David Snelling
0ddc05a5bb
- Store data opaquely in add() and update() instead of spreading object properties into top-level metadata. data is for semantic search (HNSW), metadata is for structured where-filter queries (MetadataIndex). - Fix numeric range queries in MetadataIndex — use numeric-aware comparison instead of lexicographic string comparison for normalized values. - Add data field to RelateParams and Relation types for relationship content. - Add where.type → where.noun alias in metadata-only find() path. - Rewrite README: focused ~350 lines from 791, quick start first, feature showcase with mini-snippets, organized doc links, no version callouts. - Add DATA_MODEL.md and QUERY_OPERATORS.md reference docs. - Remove 10 outdated/redundant doc files consolidated into API reference. - Improve JSDoc on Entity, Relation, AddParams, FindParams, and core methods. - Fix tests asserting data properties appear in metadata (data model violation). - Deprecate verb.source/target in favor of from/to (public) and sourceId/targetId (storage).
4.9 KiB
4.9 KiB
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.