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atlas/home-voice-agent/conversation/README.md
ilia bdbf09a9ac feat: Implement voice I/O services (TICKET-006, TICKET-010, TICKET-014) 
✅ 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/
2026-01-12 22:22:38 -05:00

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Conversation Management

This module handles multi-turn conversation sessions for the Atlas voice agent system.

Features

  • Session Management: Create, retrieve, and manage conversation sessions
  • Message History: Store and retrieve conversation messages
  • Context Window Management: Keep recent messages in context, summarize old ones
  • Session Expiry: Automatic cleanup of expired sessions
  • Persistent Storage: SQLite database for session persistence

Usage

from conversation.session_manager import get_session_manager

manager = get_session_manager()

# Create a new session
session_id = manager.create_session(agent_type="family")

# Add messages
manager.add_message(session_id, "user", "What time is it?")
manager.add_message(session_id, "assistant", "It's 3:45 PM EST.")

# Get context for LLM
context = manager.get_context_messages(session_id, max_messages=20)

# Summarize old messages
manager.summarize_old_messages(session_id, keep_recent=10)

# Cleanup expired sessions
manager.cleanup_expired_sessions()

Session Structure

Each session contains:

  • session_id: Unique identifier
  • agent_type: "work" or "family"
  • created_at: Session creation timestamp
  • last_activity: Last activity timestamp
  • messages: List of conversation messages
  • summary: Optional summary of old messages

Message Structure

Each message contains:

  • role: "user", "assistant", or "system"
  • content: Message text
  • timestamp: When the message was created
  • tool_calls: Optional list of tool calls made
  • tool_results: Optional list of tool results

Configuration

  • MAX_CONTEXT_MESSAGES: 20 (default) - Number of recent messages to keep
  • MAX_CONTEXT_TOKENS: 8000 (default) - Approximate token limit
  • SESSION_EXPIRY_HOURS: 24 (default) - Sessions expire after inactivity

Database Schema

Sessions Table

  • session_id (TEXT PRIMARY KEY)
  • agent_type (TEXT)
  • created_at (TEXT ISO format)
  • last_activity (TEXT ISO format)
  • summary (TEXT, nullable)

Messages Table

  • id (INTEGER PRIMARY KEY)
  • session_id (TEXT, foreign key)
  • role (TEXT)
  • content (TEXT)
  • timestamp (TEXT ISO format)
  • tool_calls (TEXT JSON, nullable)
  • tool_results (TEXT JSON, nullable)

Future Enhancements

  • Actual LLM-based summarization (currently placeholder)
  • Token counting for precise context management
  • Session search and retrieval
  • Conversation analytics