Commit graph

5 commits

Author SHA1 Message Date
7f4b1fd192 fix(vfs): correct root entity selection when duplicates exist
When multiple root directory entities exist, initializeRoot() was using
the wrong field name to sort by creation time, causing it to select the
NEWER root (no children) instead of the OLDER root (with children).

Changed from metadata.createdAt (doesn't exist) to entity.createdAt
(correct field). This ensures VFS correctly uses the root with all the
Contains relationships.

Fixes Workshop File Explorer showing 0 files despite 579 VFS entities
being created during import.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-24 17:07:45 -07:00
ae6fbd8c4c fix: add includeVFS parameter to getRelations() - VFS now visible
CRITICAL BUG FIX - VFS Files Were Completely Invisible

Workshop Team Issue:
- Import created 569 VFS files
- vfs.readdir('/') returned 0 items
- VFS was 100% unusable

Root Cause:
v4.4.0 added includeVFS to brain.find() but FORGOT brain.getRelations().
PathResolver.getChildren() calls getRelations() to find VFS relationships,
but those were being excluded by default - making ALL VFS files invisible!

Fix:
1. Add includeVFS parameter to GetRelationsParams interface
2. Wire includeVFS filtering in brain.getRelations()
   - Excludes VFS relationships by default (metadata.isVFS != true)
   - Include them when includeVFS: true
3. Update VFS to mark all relationships with metadata: { isVFS: true }
   - 7 relate() calls updated in VirtualFileSystem.ts
4. Update PathResolver to use includeVFS: true
   - resolveChild() line 200
   - getChildren() line 229

Impact:
- VFS is now fully functional again
- Consistent with v4.4.0 architecture (VFS separate from knowledge graph)
- All APIs now have includeVFS where needed

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-24 15:59:41 -07:00
f8d2d37b82 fix: VFS where clause field names + isVFS flag
CRITICAL FIX: VFS was using incorrect field names in where clauses
- Metadata index stores flat fields: path, vfsType, name
- VFS queried with: 'metadata.path', 'metadata.vfsType' (wrong!)
- Fixed to use correct field names in where clauses

Changes:
- initializeRoot() now uses correct where clause (no workaround needed)
- Added isVFS flag to all VFS entities (mkdir, writeFile, root)
- Updated VFSMetadata type to include isVFS field
- Removed PathResolver fallback (production code, no fallbacks)

This fixes:
- Duplicate root entities (Workshop team had ~10 roots!)
- VFS queries now work correctly with metadata index
- Clean separation between VFS and knowledge graph entities

Production-ready: No mocks, no fallbacks, no workarounds
2025-10-24 11:12:27 -07:00
4f76dac7be feat: refactor VFS to use proper Brainy graph relationships
- Replace metadata path queries with brain.getRelations() API
- Use graph traversal for parent-child relationships via VerbType.Contains
- Remove fallback metadata queries - trust graph relationships completely
- Fix getChildren() to properly query relationship graph
- Update getRelated() and getRelationships() to use native Brainy APIs

This enables full graph benefits: indexes, optimizations, and visualizations
now work correctly with VFS. The filesystem structure is now a true graph
using Brainy's native relationship system.

Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-25 14:51:08 -07:00
b3c4f348ab feat: implement complete VFS with Knowledge Layer integration
Add production-ready Virtual File System with intelligent Knowledge Layer:

Core VFS Features:
- Complete file system operations (read, write, mkdir, etc.)
- Intelligent PathResolver with 4-layer caching system
- Chunked storage for large files with real compression
- Embedding generation for semantic operations
- File relationships and metadata tracking
- Import functionality from local filesystem

Knowledge Layer Integration:
- EventRecorder for complete file history and temporal coupling
- SemanticVersioning with content-based change detection
- PersistentEntitySystem for character/entity tracking across files
- ConceptSystem for universal concept mapping and graphs
- GitBridge for import/export between VFS and Git repositories

Architecture:
- KnowledgeAugmentation properly integrated into Brainy augmentation system
- KnowledgeLayer wrapper provides real-time VFS operation interception
- Background processing ensures VFS operations remain fast
- All components use real Brainy embed() method for embeddings
- Support for creative writing, coding projects, and project management

Technical Implementation:
- Fixed all stub/mock implementations with real working code
- TypeScript compilation passes without errors
- Comprehensive test suite demonstrating all features
- Documentation covering architecture and usage patterns
- Backwards compatible with existing Brainy functionality

This enables scenarios like writing books with persistent characters,
managing coding projects with concept tracking, and complete project
coordination with intelligent file relationships.
2025-09-24 17:31:48 -07:00