brainy/README.md
David Snelling 415e824a1d
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chore: the forge is the address — retire the archived mirror from every live surface
Ruled today: the project's one public home is source.soulcraft.com. The
old public repo is archived history and no longer part of any release.

- package.json repository/homepage/bugs now point at the forge (this is
  what the npm page links as Repository/Homepage/Issues)
- README CI badge reads the forge pipeline; CONTRIBUTING drops the
  mirror paragraph (forge account or email patch were already the ruled
  contribution paths)
- release.sh: mirror push + external release step removed; publishes go
  forge-first (box-held write token, temp userconfig so the token never
  hits argv; a forge-publish failure aborts before the storefront so the
  pair can never diverge), then npmjs with the scope-override pin (the
  fleet npmrc maps @soulcraft to the forge and scope mappings beat
  --registry); release page created via forge API when a token is
  present, loud skip otherwise; changelog compare links point home
- dead external CI workflow removed (.forgejo/workflows/ci.yml is the
  live pipeline)

Historical CHANGELOG links to the archive stay as written - history is
history and the archive serves them read-only.
2026-07-23 11:09:43 -07:00

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<p align="center">
<img src="https://raw.githubusercontent.com/soulcraftlabs/brainy/main/brainy.png" alt="Brainy" width="180">
</p>
<h1 align="center">Brainy</h1>
<p align="center">
<b>Three database paradigms. One API. Zero configuration.</b><br>
The in-process knowledge database for TypeScript — vector search, graph traversal,<br>
and metadata filtering unified in a single query.
</p>
<p align="center">
<a href="https://www.npmjs.com/package/@soulcraft/brainy"><img src="https://img.shields.io/npm/v/@soulcraft/brainy.svg" alt="npm version"></a>
<a href="https://www.npmjs.com/package/@soulcraft/brainy"><img src="https://img.shields.io/npm/dm/@soulcraft/brainy.svg" alt="npm downloads"></a>
<a href="https://source.soulcraft.com/soulcraft/brainy/actions"><img src="https://source.soulcraft.com/soulcraft/brainy/actions/workflows/ci.yml/badge.svg?branch=main" alt="CI"></a>
<a href="https://soulcraft.com/docs"><img src="https://img.shields.io/badge/docs-soulcraft.com-blue.svg" alt="Documentation"></a>
<a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="MIT License"></a>
<a href="https://www.typescriptlang.org/"><img src="https://img.shields.io/badge/%3C%2F%3E-TypeScript-%230074c1.svg" alt="TypeScript"></a>
</p>
<p align="center">
<a href="#quick-start">Quick start</a> ·
<a href="#one-query-three-engines">One query</a> ·
<a href="#feature-tour">Features</a> ·
<a href="#when-you-outgrow-brainy">Scale with Cor</a> ·
<a href="#documentation">Docs</a> ·
<a href="#support--community">Support</a>
</p>
---
Built because we were tired of stitching a vector store to a graph database to a document store — and spending weeks on plumbing before writing a line of business logic. Brainy indexes every fact **three ways at once** and lets one call query them together:
| You write | Brainy indexes it as | You query it with |
|---|---|---|
| `data: 'Ada wrote the first program'` | a **384-dim vector** (local embedding — no API key) | `find({ query: 'computing pioneers' })` |
| `metadata: { field: 'CS', year: 1843 }` | **structured fields** (O(1) exact, O(log n) range) | `find({ where: { year: { lessThan: 1900 } } })` |
| `relate({ from: ada, to: babbage })` | a **typed, directed graph edge** | `find({ connected: { to: babbage, depth: 2 } })` |
It runs **inside your process** — no server, no Docker, nothing to operate — and persists to plain files you can snapshot with a hard link.
**New here?****[What is Brainy? — plain-language overview, no jargon](docs/eli5.md)**
## Quick start
```bash
bun add @soulcraft/brainy # Bun ≥ 1.1 — recommended
npm install @soulcraft/brainy # Node.js ≥ 22
```
```javascript
import { Brainy, NounType, VerbType } from '@soulcraft/brainy'
const brain = new Brainy() // in-memory; one line swaps to disk
await brain.init()
// Text auto-embeds locally; metadata auto-indexes
const react = await brain.add({
data: 'React is a JavaScript library for building user interfaces',
type: NounType.Concept,
subtype: 'library',
metadata: { category: 'frontend', year: 2013 }
})
const next = await brain.add({
data: 'Next.js is a React framework with server-side rendering',
type: NounType.Concept,
subtype: 'framework',
metadata: { category: 'frontend', year: 2016 }
})
await brain.relate({ from: next, to: react, type: VerbType.DependsOn, subtype: 'runtime' })
```
## One query, three engines
```javascript
const results = await brain.find({
query: 'modern frontend frameworks', // vector — what it means
where: { year: { greaterThan: 2015 } }, // metadata — what it is
connected: { to: react, depth: 2 } // graph — what it touches
})
```
Every clause is optional; any combination composes. Under the hood Brainy plans the query across an HNSW vector index, a roaring-bitmap field index, and an adjacency graph index — and re-validates every result against your predicate before returning it, so a corrupt index can never hand you a wrong answer.
## Feature tour
### The database is a value
Pin it, rewind it, fork it. Snapshot isolation without a server.
```javascript
const db = brain.now() // pin current state — O(1)
await brain.transact([ // atomic all-or-nothing, CAS-guarded
{ op: 'update', id: order, metadata: { status: 'paid' } },
{ op: 'relate', from: invoice, to: order, type: VerbType.References, subtype: 'billing' }
], { ifAtGeneration: db.generation })
await db.get(order) // still 'pending' — pinned forever
await brain.get(order) // 'paid' — live
const lastWeek = await brain.asOf(Date.now() - 7 * 86_400_000) // full query surface, past state
const whatIf = await db.with([{ op: 'remove', id: order }]) // speculative — never touches disk
await brain.now().persist('/backups/today') // instant hard-link snapshot
```
**[Consistency model](docs/concepts/consistency-model.md)** · **[Snapshots & time travel](docs/guides/snapshots-and-time-travel.md)**
### Local embeddings — no API keys
Strings embed on-device with a bundled MiniLM model (WASM). Semantic search works offline, in CI, and on air-gapped machines, at zero cost per call. Hybrid keyword + semantic ranking is the default:
```javascript
await brain.find({ query: 'David Smith' }) // auto: text + semantic
await brain.find({ query: 'AI concepts', searchMode: 'semantic' }) // semantic only
```
### A typed graph, not a bag of edges
42 entity types × 127 relationship types form a shared vocabulary for any domain — healthcare (`Patient → diagnoses → Condition`), finance (`Account → transfers → Transaction`), yours. Your own taxonomy layers on with `subtype`, enforced at write time:
```javascript
await brain.add({ data: 'Avery Brooks', type: NounType.Person, subtype: 'employee' })
brain.counts.bySubtype(NounType.Person) // O(1) — { employee: 12, customer: 847 }
brain.requireSubtype(NounType.Person, { values: ['employee', 'customer'], required: true })
```
**[Type system](docs/architecture/noun-verb-taxonomy.md)** · **[Subtypes & facets](docs/guides/subtypes-and-facets.md)**
### Graph analytics built in
```javascript
await brain.graph.rank() // which entities matter most (centrality)
await brain.graph.communities() // natural clusters
await brain.graph.path(a, b) // how two things connect
await brain.graph.subgraph([seed], { depth: 2 }) // bounded neighborhood → { nodes, edges }
await brain.graph.export() // whole graph, one O(N+E) streaming pass
```
### Write-time aggregations
`SUM` / `COUNT` / `AVG` / `MIN` / `MAX` with `GROUP BY` and time windows, maintained incrementally on every write — reads are O(1) lookups, not scans. **[Aggregation guide](docs/guides/aggregation.md)**
### Import anything
```javascript
await brain.import('customers.csv')
await brain.import('sales.xlsx') // every sheet
await brain.import('research-paper.pdf') // tables extracted
await brain.import('https://api.example.com/data.json')
```
Entities auto-classify on the way in; `brain.extractEntities(text)` exposes the same NER ensemble directly. **[Import guide](docs/guides/import-anything.md)**
### A filesystem that understands content
```javascript
await brain.vfs.writeFile('/docs/readme.md', 'Project documentation')
await brain.vfs.search('React components with hooks') // semantic file search
```
**[VFS quick start](docs/vfs/QUICK_START.md)**
### Operations-grade by default
- **Single-writer, many-reader** — an exclusive lock protects the data directory; `Brainy.openReadOnly()` and the `brainy inspect` CLI examine a live brain from another process, safely.
- **Self-upgrading data files** — a 7.x brain opens under 8.x and migrates itself behind an observable lock (`getIndexStatus().migration`), with an automatic pre-upgrade backup. No migration scripts.
- **No silent wrong answers** — cold-open guards self-heal or throw typed errors (`MetadataIndexNotReadyError`, `GraphIndexNotReadyError`); they never return `[]` for data that exists.
**[Multi-process model](docs/concepts/multi-process.md)** · **[Inspection guide](docs/guides/inspection.md)**
## When you outgrow Brainy
Brainy's pure-TypeScript engines carry real workloads a long way on their own — see the measured, per-operation numbers (not marketing figures) in **[docs/performance-envelopes.md](docs/performance-envelopes.md)** for what to expect, unaccelerated, on plain filesystem storage.
When a deployment needs native-scale vector/graph performance — memory-mapped indexes that don't need your dataset in RAM, billion-scale ambitions — add the native engine. **The API doesn't change:**
```bash
npm install @soulcraft/cor
```
```javascript
const brain = new Brainy({ storage: { type: 'filesystem', path: './data' } })
await brain.init() // @soulcraft/cor detected — same code, native engines underneath
```
Installing the package is the opt-in: if `@soulcraft/cor` is present, it loads and announces itself in the init log; if it's present but broken, `init()` **throws** — an installed accelerator never silently vanishes behind the JS engines. Opt out with `plugins: []`, or pin exactly what loads with `plugins: ['@soulcraft/cor']`. [`@soulcraft/cor`](https://www.npmjs.com/package/@soulcraft/cor) (Brainy 8.x ↔ Cor 3.x, version-matched) registers Rust implementations behind every provider seam: SIMD distance kernels, memory-mapped storage, a disk-native vector index that doesn't need your dataset in RAM, durable LSM field/graph indexes that serve cold opens instantly, and native aggregation. Recall@10 measured **0.99 / 0.96 / 0.96 at 1M / 10M / 100M vectors** in Cor's release gate.
Open core, commercial accelerator: Brainy is MIT and complete on its own — Cor is more headroom for when you need it, not capability held back to sell you later. Licensing and support: **cor@soulcraft.com**.
## Performance
- Per-operation p50/p95 at 1k and 10k entities, pure-JS floor, measured and re-run every release that touches a measured path: **[docs/performance-envelopes.md](docs/performance-envelopes.md)**.
- JS distance kernels: **~6× faster cosine, ~1.4× euclidean** than 7.x (measured: [`tests/benchmarks/distance-microbench.mjs`](tests/benchmarks/distance-microbench.mjs), 384-dim, median of 41).
- Whole-graph reads are single **O(N + E)** cursor walks — a consumer-measured 19k-edge export dropped from ~27 s of per-node calls to one scan.
- Capacity planning and architecture: **[docs/PERFORMANCE.md](docs/PERFORMANCE.md)** · **[docs/SCALING.md](docs/SCALING.md)**
## Use cases
**AI agent memory** — persistent semantic recall with relationship tracking · **Knowledge bases** — auto-linking and meaning-aware navigation · **Semantic search** over codebases, documents, media · **Enterprise data** — CRM, catalogs, institutional memory · **Games & simulations** — worlds and characters that remember.
## Documentation
| Start | Core | Going deeper |
|---|---|---|
| [Brainy explained simply](docs/eli5.md) | [API reference](docs/api/README.md) | [Architecture overview](docs/architecture/overview.md) |
| [Installation](docs/guides/installation.md) | [Data model](docs/DATA_MODEL.md) | [Consistency model](docs/concepts/consistency-model.md) |
| [Natural-language queries](docs/guides/natural-language.md) | [Query operators](docs/QUERY_OPERATORS.md) | [Multi-process model](docs/concepts/multi-process.md) |
| | [Find system](docs/FIND_SYSTEM.md) | [Scaling](docs/SCALING.md) |
## Requirements
**Bun ≥ 1.1** (recommended) or **Node.js ≥ 22**. Brainy 8.x is server-only; the 7.x line remains on npm for browser use.
## Support & community
- **Bugs and ideas** → **brainy@soulcraft.com** — no account needed, you'll get a receipt.
- **Security reports** → **security@soulcraft.com** — see **[SECURITY.md](SECURITY.md)**.
- **Contributing** → see **[CONTRIBUTING.md](CONTRIBUTING.md)**.
MIT © Brainy Contributors.