brainy/docs
David Snelling f019ac241e docs: complete Stage 3 CANONICAL taxonomy documentation (v5.5.0)
Added comprehensive documentation for Stage 3 taxonomy migration:

API Documentation Updates:
- Updated version header from v5.4.0 to v5.5.0
- Fixed all deprecated NounType.Content examples → Document, Concept
- Added versions.asOf() method documentation with examples
- Added comprehensive Type System Reference section

Type System Reference:
- Documented all 42 noun types organized by category
- Documented 127 verb types organized by functional groups
- Added migration guide from v5.4.0 (deprecated types)
- Breaking changes: User→Person, Topic→Concept, Content→Document
- Stage 3 adds +11 nouns, +87 verbs (169 total types)

Build Status:
-  TypeScript build passes with zero errors (stale cache issue resolved)
-  All Stage 2 references updated to Stage 3 CANONICAL
-  Type embeddings current (42 nouns + 127 verbs = 338KB)

Tested with confidential Tales from Talifar Glossary (NOT in repo):
- Successfully imported 2,284 entities across 7 noun types
- Created 2,280 relationships (contains verb)
- Noun type distribution: document (50%), thing (16%), person (16%),
  location (9%), concept (9%), collection (1%), file (<1%)
- Demonstrates Stage 3 taxonomy handles rich fantasy world data

Type System Coverage:
- 7/42 noun types used (16.7%) - appropriate for glossary domain
- 1/127 verb types used (0.8%) - opportunity for richer relationships

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

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-06 10:28:47 -08:00
..
api docs: complete Stage 3 CANONICAL taxonomy documentation (v5.5.0) 2025-11-06 10:28:47 -08:00
architecture fix: update all Stage 2 references to Stage 3 CANONICAL type counts 2025-11-06 09:40:33 -08:00
augmentations feat: add ImageHandler with EXIF extraction and comprehensive MIME detection (v5.2.0) 2025-11-03 14:06:17 -08:00
deployment chore(release): 4.0.0 2025-10-17 14:48:34 -07:00
features feat: implement complete v5.0.0 Git-style fork/merge/commit workflow 2025-11-01 11:56:11 -07:00
guides fix: update all Stage 2 references to Stage 3 CANONICAL type counts 2025-11-06 09:40:33 -08:00
operations chore(release): 4.0.0 2025-10-17 14:48:34 -07:00
vfs fix: update all Stage 2 references to Stage 3 CANONICAL type counts 2025-11-06 09:40:33 -08:00
api-returns.md fix: metadata batch reading from correct directory 2025-10-06 15:43:45 -07:00
API_DECISION_TREE.md feat: add neural extraction APIs with NounType taxonomy 2025-09-29 13:51:47 -07:00
API_REFERENCE.md feat: add confidence/weight to Entity and flatten Result fields for convenient access 2025-10-23 12:19:50 -07:00
CORE_API_PATTERNS.md fix: update all imports and references from BrainyData to Brainy 2025-09-30 17:09:15 -07:00
CREATING-AUGMENTATIONS.md feat(v4.0.0): Complete metadata/vector separation architecture with Azure support 2025-10-17 12:29:27 -07:00
DEVELOPER_LEARNING_PATH.md feat: comprehensive import progress tracking for all 7 formats 2025-10-24 14:45:46 -07:00
EXTENDING_STORAGE.md fix: update all imports and references from BrainyData to Brainy 2025-09-30 17:09:15 -07:00
FIND_SYSTEM.md fix: update all Stage 2 references to Stage 3 CANONICAL type counts 2025-11-06 09:40:33 -08:00
METADATA_CONTRACT_IMPLEMENTATION.md fix: update all imports and references from BrainyData to Brainy 2025-09-30 17:09:15 -07:00
MIGRATION-V3-TO-V4.md chore(release): 4.0.0 2025-10-17 14:48:34 -07:00
MODEL_LOADING_QUICK_REFERENCE.md fix: update all imports and references from BrainyData to Brainy 2025-09-30 17:09:15 -07:00
NEURAL_API_PATTERNS.md fix: update all imports and references from BrainyData to Brainy 2025-09-30 17:09:15 -07:00
PERFORMANCE.md fix: update all Stage 2 references to Stage 3 CANONICAL type counts 2025-11-06 09:40:33 -08:00
README.md feat: v5.1.0 - VFS auto-initialization and complete API documentation 2025-11-02 10:58:52 -08:00
RELEASE-GUIDE.md feat: Brainy 3.0 - Production-ready Triple Intelligence database 2025-09-11 16:23:32 -07:00
SCALING.md docs: add comprehensive scaling and storage architecture documentation 2025-09-08 14:49:25 -07:00
STAGE3-CANONICAL-TAXONOMY.md feat: Stage 3 CANONICAL taxonomy with 169 types (v5.5.0) 2025-11-06 09:02:23 -08:00
troubleshooting.md feat: implement always-adaptive caching with getCacheStats monitoring 2025-10-10 14:09:30 -07:00
universal-display-augmentation.md fix: update all imports and references from BrainyData to Brainy 2025-09-30 17:09:15 -07:00
VALIDATION.md feat: add comprehensive zero-config validation system 2025-09-12 14:37:39 -07:00
ZERO_CONFIG.md feat: implement always-adaptive caching with getCacheStats monitoring 2025-10-10 14:09:30 -07:00

Brainy Documentation (v4.0.0)

Welcome to the comprehensive documentation for Brainy, the multi-dimensional AI database with Triple Intelligence Engine.

🆕 What's New in v4.0.0

Production-Ready Cost Optimization:

  • Lifecycle Management: Automatic tier transitions for S3, GCS, Azure (96% cost savings!)
  • Intelligent-Tiering: S3 Intelligent-Tiering and GCS Autoclass support
  • Batch Operations: Efficient bulk delete operations (1000 objects per request)
  • Compression: Gzip compression for FileSystem storage (60-80% space savings)
  • Quota Monitoring: Real-time OPFS quota tracking for browser apps
  • Tier Management: Azure Hot/Cool/Archive tier management

Cost Impact Example (500TB dataset):

  • Before: $138,000/year
  • After v4.0.0: $5,940/year
  • Savings: $132,060/year (96%)

📊 Implementation Status

  • Production Ready: Core features working today
  • 🚧 In Development: Features coming soon
  • 📅 Roadmap: See ROADMAP.md

Getting Started

Core Concepts

API Documentation

Advanced Topics

What is Brainy?

Brainy is a next-generation AI database that combines:

  • Vector Search: Semantic similarity using HNSW indexing
  • Graph Relationships: Complex relationship mapping and traversal
  • Field Filtering: Precise metadata filtering with O(1) lookups
  • Natural Language: Query in plain English

Key Features

🧠 Triple Intelligence Engine

All three intelligence types (vector, graph, field) work together in every query for optimal results.

📝 Noun-Verb Taxonomy

Model your data naturally as entities (nouns) and relationships (verbs) - no complex schemas needed.

🌍 Natural Language Queries

Ask questions in plain English and Brainy understands your intent:

await brain.find("recent articles about AI with high ratings")

Production Ready

  • Universal storage (FileSystem, S3, OPFS, Memory)
  • Zero configuration with intelligent defaults
  • Full TypeScript support
  • Cross-platform compatibility

Quick Example

import { Brainy } from 'brainy'

// Initialize
const brain = new Brainy()
await brain.init()

// Add entities (nouns)
const articleId = await brain.add("Revolutionary AI Breakthrough", {
  type: "article",
  category: "technology",
  rating: 4.8
})

const authorId = await brain.add("Dr. Sarah Chen", {
  type: "person",
  role: "researcher"
})

// Create relationships (verbs)
await brain.relate(authorId, articleId, "authored", {
  date: "2024-01-15",
  contribution: "primary"
})

// Query naturally
const results = await brain.find("highly rated technology articles by researchers")

📚 Complete Documentation Index

🚀 Quick Start Guides

Document Description
API Reference START HERE - Complete API documentation with examples
VFS Quick Start Virtual filesystem in 30 seconds

🆕 v4.0.0 Migration & Optimization

Document Description
v3→v4 Migration Guide NEW - Upgrade guide with zero breaking changes
AWS S3 Cost Optimization NEW - 96% cost savings with lifecycle policies
GCS Cost Optimization NEW - 94% savings with Autoclass
Azure Cost Optimization NEW - 95% savings with tier management
Cloudflare R2 Cost Guide NEW - Zero egress fees + S3-compatible API

🎯 Core Concepts

Document Description
Architecture Overview High-level system design and components
Noun-Verb Taxonomy Revolutionary data model - entities and relationships
Triple Intelligence Vector + Graph + Field unified query system
Zero Configuration Auto-adapts to any environment
Storage Architecture v4.0.0 - Storage adapters and optimization
Data Storage Architecture v4.0.0 - Metadata/vector separation, sharding
Index Architecture HNSW, Graph, and Metadata indexing

💾 Storage & Deployment

Document Description
Cloud Deployment Guide v4.0.0 - Deploy on AWS, GCP, Azure, Cloudflare
AWS Deployment AWS-specific deployment patterns
GCP Deployment Google Cloud deployment
Kubernetes Deployment K8s deployment configurations
Distributed Storage Multi-node storage coordination
Extending Storage Create custom storage adapters
Capacity Planning Scale to millions of entities

📊 API Documentation

Document Description
API Reference Complete API documentation
Comprehensive API Overview All APIs with examples
API Decision Tree Choose the right API for your use case
Core API Patterns Common patterns and best practices
Neural API Patterns AI-powered query patterns
Find System Natural language find() API
API Surface Design API design principles
API Returns Return types and structures

🔧 Framework Integration

Document Description
Framework Integration Guide React, Vue, Angular, Svelte, etc.
Next.js Integration Server-side rendering with Brainy
Vue.js Integration Vue 3 integration patterns

📁 Virtual Filesystem (VFS)

Document Description
VFS Core Documentation Core VFS concepts and architecture
Semantic VFS Guide Semantic filesystem projections
VFS API Guide Complete VFS API reference
Neural Extraction AI-powered file analysis
Common Patterns VFS usage patterns
User Functions Custom VFS functions
VFS Graph Types Graph-based VFS projections
VFS Examples & Scenarios Real-world VFS examples
VFS Initialization Setup and configuration
Projection Strategy API Custom projection strategies
Building File Explorers Build custom file browsers
VFS Troubleshooting Common issues and solutions

🧠 Advanced Topics

Document Description
Natural Language Queries Query in plain English
Neural API AI-powered features
Import Anything Import data from any source
Distributed Systems Multi-node deployments
Model Loading Load and manage AI models
Model Loading Quick Reference Model loading cheat sheet
Enterprise for Everyone No paywalls, no tiers

🔌 Augmentations (Plugins)

Document Description
Creating Augmentations Build custom plugins
Augmentations Complete Reference Full augmentation API
Augmentations Developer Guide Plugin development guide
Augmentation Configuration Configure augmentations
Augmentation System System architecture
Augmentation System Audit Actual vs planned features
Augmentations Actual Currently implemented augmentations
API Server Augmentation REST API server plugin

Performance & Scaling

Document Description
Performance Guide Optimization techniques
Performance Analysis Benchmarks and analysis
Scaling Guide Scale to billions of entities
Clustering Algorithms Analysis HNSW algorithm details
Initialization & Rebuild Index management

📋 Reference

Document Description
Complete Feature List All Brainy features
v3 Features v3.x feature list
Metadata Architecture Metadata namespacing
Metadata Contract Implementation Metadata API contracts
Finite Type System Type-safe noun/verb taxonomy
Validation Data validation rules
Universal Display Augmentation Display system

🛠️ Development

Document Description
Troubleshooting Common issues and solutions
Release Guide How to release new versions

🔍 Internal Documentation

Document Description
Audit Report Feature audit
Cleanup Summary Codebase cleanup notes
Honest Status Actual implementation status

Documentation Structure

docs/
├── README.md (this file)          # Complete documentation index
├── MIGRATION-V3-TO-V4.md          # v4.0.0 migration guide
│
├── guides/                        # User guides
│   ├── natural-language.md
│   ├── neural-api.md
│   ├── import-anything.md
│   ├── framework-integration.md
│   ├── nextjs-integration.md
│   ├── vue-integration.md
│   ├── distributed-system.md
│   ├── model-loading.md
│   └── enterprise-for-everyone.md
│
├── architecture/                  # System architecture
│   ├── overview.md
│   ├── noun-verb-taxonomy.md
│   ├── triple-intelligence.md
│   ├── zero-config.md
│   ├── storage-architecture.md    # v4.0.0
│   ├── data-storage-architecture.md # v4.0.0
│   ├── index-architecture.md
│   ├── distributed-storage.md
│   ├── augmentations.md
│   ├── augmentation-system-audit.md
│   ├── augmentations-actual.md
│   ├── finite-type-system.md
│   └── ...
│
├── operations/                    # Operations guides
│   ├── cost-optimization-aws-s3.md       # v4.0.0
│   ├── cost-optimization-gcs.md          # v4.0.0
│   ├── cost-optimization-azure.md        # v4.0.0
│   ├── cost-optimization-cloudflare-r2.md # v4.0.0
│   └── capacity-planning.md
│
├── deployment/                    # Deployment guides
│   ├── CLOUD_DEPLOYMENT_GUIDE.md  # v4.0.0
│   ├── aws-deployment.md
│   ├── gcp-deployment.md
│   └── kubernetes-deployment.md
│
├── vfs/                          # Virtual Filesystem docs
│   ├── QUICK_START.md
│   ├── VFS_CORE.md
│   ├── SEMANTIC_VFS.md
│   ├── VFS_API_GUIDE.md
│   ├── NEURAL_EXTRACTION.md
│   ├── COMMON_PATTERNS.md
│   └── ...
│
├── api/                          # API documentation
│   ├── README.md
│   └── COMPREHENSIVE_API_OVERVIEW.md
│
├── augmentations/                # Augmentation docs
│   ├── COMPLETE-REFERENCE.md
│   ├── DEVELOPER-GUIDE.md
│   ├── CONFIGURATION.md
│   └── api-server.md
│
├── features/                     # Feature documentation
│   ├── complete-feature-list.md
│   └── v3-features.md
│
└── internal/                     # Internal docs
    ├── AUDIT_REPORT.md
    ├── CLEANUP_SUMMARY.md
    └── HONEST_STATUS.md

Community

License

Brainy is MIT licensed. See LICENSE for details.