✅ 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/
175 lines
5.2 KiB
Python
175 lines
5.2 KiB
Python
"""
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Memory manager - high-level interface for memory operations.
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"""
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import logging
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from typing import Optional, List
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from datetime import datetime
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from uuid import uuid4
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from memory.schema import MemoryEntry, MemoryCategory, MemorySource
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from memory.storage import MemoryStorage
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logger = logging.getLogger(__name__)
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class MemoryManager:
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"""High-level memory management."""
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def __init__(self, storage: Optional[MemoryStorage] = None):
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"""
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Initialize memory manager.
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Args:
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storage: Memory storage instance. If None, creates default.
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"""
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self.storage = storage or MemoryStorage()
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def store_fact(self,
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category: MemoryCategory,
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key: str,
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value: str,
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confidence: float = 1.0,
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source: MemorySource = MemorySource.EXPLICIT,
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context: Optional[str] = None,
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tags: Optional[List[str]] = None) -> MemoryEntry:
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"""
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Store a fact in memory.
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Args:
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category: Memory category
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key: Fact key
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value: Fact value
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confidence: Confidence level (0.0-1.0)
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source: Source of the fact
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context: Additional context
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tags: Tags for categorization
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Returns:
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Created memory entry
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"""
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entry = MemoryEntry(
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id=str(uuid4()),
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category=category,
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key=key,
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value=value,
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confidence=confidence,
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source=source,
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timestamp=datetime.now(),
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tags=tags or []
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)
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if context:
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entry.context = context
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self.storage.store(entry)
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return entry
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def get_fact(self, category: MemoryCategory, key: str) -> Optional[MemoryEntry]:
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"""
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Get a fact from memory.
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Args:
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category: Memory category
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key: Fact key
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Returns:
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Memory entry or None
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"""
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return self.storage.get(category, key)
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def get_category_facts(self, category: MemoryCategory, limit: Optional[int] = None) -> List[MemoryEntry]:
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"""
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Get all facts in a category.
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Args:
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category: Memory category
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limit: Maximum number of facts
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Returns:
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List of memory entries
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"""
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return self.storage.get_by_category(category, limit)
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def search_facts(self, query: str, category: Optional[MemoryCategory] = None, limit: int = 10) -> List[MemoryEntry]:
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"""
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Search facts by query.
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Args:
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query: Search query
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category: Optional category filter
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limit: Maximum results
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Returns:
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List of matching memory entries
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"""
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return self.storage.search(query, category, limit)
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def format_for_prompt(self, category: Optional[MemoryCategory] = None, limit: int = 20) -> str:
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"""
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Format memory entries for inclusion in LLM prompt.
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Args:
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category: Optional category filter
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limit: Maximum entries per category
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Returns:
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Formatted string for prompt
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"""
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if category:
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entries = self.get_category_facts(category, limit)
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return self._format_entries(entries, category.value)
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else:
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# Get entries from all categories
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sections = []
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for cat in MemoryCategory:
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entries = self.get_category_facts(cat, limit)
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if entries:
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sections.append(self._format_entries(entries, cat.value))
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return "\n\n".join(sections) if sections else "No memory entries."
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def _format_entries(self, entries: List[MemoryEntry], category_name: str) -> str:
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"""Format entries for a category."""
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lines = [f"## {category_name.title()} Facts"]
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for entry in entries[:20]: # Limit per category
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confidence_str = f" (confidence: {entry.confidence:.1f})" if entry.confidence < 1.0 else ""
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source_str = f" [{entry.source.value}]" if entry.source != MemorySource.EXPLICIT else ""
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lines.append(f"- {entry.key}: {entry.value}{confidence_str}{source_str}")
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return "\n".join(lines)
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def delete_fact(self, entry_id: str) -> bool:
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"""
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Delete a fact.
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Args:
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entry_id: Entry ID to delete
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Returns:
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True if deleted successfully
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"""
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return self.storage.delete(entry_id)
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def update_confidence(self, entry_id: str, confidence: float) -> bool:
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"""
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Update confidence of a fact.
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Args:
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entry_id: Entry ID
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confidence: New confidence (0.0-1.0)
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Returns:
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True if updated successfully
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"""
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return self.storage.update_confidence(entry_id, confidence)
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# Global memory manager instance
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_manager = MemoryManager()
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def get_memory_manager() -> MemoryManager:
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"""Get the global memory manager instance."""
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return _manager
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