David Snelling
c2e21b7b3c
- groupBy now supports { field, unnest: true }: an entity contributes once per
distinct element of an array field (tag frequency / faceted counts). Duplicate
elements on one entity count once; an empty/missing array joins no group. The
incremental add/update/delete paths fan out across the unnested groups.
- extractEntities/extractConcepts batch-embed the unique candidate spans in one
embedBatch call instead of one embed() per candidate (N sequential model calls);
falls back to per-candidate embedding if the batch fails. No behavior change.
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| .. | ||
| api | ||
| architecture | ||
| augmentations | ||
| concepts | ||
| deployment | ||
| features | ||
| guides | ||
| operations | ||
| vfs | ||
| BATCHING.md | ||
| CREATING-AUGMENTATIONS.md | ||
| DATA_MODEL.md | ||
| DEVELOPER_LEARNING_PATH.md | ||
| eli5.md | ||
| EXTENDING_STORAGE.md | ||
| FIND_SYSTEM.md | ||
| MIGRATION-V3-TO-V4.md | ||
| neural-extraction.md | ||
| PERFORMANCE.md | ||
| PLUGINS.md | ||
| PRODUCTION_SERVICE_ARCHITECTURE.md | ||
| QUERY_OPERATORS.md | ||
| README.md | ||
| RELEASE-GUIDE.md | ||
| SCALING.md | ||
| STAGE3-CANONICAL-TAXONOMY.md | ||
| transactions.md | ||
| troubleshooting.md | ||
| universal-display-augmentation.md | ||
Brainy Documentation
The multi-dimensional AI database with Triple Intelligence — vector search, graph traversal, and metadata filtering in one unified API.
Quick Start
import { Brainy, NounType, VerbType } from '@soulcraft/brainy'
const brain = new Brainy()
await brain.init()
// Add entities — data is embedded for semantic search, metadata is indexed for filtering
const id = await brain.add({
data: 'Revolutionary AI Breakthrough',
type: NounType.Document,
metadata: { category: 'technology', rating: 4.8 }
})
// Search with Triple Intelligence
const results = await brain.find({
query: 'artificial intelligence', // Semantic search (on data)
where: { rating: { greaterThan: 4.0 } }, // Metadata filter
connected: { from: authorId, depth: 2 } // Graph traversal
})
Core Documentation
| Document | Description |
|---|---|
| API Reference | Complete API documentation — start here |
| Data Model | Entity structure, data vs metadata, storage fields |
| Query Operators | All BFO operators with examples and indexed/in-memory matrix |
| Find System | Natural language find() and hybrid search details |
Architecture
| Document | Description |
|---|---|
| Architecture Overview | High-level system design |
| Triple Intelligence | Vector + Graph + Metadata unified query |
| Noun-Verb Taxonomy | 42 nouns + 127 verbs type system |
| Stage 3 Canonical Taxonomy | Complete type reference |
| Storage Architecture | Storage adapters and optimization |
| Index Architecture | HNSW, Graph, and Metadata indexing |
| Zero Configuration | Auto-adapts to any environment |
Virtual Filesystem (VFS)
| Document | Description |
|---|---|
| VFS Quick Start | Get started in 30 seconds |
| VFS Core | Core concepts and architecture |
| VFS API Guide | Complete VFS API reference |
| Common Patterns | VFS usage patterns |
See vfs/ for the complete VFS documentation set.
Guides
| Document | Description |
|---|---|
| Import Anything | CSV, Excel, PDF, URL imports |
| Natural Language | Query in plain English |
| Neural API | AI-powered features |
| Enterprise for Everyone | No limits, no tiers |
| Framework Integration | React, Vue, Angular, Svelte |
Storage & Deployment
| Document | Description |
|---|---|
| Cloud Deployment | Deploy on AWS, GCP, Azure, Cloudflare |
| Extending Storage | Create custom storage adapters |
| AWS S3 Cost Optimization | 96% cost savings |
| GCS Cost Optimization | 94% savings with Autoclass |
| Azure Cost Optimization | 95% savings |
| R2 Cost Optimization | Zero egress fees |
| Capacity Planning | Scale to millions of entities |
Plugins & Augmentations
| Document | Description |
|---|---|
| Plugins | Plugin system overview |
| Creating Augmentations | Build custom plugins |
| Augmentations Reference | Full augmentation API |
| Augmentations Developer Guide | Plugin development guide |
Performance & Scaling
| Document | Description |
|---|---|
| Performance | Optimization techniques |
| Scaling | Scale to billions of entities |
| Batching | Batch operations guide |
Migration & Reference
| Document | Description |
|---|---|
| v3 to v4 Migration | Upgrade guide |
| Release Guide | How to release new versions |
| Production Architecture | Ops reference |
Internal
| Document | Description |
|---|---|
| Audit Report | Feature audit |
| Honest Status | Actual implementation status |
License
Brainy is MIT licensed. See LICENSE for details.