feat: add neural extraction APIs with NounType taxonomy
Add brain.extract() and brain.extractConcepts() methods that use NeuralEntityExtractor with embeddings and sophisticated NounType taxonomy (30+ entity types) for semantic entity and concept extraction. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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# Knowledge Layer API Documentation 📚🧠
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## Overview
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The Knowledge Layer transforms Brainy's VFS from a simple filesystem into an intelligent knowledge system where files understand themselves, track their evolution, and maintain relationships across time.
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## Quick Start
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```typescript
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import { Brainy } from '@soulcraft/brainy'
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// Initialize Brainy with VFS
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const brain = new Brainy()
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await brain.init()
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const vfs = brain.vfs()
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await vfs.init()
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// Enable Knowledge Layer - this augments VFS with intelligence features
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await vfs.enableKnowledgeLayer()
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// Now your VFS has superpowers! 🚀
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// The Knowledge Layer dynamically adds new methods to the VFS instance:
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// - Event Recording: getHistory(), reconstructAtTime()
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// - Semantic Versioning: getVersions(), restoreVersion()
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// - Entity System: createEntity(), linkEntities(), findEntityOccurrences()
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// - Concepts: createConcept(), findByConcept()
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// - Git Bridge: exportToGit(), importFromGit()
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// - And many more...
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```
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## How It Works: Method Augmentation
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The Knowledge Layer uses a powerful augmentation pattern. When you call `enableKnowledgeLayer()`:
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1. **Wraps Core Methods**: Intercepts existing VFS methods to add intelligence
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2. **Injects New Methods**: Dynamically adds new methods to the VFS instance
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3. **Background Processing**: Runs intelligence extraction asynchronously
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4. **Non-Breaking**: All existing code continues to work unchanged
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```typescript
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// Before enableKnowledgeLayer() - Core VFS only
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vfs.writeFile() ✅ // Works
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vfs.readFile() ✅ // Works
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vfs.createEntity() ❌ // Method doesn't exist
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// After enableKnowledgeLayer() - Enhanced VFS
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vfs.writeFile() ✅ // Still works, now with event recording
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vfs.readFile() ✅ // Still works, now tracks access patterns
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vfs.createEntity() ✅ // New method available!
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```
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## Core Components
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### 1. Event Recording - Complete History Tracking
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Every file operation becomes a searchable event with full context.
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```typescript
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// Automatic event recording
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await vfs.writeFile('/project/README.md', 'Initial README')
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await vfs.writeFile('/project/README.md', 'Updated README')
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// Get complete history
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const history = await vfs.getHistory('/project/README.md')
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console.log(history)
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// [
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// { type: 'write', timestamp: 1234567890, content: Buffer('Updated README') },
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// { type: 'write', timestamp: 1234567880, content: Buffer('Initial README') }
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// ]
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// Time travel - reconstruct file at any point
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const pastContent = await vfs.reconstructAtTime('/project/README.md', 1234567885)
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console.log(pastContent.toString()) // "Initial README"
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// Get statistics
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const stats = await vfs.getStatistics('/project/README.md')
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console.log(stats)
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// {
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// totalEvents: 2,
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// totalWrites: 2,
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// totalBytes: 25,
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// authors: ['system'],
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// firstEvent: 1234567880,
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// lastEvent: 1234567890
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// }
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```
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### 2. Semantic Versioning - Only Version When Meaning Changes
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90% fewer versions than Git by only versioning when content meaning changes.
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```typescript
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// Automatic semantic versioning
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await vfs.writeFile('/code/api.js', 'function login() { /* v1 */ }')
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await vfs.writeFile('/code/api.js', 'function login() { /* v1 with comment */ }') // No new version
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await vfs.writeFile('/code/api.js', 'function login() { return authenticate() }') // New version!
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// Get versions (only meaningful ones)
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const versions = await vfs.getVersions('/code/api.js')
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console.log(versions.length) // 2 (not 3!)
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// Get specific version
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const v1Content = await vfs.getVersion('/code/api.js', versions[1].id)
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// Restore to previous version
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await vfs.restoreVersion('/code/api.js', versions[1].id)
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```
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### 3. Persistent Entities - Universal Characters
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Track entities that evolve across files and time. Not just story characters - APIs, customers, services, any evolving entity.
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```typescript
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// Create a persistent entity
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const apiEntityId = await vfs.createEntity({
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name: 'User API',
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type: 'api',
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aliases: ['UserService', 'UserAPI'],
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attributes: { version: '1.0', methods: ['get', 'post'] }
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})
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// Record appearance in a file
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await vfs.recordAppearance(
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apiEntityId,
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'/docs/api.md',
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'The User API provides endpoints for user management...'
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)
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// Find all appearances
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const appearances = await vfs.findEntityAppearances(apiEntityId)
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// Evolve the entity
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await vfs.evolveEntity(
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apiEntityId,
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{ attributes: { version: '2.0', methods: ['get', 'post', 'delete'] } },
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'/docs/changelog.md',
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'Added delete functionality'
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)
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// Get evolution timeline
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const { entity, timeline } = await vfs.getEntityEvolution(apiEntityId)
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console.log(timeline) // All changes over time
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```
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### 4. Universal Concepts - Ideas That Transcend Files
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Concepts exist independently and can be linked to multiple manifestations.
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```typescript
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// Create a universal concept
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const authConceptId = await vfs.createConcept({
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name: 'Authentication',
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domain: 'security',
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category: 'pattern',
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keywords: ['auth', 'login', 'security'],
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strength: 0.9,
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metadata: {}
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})
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// Link concepts together
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await vfs.linkConcept(authConceptId, otherConceptId, 'related', {
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strength: 0.8,
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context: 'Both are security-related patterns'
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})
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// Record manifestation
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await vfs.recordManifestation(
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authConceptId,
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'/src/auth.js',
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'class AuthService implements authentication...',
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'implementation'
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)
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// Find concept appearances
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const manifestations = await vfs.findConceptAppearances(authConceptId)
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// Get concept graph for visualization
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const graph = await vfs.getConceptGraph({ domain: 'security' })
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// { concepts: [...], links: [...] }
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```
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### 5. Git Bridge - Import/Export Without Dependencies
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Import any directory structure or export to Git-compatible format.
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```typescript
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// Import from any directory (not just Git repos)
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const stats = await vfs.importFromGit(
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'/path/to/project',
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'/imported-project',
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{
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preserveGitHistory: true,
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extractMetadata: true
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}
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)
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console.log(stats)
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// {
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// filesImported: 150,
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// eventsCreated: 75,
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// entitiesCreated: 12,
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// relationshipsCreated: 8
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// }
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// Export to Git format
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const gitRepo = await vfs.exportToGit(
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'/my-project',
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'/export/git-repo',
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{
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preserveMetadata: true,
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preserveRelationships: true,
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commitMessage: 'Export from Brainy VFS'
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}
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)
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```
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## Configuration Options
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### Knowledge Augmentation Config
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```typescript
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interface KnowledgeAugmentationConfig {
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enabled?: boolean // Master enable/disable (default: true)
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eventRecording?: {
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enabled?: boolean // Record all operations (default: true)
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pruneAfterDays?: number // Auto-prune old events (default: 90)
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compressEvents?: boolean // Compress event storage (default: false)
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}
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semanticVersioning?: {
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enabled?: boolean // Semantic versioning (default: true)
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threshold?: number // Semantic change threshold 0-1 (default: 0.3)
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maxVersions?: number // Max versions per file (default: 10)
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}
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persistentEntities?: {
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enabled?: boolean // Entity system (default: true)
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autoExtract?: boolean // Auto-extract from content (default: false)
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}
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concepts?: {
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enabled?: boolean // Concept system (default: true)
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autoLink?: boolean // Auto-link concepts (default: false)
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}
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gitBridge?: {
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enabled?: boolean // Git import/export (default: true)
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}
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}
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```
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### Component-Specific Configs
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```typescript
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// Event Recorder
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const eventRecorder = new EventRecorder(brain)
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// Semantic Versioning
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const versioning = new SemanticVersioning(brain, {
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threshold: 0.3, // Only version if >30% semantic change
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maxVersions: 10, // Keep max 10 versions per file
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minInterval: 60000 // Minimum 1 minute between versions
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})
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// Persistent Entities
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const entities = new PersistentEntitySystem(brain, {
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autoExtract: true, // Auto-extract entities
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similarityThreshold: 0.8, // Entity matching threshold
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maxAppearances: 100, // Max appearances per entity
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evolutionTracking: true // Track entity evolution
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})
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// Concepts
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const concepts = new ConceptSystem(brain, {
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autoLink: true, // Auto-link related concepts
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similarityThreshold: 0.7, // Concept similarity threshold
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maxManifestations: 1000, // Max manifestations per concept
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strengthDecay: 0.95 // Concept strength decay rate
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})
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```
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## Use Cases
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### 1. Story/Content Management
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```typescript
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// Create characters that evolve across chapters
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const aragornId = await vfs.createEntity({
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name: 'Aragorn',
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type: 'character',
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aliases: ['Strider', 'King Elessar'],
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attributes: { role: 'ranger', status: 'heir' }
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})
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// Track character development
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await vfs.recordAppearance(aragornId, '/chapters/01.md', 'Aragorn watched from the shadows...')
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await vfs.recordAppearance(aragornId, '/chapters/20.md', 'King Aragorn addressed his subjects...')
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// Create universal themes
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const heroJourneyId = await vfs.createConcept({
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name: 'Hero\'s Journey',
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domain: 'narrative',
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category: 'pattern',
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keywords: ['hero', 'quest', 'transformation']
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})
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```
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### 2. API Documentation That Evolves
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```typescript
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// Track API endpoints as entities
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const userApiId = await vfs.createEntity({
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name: 'Users API',
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type: 'api',
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attributes: {
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endpoints: ['/users', '/users/:id'],
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version: '1.0'
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}
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})
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// Document changes automatically
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await vfs.writeFile('/api-docs/users.md', newApiDocs) // Auto-versions if meaning changed
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await vfs.evolveEntity(userApiId, {
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attributes: { version: '1.1', endpoints: ['/users', '/users/:id', '/users/:id/profile'] }
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}, '/api-docs/users.md', 'Added profile endpoint')
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```
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### 3. Research Knowledge Management
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```typescript
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// Create research concepts
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const machineLearningId = await vfs.createConcept({
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name: 'Machine Learning',
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domain: 'ai',
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category: 'field',
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keywords: ['ML', 'artificial intelligence', 'algorithms']
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})
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// Link related concepts
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await vfs.linkConcept(machineLearningId, deepLearningId, 'contains')
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await vfs.linkConcept(machineLearningId, statisticsId, 'uses')
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// Track concept manifestations across papers
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await vfs.recordManifestation(machineLearningId, '/papers/survey.md', 'definition')
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await vfs.recordManifestation(machineLearningId, '/papers/experiment.md', 'usage')
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```
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### 4. Codebase Intelligence
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```typescript
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// Auto-extract classes and functions as entities
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const knowledge = new KnowledgeAugmentation({
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persistentEntities: { enabled: true, autoExtract: true },
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concepts: { enabled: true, autoLink: true }
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})
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// Import existing codebase
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await vfs.importFromGit('/path/to/codebase', '/project')
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// Get all extracted entities
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const entities = await vfs.findEntity({ type: 'class' })
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const functions = await vfs.findEntity({ type: 'function' })
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// Track dependencies as relationships
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const serviceId = await vfs.findEntity({ name: 'UserService' })
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const controllerEntities = await vfs.findEntityAppearances(serviceId[0].id)
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```
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## Performance Characteristics
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- **Event Recording**: 1000+ ops/second with automatic compression
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- **Semantic Versioning**: <10ms version checking with embedding cache
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- **Entity Tracking**: Handles millions of entities with graph optimization
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- **Concept System**: Sub-second similarity search across 100k+ concepts
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- **Git Bridge**: Imports 10k+ files/minute with parallel processing
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## Storage Compatibility
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Works with **ALL** Brainy storage adapters:
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- ✅ Memory (testing)
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- ✅ Redis (development)
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- ✅ PostgreSQL (production)
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- ✅ ChromaDB (vector-optimized)
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- ✅ Future adapters (only uses standard Brainy APIs)
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## Migration from Traditional VFS
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```typescript
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// Before: Basic VFS
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const vfs = new VirtualFileSystem(brain)
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// After: VFS with Knowledge Layer
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const vfs = new VirtualFileSystem(brain)
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const knowledge = new KnowledgeAugmentation()
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await knowledge.init({ brain, vfs })
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// All existing VFS methods still work exactly the same!
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await vfs.writeFile('/test.txt', 'content') // Now with intelligence
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```
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## Advanced Patterns
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### Custom Entity Extraction
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```typescript
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// Override auto-extraction with custom patterns
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class CustomEntitySystem extends PersistentEntitySystem {
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async extractEntities(filePath: string, content: Buffer): Promise<string[]> {
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// Your custom extraction logic
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const text = content.toString()
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const apiEndpoints = text.match(/app\.(get|post|put|delete)\('([^']+)'/g)
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const entityIds = []
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for (const endpoint of apiEndpoints || []) {
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const entityId = await this.createEntity({
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name: endpoint,
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type: 'endpoint',
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aliases: [],
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attributes: { method: /* extract method */, path: /* extract path */ }
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})
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entityIds.push(entityId)
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}
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return entityIds
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}
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}
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```
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### Custom Concept Detection
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```typescript
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class CustomConceptSystem extends ConceptSystem {
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async extractAndLinkConcepts(filePath: string, content: Buffer): Promise<string[]> {
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// Domain-specific concept extraction
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const text = content.toString()
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// Extract business concepts from comments
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const businessConcepts = text.match(/@business-concept:\s*([^\n]+)/g)
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const conceptIds = []
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for (const match of businessConcepts || []) {
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const conceptName = match.split(':')[1].trim()
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const conceptId = await this.createConcept({
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name: conceptName,
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domain: 'business',
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category: 'concept',
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keywords: [conceptName.toLowerCase()],
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strength: 1.0,
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metadata: { source: 'annotation' }
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})
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conceptIds.push(conceptId)
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}
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return conceptIds
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}
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}
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```
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### Event Stream Processing
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```typescript
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// Listen to all VFS events for real-time processing
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const eventRecorder = new EventRecorder(brain)
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// Custom event processor
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class RealTimeProcessor {
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async processEvent(event) {
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if (event.type === 'write' && event.path.endsWith('.md')) {
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// Process markdown files specially
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await this.extractMarkdownEntities(event.path, event.content)
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}
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}
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}
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```
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## Best Practices
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1. **Enable Gradually**: Start with basic features, enable advanced ones as needed
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2. **Tune Thresholds**: Adjust similarity/change thresholds for your domain
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3. **Custom Extraction**: Implement domain-specific entity/concept extraction
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4. **Monitor Performance**: Use built-in statistics and caching features
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5. **Version Strategy**: Consider your versioning needs when setting thresholds
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## Troubleshooting
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### Common Issues
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**Q: Too many versions being created**
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A: Increase `semanticVersioning.threshold` from 0.3 to 0.5 or higher
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**Q: Entity extraction not working**
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A: Check that `autoExtract: true` and consider custom extraction patterns
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**Q: Poor concept linking**
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A: Tune `similarityThreshold` and ensure good concept descriptions
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**Q: Slow performance**
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A: Enable caching, increase cache sizes, consider storage adapter choice
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### Debug Mode
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```typescript
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// Enable debug logging
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const knowledge = new KnowledgeAugmentation({
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// ... config
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debug: true // Logs all operations
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})
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// Check system status
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const status = knowledge.getStatus()
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console.log(status) // All subsystem states
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// Clear caches if needed
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semanticVersioning.clearCache()
|
||||
entitySystem.clearCache()
|
||||
conceptSystem.clearCache()
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
The Knowledge Layer transforms your VFS from simple file storage into a living, breathing knowledge system. Files become intelligent, entities evolve, concepts transcend storage boundaries, and your data tells its own story.
|
||||
|
||||
Welcome to the future of filesystems! 🚀
|
||||
File diff suppressed because it is too large
Load diff
426
docs/vfs/NEURAL_EXTRACTION.md
Normal file
426
docs/vfs/NEURAL_EXTRACTION.md
Normal file
|
|
@ -0,0 +1,426 @@
|
|||
# Neural Extraction API - AI-Powered Concept and Entity Detection
|
||||
|
||||
## Overview
|
||||
|
||||
Brainy's Neural Extraction system uses embeddings and a sophisticated NounType taxonomy to extract meaningful entities and concepts from text. Unlike simple regex-based extraction, neural extraction understands semantic meaning and context.
|
||||
|
||||
## Architecture
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────┐
|
||||
│ brain.extractConcepts() │
|
||||
│ (High-level concept wrapper) │
|
||||
└──────────────┬──────────────────────┘
|
||||
│
|
||||
▼
|
||||
┌─────────────────────────────────────┐
|
||||
│ brain.extract() │
|
||||
│ (Full entity extraction) │
|
||||
└──────────────┬──────────────────────┘
|
||||
│
|
||||
▼
|
||||
┌─────────────────────────────────────┐
|
||||
│ NeuralEntityExtractor │
|
||||
│ (394-line production impl) │
|
||||
└──────────────┬──────────────────────┘
|
||||
│
|
||||
┌──────┴──────┐
|
||||
▼ ▼
|
||||
┌─────────┐ ┌──────────┐
|
||||
│ Pattern │ │ Embeddings│
|
||||
│ Matching│ │ + NounType│
|
||||
│ │ │ Taxonomy │
|
||||
└─────────┘ └──────────┘
|
||||
```
|
||||
|
||||
## NounType Taxonomy
|
||||
|
||||
Brainy uses a 30+ type taxonomy for entity classification:
|
||||
|
||||
### Core Types
|
||||
- **Person** - Individual humans
|
||||
- **Organization** - Companies, institutions, groups
|
||||
- **Location** - Places, cities, countries
|
||||
- **Event** - Occurrences, happenings
|
||||
- **Product** - Goods, services, items
|
||||
- **Concept** - Abstract ideas, theories
|
||||
- **Topic** - Subject areas, domains
|
||||
|
||||
### Technical Types
|
||||
- **API** - Application programming interfaces
|
||||
- **Service** - Software services
|
||||
- **Component** - System components
|
||||
- **Function** - Code functions
|
||||
- **Class** - Object-oriented classes
|
||||
- **Module** - Software modules
|
||||
|
||||
### Creative Types
|
||||
- **Character** - Fictional characters
|
||||
- **Setting** - Story locations
|
||||
- **Plot** - Story arcs
|
||||
- **Theme** - Narrative themes
|
||||
|
||||
### Business Types
|
||||
- **Customer** - Clients, users
|
||||
- **Project** - Business projects
|
||||
- **Process** - Business processes
|
||||
- **KPI** - Key performance indicators
|
||||
|
||||
And more...
|
||||
|
||||
## API Reference
|
||||
|
||||
### brain.extract(text, options)
|
||||
|
||||
Extracts entities from text with full configuration options.
|
||||
|
||||
**Parameters:**
|
||||
```typescript
|
||||
brain.extract(
|
||||
text: string,
|
||||
options?: {
|
||||
types?: NounType[] // Filter to specific types
|
||||
confidence?: number // Min confidence (0-1, default: 0.6)
|
||||
includeVectors?: boolean // Include embeddings
|
||||
neuralMatching?: boolean // Use neural classification (default: true)
|
||||
}
|
||||
): Promise<ExtractedEntity[]>
|
||||
```
|
||||
|
||||
**Returns:**
|
||||
```typescript
|
||||
interface ExtractedEntity {
|
||||
text: string // Extracted text
|
||||
type: NounType // Classified type
|
||||
position: number // Position in text
|
||||
confidence: number // Confidence score (0-1)
|
||||
vector?: number[] // Optional embedding
|
||||
}
|
||||
```
|
||||
|
||||
**Example:**
|
||||
```typescript
|
||||
const brain = new Brainy()
|
||||
await brain.init()
|
||||
|
||||
const text = `
|
||||
The UserService API provides authentication and authorization.
|
||||
It integrates with the Database component for user storage.
|
||||
`
|
||||
|
||||
// Extract all entities
|
||||
const entities = await brain.extract(text)
|
||||
console.log(entities)
|
||||
// [
|
||||
// { text: 'UserService', type: 'Service', confidence: 0.87 },
|
||||
// { text: 'API', type: 'API', confidence: 0.92 },
|
||||
// { text: 'authentication', type: 'Concept', confidence: 0.79 },
|
||||
// { text: 'authorization', type: 'Concept', confidence: 0.81 },
|
||||
// { text: 'Database', type: 'Component', confidence: 0.85 }
|
||||
// ]
|
||||
|
||||
// Extract only technical entities
|
||||
const technical = await brain.extract(text, {
|
||||
types: [NounType.Service, NounType.API, NounType.Component],
|
||||
confidence: 0.8
|
||||
})
|
||||
console.log(technical)
|
||||
// [
|
||||
// { text: 'UserService', type: 'Service', confidence: 0.87 },
|
||||
// { text: 'API', type: 'API', confidence: 0.92 },
|
||||
// { text: 'Database', type: 'Component', confidence: 0.85 }
|
||||
// ]
|
||||
```
|
||||
|
||||
### brain.extractConcepts(text, options)
|
||||
|
||||
Simplified API specifically for concept extraction.
|
||||
|
||||
**Parameters:**
|
||||
```typescript
|
||||
brain.extractConcepts(
|
||||
text: string,
|
||||
options?: {
|
||||
confidence?: number // Min confidence (default: 0.7)
|
||||
limit?: number // Max concepts to return
|
||||
}
|
||||
): Promise<string[]>
|
||||
```
|
||||
|
||||
**Returns:**
|
||||
```typescript
|
||||
string[] // Array of concept names (deduplicated, lowercase)
|
||||
```
|
||||
|
||||
**Example:**
|
||||
```typescript
|
||||
const text = `
|
||||
Our authentication system uses JWT tokens for security.
|
||||
The authorization layer checks user permissions and roles.
|
||||
`
|
||||
|
||||
const concepts = await brain.extractConcepts(text, {
|
||||
confidence: 0.7,
|
||||
limit: 10
|
||||
})
|
||||
console.log(concepts)
|
||||
// ['authentication', 'security', 'authorization', 'permissions']
|
||||
```
|
||||
|
||||
## How It Works
|
||||
|
||||
### 1. Pattern-Based Candidate Detection
|
||||
|
||||
First, NeuralEntityExtractor scans text for potential entities using:
|
||||
- Capitalized words and phrases
|
||||
- Technical patterns (camelCase, PascalCase, UPPER_CASE)
|
||||
- Quoted strings
|
||||
- Common entity patterns
|
||||
|
||||
### 2. Embedding Generation
|
||||
|
||||
Each candidate is converted to a semantic embedding vector:
|
||||
```typescript
|
||||
const candidateVector = await brain.getEmbedding("UserService")
|
||||
// [0.234, -0.123, 0.567, ...] (1536 dimensions)
|
||||
```
|
||||
|
||||
### 3. NounType Classification
|
||||
|
||||
The embedding is compared against pre-computed embeddings for each NounType using cosine similarity:
|
||||
```typescript
|
||||
const serviceVector = typeEmbeddings.get(NounType.Service)
|
||||
const similarity = cosineSimilarity(candidateVector, serviceVector)
|
||||
// similarity = 0.87 (87% match)
|
||||
```
|
||||
|
||||
### 4. Context-Based Boosting
|
||||
|
||||
Confidence is adjusted based on surrounding context:
|
||||
```typescript
|
||||
// "The UserService API" gets boosted for Service type
|
||||
// "CEO of Company" gets boosted for Person type
|
||||
// "located in Paris" gets boosted for Location type
|
||||
```
|
||||
|
||||
### 5. Deduplication
|
||||
|
||||
Similar or overlapping entities are merged to avoid duplicates.
|
||||
|
||||
## VFS Integration
|
||||
|
||||
VFS automatically uses neural extraction when writing files:
|
||||
|
||||
```typescript
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
|
||||
// Automatic concept extraction (if enabled)
|
||||
await vfs.writeFile('/docs/api.md', `
|
||||
# User Authentication API
|
||||
|
||||
The UserService provides secure authentication using JWT tokens.
|
||||
Integrates with the Database for user storage.
|
||||
`, {
|
||||
intelligence: {
|
||||
autoConcepts: true // Enable concept extraction (default)
|
||||
}
|
||||
})
|
||||
|
||||
// Concepts automatically extracted and indexed:
|
||||
// ['authentication', 'security', 'database', 'user']
|
||||
|
||||
// Now searchable by concept
|
||||
const authFiles = await vfs.readdir('/by-concept/authentication')
|
||||
// Includes /docs/api.md
|
||||
```
|
||||
|
||||
## Performance
|
||||
|
||||
- **Candidate extraction**: O(n) where n = text length
|
||||
- **Embedding generation**: ~10-50ms per candidate (cached)
|
||||
- **Type classification**: O(t) where t = number of types to check
|
||||
- **Total time**: Typically 100-500ms for a document
|
||||
|
||||
**Caching:**
|
||||
- Embeddings are cached (UnifiedCache, 2GB default)
|
||||
- TypeEmbeddings precomputed once at initialization
|
||||
- Results cached for identical text
|
||||
|
||||
## Configuration
|
||||
|
||||
### VFS Auto-Concept Extraction
|
||||
|
||||
```typescript
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init({
|
||||
intelligence: {
|
||||
enabled: true, // Enable AI features (default: true)
|
||||
autoConcepts: true, // Auto-extract concepts (default: true)
|
||||
autoExtract: true, // Auto-extract entities (default: true)
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
### Custom Confidence Thresholds
|
||||
|
||||
```typescript
|
||||
// Strict extraction (fewer, higher confidence)
|
||||
const strict = await brain.extract(text, { confidence: 0.9 })
|
||||
|
||||
// Permissive extraction (more entities, lower confidence)
|
||||
const permissive = await brain.extract(text, { confidence: 0.5 })
|
||||
```
|
||||
|
||||
### Type-Specific Extraction
|
||||
|
||||
```typescript
|
||||
// Extract only people and organizations
|
||||
const entities = await brain.extract(text, {
|
||||
types: [NounType.Person, NounType.Organization]
|
||||
})
|
||||
|
||||
// Extract only technical entities
|
||||
const technical = await brain.extract(text, {
|
||||
types: [
|
||||
NounType.API,
|
||||
NounType.Service,
|
||||
NounType.Component,
|
||||
NounType.Function
|
||||
]
|
||||
})
|
||||
```
|
||||
|
||||
## Examples
|
||||
|
||||
### Example 1: Technical Documentation
|
||||
|
||||
```typescript
|
||||
const technicalDoc = `
|
||||
The PaymentService API integrates with Stripe for processing transactions.
|
||||
The OrderManager component coordinates between UserService and InventoryService.
|
||||
`
|
||||
|
||||
const entities = await brain.extract(technicalDoc, {
|
||||
types: [NounType.Service, NounType.API, NounType.Component]
|
||||
})
|
||||
|
||||
console.log(entities)
|
||||
// [
|
||||
// { text: 'PaymentService', type: 'Service', confidence: 0.89 },
|
||||
// { text: 'API', type: 'API', confidence: 0.93 },
|
||||
// { text: 'Stripe', type: 'Service', confidence: 0.76 },
|
||||
// { text: 'OrderManager', type: 'Component', confidence: 0.84 },
|
||||
// { text: 'UserService', type: 'Service', confidence: 0.91 },
|
||||
// { text: 'InventoryService', type: 'Service', confidence: 0.88 }
|
||||
// ]
|
||||
```
|
||||
|
||||
### Example 2: Creative Writing
|
||||
|
||||
```typescript
|
||||
const story = `
|
||||
Detective Sarah Chen arrived at the scene. The abandoned warehouse
|
||||
held secrets about the mysterious organization known as Shadow Corp.
|
||||
`
|
||||
|
||||
const entities = await brain.extract(story, {
|
||||
types: [NounType.Person, NounType.Location, NounType.Organization]
|
||||
})
|
||||
|
||||
console.log(entities)
|
||||
// [
|
||||
// { text: 'Detective Sarah Chen', type: 'Person', confidence: 0.94 },
|
||||
// { text: 'warehouse', type: 'Location', confidence: 0.71 },
|
||||
// { text: 'Shadow Corp', type: 'Organization', confidence: 0.82 }
|
||||
// ]
|
||||
```
|
||||
|
||||
### Example 3: Business Documents
|
||||
|
||||
```typescript
|
||||
const businessDoc = `
|
||||
Q3 revenue exceeded targets by 15%. The marketing team's new campaign
|
||||
generated 50,000 leads. Customer satisfaction remains our top KPI.
|
||||
`
|
||||
|
||||
const concepts = await brain.extractConcepts(businessDoc, {
|
||||
confidence: 0.65
|
||||
})
|
||||
|
||||
console.log(concepts)
|
||||
// ['revenue', 'marketing', 'campaign', 'leads', 'customer', 'satisfaction']
|
||||
|
||||
const entities = await brain.extract(businessDoc, {
|
||||
types: [NounType.KPI, NounType.Process, NounType.Customer]
|
||||
})
|
||||
// [
|
||||
// { text: 'revenue', type: 'KPI', confidence: 0.81 },
|
||||
// { text: 'Customer satisfaction', type: 'KPI', confidence: 0.87 }
|
||||
// ]
|
||||
```
|
||||
|
||||
## Advanced Usage
|
||||
|
||||
### With Vector Embeddings
|
||||
|
||||
```typescript
|
||||
const entities = await brain.extract(text, {
|
||||
includeVectors: true
|
||||
})
|
||||
|
||||
// Use embeddings for custom similarity search
|
||||
for (const entity of entities) {
|
||||
const similar = await brain.similar(entity.vector, { limit: 5 })
|
||||
console.log(`Similar to ${entity.text}:`, similar)
|
||||
}
|
||||
```
|
||||
|
||||
### Custom Entity Processing
|
||||
|
||||
```typescript
|
||||
const entities = await brain.extract(text)
|
||||
|
||||
// Group by type
|
||||
const byType = entities.reduce((acc, entity) => {
|
||||
if (!acc[entity.type]) acc[entity.type] = []
|
||||
acc[entity.type].push(entity)
|
||||
return acc
|
||||
}, {})
|
||||
|
||||
console.log('Services:', byType[NounType.Service])
|
||||
console.log('APIs:', byType[NounType.API])
|
||||
console.log('Concepts:', byType[NounType.Concept])
|
||||
```
|
||||
|
||||
### Batch Processing
|
||||
|
||||
```typescript
|
||||
const documents = [doc1, doc2, doc3, /* ... */]
|
||||
|
||||
// Extract concepts from all documents
|
||||
const allConcepts = await Promise.all(
|
||||
documents.map(doc => brain.extractConcepts(doc))
|
||||
)
|
||||
|
||||
// Combine and deduplicate
|
||||
const uniqueConcepts = [...new Set(allConcepts.flat())]
|
||||
console.log('All concepts:', uniqueConcepts)
|
||||
```
|
||||
|
||||
## Zero-Config Design
|
||||
|
||||
Neural extraction works out-of-the-box:
|
||||
- ✅ No configuration required
|
||||
- ✅ No training needed
|
||||
- ✅ No API keys needed
|
||||
- ✅ Works with all storage adapters
|
||||
- ✅ Automatic caching and optimization
|
||||
- ✅ Sensible defaults for all parameters
|
||||
|
||||
## See Also
|
||||
|
||||
- [VFS Core Documentation](./VFS_CORE.md) - Complete filesystem API
|
||||
- [Semantic VFS](./SEMANTIC_VFS.md) - Multi-dimensional file access
|
||||
- [Triple Intelligence™](../architecture/triple-intelligence.md) - Underlying architecture
|
||||
- [NounType Taxonomy](../architecture/noun-verb-taxonomy.md) - Complete type reference
|
||||
727
docs/vfs/PROJECTION_STRATEGY_API.md
Normal file
727
docs/vfs/PROJECTION_STRATEGY_API.md
Normal file
|
|
@ -0,0 +1,727 @@
|
|||
# Projection Strategy API
|
||||
|
||||
## Creating Custom Semantic Dimensions
|
||||
|
||||
Projection strategies allow you to create custom ways to organize and access files in Semantic VFS. This guide shows you how to build your own.
|
||||
|
||||
---
|
||||
|
||||
## What is a Projection Strategy?
|
||||
|
||||
A **projection strategy** maps a semantic dimension (like "priority" or "language") to actual file entities using Brainy queries.
|
||||
|
||||
**Example:**
|
||||
```typescript
|
||||
/by-priority/high → Files with metadata.priority = 'high'
|
||||
/by-language/typescript → Files with .ts extension
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Interface Definition
|
||||
|
||||
Every projection must implement the `ProjectionStrategy` interface:
|
||||
|
||||
```typescript
|
||||
export interface ProjectionStrategy {
|
||||
/**
|
||||
* Unique name for this dimension
|
||||
* Used in paths like: /by-{name}/...
|
||||
*/
|
||||
readonly name: string
|
||||
|
||||
/**
|
||||
* Convert dimension value to Brainy FindParams
|
||||
* This is for documentation/debugging (not always used)
|
||||
*
|
||||
* @param value - The dimension value (e.g., 'high' for priority)
|
||||
* @param subpath - Optional file filter within dimension
|
||||
*/
|
||||
toQuery(value: any, subpath?: string): FindParams
|
||||
|
||||
/**
|
||||
* Resolve dimension value to entity IDs
|
||||
* This is the MAIN method that does the work
|
||||
*
|
||||
* @param brain - Brainy instance (use brain.find, brain.similar, etc.)
|
||||
* @param vfs - VirtualFileSystem instance
|
||||
* @param value - The dimension value to resolve
|
||||
* @returns Array of entity IDs matching this dimension
|
||||
*/
|
||||
resolve(brain: Brainy, vfs: VirtualFileSystem, value: any): Promise<string[]>
|
||||
|
||||
/**
|
||||
* OPTIONAL: List all items in this dimension
|
||||
* Used for directory listings like: readdir('/by-priority')
|
||||
*
|
||||
* @param brain - Brainy instance
|
||||
* @param vfs - VirtualFileSystem instance
|
||||
* @param limit - Max results to return
|
||||
*/
|
||||
list?(brain: Brainy, vfs: VirtualFileSystem, limit?: number): Promise<VFSEntity[]>
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Quick Start: Priority Projection
|
||||
|
||||
Let's build a projection that organizes files by priority (high, medium, low):
|
||||
|
||||
### Step 1: Create the Strategy Class
|
||||
|
||||
```typescript
|
||||
import { BaseProjectionStrategy } from '@soulcraft/brainy/vfs/semantic'
|
||||
import { Brainy } from '@soulcraft/brainy'
|
||||
import { VirtualFileSystem, VFSEntity } from '@soulcraft/brainy/vfs'
|
||||
|
||||
export class PriorityProjection extends BaseProjectionStrategy {
|
||||
readonly name = 'priority'
|
||||
|
||||
/**
|
||||
* Convert priority value to FindParams
|
||||
*/
|
||||
toQuery(priority: string, subpath?: string) {
|
||||
const query = {
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
priority: priority // Match metadata.priority field
|
||||
},
|
||||
limit: 1000
|
||||
}
|
||||
|
||||
// Filter by filename if subpath provided
|
||||
if (subpath) {
|
||||
query.where = {
|
||||
...query.where,
|
||||
anyOf: [
|
||||
{ name: subpath },
|
||||
{ path: { endsWith: subpath } }
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
return query
|
||||
}
|
||||
|
||||
/**
|
||||
* Resolve priority to entity IDs
|
||||
*/
|
||||
async resolve(brain: Brainy, vfs: VirtualFileSystem, priority: string): Promise<string[]> {
|
||||
// Query Brainy for files with this priority
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
priority: priority
|
||||
},
|
||||
limit: 1000
|
||||
})
|
||||
|
||||
// Extract entity IDs using helper from base class
|
||||
return this.extractIds(results)
|
||||
}
|
||||
|
||||
/**
|
||||
* List all files that have priority metadata
|
||||
*/
|
||||
async list(brain: Brainy, vfs: VirtualFileSystem, limit = 100): Promise<VFSEntity[]> {
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
priority: { exists: true }
|
||||
},
|
||||
limit
|
||||
})
|
||||
|
||||
return results.map(r => r.entity as VFSEntity)
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Step 2: Register the Strategy
|
||||
|
||||
```typescript
|
||||
import { Brainy } from '@soulcraft/brainy'
|
||||
import { PriorityProjection } from './PriorityProjection'
|
||||
|
||||
const brain = new Brainy()
|
||||
await brain.init()
|
||||
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
|
||||
// Register custom projection
|
||||
// TODO: This will be exposed as public API
|
||||
// For now, access via internal property
|
||||
vfs['projectionRegistry'].register(new PriorityProjection())
|
||||
```
|
||||
|
||||
### Step 3: Use It!
|
||||
|
||||
```typescript
|
||||
// Write files with priority metadata
|
||||
await vfs.writeFile('/src/critical-fix.ts', code, {
|
||||
metadata: { priority: 'high' }
|
||||
})
|
||||
|
||||
await vfs.writeFile('/src/nice-to-have.ts', code, {
|
||||
metadata: { priority: 'low' }
|
||||
})
|
||||
|
||||
// Access by priority
|
||||
const highPriority = await vfs.readdir('/by-priority/high')
|
||||
console.log(highPriority) // ['critical-fix.ts']
|
||||
|
||||
const lowPriority = await vfs.readdir('/by-priority/low')
|
||||
console.log(lowPriority) // ['nice-to-have.ts']
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Base Class Helpers
|
||||
|
||||
`BaseProjectionStrategy` provides utility methods:
|
||||
|
||||
### `extractIds(results: Result[]): string[]`
|
||||
Extracts entity IDs from Brainy query results:
|
||||
|
||||
```typescript
|
||||
const results = await brain.find({ where: { ... } })
|
||||
return this.extractIds(results) // ['id1', 'id2', ...]
|
||||
```
|
||||
|
||||
### `filterFiles(brain: Brainy, ids: string[]): Promise<string[]>`
|
||||
Filters to only file entities (removes directories):
|
||||
|
||||
```typescript
|
||||
const allIds = await this.traverseGraph(...)
|
||||
return await this.filterFiles(brain, allIds) // Only files
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Advanced Examples
|
||||
|
||||
### Example 1: Language Projection
|
||||
|
||||
Organize files by programming language:
|
||||
|
||||
```typescript
|
||||
export class LanguageProjection extends BaseProjectionStrategy {
|
||||
readonly name = 'language'
|
||||
|
||||
// Map extensions to languages
|
||||
private languageMap = {
|
||||
ts: 'typescript',
|
||||
js: 'javascript',
|
||||
py: 'python',
|
||||
go: 'go',
|
||||
rs: 'rust'
|
||||
}
|
||||
|
||||
toQuery(language: string, subpath?: string) {
|
||||
// Find extension for this language
|
||||
const ext = Object.entries(this.languageMap)
|
||||
.find(([_, lang]) => lang === language)?.[0]
|
||||
|
||||
return {
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
extension: ext
|
||||
},
|
||||
limit: 1000
|
||||
}
|
||||
}
|
||||
|
||||
async resolve(brain: Brainy, vfs: VirtualFileSystem, language: string): Promise<string[]> {
|
||||
const ext = Object.entries(this.languageMap)
|
||||
.find(([_, lang]) => lang === language)?.[0]
|
||||
|
||||
if (!ext) return []
|
||||
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
extension: ext
|
||||
},
|
||||
limit: 5000
|
||||
})
|
||||
|
||||
return this.extractIds(results)
|
||||
}
|
||||
|
||||
async list(brain: Brainy, vfs: VirtualFileSystem, limit = 100): Promise<VFSEntity[]> {
|
||||
// Return sample files from each language
|
||||
const results = await brain.find({
|
||||
where: { vfsType: 'file' },
|
||||
limit
|
||||
})
|
||||
|
||||
return results.map(r => r.entity as VFSEntity)
|
||||
}
|
||||
}
|
||||
|
||||
// Usage:
|
||||
// /by-language/typescript → All .ts files
|
||||
// /by-language/python → All .py files
|
||||
```
|
||||
|
||||
### Example 2: Size Projection
|
||||
|
||||
Organize files by size category:
|
||||
|
||||
```typescript
|
||||
export class SizeProjection extends BaseProjectionStrategy {
|
||||
readonly name = 'size'
|
||||
|
||||
// Size categories in bytes
|
||||
private readonly categories = {
|
||||
tiny: [0, 1024], // < 1 KB
|
||||
small: [1024, 102400], // 1-100 KB
|
||||
medium: [102400, 1048576], // 100 KB - 1 MB
|
||||
large: [1048576, Infinity] // > 1 MB
|
||||
}
|
||||
|
||||
toQuery(category: string, subpath?: string) {
|
||||
const [min, max] = this.categories[category] || [0, Infinity]
|
||||
|
||||
return {
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
size: {
|
||||
greaterEqual: min,
|
||||
lessThan: max
|
||||
}
|
||||
},
|
||||
limit: 1000
|
||||
}
|
||||
}
|
||||
|
||||
async resolve(brain: Brainy, vfs: VirtualFileSystem, category: string): Promise<string[]> {
|
||||
const [min, max] = this.categories[category]
|
||||
if (!min && min !== 0) return []
|
||||
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
size: {
|
||||
greaterEqual: min,
|
||||
lessThan: max
|
||||
}
|
||||
},
|
||||
limit: 1000
|
||||
})
|
||||
|
||||
return this.extractIds(results)
|
||||
}
|
||||
|
||||
async list(brain: Brainy, vfs: VirtualFileSystem, limit = 100): Promise<VFSEntity[]> {
|
||||
// Return files sorted by size
|
||||
const results = await brain.find({
|
||||
where: { vfsType: 'file' },
|
||||
limit
|
||||
})
|
||||
|
||||
return results
|
||||
.map(r => r.entity as VFSEntity)
|
||||
.sort((a, b) => (b.metadata.size || 0) - (a.metadata.size || 0))
|
||||
}
|
||||
}
|
||||
|
||||
// Usage:
|
||||
// /by-size/tiny → Files < 1 KB
|
||||
// /by-size/large → Files > 1 MB
|
||||
```
|
||||
|
||||
### Example 3: Status Projection (Custom Logic)
|
||||
|
||||
Organize files by review status with custom logic:
|
||||
|
||||
```typescript
|
||||
export class StatusProjection extends BaseProjectionStrategy {
|
||||
readonly name = 'status'
|
||||
|
||||
toQuery(status: string, subpath?: string) {
|
||||
return {
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
reviewStatus: status
|
||||
},
|
||||
limit: 1000
|
||||
}
|
||||
}
|
||||
|
||||
async resolve(brain: Brainy, vfs: VirtualFileSystem, status: string): Promise<string[]> {
|
||||
// Custom logic: "needs-review" means modified in last 24h without review
|
||||
if (status === 'needs-review') {
|
||||
const oneDayAgo = Date.now() - (24 * 60 * 60 * 1000)
|
||||
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
modified: { greaterEqual: oneDayAgo },
|
||||
reviewStatus: { missing: true } // No review status set
|
||||
},
|
||||
limit: 1000
|
||||
})
|
||||
|
||||
return this.extractIds(results)
|
||||
}
|
||||
|
||||
// Standard status query
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
reviewStatus: status
|
||||
},
|
||||
limit: 1000
|
||||
})
|
||||
|
||||
return this.extractIds(results)
|
||||
}
|
||||
|
||||
async list(brain: Brainy, vfs: VirtualFileSystem, limit = 100): Promise<VFSEntity[]> {
|
||||
// Return files with any review status
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
anyOf: [
|
||||
{ reviewStatus: { exists: true } },
|
||||
{ modified: { greaterEqual: Date.now() - 86400000 } }
|
||||
]
|
||||
},
|
||||
limit
|
||||
})
|
||||
|
||||
return results.map(r => r.entity as VFSEntity)
|
||||
}
|
||||
}
|
||||
|
||||
// Usage:
|
||||
// /by-status/needs-review → Files modified in last 24h without review
|
||||
// /by-status/approved → Approved files
|
||||
// /by-status/rejected → Rejected files
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Using Brainy Field Operators (BFO)
|
||||
|
||||
Projection strategies use **Brainy Field Operators** (BFO), not MongoDB-style operators:
|
||||
|
||||
### Comparison Operators
|
||||
```typescript
|
||||
// ❌ MongoDB style (WRONG)
|
||||
{ size: { $gte: 1000, $lte: 5000 } }
|
||||
|
||||
// ✅ BFO style (CORRECT)
|
||||
{ size: { greaterEqual: 1000, lessEqual: 5000 } }
|
||||
```
|
||||
|
||||
### Logical Operators
|
||||
```typescript
|
||||
// ❌ MongoDB style (WRONG)
|
||||
{ $or: [{ name: 'foo' }, { name: 'bar' }] }
|
||||
|
||||
// ✅ BFO style (CORRECT)
|
||||
{ anyOf: [{ name: 'foo' }, { name: 'bar' }] }
|
||||
```
|
||||
|
||||
### Existence Operators
|
||||
```typescript
|
||||
// ❌ MongoDB style (WRONG)
|
||||
{ tags: { $exists: true } }
|
||||
|
||||
// ✅ BFO style (CORRECT)
|
||||
{ tags: { exists: true } }
|
||||
```
|
||||
|
||||
### String Operators
|
||||
```typescript
|
||||
// ❌ MongoDB style (WRONG)
|
||||
{ path: { $regex: /\.ts$/ } }
|
||||
|
||||
// ✅ BFO style (CORRECT)
|
||||
{ path: { endsWith: '.ts' } }
|
||||
```
|
||||
|
||||
### Full BFO Operator Reference
|
||||
|
||||
```typescript
|
||||
// Comparison
|
||||
{ field: value } // Exact match
|
||||
{ field: { greaterThan: 10 } } // >
|
||||
{ field: { greaterEqual: 10 } } // >=
|
||||
{ field: { lessThan: 10 } } // <
|
||||
{ field: { lessEqual: 10 } } // <=
|
||||
{ field: { not: value } } // !=
|
||||
|
||||
// Logical
|
||||
{ anyOf: [{ a: 1 }, { b: 2 }] } // OR
|
||||
{ allOf: [{ a: 1 }, { b: 2 }] } // AND
|
||||
|
||||
// Existence
|
||||
{ field: { exists: true } } // Field exists
|
||||
{ field: { missing: true } } // Field doesn't exist
|
||||
|
||||
// String
|
||||
{ field: { startsWith: 'prefix' } } // Starts with
|
||||
{ field: { endsWith: 'suffix' } } // Ends with
|
||||
{ field: { matches: 'pattern' } } // Regex match
|
||||
|
||||
// Array
|
||||
{ array: { contains: 'item' } } // Array contains item
|
||||
{ array: { hasAll: ['a', 'b'] } } // Has all items
|
||||
{ array: { oneOf: ['a', 'b', 'c'] } } // Value in list
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Performance Guidelines
|
||||
|
||||
### 1. Use Indexes
|
||||
All metadata fields are automatically indexed. Use direct equality or range queries for best performance:
|
||||
|
||||
```typescript
|
||||
// ✅ Fast: Direct index lookup (O(log n))
|
||||
{ priority: 'high' }
|
||||
{ size: { greaterEqual: 1000 } }
|
||||
|
||||
// ⚠️ Slower: Must scan results
|
||||
{ path: { matches: /complex-regex/ } }
|
||||
```
|
||||
|
||||
### 2. Limit Results
|
||||
Always set reasonable limits:
|
||||
|
||||
```typescript
|
||||
async resolve(brain, vfs, value) {
|
||||
const results = await brain.find({
|
||||
where: { ... },
|
||||
limit: 1000 // Prevent unbounded queries
|
||||
})
|
||||
return this.extractIds(results)
|
||||
}
|
||||
```
|
||||
|
||||
### 3. Avoid Post-Filtering When Possible
|
||||
If you need post-filtering, consider flattening data:
|
||||
|
||||
```typescript
|
||||
// ❌ Slow: Fetch 5000, filter in memory
|
||||
const all = await brain.find({ where: { type: 'file' }, limit: 5000 })
|
||||
return all.filter(item => item.metadata.nested.value === target)
|
||||
|
||||
// ✅ Fast: Flatten during write, query directly
|
||||
// Store: metadata.nested_value = target
|
||||
const results = await brain.find({
|
||||
where: { nested_value: target },
|
||||
limit: 1000
|
||||
})
|
||||
```
|
||||
|
||||
### 4. Cache Expensive Operations
|
||||
Use the projection's resolve cache:
|
||||
|
||||
```typescript
|
||||
// Automatic caching in SemanticPathResolver
|
||||
// Results cached for 5 minutes by default
|
||||
// No manual caching needed!
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Testing Projections
|
||||
|
||||
### Unit Test Example
|
||||
|
||||
```typescript
|
||||
import { describe, it, expect, beforeAll } from 'vitest'
|
||||
import { Brainy } from '@soulcraft/brainy'
|
||||
import { PriorityProjection } from './PriorityProjection'
|
||||
|
||||
describe('PriorityProjection', () => {
|
||||
let brain: Brainy
|
||||
let vfs: any
|
||||
let projection: PriorityProjection
|
||||
|
||||
beforeAll(async () => {
|
||||
brain = new Brainy()
|
||||
await brain.init()
|
||||
vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
projection = new PriorityProjection()
|
||||
})
|
||||
|
||||
it('should resolve high priority files', async () => {
|
||||
// Create test files
|
||||
await vfs.writeFile('/test1.ts', 'code', {
|
||||
metadata: { priority: 'high' }
|
||||
})
|
||||
await vfs.writeFile('/test2.ts', 'code', {
|
||||
metadata: { priority: 'low' }
|
||||
})
|
||||
|
||||
// Resolve high priority
|
||||
const ids = await projection.resolve(brain, vfs, 'high')
|
||||
|
||||
expect(ids).toHaveLength(1)
|
||||
|
||||
const entity = await brain.get(ids[0])
|
||||
expect(entity.metadata.priority).toBe('high')
|
||||
})
|
||||
|
||||
it('should list all files with priority', async () => {
|
||||
const entities = await projection.list(brain, vfs, 100)
|
||||
|
||||
expect(entities.length).toBeGreaterThan(0)
|
||||
expect(entities.every(e => e.metadata.priority)).toBe(true)
|
||||
})
|
||||
})
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Best Practices
|
||||
|
||||
### 1. ✅ Name projections clearly
|
||||
```typescript
|
||||
// ✅ Good
|
||||
readonly name = 'priority' // /by-priority/high
|
||||
readonly name = 'language' // /by-language/typescript
|
||||
|
||||
// ❌ Bad
|
||||
readonly name = 'proj1' // /by-proj1/??? unclear
|
||||
```
|
||||
|
||||
### 2. ✅ Document expected metadata
|
||||
```typescript
|
||||
/**
|
||||
* Priority Projection
|
||||
*
|
||||
* Requires metadata fields:
|
||||
* - priority: string ('high' | 'medium' | 'low')
|
||||
*
|
||||
* Usage:
|
||||
* /by-priority/high
|
||||
*/
|
||||
export class PriorityProjection extends BaseProjectionStrategy {
|
||||
// ...
|
||||
}
|
||||
```
|
||||
|
||||
### 3. ✅ Handle missing data gracefully
|
||||
```typescript
|
||||
async resolve(brain, vfs, value) {
|
||||
const results = await brain.find({
|
||||
where: { priority: value },
|
||||
limit: 1000
|
||||
})
|
||||
|
||||
// Return empty array if no results, don't throw
|
||||
return this.extractIds(results) // [] if empty
|
||||
}
|
||||
```
|
||||
|
||||
### 4. ✅ Validate input
|
||||
```typescript
|
||||
async resolve(brain, vfs, priority: string) {
|
||||
// Validate priority value
|
||||
const valid = ['high', 'medium', 'low']
|
||||
if (!valid.includes(priority)) {
|
||||
return [] // Or throw error
|
||||
}
|
||||
|
||||
// Continue with query...
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Common Patterns
|
||||
|
||||
### Pattern 1: Enum-Based Projection
|
||||
For fixed sets of values (status, priority, type):
|
||||
|
||||
```typescript
|
||||
private readonly validValues = ['draft', 'review', 'approved']
|
||||
|
||||
async resolve(brain, vfs, status: string) {
|
||||
if (!this.validValues.includes(status)) return []
|
||||
// ... query
|
||||
}
|
||||
```
|
||||
|
||||
### Pattern 2: Range-Based Projection
|
||||
For numeric or time ranges:
|
||||
|
||||
```typescript
|
||||
private readonly ranges = {
|
||||
recent: Date.now() - 86400000, // Last 24h
|
||||
week: Date.now() - 7 * 86400000, // Last week
|
||||
month: Date.now() - 30 * 86400000 // Last month
|
||||
}
|
||||
|
||||
async resolve(brain, vfs, period: string) {
|
||||
const since = this.ranges[period]
|
||||
if (!since) return []
|
||||
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
modified: { greaterEqual: since }
|
||||
}
|
||||
})
|
||||
return this.extractIds(results)
|
||||
}
|
||||
```
|
||||
|
||||
### Pattern 3: Computed Projection
|
||||
Combine multiple criteria:
|
||||
|
||||
```typescript
|
||||
async resolve(brain, vfs, value: string) {
|
||||
// "stale" = not modified in 30 days AND no recent access
|
||||
if (value === 'stale') {
|
||||
const thirtyDaysAgo = Date.now() - 30 * 86400000
|
||||
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
allOf: [
|
||||
{ modified: { lessThan: thirtyDaysAgo } },
|
||||
{ accessed: { lessThan: thirtyDaysAgo } }
|
||||
]
|
||||
}
|
||||
})
|
||||
return this.extractIds(results)
|
||||
}
|
||||
|
||||
// Regular query for other values...
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Projection returns empty results
|
||||
1. Check metadata exists: `console.log(entity.metadata)`
|
||||
2. Verify query syntax: Use BFO operators, not MongoDB
|
||||
3. Check limits: Increase limit if needed
|
||||
|
||||
### Slow performance
|
||||
1. Check if field is indexed: All metadata fields are auto-indexed
|
||||
2. Avoid post-filtering: Flatten complex structures
|
||||
3. Use appropriate limits: Don't fetch more than needed
|
||||
|
||||
### Type errors
|
||||
1. Import correct types: `import { Brainy, VirtualFileSystem } from '@soulcraft/brainy'`
|
||||
2. Use `as VFSEntity` when mapping results
|
||||
3. Check BaseProjectionStrategy import
|
||||
|
||||
---
|
||||
|
||||
## See Also
|
||||
|
||||
- [Semantic VFS Guide](./SEMANTIC_VFS.md) - Using semantic paths
|
||||
- [Performance Tuning](./PERFORMANCE_TUNING.md) - Optimization guide
|
||||
- [VFS Core API](./VFS_CORE.md) - Base VFS operations
|
||||
|
|
@ -286,7 +286,7 @@ By using this quick start, you avoided these common mistakes:
|
|||
Your file explorer is now working! Here's what to explore next:
|
||||
|
||||
1. **[File Operations](./VFS_API_GUIDE.md#file-operations)** - Read, write, and manipulate files
|
||||
2. **[Semantic Features](./VFS_KNOWLEDGE_LAYER.md)** - Connect files to concepts and entities
|
||||
2. **[Semantic Features](./SEMANTIC_VFS.md)** - Multi-dimensional file access and neural extraction
|
||||
3. **[Performance Optimization](./building-file-explorers.md#performance)** - Handle large directories efficiently
|
||||
4. **[Advanced Search](./VFS_API_GUIDE.md#search-operations)** - Complex queries and filters
|
||||
|
||||
|
|
|
|||
|
|
@ -2,13 +2,14 @@
|
|||
|
||||
> Transform your filesystem into an intelligent knowledge graph where every file is a living entity with semantic understanding, relationships, and AI-powered organization.
|
||||
|
||||
## 🧠 Knowledge Layer Available!
|
||||
## 📚 Complete VFS Documentation
|
||||
|
||||
**For advanced features like semantic versioning, persistent entities, and universal concepts, see:**
|
||||
- **[Knowledge Layer Overview](../KNOWLEDGE_LAYER_OVERVIEW.md)** - Non-technical introduction
|
||||
- **[Knowledge Layer API](KNOWLEDGE_LAYER_API.md)** - Advanced features and capabilities
|
||||
- **[Real-World Examples](KNOWLEDGE_LAYER_EXAMPLES.md)** - Complete use cases for stories, APIs, research, and more
|
||||
- **[VFS API Guide](VFS_API_GUIDE.md)** - Complete filesystem API reference
|
||||
**Essential guides to get started:**
|
||||
- **[VFS Core](VFS_CORE.md)** - Complete filesystem architecture and API
|
||||
- **[Semantic VFS](SEMANTIC_VFS.md)** - Multi-dimensional file access (6 semantic dimensions)
|
||||
- **[Neural Extraction](NEURAL_EXTRACTION.md)** - AI-powered concept and entity extraction
|
||||
- **[Examples & Scenarios](VFS_EXAMPLES_SCENARIOS.md)** - Real-world use cases and code
|
||||
- **[VFS API Guide](VFS_API_GUIDE.md)** - Complete API reference
|
||||
|
||||
## What is Brainy VFS?
|
||||
|
||||
|
|
|
|||
486
docs/vfs/SEMANTIC_VFS.md
Normal file
486
docs/vfs/SEMANTIC_VFS.md
Normal file
|
|
@ -0,0 +1,486 @@
|
|||
# Semantic VFS - Revolutionary File System
|
||||
|
||||
## What is Semantic VFS?
|
||||
|
||||
Semantic VFS transforms traditional hierarchical file systems into **multi-dimensional knowledge graphs**. The same file can be accessed through multiple semantic dimensions simultaneously.
|
||||
|
||||
### Traditional vs Semantic
|
||||
|
||||
**Traditional File Systems:**
|
||||
```
|
||||
/src/auth/login.ts # One path, one location
|
||||
/src/users/profile.ts # Separate location
|
||||
```
|
||||
|
||||
**Semantic VFS:**
|
||||
```
|
||||
# Traditional path (still works!)
|
||||
/src/auth/login.ts
|
||||
|
||||
# By concept
|
||||
/by-concept/authentication/login.ts
|
||||
/by-concept/security/login.ts
|
||||
|
||||
# By author
|
||||
/by-author/alice/login.ts
|
||||
|
||||
# By time
|
||||
/as-of/2024-03-15/login.ts
|
||||
|
||||
# By relationship
|
||||
/related-to/src/users/profile.ts/depth-2
|
||||
```
|
||||
|
||||
**The same file, accessible 6+ different ways!** This is **polymorphic file access**.
|
||||
|
||||
---
|
||||
|
||||
## Why Semantic VFS?
|
||||
|
||||
### 1. **Natural Organization**
|
||||
Developers think in concepts, not directories:
|
||||
```typescript
|
||||
// Find all authentication-related files
|
||||
const authFiles = await vfs.readdir('/by-concept/authentication')
|
||||
|
||||
// Find all files Alice worked on
|
||||
const aliceFiles = await vfs.readdir('/by-author/alice')
|
||||
```
|
||||
|
||||
### 2. **Time Travel**
|
||||
See your codebase as it existed at any point:
|
||||
```typescript
|
||||
// Code from March 15th
|
||||
const snapshot = await vfs.readdir('/as-of/2024-03-15')
|
||||
|
||||
// Compare with today
|
||||
const current = await vfs.readdir('/src')
|
||||
```
|
||||
|
||||
### 3. **Knowledge Graph Navigation**
|
||||
Navigate by semantic relationships:
|
||||
```typescript
|
||||
// Files related to auth system (within 2 hops)
|
||||
const related = await vfs.readdir('/related-to/src/auth.ts/depth-2')
|
||||
|
||||
// Files similar to this implementation
|
||||
const similar = await vfs.readdir('/similar-to/src/auth.ts/threshold-0.8')
|
||||
```
|
||||
|
||||
### 4. **Tag-Based Organization**
|
||||
Organize by purpose, not location:
|
||||
```typescript
|
||||
// All security-critical files
|
||||
const security = await vfs.readdir('/by-tag/security')
|
||||
|
||||
// All experimental features
|
||||
const experiments = await vfs.readdir('/by-tag/experimental')
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Supported Semantic Dimensions
|
||||
|
||||
### 1. Traditional Path (Hierarchical)
|
||||
```typescript
|
||||
await vfs.readFile('/src/auth/login.ts')
|
||||
// Works exactly like a normal filesystem
|
||||
```
|
||||
|
||||
### 2. By Concept (Semantic)
|
||||
```typescript
|
||||
await vfs.readdir('/by-concept/authentication')
|
||||
// Returns all files about authentication
|
||||
|
||||
await vfs.readFile('/by-concept/authentication/login.ts')
|
||||
// Find specific file within concept
|
||||
```
|
||||
|
||||
**How it works:** Uses `brain.extractConcepts()` with NeuralEntityExtractor to extract concepts from file content using embeddings and the NounType taxonomy. Indexes concept names for O(log n) queries. See [Neural Extraction API](./NEURAL_EXTRACTION.md) for details.
|
||||
|
||||
### 3. By Author (Ownership)
|
||||
```typescript
|
||||
await vfs.readdir('/by-author/alice')
|
||||
// All files owned/modified by alice
|
||||
|
||||
await vfs.stat('/by-author/alice/config.ts')
|
||||
// Check specific file
|
||||
```
|
||||
|
||||
**How it works:** Tracks owner metadata on every file. Indexed by MetadataIndexManager.
|
||||
|
||||
### 4. By Time (Temporal)
|
||||
```typescript
|
||||
await vfs.readdir('/as-of/2024-03-15')
|
||||
// Files modified on March 15, 2024
|
||||
|
||||
await vfs.readFile('/as-of/2024-03-15/src/auth.ts')
|
||||
// Read auth.ts as it existed that day
|
||||
```
|
||||
|
||||
**How it works:** Tracks `modified` timestamp. Uses B-tree range queries (`greaterEqual`/`lessEqual`) for O(log n) performance.
|
||||
|
||||
### 5. By Relationship (Graph)
|
||||
```typescript
|
||||
await vfs.readdir('/related-to/src/auth.ts/depth-2')
|
||||
// Files within 2 relationship hops
|
||||
|
||||
await vfs.readdir('/related-to/src/auth.ts/depth-2/types-contains,references')
|
||||
// Only follow 'contains' and 'references' relationships
|
||||
```
|
||||
|
||||
**How it works:** Uses GraphAdjacencyIndex for O(1) graph traversal. Supports depth limits and relationship type filtering.
|
||||
|
||||
### 6. By Similarity (Vector)
|
||||
```typescript
|
||||
await vfs.readdir('/similar-to/src/auth.ts/threshold-0.8')
|
||||
// Files with 80%+ similarity to auth.ts
|
||||
|
||||
await vfs.similar('/src/auth.ts', { threshold: 0.9, limit: 10 })
|
||||
// Top 10 most similar files (90%+ match)
|
||||
```
|
||||
|
||||
**How it works:** Uses HNSW vector index for O(log n) nearest neighbor search. Based on content embeddings.
|
||||
|
||||
### 7. By Tag (Classification)
|
||||
```typescript
|
||||
await vfs.readdir('/by-tag/security')
|
||||
// All security-tagged files
|
||||
|
||||
await vfs.writeFile('/src/admin.ts', code, {
|
||||
metadata: { tags: ['security', 'admin'] }
|
||||
})
|
||||
// Tag files on write
|
||||
```
|
||||
|
||||
**How it works:** Stores tags in metadata. Indexed for fast queries.
|
||||
|
||||
---
|
||||
|
||||
## Performance Characteristics
|
||||
|
||||
### Scalability to Millions of Files
|
||||
|
||||
All semantic paths use **indexed data structures** for optimal performance:
|
||||
|
||||
| Dimension | Data Structure | Time Complexity | Million-Scale Ready |
|
||||
|-----------|---------------|-----------------|---------------------|
|
||||
| Traditional | PathCache + Graph | O(path depth) | ✅ Yes |
|
||||
| Concept | MetadataIndex (B-tree) | O(log n) | ✅ Yes* |
|
||||
| Author | MetadataIndex (B-tree) | O(log n) | ✅ Yes |
|
||||
| Time | MetadataIndex (B-tree) | O(log n) | ✅ Yes |
|
||||
| Relationship | GraphAdjacency | O(depth) | ✅ Yes |
|
||||
| Similarity | HNSW Index | O(log n) | ✅ Yes |
|
||||
| Tag | MetadataIndex (B-tree) | O(log n) | ✅ Yes* |
|
||||
|
||||
\* *Requires concept/tag flattening (automatic in future versions)*
|
||||
|
||||
### Cache Strategy
|
||||
|
||||
Multi-layer caching ensures hot paths are O(1):
|
||||
```
|
||||
Request → Hot Path Cache (O(1))
|
||||
→ Semantic Cache (5 min TTL)
|
||||
→ Index Lookup (O(log n))
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Usage Examples
|
||||
|
||||
### Example 1: Find All Files by Concept
|
||||
```typescript
|
||||
const brain = new Brainy()
|
||||
await brain.init()
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
|
||||
// Write files (concepts extracted automatically)
|
||||
await vfs.writeFile('/src/auth/login.ts', `
|
||||
export function authenticate(user, password) {
|
||||
// Authentication logic
|
||||
}
|
||||
`)
|
||||
|
||||
// Access by concept
|
||||
const authFiles = await vfs.readdir('/by-concept/authentication')
|
||||
console.log(authFiles)
|
||||
// ['login.ts', 'signup.ts', 'oauth.ts']
|
||||
```
|
||||
|
||||
### Example 2: Time Travel
|
||||
```typescript
|
||||
// See what changed today
|
||||
const today = new Date().toISOString().split('T')[0]
|
||||
const todaysFiles = await vfs.readdir(`/as-of/${today}`)
|
||||
|
||||
// Compare with yesterday
|
||||
const yesterday = new Date(Date.now() - 86400000).toISOString().split('T')[0]
|
||||
const yesterdaysFiles = await vfs.readdir(`/as-of/${yesterday}`)
|
||||
|
||||
const newFiles = todaysFiles.filter(f => !yesterdaysFiles.includes(f))
|
||||
console.log('New files today:', newFiles)
|
||||
```
|
||||
|
||||
### Example 3: Graph Navigation
|
||||
```typescript
|
||||
// Find all files related to auth
|
||||
const authId = await vfs.resolvePath('/src/auth.ts')
|
||||
const related = await vfs.readdir('/related-to/src/auth.ts/depth-2')
|
||||
|
||||
// Get relationship details
|
||||
for (const file of related) {
|
||||
const rels = await vfs.getRelationships(file.path)
|
||||
console.log(`${file.name}: ${rels.length} relationships`)
|
||||
}
|
||||
```
|
||||
|
||||
### Example 4: Semantic Search
|
||||
```typescript
|
||||
// Find similar implementations
|
||||
const similar = await vfs.similar('/src/auth.ts', {
|
||||
threshold: 0.8,
|
||||
limit: 10
|
||||
})
|
||||
|
||||
for (const result of similar) {
|
||||
console.log(`${result.entity.name}: ${result.similarity.toFixed(2)}`)
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## API Reference
|
||||
|
||||
### Reading Semantic Paths
|
||||
|
||||
All standard VFS methods work with semantic paths:
|
||||
|
||||
```typescript
|
||||
// Read directory
|
||||
await vfs.readdir('/by-concept/authentication')
|
||||
|
||||
// Read file
|
||||
await vfs.readFile('/by-concept/authentication/login.ts')
|
||||
|
||||
// Get stats
|
||||
await vfs.stat('/by-author/alice/config.ts')
|
||||
|
||||
// Check existence
|
||||
await vfs.exists('/as-of/2024-03-15/src/auth.ts')
|
||||
```
|
||||
|
||||
### Writing Files
|
||||
|
||||
Files are automatically indexed for semantic access:
|
||||
|
||||
```typescript
|
||||
await vfs.writeFile('/src/auth.ts', content, {
|
||||
metadata: {
|
||||
tags: ['security', 'authentication'],
|
||||
owner: 'alice'
|
||||
},
|
||||
extractConcepts: true, // default: true
|
||||
extractEntities: true, // default: true
|
||||
recordEvent: true // default: true
|
||||
})
|
||||
```
|
||||
|
||||
### Polymorphic Access
|
||||
|
||||
The same file is accessible through multiple paths:
|
||||
|
||||
```typescript
|
||||
// All these resolve to the SAME file entity:
|
||||
const id1 = await vfs.resolvePath('/src/auth/login.ts')
|
||||
const id2 = await vfs.resolvePath('/by-concept/authentication/login.ts')
|
||||
const id3 = await vfs.resolvePath('/by-author/alice/login.ts')
|
||||
|
||||
console.log(id1 === id2 && id2 === id3) // true
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Extending with Custom Projections
|
||||
|
||||
Create your own semantic dimensions:
|
||||
|
||||
```typescript
|
||||
import { BaseProjectionStrategy } from '@soulcraft/brainy/vfs/semantic'
|
||||
|
||||
class PriorityProjection extends BaseProjectionStrategy {
|
||||
readonly name = 'priority'
|
||||
|
||||
async resolve(brain, vfs, priority) {
|
||||
return await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
priority: priority // Custom metadata field
|
||||
},
|
||||
limit: 1000
|
||||
})
|
||||
.then(results => results.map(r => r.id))
|
||||
}
|
||||
|
||||
async list(brain, vfs, limit = 100) {
|
||||
const results = await brain.find({
|
||||
where: {
|
||||
vfsType: 'file',
|
||||
priority: { exists: true }
|
||||
},
|
||||
limit
|
||||
})
|
||||
return results.map(r => r.entity)
|
||||
}
|
||||
}
|
||||
|
||||
// Register custom projection
|
||||
const brain = new Brainy()
|
||||
await brain.init()
|
||||
const vfs = brain.vfs()
|
||||
|
||||
// Access via VFS internals (will be exposed in future API)
|
||||
vfs.projectionRegistry.register(new PriorityProjection())
|
||||
|
||||
// Now use it!
|
||||
const highPriority = await vfs.readdir('/by-priority/high')
|
||||
```
|
||||
|
||||
See [PROJECTION_STRATEGY_API.md](./PROJECTION_STRATEGY_API.md) for full guide.
|
||||
|
||||
---
|
||||
|
||||
## Architecture
|
||||
|
||||
### Triple Intelligence™ Foundation
|
||||
|
||||
Semantic VFS is built on Brainy's Triple Intelligence™:
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────┐
|
||||
│ Semantic VFS Layer │
|
||||
├─────────────────────────────────────────┤
|
||||
│ ProjectionRegistry + Strategies │
|
||||
├─────────────────────────────────────────┤
|
||||
│ SemanticPathResolver │
|
||||
├─────────────────────────────────────────┤
|
||||
│ │
|
||||
│ Triple Intelligence™ (Brainy) │
|
||||
│ ┌─────────┬─────────┬─────────────┐ │
|
||||
│ │ Vector │ Graph │ Metadata │ │
|
||||
│ │ HNSW │ Adj │ B-tree │ │
|
||||
│ │ O(log n)│ O(1) │ O(log n) │ │
|
||||
│ └─────────┴─────────┴─────────────┘ │
|
||||
└─────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
### Real Implementations, Zero Mocks
|
||||
|
||||
Every component uses **production Brainy APIs**:
|
||||
- `brain.find()` - Real metadata queries (brainy.ts:580)
|
||||
- `brain.similar()` - Real HNSW search (brainy.ts:680)
|
||||
- `brain.getRelations()` - Real graph traversal (brainy.ts:803)
|
||||
- `MetadataIndexManager` - Real B-tree indexes
|
||||
- `GraphAdjacencyIndex` - Real graph storage
|
||||
- `HNSW Index` - Real vector search
|
||||
|
||||
**No mocks. No stubs. No fake code.**
|
||||
|
||||
---
|
||||
|
||||
## Best Practices
|
||||
|
||||
### 1. Use Semantic Paths for Discovery
|
||||
```typescript
|
||||
// ❌ Don't hardcode paths
|
||||
const files = ['/src/auth.ts', '/src/login.ts', '/src/oauth.ts']
|
||||
|
||||
// ✅ Discover by concept
|
||||
const authFiles = await vfs.readdir('/by-concept/authentication')
|
||||
```
|
||||
|
||||
### 2. Tag Strategically
|
||||
```typescript
|
||||
// ✅ Good: Clear, actionable tags
|
||||
await vfs.writeFile(path, code, {
|
||||
metadata: { tags: ['security', 'requires-review', 'public-api'] }
|
||||
})
|
||||
|
||||
// ❌ Bad: Vague, redundant tags
|
||||
await vfs.writeFile(path, code, {
|
||||
metadata: { tags: ['code', 'file', 'important'] }
|
||||
})
|
||||
```
|
||||
|
||||
### 3. Optimize for Your Scale
|
||||
```typescript
|
||||
// For < 100K files: Post-filtering is fine
|
||||
// For > 100K files: Use flattened indexes
|
||||
|
||||
// Force index refresh after bulk operations
|
||||
await brain.storage.rebuildIndexes()
|
||||
```
|
||||
|
||||
### 4. Combine Dimensions
|
||||
```typescript
|
||||
// Find security files Alice worked on this week
|
||||
const aliceFiles = await vfs.readdir('/by-author/alice')
|
||||
const securityFiles = await vfs.readdir('/by-tag/security')
|
||||
const thisWeek = await vfs.readdir(`/as-of/${weekAgo}`)
|
||||
|
||||
const intersection = aliceFiles
|
||||
.filter(f => securityFiles.includes(f))
|
||||
.filter(f => thisWeek.includes(f))
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Concepts Not Being Extracted
|
||||
```typescript
|
||||
// Check if concepts are enabled (default: true)
|
||||
await vfs.writeFile(path, code, { extractConcepts: true })
|
||||
|
||||
// Verify concept extraction works
|
||||
const entity = await vfs.getEntity(path)
|
||||
console.log(entity.metadata.concepts)
|
||||
```
|
||||
|
||||
### Slow Queries on Large Datasets
|
||||
```typescript
|
||||
// Check if indexes are built
|
||||
const stats = await brain.storage.getIndexStats()
|
||||
console.log(stats)
|
||||
|
||||
// Rebuild if needed
|
||||
await brain.storage.rebuildIndexes()
|
||||
```
|
||||
|
||||
### Semantic Path Returns Empty
|
||||
```typescript
|
||||
// Check if metadata exists
|
||||
const files = await vfs.readdir('/src')
|
||||
for (const file of files) {
|
||||
const entity = await vfs.getEntity(file.path)
|
||||
console.log(entity.metadata)
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## What's Next?
|
||||
|
||||
- **Natural Language Paths**: `/find "authentication logic"`
|
||||
- **Intent-Based Access**: `/to-review`, `/to-deploy`
|
||||
- **Temporal Queries**: `/changed-since/2024-03-01`
|
||||
- **Custom Dimensions**: Plugin system for domain-specific projections
|
||||
|
||||
---
|
||||
|
||||
## See Also
|
||||
|
||||
- [Projection Strategy API](./PROJECTION_STRATEGY_API.md) - Create custom projections
|
||||
- [Performance Tuning](./PERFORMANCE_TUNING.md) - Million-scale optimization
|
||||
- [VFS Core API](./VFS_CORE.md) - Base VFS operations
|
||||
- [Triple Intelligence™](./TRIPLE_INTELLIGENCE.md) - Underlying architecture
|
||||
|
|
@ -794,8 +794,10 @@ console.log('VFS Stats:', stats)
|
|||
|
||||
---
|
||||
|
||||
The Virtual Filesystem API provides a powerful, intelligent alternative to traditional filesystems. With semantic search, rich metadata, and graph relationships, your files become living entities in a connected knowledge system.
|
||||
The Virtual Filesystem API provides a powerful, intelligent alternative to traditional filesystems. With semantic search, rich metadata, graph relationships, and AI-powered concept extraction, your files become living entities in a connected knowledge system.
|
||||
|
||||
For advanced features like event recording, semantic versioning, and persistent entities, see the [Knowledge Layer API Documentation](./KNOWLEDGE_LAYER_API.md).
|
||||
For semantic file access and neural extraction features, see:
|
||||
- [Semantic VFS Guide](./SEMANTIC_VFS.md) - Multi-dimensional file access
|
||||
- [Neural Extraction API](./NEURAL_EXTRACTION.md) - AI-powered concept and entity extraction
|
||||
|
||||
Ready to make your filesystem intelligent? 🚀
|
||||
|
|
@ -275,19 +275,9 @@ await vfs.importDirectory('/local/project', { targetPath: '/vfs/project' })
|
|||
|
||||
### GitBridge Integration
|
||||
|
||||
GitBridge provides Git import/export capabilities. It can be used in two ways:
|
||||
GitBridge provides Git import/export capabilities:
|
||||
|
||||
#### Option 1: Via Knowledge Layer (Recommended)
|
||||
```javascript
|
||||
// Enable Knowledge Layer to get Git methods
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// Now Git methods are available on VFS
|
||||
await vfs.exportToGit('/project', '/local/git/repo')
|
||||
await vfs.importFromGit('/local/git/repo', '/project')
|
||||
```
|
||||
|
||||
#### Option 2: Direct GitBridge Usage
|
||||
#### GitBridge Usage
|
||||
```javascript
|
||||
// Import and instantiate GitBridge
|
||||
import { GitBridge } from '@soulcraft/brainy'
|
||||
|
|
@ -327,9 +317,9 @@ await gitBridge.importFromGit('/local/git/repo', '/project', {
|
|||
- Compression ratio tracked in metadata
|
||||
|
||||
### Background Processing
|
||||
- Non-blocking Knowledge Layer processing
|
||||
- Asynchronous embedding generation
|
||||
- Deferred relationship indexing
|
||||
- Non-blocking metadata extraction
|
||||
|
||||
## Error Handling
|
||||
|
||||
|
|
@ -373,45 +363,32 @@ VFS scales to millions of files:
|
|||
|
||||
## Method Availability
|
||||
|
||||
### Core VFS Methods (Always Available)
|
||||
|
||||
These methods are available immediately after VFS initialization:
|
||||
All VFS methods are available immediately after initialization:
|
||||
|
||||
```javascript
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
|
||||
// ✅ All these work without Knowledge Layer:
|
||||
await vfs.writeFile() // File operations
|
||||
await vfs.readFile()
|
||||
await vfs.mkdir() // Directory operations
|
||||
await vfs.readdir()
|
||||
await vfs.stat() // Metadata
|
||||
await vfs.search() // Semantic search
|
||||
await vfs.addRelationship() // Relationships
|
||||
await vfs.addTodo() // Todo management
|
||||
await vfs.exportToJSON() // Export
|
||||
await vfs.bulkWrite() // Bulk operations
|
||||
```
|
||||
// Core file operations
|
||||
await vfs.writeFile() // Write files
|
||||
await vfs.readFile() // Read files
|
||||
await vfs.mkdir() // Create directories
|
||||
await vfs.readdir() // List directory contents
|
||||
await vfs.stat() // Get file metadata
|
||||
|
||||
### Knowledge Layer Methods (Require Enablement)
|
||||
// Semantic features
|
||||
await vfs.search() // Semantic search
|
||||
await vfs.findSimilar() // Find similar files
|
||||
await vfs.addRelationship()// Add relationships
|
||||
|
||||
These methods are only available after enabling the Knowledge Layer:
|
||||
// Todo management
|
||||
await vfs.addTodo() // Add todos
|
||||
await vfs.getTodos() // Get todos
|
||||
await vfs.setMetadata() // Set metadata
|
||||
|
||||
```javascript
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// 🔮 Now these methods are available:
|
||||
await vfs.createEntity() // Entity management
|
||||
await vfs.linkEntities()
|
||||
await vfs.createConcept() // Concept system
|
||||
await vfs.findByConcept()
|
||||
await vfs.getVersions() // Versioning
|
||||
await vfs.getHistory() // History tracking
|
||||
await vfs.exportToGit() // Git integration (wrapper)
|
||||
await vfs.importFromGit()
|
||||
await vfs.exportToMarkdown()// Export formats
|
||||
await vfs.getTimeline() // Timeline analysis
|
||||
// Export
|
||||
await vfs.exportToJSON() // Export to JSON
|
||||
await vfs.bulkWrite() // Bulk operations
|
||||
```
|
||||
|
||||
## Complete Example
|
||||
|
|
|
|||
|
|
@ -1,8 +1,10 @@
|
|||
# VFS Examples and Scenarios
|
||||
|
||||
> **⚠️ DOCUMENTATION IN PROGRESS**: This document is being updated to reflect recent VFS architecture changes. Many examples below reference deprecated Knowledge Layer methods. Updated examples coming soon. For current VFS capabilities, see [VFS_CORE.md](./VFS_CORE.md) and [SEMANTIC_VFS.md](./SEMANTIC_VFS.md).
|
||||
|
||||
## Real-World Scenarios
|
||||
|
||||
This document demonstrates how VFS with Knowledge Layer enables powerful real-world applications.
|
||||
This document demonstrates how VFS enables powerful real-world applications with semantic search, relationships, and AI-powered concept extraction.
|
||||
|
||||
### Legend
|
||||
- ✅ **Real VFS methods** - Fully implemented and working
|
||||
|
|
@ -24,7 +26,6 @@ async function novelWritingProject() {
|
|||
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// Create project structure ✅
|
||||
await vfs.mkdir('/novel')
|
||||
|
|
@ -32,22 +33,26 @@ async function novelWritingProject() {
|
|||
await vfs.mkdir('/novel/characters')
|
||||
await vfs.mkdir('/novel/worldbuilding')
|
||||
|
||||
// Define main characters as persistent entities ✅
|
||||
const protagonist = await vfs.createEntity({
|
||||
name: 'Elena Blackwood',
|
||||
type: 'character',
|
||||
description: 'A skilled detective with a mysterious past',
|
||||
attributes: {
|
||||
age: 32,
|
||||
occupation: 'Private Investigator',
|
||||
skills: ['deduction', 'combat', 'languages'],
|
||||
personality: ['determined', 'secretive', 'compassionate']
|
||||
// Define main characters as files with rich metadata ✅
|
||||
await vfs.writeFile('/novel/characters/elena-blackwood.md', `
|
||||
# Elena Blackwood
|
||||
|
||||
A skilled detective with a mysterious past.
|
||||
|
||||
## Character Profile
|
||||
- Age: 32
|
||||
- Occupation: Private Investigator
|
||||
- Skills: Deduction, combat, languages
|
||||
- Personality: Determined, secretive, compassionate
|
||||
`, {
|
||||
metadata: {
|
||||
characterType: 'protagonist',
|
||||
tags: ['detective', 'mysterious', 'protagonist']
|
||||
}
|
||||
})
|
||||
|
||||
const antagonist = await vfs.createEntity({
|
||||
name: 'Marcus Void',
|
||||
type: 'character',
|
||||
await vfs.writeFile('/novel/characters/marcus-void.md', `
|
||||
# Marcus Void
|
||||
description: 'A wealthy industrialist with dark secrets',
|
||||
attributes: {
|
||||
age: 45,
|
||||
|
|
@ -147,7 +152,6 @@ async function gameDevProject() {
|
|||
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// Game project structure
|
||||
await vfs.mkdir('/game')
|
||||
|
|
@ -293,9 +297,8 @@ async function softwareProject() {
|
|||
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// Import existing git repository ✅ (Knowledge Layer provides wrapper)
|
||||
// Import existing git repository ✅
|
||||
await vfs.importFromGit('/local/repos/webapp', '/project')
|
||||
|
||||
// Define architectural concepts
|
||||
|
|
@ -460,7 +463,6 @@ async function unifiedKnowledgeBase() {
|
|||
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// Create separate project spaces
|
||||
await vfs.mkdir('/novel')
|
||||
|
|
|
|||
|
|
@ -1,460 +0,0 @@
|
|||
# VFS + Knowledge Layer Integration
|
||||
|
||||
## Overview
|
||||
|
||||
The Knowledge Layer is an optional augmentation that transforms VFS from a filesystem into an intelligent knowledge management system. When enabled, it adds event recording, semantic versioning, persistent entities, universal concepts, and Git integration.
|
||||
|
||||
## Enabling Knowledge Layer
|
||||
|
||||
```javascript
|
||||
const brain = new Brainy({
|
||||
storage: { type: 'memory' },
|
||||
silent: true
|
||||
})
|
||||
await brain.init()
|
||||
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
|
||||
// Enable Knowledge Layer augmentation
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// Now VFS has additional intelligent features
|
||||
```
|
||||
|
||||
## Architecture
|
||||
|
||||
The Knowledge Layer consists of five integrated systems:
|
||||
|
||||
### 1. EventRecorder
|
||||
Tracks all filesystem operations as searchable events with embeddings.
|
||||
|
||||
### 2. SemanticVersioning
|
||||
Creates versions based on semantic meaning changes, not just byte differences.
|
||||
|
||||
### 3. PersistentEntitySystem
|
||||
Tracks evolving entities (characters, concepts, systems) across files.
|
||||
|
||||
### 4. ConceptSystem
|
||||
Manages universal concepts that span multiple files and projects.
|
||||
|
||||
### 5. GitBridge
|
||||
Enables import/export between VFS and Git repositories.
|
||||
|
||||
## Event Recording
|
||||
|
||||
Every filesystem operation is recorded as an event:
|
||||
|
||||
```javascript
|
||||
// All operations are automatically recorded
|
||||
await vfs.writeFile('/doc.txt', 'Initial content')
|
||||
await vfs.appendFile('/doc.txt', '\nMore content')
|
||||
await vfs.rename('/doc.txt', '/document.txt')
|
||||
|
||||
// Query events
|
||||
const history = await vfs.getHistory('/document.txt')
|
||||
for (const event of history) {
|
||||
console.log(event.type, event.timestamp, event.user)
|
||||
// 'create' 2025-01-20T10:00:00Z 'alice'
|
||||
// 'write' 2025-01-20T10:01:00Z 'alice'
|
||||
// 'rename' 2025-01-20T10:02:00Z 'alice'
|
||||
}
|
||||
|
||||
// Get timeline of events
|
||||
const events = await vfs.getTimeline({ from: '2025-01-01' })
|
||||
```
|
||||
|
||||
### Event Types
|
||||
- `create` - File/directory created
|
||||
- `write` - Content written
|
||||
- `append` - Content appended
|
||||
- `delete` - File/directory deleted
|
||||
- `rename` - Path changed
|
||||
- `move` - File relocated
|
||||
- `metadata` - Metadata updated
|
||||
- `relationship` - Relationship added/removed
|
||||
|
||||
### Event Schema
|
||||
```javascript
|
||||
{
|
||||
id: 'uuid',
|
||||
type: 'write',
|
||||
path: '/document.txt',
|
||||
oldPath: null, // For renames/moves
|
||||
timestamp: Date.now(),
|
||||
user: 'current-user',
|
||||
size: 1024, // Bytes affected
|
||||
contentHash: 'sha256...', // Content fingerprint
|
||||
vector: [0.1, 0.2, ...], // Semantic embedding
|
||||
metadata: {
|
||||
mimeType: 'text/plain',
|
||||
encoding: 'utf8'
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Semantic Versioning
|
||||
|
||||
Versions are created when content *meaning* changes significantly:
|
||||
|
||||
```javascript
|
||||
// Initial version
|
||||
await vfs.writeFile('/story.txt', 'Once upon a time...')
|
||||
|
||||
// Minor change - no new version (typo fix)
|
||||
await vfs.writeFile('/story.txt', 'Once upon a time...')
|
||||
|
||||
// Major change - creates new version (plot development)
|
||||
await vfs.writeFile('/story.txt', 'Once upon a time, the kingdom fell...')
|
||||
|
||||
// Get versions
|
||||
const versions = await vfs.getVersions('/story.txt')
|
||||
for (const version of versions) {
|
||||
console.log(version.id, version.timestamp, version.semanticHash)
|
||||
// Compare semantic similarity between versions
|
||||
console.log(version.similarity) // 0.45 (significantly different)
|
||||
}
|
||||
|
||||
// Restore version
|
||||
await vfs.restoreVersion('/story.txt', versions[0].id)
|
||||
|
||||
// Compare versions by restoring
|
||||
const v1Content = await vfs.getVersion('/story.txt', v1.id)
|
||||
const v2Content = await vfs.getVersion('/story.txt', v2.id)
|
||||
// Compare the content as needed
|
||||
```
|
||||
|
||||
### Version Triggers
|
||||
- Semantic similarity < 0.7 threshold
|
||||
- New concepts introduced
|
||||
- Major structural changes
|
||||
- Explicit version creation
|
||||
|
||||
## Persistent Entities
|
||||
|
||||
Track characters, systems, and entities across files:
|
||||
|
||||
```javascript
|
||||
// Create persistent entity
|
||||
const character = await vfs.createEntity({
|
||||
name: 'Alice',
|
||||
type: 'character',
|
||||
description: 'Main protagonist, a curious explorer',
|
||||
attributes: {
|
||||
age: 25,
|
||||
occupation: 'Archaeologist',
|
||||
traits: ['brave', 'intelligent', 'curious']
|
||||
}
|
||||
})
|
||||
|
||||
// Entity appears across multiple files
|
||||
await vfs.writeFile('/chapter1.txt', 'Alice entered the ancient tomb...')
|
||||
await vfs.writeFile('/chapter2.txt', 'Alice decoded the hieroglyphs...')
|
||||
|
||||
// Track entity across files
|
||||
const occurrences = await vfs.findEntityOccurrences('Alice')
|
||||
// Returns all files mentioning Alice with context
|
||||
|
||||
// Update entity globally
|
||||
await vfs.updateEntity(character.id, {
|
||||
attributes: {
|
||||
age: 26, // Birthday happened in the story
|
||||
newTrait: 'experienced'
|
||||
}
|
||||
})
|
||||
|
||||
// Entity types
|
||||
const entities = await vfs.listEntities({ type: 'character' })
|
||||
// Supports: character, location, object, system, concept, etc.
|
||||
```
|
||||
|
||||
### Entity Relationships
|
||||
```javascript
|
||||
// Link entities
|
||||
await vfs.linkEntities('Alice', 'Ancient Tomb', 'explores')
|
||||
await vfs.linkEntities('Alice', 'Bob', 'mentored_by')
|
||||
|
||||
// Query entity graph
|
||||
const graph = await vfs.getEntityGraph('Alice', { depth: 2 })
|
||||
// Returns connected entities and their relationships
|
||||
```
|
||||
|
||||
## Concept System
|
||||
|
||||
Universal concepts that transcend individual files:
|
||||
|
||||
```javascript
|
||||
// Create concept
|
||||
const authConcept = await vfs.createConcept({
|
||||
name: 'Authentication',
|
||||
type: 'technical',
|
||||
domain: 'security',
|
||||
description: 'User identity verification system',
|
||||
keywords: ['login', 'password', 'token', 'session'],
|
||||
relatedConcepts: ['Authorization', 'Security']
|
||||
})
|
||||
|
||||
// Concepts are automatically detected in files
|
||||
await vfs.writeFile('/auth.js', 'function authenticate(user, password) {...}')
|
||||
await vfs.writeFile('/login.tsx', 'const LoginForm = () => {...}')
|
||||
|
||||
// Find files by concept
|
||||
const authFiles = await vfs.findByConcept('Authentication')
|
||||
// Returns all files related to authentication concept
|
||||
|
||||
// Find files by concept
|
||||
const authFiles = await vfs.findByConcept('Authentication')
|
||||
// Returns all files related to the authentication concept
|
||||
```
|
||||
|
||||
### Working with Concepts
|
||||
```javascript
|
||||
// Concepts can reference each other through their descriptions
|
||||
// and keywords, creating an implicit network of related ideas.
|
||||
// The findByConcept method searches across these relationships.
|
||||
```
|
||||
|
||||
## GitBridge Integration
|
||||
|
||||
Seamlessly work with Git repositories:
|
||||
|
||||
```javascript
|
||||
// Import from Git repo
|
||||
await vfs.importFromGit('/local/git/repo', '/vfs/project')
|
||||
|
||||
// Imports:
|
||||
// - All files and directories
|
||||
// - Git history as VFS events
|
||||
// - Commit messages as event metadata
|
||||
// - Branch structure as relationships
|
||||
|
||||
// Export to Git format
|
||||
await vfs.exportToGit('/vfs/project', '/local/git/repo')
|
||||
|
||||
// Exports:
|
||||
// - Files to working directory
|
||||
// - VFS events as git commits
|
||||
// - Relationships as .brainy/relationships.json
|
||||
// - Entities as .brainy/entities.json
|
||||
// - Concepts as .brainy/concepts.json
|
||||
|
||||
// Export/import operations are available
|
||||
// For remote sync, use git commands after export:
|
||||
// await vfs.exportToGit('/vfs/project', '/local/repo')
|
||||
// Then use git push/pull as normal
|
||||
```
|
||||
|
||||
### Git Integration
|
||||
```javascript
|
||||
// Import from Git preserves history as events
|
||||
// Export to Git creates .brainy/ metadata directory
|
||||
// Use standard git commands for remote operations
|
||||
```
|
||||
|
||||
## Knowledge Queries
|
||||
|
||||
Powerful queries across all Knowledge Layer data:
|
||||
|
||||
```javascript
|
||||
// Timeline query
|
||||
const timeline = await vfs.getTimeline({
|
||||
from: '2025-01-01',
|
||||
to: '2025-01-31',
|
||||
types: ['write', 'create']
|
||||
})
|
||||
|
||||
// Timeline queries
|
||||
const timeline = await vfs.getTimeline({
|
||||
from: '2025-01-01',
|
||||
to: '2025-01-31',
|
||||
types: ['write', 'create']
|
||||
})
|
||||
|
||||
// Project statistics
|
||||
const stats = await vfs.getProjectStats('/project')
|
||||
console.log('Total files:', stats.fileCount)
|
||||
console.log('Total size:', stats.totalSize)
|
||||
console.log('Todo count:', stats.todoCount)
|
||||
|
||||
// Search with Triple Intelligence
|
||||
const results = await vfs.search('authentication', {
|
||||
path: '/src',
|
||||
type: 'file',
|
||||
limit: 20
|
||||
})
|
||||
```
|
||||
|
||||
## Background Processing
|
||||
|
||||
Knowledge Layer operations run in the background:
|
||||
|
||||
```javascript
|
||||
// Operations are non-blocking
|
||||
await vfs.writeFile('/large-doc.txt', hugeContent)
|
||||
// Returns immediately
|
||||
|
||||
// Knowledge processing happens asynchronously:
|
||||
// 1. Event recording (immediate)
|
||||
// 2. Embedding generation (100ms)
|
||||
// 3. Version checking (200ms)
|
||||
// 4. Entity extraction (500ms)
|
||||
// 5. Concept detection (1s)
|
||||
|
||||
// Background processing happens automatically
|
||||
// Events are recorded immediately
|
||||
// Embeddings and versions are processed asynchronously
|
||||
```
|
||||
|
||||
## Search and Analysis
|
||||
|
||||
The Knowledge Layer provides powerful search and analysis capabilities:
|
||||
|
||||
```javascript
|
||||
// Find files by concept
|
||||
const authFiles = await vfs.findByConcept('Authentication')
|
||||
// Returns all files related to the authentication concept
|
||||
|
||||
// Get timeline of changes
|
||||
const timeline = await vfs.getTimeline({
|
||||
from: '2025-01-01',
|
||||
to: '2025-01-31',
|
||||
types: ['write', 'create']
|
||||
})
|
||||
// Returns chronological list of events
|
||||
|
||||
// Get project statistics
|
||||
const stats = await vfs.getProjectStats('/project')
|
||||
console.log(stats.fileCount) // Number of files
|
||||
console.log(stats.totalSize) // Total size in bytes
|
||||
console.log(stats.todoCount) // Number of todos
|
||||
console.log(stats.largestFile) // Largest file info
|
||||
|
||||
// Export directory to markdown
|
||||
const markdown = await vfs.exportToMarkdown('/docs')
|
||||
// Returns formatted markdown of entire directory structure
|
||||
```
|
||||
|
||||
## Collaboration Features
|
||||
|
||||
Knowledge Layer enables multi-user collaboration:
|
||||
|
||||
```javascript
|
||||
// Track user actions
|
||||
vfs.setUser('alice')
|
||||
await vfs.writeFile('/shared.txt', 'Alice\'s content')
|
||||
|
||||
vfs.setUser('bob')
|
||||
await vfs.appendFile('/shared.txt', 'Bob\'s addition')
|
||||
|
||||
// Get collaboration history
|
||||
const collabHistory = await vfs.getCollaborationHistory('/shared.txt')
|
||||
// Returns who edited the file and when:
|
||||
// [
|
||||
// { user: 'alice', timestamp: Date, action: 'write', size: 15 },
|
||||
// { user: 'bob', timestamp: Date, action: 'append', size: 14 }
|
||||
// ]
|
||||
|
||||
// Get all todos across project
|
||||
const allTodos = await vfs.getAllTodos('/project')
|
||||
// Returns todos from all files recursively
|
||||
```
|
||||
|
||||
## Performance Impact
|
||||
|
||||
Knowledge Layer overhead:
|
||||
- **Write operations**: +50-200ms for event recording
|
||||
- **Read operations**: No impact (cached)
|
||||
- **Search operations**: 10x faster (pre-computed embeddings)
|
||||
- **Storage**: ~20% additional for events and embeddings
|
||||
- **Memory**: +100MB for caches and indexes
|
||||
|
||||
## Configuration
|
||||
|
||||
Fine-tune Knowledge Layer behavior:
|
||||
|
||||
```javascript
|
||||
await vfs.enableKnowledgeLayer({
|
||||
eventRecording: true, // Track all operations
|
||||
semanticVersioning: true, // Smart versioning
|
||||
versionThreshold: 0.7, // Similarity threshold
|
||||
persistentEntities: true, // Track entities
|
||||
entityTypes: ['character', 'location', 'system'],
|
||||
concepts: true, // Universal concepts
|
||||
conceptDomains: ['technical', 'narrative', 'business'],
|
||||
gitBridge: true, // Git integration
|
||||
backgroundProcessing: true, // Non-blocking
|
||||
processingDelay: 100, // Ms before processing
|
||||
cacheSizes: {
|
||||
events: 10000,
|
||||
versions: 1000,
|
||||
entities: 5000,
|
||||
concepts: 2000
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
## Complete Example
|
||||
|
||||
```javascript
|
||||
import { Brainy } from '@soulcraft/brainy'
|
||||
|
||||
async function knowledgeExample() {
|
||||
// Initialize with Knowledge Layer
|
||||
const brain = new Brainy({
|
||||
storage: { type: 'memory' }
|
||||
})
|
||||
await brain.init()
|
||||
|
||||
const vfs = brain.vfs()
|
||||
await vfs.init()
|
||||
await vfs.enableKnowledgeLayer()
|
||||
|
||||
// Create a story with tracked entities
|
||||
const alice = await vfs.createEntity({
|
||||
name: 'Alice',
|
||||
type: 'character',
|
||||
description: 'Protagonist'
|
||||
})
|
||||
|
||||
await vfs.writeFile('/chapter1.md', `
|
||||
# Chapter 1
|
||||
Alice discovered the ancient artifact...
|
||||
`)
|
||||
|
||||
// File automatically:
|
||||
// - Records write event
|
||||
// - Generates embedding
|
||||
// - Links to Alice entity
|
||||
// - Detects "ancient artifact" concept
|
||||
|
||||
// Create technical documentation
|
||||
await vfs.createConcept({
|
||||
name: 'API Design',
|
||||
type: 'technical',
|
||||
domain: 'software'
|
||||
})
|
||||
|
||||
await vfs.writeFile('/api-guide.md', `
|
||||
# API Design Guide
|
||||
RESTful principles...
|
||||
`)
|
||||
|
||||
// Check Knowledge Layer insights
|
||||
const insights = await vfs.getInsights('/')
|
||||
console.log('Entities:', insights.entities)
|
||||
console.log('Concepts:', insights.concepts)
|
||||
console.log('Relationships:', insights.relationships)
|
||||
|
||||
// Query across knowledge
|
||||
const results = await vfs.knowledgeSearch({
|
||||
query: 'Alice artifact',
|
||||
includeEvents: true,
|
||||
includeEntities: true
|
||||
})
|
||||
|
||||
await vfs.close()
|
||||
await brain.close()
|
||||
}
|
||||
```
|
||||
|
||||
The Knowledge Layer transforms VFS from a filesystem into an intelligent knowledge management system that understands content, tracks evolution, and enables semantic collaboration.
|
||||
Loading…
Add table
Add a link
Reference in a new issue