brainy/docs/api/README.md
David Snelling cca1cd8ce2 feat: add structured content extraction and batch embedding optimization to highlight()
Fix highlight() hanging on structured text input by addressing 3 root causes:

1. embedBatch() now uses native WASM batch API (single forward pass instead
   of N individual embed() calls via Promise.all)

2. highlight() auto-detects content type (plain text, rich-text JSON, HTML,
   Markdown) and extracts meaningful text segments. Supports TipTap, Slate.js,
   Lexical, Draft.js, and Quill Delta formats. New contentType hint and
   contentExtractor callback for custom parsers.

3. Semantic matching phase has 10s timeout - falls back to text-only matches
   instead of hanging indefinitely.

Also fixes extractTextContent() array check: uses type-based detection
(typeof data[0] === 'number') instead of length-based (data.length > 10)
so arrays of objects are properly indexed for text search.

New types: ContentType, ContentCategory, ExtractedSegment
New fields: HighlightParams.contentType, HighlightParams.contentExtractor,
            Highlight.contentCategory
2026-01-27 10:27:22 -08:00

2179 lines
54 KiB
Markdown

# 🧠 Brainy v7.1.0 API Reference
> **Complete API documentation for Brainy v7.1.0**
> Zero Configuration • Triple Intelligence • Git-Style Branching • Entity Versioning • Candle WASM Embeddings
**Updated:** 2026-01-06 for v7.1.0
**All APIs verified against actual code**
---
## Quick Start
```typescript
import { Brainy, NounType, VerbType } from '@soulcraft/brainy'
const brain = new Brainy() // Zero config!
await brain.init() // VFS auto-initialized in v5.1.0!
// Add data (text auto-embeds!)
const id = await brain.add({
data: 'The future of AI is here',
type: NounType.Concept,
metadata: { category: 'technology' }
})
// Search with Triple Intelligence
const results = await brain.find({
query: 'artificial intelligence',
where: { year: { greaterThan: 2020 } },
connected: { from: id, depth: 2 }
})
// Fork for safe experimentation (v5.0.0+)
const experiment = await brain.fork('test-feature')
await experiment.add({ data: 'test', type: NounType.Document })
await experiment.commit({ message: 'Add test data' })
// Entity versioning (v5.3.0+)
await brain.versions.save(id, { tag: 'v1.0', description: 'Initial version' })
await brain.update(id, { category: 'AI' })
await brain.versions.save(id, { tag: 'v2.0' })
```
---
## Core Concepts
### 🧬 Entities (Nouns)
Semantic vectors with metadata and relationships - the fundamental data unit in Brainy.
### 🔗 Relationships (Verbs)
Typed connections between entities - building knowledge graphs.
### 🧠 Triple Intelligence
Vector search + Graph traversal + Metadata filtering in one unified query.
### 🌳 Git-Style Branching (v5.0.0+)
Fork, experiment, and commit - Snowflake-style copy-on-write isolation.
### 📜 Entity Versioning (v5.3.0+)
Time-travel and history tracking for individual entities - Git-like version control with content-addressable storage.
---
## Table of Contents
- [Core CRUD Operations](#core-crud-operations)
- [Search & Query](#search--query)
- [Relationships](#relationships)
- [Batch Operations](#batch-operations)
- [Branch Management (v5.0+)](#branch-management-v50)
- [Entity Versioning (v5.3.0+)](#entity-versioning-v530)
- [Virtual Filesystem (VFS)](#virtual-filesystem-vfs)
- [Neural API](#neural-api)
- [Import & Export](#import--export)
- [Configuration](#configuration)
- [Storage Adapters](#storage-adapters)
- [Utility Methods](#utility-methods)
- [Embedding & Analysis APIs (v7.1.0)](#embedding--analysis-apis-v710)
- [Type System Reference](#type-system-reference)
---
## Core CRUD Operations
### `add(params)` → `Promise<string>`
Add a single entity to the database.
```typescript
const id = await brain.add({
data: 'JavaScript is a programming language', // Text or pre-computed vector
type: NounType.Concept, // Required: Entity type
metadata: { // Optional metadata
category: 'programming',
year: 1995
}
})
```
**Parameters:**
- `data`: `string | number[]` - Text (auto-embeds) or vector
- `type`: `NounType` - Entity type (required)
- `metadata?`: `object` - Additional metadata
**Returns:** `Promise<string>` - Entity ID
---
### `get(id)` → `Promise<Entity | null>`
Retrieve a single entity by ID.
```typescript
const entity = await brain.get(id)
console.log(entity?.data) // Original data
console.log(entity?.metadata) // Metadata
console.log(entity?.vector) // Embedding vector
```
**Parameters:**
- `id`: `string` - Entity ID
**Returns:** `Promise<Entity | null>` - Entity or null if not found
---
### `update(params)` → `Promise<void>`
Update an existing entity.
```typescript
await brain.update({
id: entityId,
data: 'Updated content', // Optional: new data
metadata: { updated: true } // Optional: new metadata (merges)
})
```
**Parameters:**
- `id`: `string` - Entity ID
- `data?`: `string | number[]` - New data/vector
- `metadata?`: `object` - Metadata to merge
**Returns:** `Promise<void>`
---
### `delete(id)` → `Promise<void>`
Delete a single entity.
```typescript
await brain.delete(id)
```
**Parameters:**
- `id`: `string` - Entity ID
**Returns:** `Promise<void>`
---
## Search & Query
### `find(query)` → `Promise<Result[]>`
**Triple Intelligence** - Vector + Graph + Metadata in ONE query.
```typescript
// Simple text search
const results = await brain.find('machine learning')
// Advanced Triple Intelligence query
const results = await brain.find({
query: 'artificial intelligence', // Vector similarity
where: { // Metadata filtering
year: { greaterThan: 2020 },
category: { oneOf: ['AI', 'ML'] }
},
connected: { // Graph traversal
to: conceptId,
depth: 2,
type: VerbType.RelatedTo
},
limit: 10
})
```
**Parameters:**
- `query`: `string | FindParams`
- **Simple:** Just text for vector search
- **Advanced:** Object with vector + graph + metadata filters
**FindParams:**
- `query?`: `string` - Text for vector similarity
- `where?`: `object` - Metadata filters (see [Query Operators](#query-operators))
- `connected?`: `object` - Graph traversal options
- `to?`: `string` - Target entity ID
- `from?`: `string` - Source entity ID
- `type?`: `VerbType` - Relationship type
- `depth?`: `number` - Traversal depth
- `limit?`: `number` - Max results (default: 10)
- `offset?`: `number` - Skip results
- `searchMode?`: `'auto' | 'text' | 'semantic' | 'hybrid'` - Search strategy (v7.7.0):
- `'auto'` (default): Zero-config hybrid combining text + semantic search
- `'text'`: Pure keyword/text matching
- `'semantic'`: Pure vector similarity
- `'hybrid'`: Explicit hybrid mode
- `hybridAlpha?`: `number` - Balance between text (0.0) and semantic (1.0) search. Auto-detected by query length if not specified.
**Returns:** `Promise<Result[]>` - Matching entities with scores
---
### Hybrid Search (v7.7.0)
Brainy automatically combines text (keyword) and semantic (vector) search for optimal results. No configuration needed.
```typescript
// Zero-config hybrid search (just works)
const results = await brain.find({
query: 'David Smith' // Finds both exact text matches AND semantically similar
})
// Force text-only search (exact keyword matching)
const textResults = await brain.find({
query: 'exact keyword',
searchMode: 'text'
})
// Force semantic-only search (vector similarity)
const semanticResults = await brain.find({
query: 'artificial intelligence concepts',
searchMode: 'semantic'
})
// Custom hybrid weighting (0 = text only, 1 = semantic only)
const customResults = await brain.find({
query: 'David Smith',
hybridAlpha: 0.3 // Favor text matching
})
```
**How it works:**
- Short queries (1-2 words) automatically favor text matching
- Long queries (5+ words) automatically favor semantic search
- Results are combined using Reciprocal Rank Fusion (RRF)
---
### Match Visibility (v7.8.0)
Search results include detailed match information:
```typescript
const results = await brain.find({ query: 'david the warrior' })
// Each result now includes:
results[0].textMatches // ["david", "warrior"] - exact query words found
results[0].textScore // 0.25 - text match quality (0-1)
results[0].semanticScore // 0.87 - semantic similarity (0-1)
results[0].matchSource // 'both' | 'text' | 'semantic'
```
**Use cases:**
- Highlight exact matches in UI (textMatches)
- Explain why a result ranked high (matchSource)
- Debug search behavior (separate scores)
---
### `highlight(params)` → `Promise<Highlight[]>` ✨ *New v7.8.0, Enhanced v7.9.0*
Zero-config highlighting for both exact matches AND semantic concepts.
Handles plain text, rich-text JSON (TipTap, Slate, Lexical, Draft.js, Quill), HTML, and Markdown automatically.
```typescript
// Plain text (works as before)
const highlights = await brain.highlight({
query: "david the warrior",
text: "David Smith is a brave fighter who battles dragons"
})
// [
// { text: "David", score: 1.0, position: [0, 5], matchType: 'text' },
// { text: "fighter", score: 0.78, position: [25, 32], matchType: 'semantic' },
// { text: "battles", score: 0.72, position: [37, 44], matchType: 'semantic' }
// ]
// Rich-text JSON (auto-detected, v7.9.0)
const highlights = await brain.highlight({
query: "david the warrior",
text: JSON.stringify(tiptapDocument) // TipTap, Slate, Lexical, Draft.js, Quill
})
// Extracts text from nodes, annotates with contentCategory:
// [
// { text: "David", score: 1.0, matchType: 'text', contentCategory: 'heading' },
// { text: "fighter", score: 0.78, matchType: 'semantic', contentCategory: 'prose' }
// ]
// HTML input (auto-detected, v7.9.0)
const highlights = await brain.highlight({
query: "warrior",
text: "<h1>David the Warrior</h1><p>A brave fighter.</p>"
})
// Custom extractor for proprietary formats (v7.9.0)
const highlights = await brain.highlight({
query: "function",
text: sourceCode,
contentExtractor: (text) => treeSitterParse(text) // Your custom parser
})
```
**Parameters:**
- `query`: `string` - The search query
- `text`: `string` - Text to highlight (plain text, JSON, HTML, or Markdown)
- `granularity?`: `'word' | 'phrase' | 'sentence'` - Highlight unit (default: 'word')
- `threshold?`: `number` - Min similarity for semantic matches (default: 0.5)
- `contentType?`: `ContentType` - Optional hint: `'plaintext' | 'richtext-json' | 'html' | 'markdown'`. Skips auto-detection when provided. *(v7.9.0)*
- `contentExtractor?`: `(text: string) => ExtractedSegment[]` - Custom parser. Bypasses built-in detection entirely. *(v7.9.0)*
**Returns:** `Promise<Highlight[]>`
- `text` - The matched text
- `score` - Match score (1.0 for text matches, varies for semantic)
- `position` - [start, end] indices in extracted text
- `matchType` - `'text'` (exact) or `'semantic'` (concept)
- `contentCategory?` - `'prose' | 'heading' | 'code' | 'label'` — Role of the source text in the document. Present when input is structured. *(v7.9.0)*
**Supported Rich-Text Formats (v7.9.0):**
| Format | Detection | Text nodes |
|--------|-----------|------------|
| TipTap / ProseMirror | `{ type: 'doc', content: [...] }` | `{ type: 'text', text }` |
| Slate.js | `[{ type, children }]` | `{ text }` |
| Lexical | `{ root: { children } }` | `{ type: 'text', text }` |
| Draft.js | `{ blocks: [{ text }] }` | `{ text }` in block |
| Quill Delta | `{ ops: [{ insert }] }` | `{ insert }` |
| HTML | Tags like `<h1>`, `<p>`, `<code>` | Visible text content |
| Markdown | `#` headings, ` ``` ` code blocks | Stripped markup |
**Timeout Protection (v7.9.0):**
Semantic matching has a 10-second timeout. If embedding takes too long (e.g., WASM stall), `highlight()` returns text-only matches instead of hanging.
**UI Pattern:**
```typescript
// Style differently based on match type and content category
highlights.forEach(h => {
const style = h.matchType === 'text' ? 'font-weight: bold' : 'background: yellow'
if (h.contentCategory === 'heading') { /* render as heading highlight */ }
if (h.contentCategory === 'code') { /* render with code styling */ }
// Apply style from h.position[0] to h.position[1]
})
```
---
### Query Operators
Brainy uses clean, readable operators:
| Operator | Description | Example |
|----------|-------------|---------|
| `equals` | Exact match | `{age: {equals: 25}}` |
| `greaterThan` | Greater than | `{age: {greaterThan: 18}}` |
| `lessThan` | Less than | `{price: {lessThan: 100}}` |
| `greaterEqual` | Greater or equal | `{score: {greaterEqual: 90}}` |
| `lessEqual` | Less or equal | `{rating: {lessEqual: 3}}` |
| `oneOf` | In array | `{color: {oneOf: ['red', 'blue']}}` |
| `notOneOf` | Not in array | `{status: {notOneOf: ['deleted']}}` |
| `contains` | Contains value | `{tags: {contains: 'ai'}}` |
| `startsWith` | String prefix | `{name: {startsWith: 'John'}}` |
| `endsWith` | String suffix | `{email: {endsWith: '@gmail.com'}}` |
| `matches` | Pattern match | `{text: {matches: /^[A-Z]/}}` |
| `between` | Range | `{year: {between: [2020, 2024]}}` |
---
## Relationships
### `relate(params)` → `Promise<string>`
Create a typed relationship between entities.
```typescript
const relId = await brain.relate({
from: sourceId,
to: targetId,
type: VerbType.RelatedTo,
metadata: { // Optional
strength: 0.9,
confidence: 0.85
}
})
```
**Parameters:**
- `from`: `string` - Source entity ID
- `to`: `string` - Target entity ID
- `type`: `VerbType` - Relationship type
- `metadata?`: `object` - Optional metadata
**Returns:** `Promise<string>` - Relationship ID
---
### `getRelations(params)` → `Promise<Relation[]>`
Get relationships for an entity.
```typescript
// Get all relationships FROM an entity
const outgoing = await brain.getRelations({ from: entityId })
// Get all relationships TO an entity
const incoming = await brain.getRelations({ to: entityId })
// Filter by type
const related = await brain.getRelations({
from: entityId,
type: VerbType.Contains
})
```
**Parameters:**
- `from?`: `string` - Source entity ID
- `to?`: `string` - Target entity ID
- `type?`: `VerbType` - Filter by relationship type
**Returns:** `Promise<Relation[]>` - Matching relationships
---
## Batch Operations
### `addMany(params)` → `Promise<BatchResult<string>>`
Add multiple entities in one operation.
```typescript
const result = await brain.addMany({
items: [
{ data: 'Entity 1', type: NounType.Document },
{ data: 'Entity 2', type: NounType.Concept }
]
})
console.log(result.successful) // Array of IDs
console.log(result.failed) // Array of errors
```
**Returns:** `Promise<BatchResult<string>>` - Success/failure results
---
### `deleteMany(params)` → `Promise<BatchResult<string>>`
Delete multiple entities.
```typescript
const result = await brain.deleteMany({
ids: [id1, id2, id3]
})
```
---
### `updateMany(params)` → `Promise<BatchResult<string>>`
Update multiple entities.
```typescript
const result = await brain.updateMany({
updates: [
{ id: id1, metadata: { updated: true } },
{ id: id2, data: 'New content' }
]
})
```
---
### `relateMany(params)` → `Promise<string[]>`
Create multiple relationships.
```typescript
const ids = await brain.relateMany({
relations: [
{ from: id1, to: id2, type: VerbType.RelatedTo },
{ from: id1, to: id3, type: VerbType.Contains }
]
})
```
---
## Branch Management (v5.0+)
**NEW in v5.0.0:** Git-style branching with Snowflake-style copy-on-write.
### `fork(branch?, options?)` → `Promise<Brainy>`
Create an instant fork (<100ms) with full isolation.
```typescript
// Create a fork
const experiment = await brain.fork('test-feature')
// Make changes safely in isolation
await experiment.add({ data: 'Test entity', type: NounType.Document })
await experiment.update({ id: someId, metadata: { modified: true } })
// Parent is unaffected!
const parentData = await brain.find({}) // Original data unchanged
```
**Parameters:**
- `branch?`: `string` - Branch name (auto-generated if omitted)
- `options?`: `object`
- `description?`: `string` - Branch description
**Returns:** `Promise<Brainy>` - New Brainy instance on forked branch
**How it works:** Snowflake-style COW shares HNSW index, copies only modified nodes (10-20% memory overhead).
---
### `checkout(branch)` → `Promise<void>`
Switch to a different branch.
```typescript
await brain.checkout('main')
await brain.checkout('test-feature')
```
**Parameters:**
- `branch`: `string` - Branch name
---
### `listBranches()` → `Promise<string[]>`
List all branches.
```typescript
const branches = await brain.listBranches()
// ['main', 'test-feature', 'experiment-2']
```
---
### `getCurrentBranch()` → `Promise<string>`
Get current branch name.
```typescript
const current = await brain.getCurrentBranch()
// 'main'
```
---
### `commit(options?)` → `Promise<string>`
Create a commit snapshot.
```typescript
const commitId = await brain.commit({
message: 'Add new features',
author: 'dev@example.com',
metadata: { ticket: 'PROJ-123' }
})
```
**Parameters:**
- `message?`: `string` - Commit message
- `author?`: `string` - Author email
- `metadata?`: `object` - Additional commit metadata
**Returns:** `Promise<string>` - Commit ID
---
### `deleteBranch(branch)` → `Promise<void>`
Delete a branch (cannot delete 'main').
```typescript
await brain.deleteBranch('old-experiment')
```
---
### `getHistory(options?)` → `Promise<Commit[]>`
Get commit history.
```typescript
const history = await brain.getHistory({
branch: 'main',
limit: 10
})
```
---
### `asOf(commitId, options?)` → `Promise<Brainy>`
Create a read-only snapshot at a specific commit for time-travel queries.
```typescript
// Get commit ID from history
const commits = await brain.getHistory({ limit: 1 })
const commitId = commits[0].id
// Create snapshot (lazy-loading, no eager data loading)
const snapshot = await brain.asOf(commitId, {
cacheSize: 10000 // LRU cache size (default: 10000)
})
// Query historical state - full Triple Intelligence works!
const results = await snapshot.find({
query: 'AI research',
where: { category: 'technology' }
})
// Get historical relationships
const related = await snapshot.getRelated(entityId, { depth: 2 })
// MUST close when done to free memory
await snapshot.close()
```
**Parameters:**
- `commitId`: `string` - Commit hash to snapshot from
- `options?`: `object`
- `cacheSize?`: `number` - LRU cache size for lazy-loading (default: 10000)
**Returns:** `Promise<Brainy>` - Read-only Brainy instance with historical state
**Features:**
- **Lazy-Loading** - Loads entities on-demand, not eagerly
- **Bounded Memory** - LRU cache prevents memory bloat
- **Full Query Support** - All find(), getRelated(), etc. work on historical data
- **Read-Only** - Prevents accidental modifications to history
**Important:** Always call `snapshot.close()` when done to release resources.
---
## Entity Versioning (v5.3.0+)
**NEW in v5.3.0:** Git-style versioning for individual entities with content-addressable storage.
### Overview
Entity Versioning provides time-travel and history tracking for individual entities:
- **Content-Addressable Storage** - Deduplication via SHA-256 hashing
- **Zero-Config** - Lazy initialization, uses existing indexes
- **Branch-Isolated** - Versions isolated per branch
- **Selective Auto-Versioning** - Optional augmentation for automatic version creation
- **Production-Scale** - Designed for billions of entities
- **VFS File Support (v6.3.2+)** - Full versioning for VFS files with actual blob content
---
### `versions.save(entityId, options?)` → `Promise<EntityVersion>`
Save a new version of an entity.
```typescript
// Save version with tag
const version = await brain.versions.save('user-123', {
tag: 'v1.0',
description: 'Initial user profile',
metadata: { author: 'dev@example.com' }
})
console.log(version.version) // 1
console.log(version.contentHash) // SHA-256 hash
console.log(version.createdAt) // Timestamp
```
**Parameters:**
- `entityId`: `string` - Entity ID to version
- `options?`: `object`
- `tag?`: `string` - Version tag (e.g., 'v1.0', 'beta')
- `description?`: `string` - Version description
- `metadata?`: `object` - Additional version metadata
**Returns:** `Promise<EntityVersion>` - Created version
**Features:**
- Automatic deduplication (identical content = same version)
- Sequential version numbering (1, 2, 3, ...)
- Content-addressable storage (SHA-256)
---
### `versions.list(entityId, options?)` → `Promise<EntityVersion[]>`
List all versions of an entity.
```typescript
const versions = await brain.versions.list('user-123', {
limit: 10,
offset: 0
})
versions.forEach(v => {
console.log(`Version ${v.version}: ${v.tag} - ${v.description}`)
})
```
**Parameters:**
- `entityId`: `string` - Entity ID
- `options?`: `object`
- `limit?`: `number` - Max versions to return
- `offset?`: `number` - Skip versions
**Returns:** `Promise<EntityVersion[]>` - Versions (newest first)
---
### `versions.restore(entityId, versionOrTag)` → `Promise<void>`
Restore entity to a previous version.
```typescript
// Restore by version number
await brain.versions.restore('user-123', 1)
// Restore by tag
await brain.versions.restore('user-123', 'beta')
```
**Parameters:**
- `entityId`: `string` - Entity ID
- `versionOrTag`: `number | string` - Version number or tag
---
### `versions.compare(entityId, version1, version2)` → `Promise<VersionDiff>`
Compare two versions.
```typescript
const diff = await brain.versions.compare('user-123', 1, 2)
console.log(diff.totalChanges) // Total changes
console.log(diff.modified) // Modified fields
console.log(diff.added) // Added fields
console.log(diff.removed) // Removed fields
// Check specific changes
const nameChange = diff.modified.find(c => c.path === 'metadata.name')
console.log(`${nameChange.oldValue}${nameChange.newValue}`)
```
**Returns:** `Promise<VersionDiff>` - Detailed diff with field-level changes
---
### `versions.getContent(entityId, versionOrTag)` → `Promise<EntitySnapshot>`
Get version content without restoring.
```typescript
// View old version without changing current state
const v1Content = await brain.versions.getContent('user-123', 1)
console.log(v1Content.metadata.name) // Old name
// Current state unchanged
const current = await brain.get('user-123')
console.log(current.metadata.name) // Current name
```
---
### `versions.undo(entityId)` → `Promise<void>`
Undo to previous version (shorthand for restore to latest-1).
```typescript
// Make a bad change
await brain.update('user-123', { status: 'deleted' })
// Undo immediately
await brain.versions.undo('user-123')
```
**Alias:** `versions.revert(entityId)`
---
### `versions.prune(entityId, options)` → `Promise<PruneResult>`
Clean up old versions.
```typescript
const result = await brain.versions.prune('user-123', {
keepRecent: 10, // Keep 10 most recent
keepTagged: true, // Always keep tagged versions
olderThan: Date.now() - 30 * 24 * 60 * 60 * 1000 // Older than 30 days
})
console.log(`Deleted ${result.deleted}, kept ${result.kept}`)
```
**Parameters:**
- `keepRecent?`: `number` - Keep N most recent versions
- `keepTagged?`: `boolean` - Always keep tagged versions (default: true)
- `olderThan?`: `number` - Only prune versions older than timestamp
---
### `versions.getLatest(entityId)` → `Promise<EntityVersion | null>`
Get latest version.
```typescript
const latest = await brain.versions.getLatest('user-123')
if (latest) {
console.log(`Latest: v${latest.version} (${latest.tag})`)
}
```
---
### `versions.getVersionByTag(entityId, tag)` → `Promise<EntityVersion | null>`
Get version by tag.
```typescript
const beta = await brain.versions.getVersionByTag('user-123', 'beta')
```
---
### `versions.count(entityId)` → `Promise<number>`
Count versions for an entity.
```typescript
const count = await brain.versions.count('user-123')
console.log(`${count} versions saved`)
```
---
### `versions.hasVersions(entityId)` → `Promise<boolean>`
Check if entity has versions.
```typescript
if (await brain.versions.hasVersions('user-123')) {
console.log('Entity has version history')
}
```
---
### Auto-Versioning Augmentation
Automatically create versions on entity updates.
```typescript
import { VersioningAugmentation } from '@soulcraft/brainy'
// Configure auto-versioning
const versioning = new VersioningAugmentation({
enabled: true,
onUpdate: true, // Version on update()
onDelete: false, // Don't version on delete
entities: ['user-*'], // Only version users
excludeEntities: ['temp-*'],
excludeTypes: ['temporary'],
keepRecent: 50, // Auto-prune old versions
keepTagged: true
})
// Apply augmentation
brain.augment(versioning)
// Now updates auto-create versions
await brain.update('user-123', { name: 'New Name' })
// Version automatically created!
const versions = await brain.versions.list('user-123')
console.log(`Auto-created version: ${versions[0].version}`)
```
**Configuration:**
- `enabled`: `boolean` - Enable/disable augmentation
- `onUpdate`: `boolean` - Version on entity updates
- `onDelete`: `boolean` - Version before deletion
- `entities`: `string[]` - Entity ID patterns (glob-style)
- `excludeEntities`: `string[]` - Exclusion patterns
- `types`: `string[]` - Entity types to version
- `excludeTypes`: `string[]` - Types to exclude
- `keepRecent`: `number` - Auto-prune to keep N versions
- `keepTagged`: `boolean` - Always keep tagged versions
**Pattern Matching:**
- `['*']` - All entities
- `['user-*']` - All IDs starting with "user-"
- `['*-prod']` - All IDs ending with "-prod"
- `['user-*', 'account-*']` - Multiple patterns
---
### Branch Isolation
Versions are isolated per branch.
```typescript
// Save version on main
await brain.versions.save('doc-1', { tag: 'main-v1' })
// Fork and create version
const feature = await brain.fork('feature')
await feature.update('doc-1', { content: 'Feature update' })
await feature.versions.save('doc-1', { tag: 'feature-v1' })
// Versions are isolated
const mainVersions = await brain.versions.list('doc-1')
const featureVersions = await feature.versions.list('doc-1')
console.log(mainVersions.length !== featureVersions.length) // true
```
---
### Architecture
**Content-Addressable Storage:**
- SHA-256 hashing for deduplication
- Identical content = single storage blob
- Efficient for entities with few changes
**Metadata Indexing:**
- Leverages existing MetadataIndexManager
- Fast lookups by entity ID
- Version number indexing
**Storage Structure:**
```
_version:{entityId}:{versionNum}:{branch} // Version metadata
_version_blob:{contentHash} // Content blob (deduplicated)
```
**Performance:**
- Version save: O(1) if duplicate, O(log N) for index update
- Version list: O(K) where K = version count
- Version restore: O(log N) lookup + O(1) restore
- Pruning: O(K) where K = versions pruned
---
### Examples
#### Basic Versioning Workflow
```typescript
// Create entity
await brain.add({
data: 'User profile',
id: 'user-123',
type: 'user',
metadata: { name: 'Alice', email: 'alice@example.com' }
})
// Save v1
await brain.versions.save('user-123', { tag: 'v1.0' })
// Make changes
await brain.update('user-123', { name: 'Alice Smith' })
// Save v2
await brain.versions.save('user-123', { tag: 'v2.0' })
// Compare versions
const diff = await brain.versions.compare('user-123', 1, 2)
// Restore to v1 if needed
await brain.versions.restore('user-123', 'v1.0')
```
#### Release Management
```typescript
// Development workflow
await brain.update('app-config', { version: '1.0.0-alpha' })
await brain.versions.save('app-config', { tag: 'alpha' })
await brain.update('app-config', { version: '1.0.0-beta' })
await brain.versions.save('app-config', { tag: 'beta' })
await brain.update('app-config', { version: '1.0.0' })
await brain.versions.save('app-config', { tag: 'release' })
// Rollback to beta if issues found
await brain.versions.restore('app-config', 'beta')
```
#### Audit Trail
```typescript
// Track all changes
const versioning = new VersioningAugmentation({
enabled: true,
onUpdate: true,
entities: ['audit-*'],
keepRecent: 100 // Keep 100 versions for audit
})
brain.augment(versioning)
// All updates now tracked
await brain.update('audit-record-1', { status: 'modified' })
await brain.update('audit-record-1', { status: 'approved' })
// View complete history
const versions = await brain.versions.list('audit-record-1')
versions.forEach(v => {
console.log(`${v.createdAt}: ${v.description}`)
})
```
#### VFS File Versioning (v6.3.2+)
```typescript
// VFS files can be versioned with actual blob content
await brain.vfs.writeFile('/docs/readme.md', 'Version 1 content')
// Get the file's entity ID
const stat = await brain.vfs.stat('/docs/readme.md')
// Save version 1
await brain.versions.save(stat.entityId, { tag: 'v1', description: 'Initial draft' })
// Modify the file
await brain.vfs.writeFile('/docs/readme.md', 'Version 2 - updated content')
// Save version 2
await brain.versions.save(stat.entityId, { tag: 'v2', description: 'Updated docs' })
// Compare versions - content is DIFFERENT (fixed in v6.3.2)
const v1 = await brain.versions.getContent(stat.entityId, 1)
const v2 = await brain.versions.getContent(stat.entityId, 2)
console.log(v1.data !== v2.data) // true
// Restore to v1 - writes content back to blob storage
await brain.versions.restore(stat.entityId, 'v1')
// File is now back to v1
const content = await brain.vfs.readFile('/docs/readme.md')
console.log(content.toString()) // 'Version 1 content'
```
---
**[📖 Complete Versioning Guide →](../features/entity-versioning.md)**
---
## Virtual Filesystem (VFS)
**Auto-initialized in v5.1.0!** Access via `brain.vfs` (property, not method).
### Filtering VFS Entities
**NEW in v5.3.0:** All VFS entities (files/folders) have `metadata.isVFSEntity: true` set automatically.
Use this to filter VFS entities from semantic search results:
```typescript
// Exclude VFS entities from semantic search
const semanticOnly = await brain.find({
query: 'artificial intelligence',
where: {
isVFSEntity: { notEquals: true } // Only semantic entities
}
})
// Or filter to ONLY VFS entities
const vfsOnly = await brain.find({
where: {
isVFSEntity: { equals: true } // Only VFS files/folders
}
})
// Check if an entity is a VFS entity
if (entity.metadata.isVFSEntity === true) {
console.log('This is a VFS file or folder')
}
```
**Why this matters:** Without filtering, VFS files/folders can appear in concept explorers and semantic search results where they don't belong.
---
### Basic File Operations
#### `vfs.readFile(path, options?)` → `Promise<Buffer>`
Read file content.
```typescript
const content = await brain.vfs.readFile('/docs/README.md')
console.log(content.toString())
```
---
#### `vfs.writeFile(path, data, options?)` → `Promise<void>`
Write file content.
```typescript
await brain.vfs.writeFile('/docs/README.md', 'New content', {
encoding: 'utf-8'
})
```
---
#### `vfs.unlink(path)` → `Promise<void>`
Delete a file.
```typescript
await brain.vfs.unlink('/docs/old-file.md')
```
---
### Directory Operations
#### `vfs.mkdir(path, options?)` → `Promise<void>`
Create directory.
```typescript
await brain.vfs.mkdir('/projects/new-app', { recursive: true })
```
---
#### `vfs.readdir(path, options?)` → `Promise<string[] | Dirent[]>`
List directory contents.
```typescript
const files = await brain.vfs.readdir('/projects')
// With file types
const entries = await brain.vfs.readdir('/projects', { withFileTypes: true })
entries.forEach(entry => {
console.log(entry.name, entry.isDirectory() ? 'DIR' : 'FILE')
})
```
---
#### `vfs.rmdir(path, options?)` → `Promise<void>`
Remove directory.
```typescript
await brain.vfs.rmdir('/old-project', { recursive: true })
```
---
#### `vfs.stat(path)` → `Promise<Stats>`
Get file/directory stats.
```typescript
const stats = await brain.vfs.stat('/docs/README.md')
console.log(stats.size) // File size
console.log(stats.mtime) // Modified time
console.log(stats.isDirectory()) // Is directory?
```
---
### Semantic Operations
#### `vfs.search(query, options?)` → `Promise<SearchResult[]>`
Semantic file search.
```typescript
const results = await brain.vfs.search('React components with hooks', {
path: '/src',
limit: 10
})
```
---
#### `vfs.findSimilar(path, options?)` → `Promise<SearchResult[]>`
Find similar files.
```typescript
const similar = await brain.vfs.findSimilar('/src/App.tsx', {
limit: 5,
threshold: 0.7
})
```
---
### Tree Operations
#### `vfs.getTreeStructure(path, options?)` → `Promise<TreeNode>`
Get directory tree (prevents infinite recursion).
```typescript
const tree = await brain.vfs.getTreeStructure('/projects', {
maxDepth: 3
})
```
---
#### `vfs.getDescendants(path, options?)` → `Promise<VFSEntity[]>`
Get all descendants with optional filtering.
```typescript
const files = await brain.vfs.getDescendants('/src', {
filter: (entity) => entity.name.endsWith('.tsx')
})
```
---
### Metadata & Relationships
#### `vfs.getMetadata(path)` → `Promise<Metadata>`
Get file metadata.
```typescript
const meta = await brain.vfs.getMetadata('/src/App.tsx')
console.log(meta.todos) // Extracted TODOs
console.log(meta.tags) // Tags
```
---
#### `vfs.getRelationships(path)` → `Promise<Relation[]>`
Get file relationships.
```typescript
const rels = await brain.vfs.getRelationships('/src/App.tsx')
// Returns: imports, references, dependencies
```
---
#### `vfs.getTodos(path)` → `Promise<Todo[]>`
Get TODOs from a file.
```typescript
const todos = await brain.vfs.getTodos('/src/App.tsx')
```
---
#### `vfs.getAllTodos(path?)` → `Promise<Todo[]>`
Get all TODOs from directory tree.
```typescript
const allTodos = await brain.vfs.getAllTodos('/src')
```
---
### Project Analysis
#### `vfs.getProjectStats(path?)` → `Promise<Stats>`
Get project statistics.
```typescript
const stats = await brain.vfs.getProjectStats('/projects/my-app')
console.log(stats.fileCount)
console.log(stats.totalSize)
console.log(stats.fileTypes) // Breakdown by extension
```
---
#### `vfs.searchEntities(query)` → `Promise<VFSEntity[]>`
Search for VFS entities by metadata.
```typescript
const tsxFiles = await brain.vfs.searchEntities({
type: 'file',
extension: '.tsx'
})
```
---
**[📖 Complete VFS Documentation →](../vfs/QUICK_START.md)**
---
## Neural API
Access advanced AI features via `brain.neural()` (method that returns NeuralAPI instance).
### `neural().similar(a, b, options?)` → `Promise<number | SimilarityResult>`
Calculate semantic similarity.
```typescript
// Simple similarity score
const score = await brain.neural().similar(
'renewable energy',
'sustainable power'
) // 0.87
// Detailed result
const result = await brain.neural().similar('text1', 'text2', {
detailed: true
})
console.log(result.score)
console.log(result.explanation)
```
---
### `neural().clusters(input?, options?)` → `Promise<Cluster[]>`
Automatic clustering.
```typescript
const clusters = await brain.neural().clusters({
algorithm: 'kmeans',
k: 5,
minSize: 3
})
clusters.forEach(cluster => {
console.log(cluster.label)
console.log(cluster.items)
console.log(cluster.centroid)
})
```
---
### `neural().neighbors(id, options?)` → `Promise<Neighbor[]>`
Find k-nearest neighbors.
```typescript
const neighbors = await brain.neural().neighbors(entityId, {
k: 10,
threshold: 0.7
})
```
---
### `neural().outliers(threshold?)` → `Promise<string[]>`
Detect outlier entities.
```typescript
const outliers = await brain.neural().outliers(0.3)
// Returns entity IDs that are outliers
```
---
### `neural().visualize(options?)` → `Promise<VizData>`
Generate visualization data.
```typescript
const vizData = await brain.neural().visualize({
maxNodes: 100,
dimensions: 3,
algorithm: 'force',
includeEdges: true
})
// Use with D3.js, Cytoscape, GraphML tools
```
---
### Performance Methods
#### `neural().clusterFast(options)` → `Promise<Cluster[]>`
Fast clustering for large datasets.
```typescript
const clusters = await brain.neural().clusterFast({
k: 10,
maxIterations: 50
})
```
---
#### `neural().clusterLarge(options)` → `Promise<Cluster[]>`
Streaming clustering for very large datasets.
```typescript
const clusters = await brain.neural().clusterLarge({
k: 20,
batchSize: 1000
})
```
---
## Import & Export
### `import(source, options?)` → `Promise<ImportResult>`
Smart import with auto-detection (CSV, Excel, PDF, JSON, URLs).
```typescript
// CSV import
await brain.import('data.csv', {
format: 'csv',
createEntities: true
})
// Excel import
await brain.import('sales.xlsx', {
format: 'excel',
sheets: ['Q1', 'Q2']
})
// PDF import
await brain.import('research.pdf', {
format: 'pdf',
extractTables: true
})
// URL import
await brain.import('https://api.example.com/data.json')
```
**Parameters:**
- `source`: `string | Buffer | object` - File path, URL, buffer, or object
- `options?`: Import configuration
- `format?`: `'csv' | 'excel' | 'pdf' | 'json'` - Auto-detected if omitted
- `createEntities?`: `boolean` - Create entities from rows
- `sheets?`: `string[]` - Excel sheets to import
- `extractTables?`: `boolean` - Extract tables from PDF
**Returns:** `Promise<ImportResult>` - Import statistics
**Note:** Import always uses the current branch (v5.1.0 verified).
**[📖 Complete Import Guide →](../guides/import-anything.md)**
---
### Export & Snapshots
```typescript
// Export to file
await brain.export('/path/to/backup.brainy')
// Create instant snapshot using COW fork
await brain.fork('backup-2025-01-19')
// Time-travel to specific commit
const snapshot = await brain.asOf(commitId)
const entities = await snapshot.find({ limit: 100 })
```
---
## Configuration
### Constructor Options
```typescript
const brain = new Brainy({
// Storage configuration
storage: {
type: 'memory', // memory | opfs | filesystem | s3 | r2 | gcs | azure
path: './brainy-data', // For filesystem storage
compression: true, // Enable gzip compression (60-80% savings)
// Cloud storage configs (see Storage Adapters section)
s3Storage: { ... },
r2Storage: { ... },
gcsStorage: { ... },
azureStorage: { ... }
},
// HNSW vector index config
hnsw: {
M: 16, // Connections per layer
efConstruction: 200, // Construction quality
efSearch: 100, // Search quality
typeAware: true // Enable type-aware indexing (v4.0+)
},
// Model configuration (embedded in WASM - zero config needed)
// Model: all-MiniLM-L6-v2 (384 dimensions)
// Device: CPU via WASM (works everywhere)
// Cache configuration
cache: {
enabled: true,
maxSize: 10000,
ttl: 3600000 // 1 hour in ms
}
})
await brain.init() // Required! VFS auto-initialized in v5.1.0
```
---
## Storage Adapters
All 7 storage adapters support **copy-on-write branching** (v5.0+).
### Memory (Default)
```typescript
const brain = new Brainy({
storage: { type: 'memory' }
})
```
**Use case:** Development, testing, prototyping
---
### OPFS (Browser)
```typescript
const brain = new Brainy({
storage: { type: 'opfs' }
})
```
**Use case:** Browser applications with persistent storage
---
### Filesystem (Node.js)
```typescript
const brain = new Brainy({
storage: {
type: 'filesystem',
path: './brainy-data',
compression: true // 60-80% space savings
}
})
```
**Use case:** Node.js applications, local persistence
---
### AWS S3
```typescript
const brain = new Brainy({
storage: {
type: 's3',
s3Storage: {
bucketName: 'my-brainy-data',
region: 'us-east-1',
accessKeyId: process.env.AWS_ACCESS_KEY_ID,
secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY
}
}
})
// Enable Intelligent-Tiering for 96% cost savings
await brain.storage.enableIntelligentTiering('entities/', 'auto-tier')
```
**Use case:** Production deployments, scalable storage
**[📖 AWS S3 Cost Optimization →](../operations/cost-optimization-aws-s3.md)**
---
### Cloudflare R2
```typescript
const brain = new Brainy({
storage: {
type: 'r2',
r2Storage: {
accountId: process.env.CF_ACCOUNT_ID,
bucketName: 'my-brainy-data',
accessKeyId: process.env.CF_ACCESS_KEY_ID,
secretAccessKey: process.env.CF_SECRET_ACCESS_KEY
}
}
})
```
**Use case:** Zero egress fees, cost-effective storage
**[📖 R2 Cost Optimization →](../operations/cost-optimization-cloudflare-r2.md)**
---
### Google Cloud Storage (GCS)
```typescript
const brain = new Brainy({
storage: {
type: 'gcs',
gcsStorage: {
bucketName: 'my-brainy-data',
projectId: process.env.GCP_PROJECT_ID,
keyFilename: './gcp-key.json'
}
}
})
// Enable auto-tiering
await brain.storage.enableAutoclass({
terminalStorageClass: 'ARCHIVE'
})
```
**Use case:** Google Cloud ecosystem, global distribution
**[📖 GCS Cost Optimization →](../operations/cost-optimization-gcs.md)**
---
### Azure Blob Storage
```typescript
const brain = new Brainy({
storage: {
type: 'azure',
azureStorage: {
accountName: process.env.AZURE_STORAGE_ACCOUNT,
accountKey: process.env.AZURE_STORAGE_KEY,
containerName: 'brainy-data'
}
}
})
```
**Use case:** Azure ecosystem, enterprise deployments
**[📖 Azure Cost Optimization →](../operations/cost-optimization-azure.md)**
---
## Utility Methods
### `clear()` → `Promise<void>`
Clear all data (entities and relationships).
```typescript
await brain.clear()
```
---
### `getNounCount()` → `Promise<number>`
Get total entity count.
```typescript
const count = await brain.getNounCount()
```
---
### `getVerbCount()` → `Promise<number>`
Get total relationship count.
```typescript
const count = await brain.getVerbCount()
```
---
### `embed(data)` → `Promise<number[]>` ✨ *Enhanced v7.1.0*
Generate embedding vector from text or data.
```typescript
const vector = await brain.embed('Hello world')
// 384-dimensional vector
console.log(vector.length) // 384
```
---
### `embedBatch(texts)` → `Promise<number[][]>` ✨ *New v7.1.0, Optimized v7.9.0*
Batch embed multiple texts using native WASM batch API (single forward pass).
```typescript
const embeddings = await brain.embedBatch([
'Machine learning is fascinating',
'Deep neural networks',
'Natural language processing'
])
console.log(embeddings.length) // 3
console.log(embeddings[0].length) // 384
```
> **v7.9.0**: Now uses the WASM engine's native `embed_batch()` for a single model forward pass instead of N individual calls. This is the same batch API used internally by `highlight()`.
---
### `similarity(textA, textB)` → `Promise<number>` ✨ *New v7.1.0*
Calculate semantic similarity between two texts.
```typescript
const score = await brain.similarity(
'The cat sat on the mat',
'A feline was resting on the rug'
)
console.log(score) // ~0.85 (high semantic similarity)
```
**Returns:** Score from 0 (different) to 1 (identical meaning)
---
### `neighbors(entityId, options?)` → `Promise<string[]>` ✨ *New v7.1.0*
Get graph neighbors of an entity.
```typescript
// Get all connected entities
const neighbors = await brain.neighbors(entityId)
// Get outgoing connections only
const outgoing = await brain.neighbors(entityId, {
direction: 'outgoing',
limit: 10
})
// Multi-hop traversal
const extended = await brain.neighbors(entityId, {
depth: 2,
direction: 'both'
})
```
**Options:**
- `direction`: `'outgoing' | 'incoming' | 'both'` (default: 'both')
- `depth`: `number` - Traversal depth (default: 1)
- `verbType`: `VerbType` - Filter by relationship type
- `limit`: `number` - Maximum neighbors to return
---
### `findDuplicates(options?)` → `Promise<DuplicateResult[]>` ✨ *New v7.1.0*
Find semantic duplicates in the database.
```typescript
// Find all duplicates
const duplicates = await brain.findDuplicates()
for (const group of duplicates) {
console.log('Original:', group.entity.id)
for (const dup of group.duplicates) {
console.log(` Duplicate: ${dup.entity.id} (${dup.similarity.toFixed(2)})`)
}
}
// Find person duplicates with higher threshold
const personDupes = await brain.findDuplicates({
type: NounType.PERSON,
threshold: 0.9,
limit: 50
})
```
**Options:**
- `threshold`: `number` - Minimum similarity (default: 0.85)
- `type`: `NounType` - Filter by entity type
- `limit`: `number` - Maximum duplicate groups (default: 100)
---
### `indexStats()` → `Promise<IndexStats>` ✨ *New v7.1.0*
Get comprehensive index statistics.
```typescript
const stats = await brain.indexStats()
console.log(`Entities: ${stats.entities}`)
console.log(`Vectors: ${stats.vectors}`)
console.log(`Relationships: ${stats.relationships}`)
console.log(`Memory: ${(stats.memoryUsage.total / 1024 / 1024).toFixed(1)}MB`)
console.log(`Fields: ${stats.metadataFields.join(', ')}`)
```
**Returns:**
- `entities` - Total entity count
- `vectors` - Total vectors in HNSW index
- `relationships` - Total relationships in graph
- `metadataFields` - Indexed metadata fields
- `memoryUsage.vectors` - Vector memory (bytes)
- `memoryUsage.graph` - Graph memory (bytes)
- `memoryUsage.metadata` - Metadata index memory (bytes)
- `memoryUsage.total` - Total memory usage
---
### `cluster(options?)` → `Promise<ClusterResult[]>` ✨ *New v7.1.0*
Cluster entities by semantic similarity.
```typescript
// Find all clusters
const clusters = await brain.cluster()
for (const cluster of clusters) {
console.log(`${cluster.clusterId}: ${cluster.entities.length} entities`)
}
// Find document clusters with centroids
const docClusters = await brain.cluster({
type: NounType.Document,
threshold: 0.85,
minClusterSize: 3,
includeCentroid: true
})
```
**Options:**
- `threshold`: `number` - Similarity threshold (default: 0.8)
- `type`: `NounType` - Filter by entity type
- `minClusterSize`: `number` - Minimum cluster size (default: 2)
- `limit`: `number` - Maximum clusters to return (default: 100)
- `includeCentroid`: `boolean` - Calculate cluster centroids (default: false)
**Returns:**
- `clusterId` - Unique cluster identifier
- `entities` - Array of entities in the cluster
- `centroid` - Average embedding vector (if includeCentroid is true)
---
### `getStats()` → `Statistics`
Get comprehensive statistics.
```typescript
const stats = brain.getStats()
console.log(stats.entityCount)
console.log(stats.relationshipCount)
console.log(stats.cacheHitRate)
```
---
## Lifecycle
### Initialization
```typescript
const brain = new Brainy(config)
await brain.init() // Required! VFS auto-initialized here (v5.1.0)
```
**v5.1.0 Change:** VFS is now auto-initialized during `brain.init()` - no separate `vfs.init()` needed!
---
### Shutdown
```typescript
await brain.shutdown() // Graceful shutdown, flush caches
```
---
## Examples
### Basic CRUD
```typescript
// Create
const id = await brain.add({
data: 'Quantum computing breakthrough',
type: NounType.Concept,
metadata: { category: 'tech', year: 2024 }
})
// Read
const entity = await brain.get(id)
// Update
await brain.update({
id,
metadata: { updated: true }
})
// Delete
await brain.delete(id)
```
---
### Knowledge Graphs
```typescript
// Create entities
const ai = await brain.add({
data: 'Artificial Intelligence',
type: NounType.Concept
})
const ml = await brain.add({
data: 'Machine Learning',
type: NounType.Concept
})
// Create relationship
await brain.relate({
from: ml,
to: ai,
type: VerbType.IsA
})
// Traverse graph
const results = await brain.find({
connected: { from: ai, depth: 2 }
})
```
---
### Triple Intelligence Query
```typescript
const results = await brain.find({
query: 'modern frontend frameworks', // 🔍 Vector
where: { // 📊 Document
year: { greaterThan: 2020 },
category: { oneOf: ['framework', 'library'] }
},
connected: { // 🕸️ Graph
to: reactId,
depth: 2,
type: VerbType.BuiltOn
},
limit: 10
})
```
---
### Git-Style Workflow (v5.0+)
```typescript
// Fork for experimentation
const experiment = await brain.fork('test-migration')
// Make changes in isolation
await experiment.add({
data: 'New feature',
type: NounType.Document
})
// Commit your work
await experiment.commit({
message: 'Add new feature',
author: 'dev@example.com'
})
// Switch to experimental branch to make it active
await brain.checkout('test-migration')
```
---
### VFS File Management
```typescript
// Write files
await brain.vfs.writeFile('/docs/README.md', 'Project documentation')
await brain.vfs.mkdir('/src/components', { recursive: true })
// Read files
const content = await brain.vfs.readFile('/docs/README.md')
// Semantic search
const reactFiles = await brain.vfs.search('React components with hooks', {
path: '/src'
})
// Get tree structure (safe, prevents infinite recursion)
const tree = await brain.vfs.getTreeStructure('/projects', {
maxDepth: 3
})
```
---
## Type System Reference
**NEW in v5.5.0:** Stage 3 CANONICAL taxonomy with 169 types (42 nouns + 127 verbs)
### Noun Types (42)
Brainy uses a comprehensive noun type system covering 96-97% of human knowledge:
**Core Entity Types (7)**
- `NounType.Person` - Individual human entities
- `NounType.Organization` - Companies, institutions, collectives
- `NounType.Location` - Geographic and spatial entities
- `NounType.Thing` - Physical objects and artifacts
- `NounType.Concept` - Abstract ideas and principles
- `NounType.Event` - Temporal occurrences
- `NounType.Agent` - AI agents, bots, automated systems
**Digital/Content Types (4)**
- `NounType.Document` - Text-based files and written content
- `NounType.Media` - Audio, video, images
- `NounType.File` - Generic digital files
- `NounType.Message` - Communication content
**Business Types (4)**
- `NounType.Product` - Commercial products
- `NounType.Service` - Service offerings
- `NounType.Task` - Actions, todos, work items
- `NounType.Project` - Organized initiatives
**Scientific Types (2)**
- `NounType.Hypothesis` - Theories and propositions
- `NounType.Experiment` - Studies and investigations
**And 25 more types** including: `Organism`, `Substance`, `Quality`, `TimeInterval`, `Function`, `Proposition`, `Collection`, `Dataset`, `Process`, `State`, `Role`, `Language`, `Currency`, `Measurement`, `Contract`, `Regulation`, `Interface`, `Resource`, `Custom`, `SocialGroup`, `Institution`, `Norm`, `InformationContent`, `InformationBearer`, `Relationship`
### Verb Types (127)
Brainy supports 127 relationship types organized into categories:
**Foundational (7)**
- `VerbType.InstanceOf`, `VerbType.SubclassOf`, `VerbType.ParticipatesIn`
- `VerbType.RelatedTo`, `VerbType.Contains`, `VerbType.PartOf`, `VerbType.References`
**Spatial & Temporal (14)**
- Location: `LocatedAt`, `AdjacentTo`, `ContainsSpatially`, `OverlapsSpatially`, `Above`, `Below`, `Inside`, `Outside`, `Facing`
- Time: `Precedes`, `During`, `OccursAt`, `Overlaps`, `ImmediatelyAfter`, `SimultaneousWith`
**Causal & Dependency (11)**
- Direct: `Causes`, `Enables`, `Prevents`, `DependsOn`, `Requires`
- Modal: `CanCause`, `MustCause`, `WouldCauseIf`, `ProbablyCauses`
- Variations: `RigidlyDependsOn`, `FunctionallyDependsOn`, `HistoricallyDependsOn`
**Creation & Change (10)**
- Lifecycle: `Creates`, `Transforms`, `Becomes`, `Modifies`, `Consumes`, `Destroys`
- Properties: `GainsProperty`, `LosesProperty`, `RemainsSame`, `PersistsThrough`
**Social & Communication (8)**
- `MemberOf`, `WorksWith`, `FriendOf`, `Follows`, `Likes`, `ReportsTo`, `Mentors`, `Communicates`
**Epistemic & Modal (14)**
- Knowledge: `Knows`, `Doubts`, `Believes`, `Learns`
- Mental states: `Desires`, `Intends`, `Fears`, `Loves`, `Hates`, `Hopes`, `Perceives`
- Modality: `CouldBe`, `MustBe`, `Counterfactual`
**Measurement & Comparison (9)**
- `Measures`, `MeasuredIn`, `ConvertsTo`, `HasMagnitude`, `GreaterThan`
- `SimilarityDegree`, `ApproximatelyEquals`, `MoreXThan`, `HasDegree`
**And 54 more specialized verbs** including ownership, composition, uncertainty, deontic relationships (obligations/permissions), context-dependent truth, spatial/temporal variations, information theory, and meta-level relationships.
### Complete Reference
For the full taxonomy with all 169 types and their descriptions, see:
- **[Stage 3 CANONICAL Taxonomy](../STAGE3-CANONICAL-TAXONOMY.md)** - Complete list with categories
- **[Noun-Verb Taxonomy Architecture](../architecture/noun-verb-taxonomy.md)** - Design rationale
### Migration from v5.4.0
**Breaking Changes:**
- `NounType.Content` removed Use `Document`, `Message`, or `InformationContent`
- `NounType.User` removed Use `Person` or `Agent`
- `NounType.Topic` removed Use `Concept` or `Category`
**New Types Added:**
- **+11 noun types**: Agent, Organism, Substance, Quality, TimeInterval, Function, Proposition, Custom, SocialGroup, Institution, Norm, InformationContent, InformationBearer, Relationship
- **+87 verb types**: Extensive additions across all categories
---
## What's New in v5.0
### v5.3.0 (Latest)
- **Entity Versioning** - Git-style versioning for individual entities
- **Content-Addressable Storage** - SHA-256 deduplication for versions
- **Auto-Versioning Augmentation** - Automatic version creation on updates
- **Branch-Isolated Versions** - Versions isolated per branch
- **VFS Entity Filtering** - All VFS entities now have `isVFSEntity: true` flag
- **CRITICAL FIX:** commit() now updates branch refs correctly (brainy.ts:2385)
- **CRITICAL FIX:** VFS entities now properly flagged for filtering
### v5.1.0
- **VFS Auto-Initialization** - No more separate `vfs.init()` calls
- **VFS Property Access** - Use `brain.vfs.method()` instead of `brain.vfs().method()`
- **Complete COW Support** - All 20 TypeAware methods use COW helpers
- **Verified Import/Export** - Work correctly with current branch
### v5.0.0
- **Instant Fork** - Snowflake-style copy-on-write (<100ms fork time)
- **Git-Style Branching** - fork, commit, checkout, listBranches
- **Full Branch Isolation** - Parent and fork fully isolated
- **Read-Through Inheritance** - Forks see parent + own data
- **Universal Storage Support** - All 7 adapters support branching
**[📖 Complete v5.0 Changes →](../../.strategy/v5.1.0-CHANGES.md)**
---
## Support & Resources
- **📖 Documentation:** [Full Documentation](../)
- **🐛 Issues:** [GitHub Issues](https://github.com/soulcraftlabs/brainy/issues)
- **💬 Discussions:** [GitHub Discussions](https://github.com/soulcraftlabs/brainy/discussions)
- **📦 NPM:** [@soulcraft/brainy](https://www.npmjs.com/package/@soulcraft/brainy)
- **⭐ GitHub:** [Star us](https://github.com/soulcraftlabs/brainy)
---
## See Also
- **[Triple Intelligence Architecture](../architecture/triple-intelligence.md)** - How vector + graph + document work together
- **[VFS Quick Start](../vfs/QUICK_START.md)** - Complete VFS documentation
- **[Import Anything Guide](../guides/import-anything.md)** - CSV, Excel, PDF, URL imports
- **[Cloud Deployment](../deployment/CLOUD_DEPLOYMENT_GUIDE.md)** - Production deployment
- **[Instant Fork](../features/instant-fork.md)** - Git-style branching guide
---
**License:** MIT © Brainy Contributors
---
*Brainy v5.0+ - The Knowledge Operating System*
*From prototype to planet-scale • Zero configuration • Triple Intelligence™ • Git-Style Branching*