Add safe tree operations that guarantee no directory appears as its own child:
- getDirectChildren() returns only immediate children
- getTreeStructure() builds safe tree with recursion protection
- getDescendants() gets all descendants efficiently
- inspect() provides comprehensive path information
Also includes VFSTreeUtils for building and validating tree structures.
This resolves the common infinite recursion issue when building file
explorers, as discovered by the Soulcraft Studio team.
Co-Authored-By: User <noreply@user.local>
- 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>
- Add importFile() method for single file imports
- Implement entity helper methods (linkEntities, findEntityOccurrences)
- Fix critical embedding tokenizer bug (char.charCodeAt error)
- Fix removeRelationship to actually remove using brain.unrelate()
- Add setMetadata/getMetadata methods
- Fix GitBridge to query real relationships and events
- Enable background Knowledge Layer processing
- Rewrite README to emphasize knowledge over files
- Add comprehensive VFS documentation (core, knowledge layer, examples)
- Add complete test suite covering all VFS methods
This completes the VFS implementation with full Knowledge Layer support,
enabling files as living knowledge that understand themselves, evolve
over time, and connect to everything related.
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.
- Modernize BrainyInterface to only contain current API methods (add, relate, find, get)
- Update all interface consumers to use modern API patterns
- Make Brainy class implement clean modernized interface
- Update CLI commands to use add() and relate() instead of deprecated methods
- Update all source code components to use modern API consistently
- Update examples and integration tests to modern patterns
- Improve architectural consistency across the entire codebase
BREAKING: BrainyInterface no longer contains deprecated methods
Migration: Use add() instead of addNoun(), relate() instead of addVerb()
- Implement self-configuring validation that adapts to system resources
- Add validation for all CRUD operations (add, update, delete, find, relate)
- Auto-configure limits based on available memory (1GB = 10K limit, 8GB = 80K)
- Monitor and auto-tune performance based on query response times
- Fix multiple type filtering with proper anyOf structure
- Enhance type safety by requiring NounType/VerbType enums
- Fix tests to validate correct behavior (no fake implementations)
- Add comprehensive VALIDATION.md documentation
- Update API_REFERENCE.md with validation rules and examples
- Clarify metadata update behavior (null keeps existing, {} clears)
BREAKING CHANGE: getFieldsForType() now requires NounType enum instead of string
Co-Authored-By: Claude <noreply@anthropic.com>
Major enhancements for type safety and developer experience:
- Add BrainyTypes static API for type management and AI-powered suggestions
- Implement strict type validation for all 31 NounType categories
- Remove dangerous generic add() method that bypassed type safety
- Add intelligent type inference with confidence scoring
- Provide helpful error messages with typo suggestions using Levenshtein distance
- Update all internal code, examples, and documentation to use typed methods
- Enhance CLI with new type management commands (types, suggest, validate)
Breaking changes:
- Remove deprecated add() method - use addNoun() with explicit type parameter
- All addNoun() calls now require explicit type as second parameter
This release significantly improves type safety across the entire system while
maintaining backward compatibility for properly typed method calls.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Implements intelligent display fields with AI-generated titles and descriptions
- Leverages existing IntelligentTypeMatcher for semantic type detection
- Adds lazy computation with LRU caching for zero performance impact
- Enhances CLI with clean, minimal formatting (no visual clutter)
- Provides method-based API (getDisplay()) to avoid namespace conflicts
- Maintains 100% backward compatibility with existing code
- Enables by default with complete isolation architecture
- Includes comprehensive tests and documentation
The augmentation transforms search results and data display with smart,
contextual information while maintaining Soulcraft's clean aesthetic.
BREAKING CHANGE: Remove hard delete option from deleteVerb() for consistent API
- Add complete metadata namespace architecture with O(1) soft delete performance
- Implement periodic cleanup system for old soft-deleted items
- Add restore methods for both nouns and verbs
- Require metadata contracts for all augmentations
- Eliminate namespace collisions with clean separation (_brainy, _augmentations, _audit)
- Optimize index performance using flattened dot-notation for O(1) lookups
- Add comprehensive augmentation safety system with type-safe access control
- Maintain full backward compatibility for existing data
- Add enterprise-grade cleanup with configurable age thresholds and batch processing
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
✨ ONE universal import method for everything
- Auto-detects files, URLs, and raw data
- Intelligent noun/verb type matching using embeddings
- Support for JSON, CSV, YAML, and text formats
- Zero configuration required
🧠 Intelligent Type Matching
- Uses semantic embeddings to match 31 noun types
- Automatically detects 40 verb relationship types
- Confidence scores for type predictions
- Caching for improved performance
📦 Import Manager
- Centralized import logic with lazy loading
- Integrates NeuralImportAugmentation for AI processing
- Proper CSV parsing with quote handling
- Basic YAML support
🎯 Simplified API
- brain.import() - ONE method that handles everything
- Auto-detection of URLs and file paths
- Backwards compatible with existing code
- Clean, modern, delightful developer experience
📚 Documentation
- Comprehensive import guide in docs/guides/import-anything.md
- Examples for every format and use case
- Philosophy of simplicity and zero config
✅ Tests
- Full unit test coverage for import functionality
- Type matching tests for all 31 nouns and 40 verbs
- Tests for CSV, YAML, JSON, and text formats
BREAKING CHANGES: None - fully backward compatible
