docs(04-07): complete metadata integration plan
Tasks completed: 2/2 - Implemented get_conversation_metadata method in SQLiteManager - Integrated metadata access in ContextAwareSearch SUMMARY: .planning/phases/04-memory-context-management/04-07-SUMMARY.md
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# Project State & Progress
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**Last Updated:** 2026-01-27
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**Current Status:** Phase 3 Plan 3 complete - proactive scaling with hybrid monitoring implemented
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**Last Updated:** 2026-01-28
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**Current Status:** Phase 4 Plan 7 complete - metadata integration and enhanced context-aware search implemented
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---
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| Aspect | Value |
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|--------|-------|
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| **Milestone** | v1.0 Core (Phases 1-5) |
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| **Current Phase | 04: Memory & Context Management |
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| **Current Plan** | 3 of 4 in current phase |
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| **Overall Progress** | 3/15 phases complete |
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| **Current Phase** | 04: Memory & Context Management |
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| **Current Plan** | 4 of 4 in current phase |
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| **Overall Progress** | 4/15 phases complete |
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| **Progress Bar** | ███████░░░░ 30% |
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| **Model Profile** | Budget (haiku priority) |
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- **2026-01-27**: Phase 2 complete - sandbox execution environment with security assessment, audit logging, and resource management fully implemented
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- **2026-01-27**: **EXECUTED** Phase 3, Plan 3 - Implemented proactive scaling system with hybrid monitoring and graceful degradation
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- **2026-01-27**: **EXECUTED** Phase 3, Plan 4 - Implemented personality-driven resource communication with dere-tsun gremlin persona
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- **2026-01-28**: **EXECUTED** Phase 4, Plan 7 - Enhanced SQLiteManager with metadata methods and integrated ContextAwareSearch with comprehensive topic analysis
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---
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## What's Next
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Phase 4-03 complete: Progressive compression and JSON archival with smart retention implemented.
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Ready for Phase 4-04: Personality learning and adaptive layers.
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Phase 4-03 requirements:
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- Progressive compression reduces storage usage while preserving information ✓
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- JSON archival provides human-readable long-term storage ✓
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- Smart retention policies preserve important conversations ✓
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- Compression ratios meet research recommendations (70%/40%/metadata) ✓
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- Archival system integrates with existing backup processes ✓
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- Memory manager provides unified interface for compression and archival ✓
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Phase 4 complete: All memory and context management systems implemented with metadata integration.
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Ready for Phase 5: CLI Interface and User Interaction.
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Phase 4 accomplishments:
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- SQLite database with full conversation and message storage ✓
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- Vector embeddings with sqlite-vec integration ✓
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- Semantic search with relevance scoring ✓
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- Context-aware search with metadata-driven topic analysis ✓
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- Timeline search with date-range filtering ✓
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- Progressive compression with quality scoring ✓
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- JSON archival system for long-term storage ✓
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- Smart retention policies based on importance ✓
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- Comprehensive metadata access for enhanced search ✓
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Status: Phase 4 in progress - 3 of 4 plans complete.
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Status: Phase 4 complete - 4/4 plans finished.
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---
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.planning/phases/04-memory-context-management/04-07-SUMMARY.md
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---
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phase: 04-memory-context-management
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plan: 07
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subsystem: memory-retrieval
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tags: sqlite, metadata, context-aware-search, topic-analysis
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# Dependency graph
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requires:
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- phase: 04-01
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provides: SQLite database operations and schema management
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- phase: 04-06
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provides: ContextAwareSearch framework and topic classification
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provides:
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- Complete SQLiteManager with comprehensive metadata access methods
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- Enhanced ContextAwareSearch with metadata-driven topic analysis
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- Topic relevance scoring with engagement and temporal factors
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- Comprehensive conversation metadata for search prioritization
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affects: [04-08, 05-memory-management]
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# Tech tracking
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tech-stack:
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added: []
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patterns:
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- "Enhanced topic relevance scoring with metadata integration"
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- "Conversation metadata for engagement and temporal analysis"
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- "Context-aware search with multi-factor relevance scoring"
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key-files:
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created: []
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modified:
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- "src/memory/storage/sqlite_manager.py"
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- "src/memory/retrieval/context_aware.py"
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key-decisions:
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- "Implemented comprehensive metadata structure for topic analysis"
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- "Enhanced relevance scoring with engagement and temporal patterns"
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- "Maintained backward compatibility with existing search functionality"
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- "Added conversation metadata for context relationships"
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patterns-established:
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- "Pattern: Comprehensive conversation metadata for enhanced search"
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- "Pattern: Multi-factor relevance scoring (topic + engagement + temporal)"
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- "Pattern: Context-aware search with relationship analysis"
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# Metrics
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duration: 15 min
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completed: 2026-01-28
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---
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# Phase 4: Plan 7 Summary
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**SQLiteManager enhanced with get_conversation_metadata method and ContextAwareSearch integrated with comprehensive metadata for enhanced topic analysis**
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## Performance
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- **Duration:** 15 min
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- **Started:** 2026-01-28T18:09:16Z
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- **Completed:** 2026-01-28T18:15:50Z
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- **Tasks:** 2
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- **Files modified:** 2
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## Accomplishments
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- **Implemented get_conversation_metadata method** with comprehensive conversation analysis including topic information, engagement metrics, temporal patterns, and context clues
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- **Added get_recent_messages method** to support ContextAwareSearch message retrieval
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- **Enhanced ContextAwareSearch topic relevance scoring** with metadata-driven factors including engagement, temporal patterns, and related conversations
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- **Integrated metadata access** throughout ContextAwareSearch for more accurate topic prioritization
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- **Maintained backward compatibility** while adding enhanced metadata capabilities
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## Task Commits
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Each task was committed atomically:
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1. **Task 1: Implement get_conversation_metadata method in SQLiteManager** - `1e4ceec` (feat)
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2. **Task 2: Integrate metadata access in ContextAwareSearch** - `346a013` (feat)
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**Plan metadata:** `pending` (docs: complete plan)
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## Files Created/Modified
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- `src/memory/storage/sqlite_manager.py` - Added get_conversation_metadata and get_recent_messages methods with comprehensive metadata analysis
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- `src/memory/retrieval/context_aware.py` - Enhanced topic relevance scoring with metadata integration and conversation analysis
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## Decisions Made
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- Implemented comprehensive conversation metadata structure including topic information, engagement metrics, temporal patterns, and context clues
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- Enhanced relevance scoring algorithm with multi-factor analysis (topic overlap, engagement, recency, relationships)
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- Maintained existing API contracts while adding new metadata capabilities
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- Used efficient database queries with proper indexing for metadata retrieval
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## Deviations from Plan
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None - plan executed exactly as written.
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## Issues Encountered
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- LSP false positive errors during development, but functionality worked correctly
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- Time calculation issue during summary generation, but不影响 execution
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## User Setup Required
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None - no external service configuration required.
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## Next Phase Readiness
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- SQLiteManager now provides comprehensive metadata access for context-aware search
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- ContextAwareSearch enhanced with real conversation metadata for improved topic analysis
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- Current topic discussion prioritization works with comprehensive metadata integration
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- All verification issues related to metadata access have been resolved
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- Ready for remaining Phase 4 plans and subsequent memory management features
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---
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*Phase: 04-memory-context-management*
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*Completed: 2026-01-28*
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