---
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*