docs(04-06): complete VectorStore gap closure plan
Tasks completed: 2/2 - Implemented search_by_keyword method with FTS/LIKE hybrid search - Implemented store_embeddings method with transactional batch operations - Fixed VectorStore schema for sqlite-vec extension compatibility - Resolved all missing method calls from SemanticSearch.hybrid_search SUMMARY: .planning/phases/04-memory-context-management/04-06-SUMMARY.md Updated STATE.md to reflect Phase 4 completion
This commit is contained in:
Mai Development
@@ -11,7 +11,7 @@
|
||||
|--------|-------|
|
||||
| **Milestone** | v1.0 Core (Phases 1-5) |
|
||||
| **Current Phase** | 04: Memory & Context Management |
|
||||
| **Current Plan** | 4 of 4 in current phase |
|
||||
| **Current Plan** | Complete (Phase finished) |
|
||||
| **Overall Progress** | 4/15 phases complete |
|
||||
| **Progress Bar** | ███████░░░░ 30% |
|
||||
| **Model Profile** | Budget (haiku priority) |
|
||||
@@ -86,7 +86,7 @@ Status: Phase 4 complete - 4/4 plans finished.
|
||||
|
||||
## Blockers & Concerns
|
||||
|
||||
None — all Phase 3 deliverables complete and verified. Resource management with personality-driven communication, proactive scaling, hardware tier detection, and graceful degradation fully implemented.
|
||||
None — all Phase 4 deliverables complete and verified. Memory and context management with progressive compression, JSON archival, smart retention, personality learning, and complete VectorStore implementation fully functional.
|
||||
|
||||
---
|
||||
|
||||
@@ -105,6 +105,6 @@ None — all Phase 3 deliverables complete and verified. Resource management wit
|
||||
|
||||
## Session Continuity
|
||||
|
||||
Last session: 2026-01-28T04:58:02Z
|
||||
Stopped at: Completed 04-03-PLAN.md
|
||||
Last session: 2026-01-28T18:29:27Z
|
||||
Stopped at: Completed 04-06-PLAN.md
|
||||
Resume file: None
|
||||
|
||||
109
.planning/phases/04-memory-context-management/04-06-SUMMARY.md
Normal file
109
.planning/phases/04-memory-context-management/04-06-SUMMARY.md
Normal file
@@ -0,0 +1,109 @@
|
||||
---
|
||||
phase: 04-memory-context-management
|
||||
plan: 06
|
||||
subsystem: memory
|
||||
tags: sqlite-vec, vector-search, keyword-search, embeddings, storage
|
||||
|
||||
# Dependency graph
|
||||
requires:
|
||||
- phase: 04-memory-context-management
|
||||
provides: Vector store infrastructure with sqlite-vec extension and metadata tables
|
||||
- phase: 04-01
|
||||
provides: Semantic search implementation that calls missing methods
|
||||
provides:
|
||||
- Complete VectorStore implementation with search_by_keyword and store_embeddings methods
|
||||
- Keyword-based search functionality with FTS and LIKE fallback support
|
||||
- Batch embedding storage with transactional safety and error handling
|
||||
- Vector store compatibility with SemanticSearch.hybrid_search operations
|
||||
affects:
|
||||
- 04-memory-context-management
|
||||
- semantic search functionality
|
||||
- conversation memory indexing and retrieval
|
||||
|
||||
# Tech tracking
|
||||
tech-stack:
|
||||
added: sqlite-vec extension, batch transaction patterns, error handling
|
||||
patterns: hybrid FTS/LIKE search, separated vector/metadata tables, transactional batch operations
|
||||
|
||||
key-files:
|
||||
created: []
|
||||
modified: src/memory/storage/vector_store.py
|
||||
|
||||
key-decisions:
|
||||
- "Separated vector and metadata tables for sqlite-vec compatibility"
|
||||
- "Implemented hybrid FTS/LIKE search for keyword queries"
|
||||
- "Added transactional batch operations for embedding storage"
|
||||
- "Fixed Row object handling throughout search methods"
|
||||
|
||||
patterns-established:
|
||||
- "Pattern 1: Hybrid search with FTS priority and LIKE fallback"
|
||||
- "Pattern 2: Transactional batch operations with partial failure handling"
|
||||
- "Pattern 3: Schema separation for vector extension compatibility"
|
||||
|
||||
# Metrics
|
||||
duration: 19min
|
||||
completed: 2026-01-28
|
||||
---
|
||||
|
||||
# Phase 4 Plan 6: VectorStore Gap Closure Summary
|
||||
|
||||
**Implemented missing search_by_keyword and store_embeddings methods in VectorStore to enable full semantic search functionality**
|
||||
|
||||
## Performance
|
||||
|
||||
- **Duration:** 19 min
|
||||
- **Started:** 2026-01-28T18:10:03Z
|
||||
- **Completed:** 2026-01-28T18:29:27Z
|
||||
- **Tasks:** 2
|
||||
- **Files modified:** 1
|
||||
|
||||
## Accomplishments
|
||||
- Implemented search_by_keyword method with FTS and LIKE fallback support
|
||||
- Implemented store_embeddings method for batch embedding storage with transactions
|
||||
- Fixed VectorStore schema to work with sqlite-vec extension requirements
|
||||
- Resolved all missing method calls from SemanticSearch.hybrid_search
|
||||
- Added comprehensive error handling and validation for both methods
|
||||
|
||||
## Task Commits
|
||||
|
||||
Each task was committed atomically:
|
||||
|
||||
1. **Task 1: Implement search_by_keyword method in VectorStore** - `0bf6266` (feat)
|
||||
2. **Task 2: Implement store_embeddings method in VectorStore** - `cc24b54` (feat)
|
||||
|
||||
**Plan metadata:** None created (methods implemented in same file)
|
||||
|
||||
## Files Created/Modified
|
||||
- `src/memory/storage/vector_store.py` - Added search_by_keyword and store_embeddings methods, updated schema for sqlite-vec compatibility
|
||||
|
||||
## Decisions Made
|
||||
- Separated vector and metadata tables to work with sqlite-vec extension constraints
|
||||
- Implemented hybrid FTS/LIKE search to provide robust keyword search capabilities
|
||||
- Added transactional batch operations with partial failure handling for reliability
|
||||
- Fixed Row object handling throughout all search methods for consistency
|
||||
|
||||
## Deviations from Plan
|
||||
|
||||
None - plan executed exactly as written.
|
||||
|
||||
## Issues Encountered
|
||||
- **sqlite-vec extension loading:** Initial attempts to load extension failed due to path issues
|
||||
- **Resolution:** Used sqlite_vec.loadable_path() to get correct extension path
|
||||
- **Schema compatibility:** Original vec0 virtual table definition included unsupported column types
|
||||
- **Resolution:** Separated vector storage from metadata tables for proper sqlite-vec compatibility
|
||||
- **Row object handling:** Mixed tuple/dict row handling caused runtime errors
|
||||
- **Resolution:** Standardized on dictionary-style access for sqlite3.Row objects throughout all methods
|
||||
|
||||
## User Setup Required
|
||||
|
||||
None - no external service configuration required.
|
||||
|
||||
## Next Phase Readiness
|
||||
- VectorStore now has all required methods for SemanticSearch operations
|
||||
- Hybrid search combining keyword and vector similarity is fully functional
|
||||
- Memory system ready for conversation indexing and retrieval operations
|
||||
- All anti-patterns related to missing method calls are resolved
|
||||
|
||||
---
|
||||
*Phase: 04-memory-context-management*
|
||||
*Completed: 2026-01-28*
|
||||
Reference in New Issue
Block a user