpoint with configured model
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## API Usage
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### List Models
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```bash
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curl http://10.0.30.63:11434/api/tags
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```
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### Chat Request
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```bash
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curl http://10.0.30.63:11434/api/chat -d '{
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"model": "deepseek-r1:70b",
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"messages": [
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{"role": "user", "content": "Hello"}
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],
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"stream": false
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}'
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```
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### With Function Calling
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```bash
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curl http://10.0.30.63:11434/api/chat -d '{
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"model": "deepseek-r1:70b",
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"messages": [
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{"role": "user", "content": "What is the weather in San Francisco?"}
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],
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"tools": [...],
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"stream": false
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}'
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```
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## Integration
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The MCP adapter can connect to this server by setting:
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```python
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OLLAMA_BASE_URL = "http://10.0.30.63:11434"
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```
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## Notes
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- The server is already running on the GPU VM
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- No local installation needed - just configure the endpoint
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- Model selection can be changed in `config.py`
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- If you need `llama3.1:70b-q4_0`, pull it on the server:
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```bash
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# On the GPU VM
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ollama pull llama3.1:70b-q4_0
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```
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