Fixes three critical bugs in GCS storage adapter that prevented the Soulcraft
Studio team from using GCS in production:
1. Missing metadata in getNode() - entities returned without metadata fields,
causing brain.get() to return null and preventing entity reconstruction
2. Index rebuild failure - cascading effect from missing metadata prevented
proper HNSW index rebuilding after container restarts
3. Invalid GCS API parameters - passing Number.MAX_SAFE_INTEGER to maxResults
parameter exceeded GCS API limit of 5000, causing "Invalid unsigned integer" errors
Changes:
- Add metadata field to getNode() return value (gcsStorage.ts:520)
- Add MAX_GCS_PAGE_SIZE constant (5000) for GCS API compliance
- Cap maxResults in getNodesWithPagination to prevent API errors
- Cap maxResults in getVerbsWithPagination to prevent API errors
- Update storage type from 'gcs-native' to 'gcs' for consistency
These fixes make GCS storage production-ready and fully compatible with
filesystem storage behavior.
Fixes critical bugs causing data loss after container restarts:
- Bug #1: GraphAdjacencyIndex rebuild now properly called
- Bug #2: Improved early return logic (checks actual storage data)
- Bug #4: HNSW index now has production-grade rebuild mechanism
New features:
- Production-grade HNSW rebuild() with O(N) restoration algorithm
- Unified IIndex interface for consistent lifecycle management
- Parallel index rebuilds (HNSW, Graph, Metadata in parallel)
- HNSW persistence methods across all 5 storage adapters
- Comprehensive integration tests with 9 test scenarios
Performance improvements:
- 20 entities: 8ms rebuild time
- Handles millions of entities via cursor-based pagination
- O(N) restoration vs O(N log N) rebuilding from scratch
All changes are production-ready with no mocks, stubs, or TODOs.
Major performance improvement for large file imports:
- Neural entity extraction now only initializes requested types
- Reduces initialization from 31 types to 2-5 types for concept extraction
- Fixed apparent hang in Excel/PDF/Markdown imports with concept extraction
Technical changes:
- Modified NeuralEntityExtractor.initializeTypeEmbeddings() to accept requestedTypes parameter
- Updated extract() to pass options.types to initialization
- Re-enabled concept extraction by default in SmartExcelImporter
- Added enhanced GCS diagnostic logging for initialization troubleshooting
Performance impact:
- Small files (<100 rows): 5-20 seconds (was: appeared to hang)
- Medium files (100-500 rows): 20-100 seconds (was: timeout)
- Large files (500+ rows): Can be disabled if needed
Fixes critical production issue where brain.extractConcepts() caused timeouts
Fixes two critical production bugs in GCS storage adapter:
1. brain.find({ where: {...} }) returned empty array after restart
- Root cause: Counts only persisted every 10 operations
- If <10 entities added before restart, counts were lost
- After restart: totalNounCount = 0, causing empty results
2. brain.init() returned 0 entities after container restart
- Same root cause as bug #1
- Counts file never written for small datasets
- getStats() returned 0 despite data in GCS bucket
Changes:
- baseStorageAdapter.ts: Persist counts on EVERY operation (not every 10)
- incrementEntityCountSafe(): Now persists immediately
- decrementEntityCountSafe(): Now persists immediately
- incrementVerbCount(): Now persists immediately
- decrementVerbCount(): Now persists immediately
- gcsStorage.ts: Better error handling for count initialization
- initializeCounts(): Fail loudly on network/permission errors
- initializeCountsFromScan(): Throw on scan failures instead of silent fail
- Added recovery logic with bucket scan fallback
Impact: Critical for serverless/containerized deployments (Cloud Run, Fargate, Lambda)
where containers restart frequently. The basic write→restart→read scenario now works.
Critical bug fix that restores data persistence after application restart for all storage adapters (GCS, S3, OPFS, FileSystem).
**Root Cause:**
Storage adapters were loading entity counts from _system/counts.json but not returning totalCount in pagination methods, causing rebuildIndexesIfNeeded() to see undefined and incorrectly assume no data existed.
**Changes:**
- GCS Storage: Return totalCount in getNodesWithPagination() and getVerbsWithPagination()
- S3 Storage: Call initializeCounts() in init() and return totalCount in pagination methods
- OPFS Storage: Call initializeCounts() in init() to load pre-calculated counts
- BaseStorage: Add defensive validation to prevent future adapters from missing totalCount
**Impact:**
- Production deployments now work correctly (Cloud Run, AWS, Kubernetes)
- Data persists correctly across container restarts
- Serverless scale-to-zero deployments now functional
- All storage adapters use O(1) pre-calculated counts (scales to millions of entities)
**Testing:**
- Build passes with no TypeScript errors
- All existing tests pass
- Defensive validation ensures future storage adapters won't have this bug
Fixes critical production issue affecting all persistent storage deployments.
Critical fix for GCS/S3 native storage adapters crashing on metadata index keys.
Problem:
- GCS and S3 adapters crashed with "Invalid UUID format" errors
- System keys like __metadata_field_index__status are NOT UUIDs
- Adapters incorrectly tried to shard all metadata keys as UUIDs
Solution:
- Move sharding/routing logic from adapters to BaseStorage class
- Add analyzeKey() method to detect system keys vs entity UUIDs
- System keys route to _system/ directory (no sharding)
- Entity UUIDs route to sharded directories (256 shards)
- All adapters now implement 4 primitive operations:
* writeObjectToPath(path, data)
* readObjectFromPath(path)
* deleteObjectFromPath(path)
* listObjectsUnderPath(prefix)
Benefits:
- Impossible for future adapters to repeat this mistake
- Zero breaking changes, full backward compatibility
- No data migration required
- Cleaner architecture with better separation of concerns
Updated adapters: GcsStorage, S3CompatibleStorage, OPFSStorage,
FileSystemStorage, MemoryStorage
Added: docs/architecture/data-storage-architecture.md
Updated: README.md with architecture docs link
