David Snelling 40d2cd5419 docs(8.0): correct public docs to the real 8.0 API + honest perf claims

The GA-readiness audit found the public docs had drifted from the shipped
surface and presented uncited performance numbers as measured fact.

- quick-start: `FindResult`→`Result`, `VerbType.BuiltOn`→`DependsOn` (the
  canonical getting-started example now compiles).
- noun-verb-taxonomy: rewrote every sample off removed/fictional APIs
  (`augment`/`connectModel`/`getVerbs`/two-arg `add`/`like`/`$gte`) onto the
  real single-object `add`/`find`/`relate`/`related`; replaced the stale
  31-noun/40-verb catalogs with accurate, complete tables (42 nouns, 127 verbs).
- triple-intelligence: `like:`→`query:`, dollar-operators→bare operators, and
  several other fictional keys swept to the real `FindParams`.
- FIND_SYSTEM / PERFORMANCE / index-architecture / BATCHING: replaced
  fabricated, mutually-inconsistent latency tables and uncited speedup
  multipliers with Big-O characterizations, qualitative mechanism descriptions,
  and the one genuinely-measured benchmark (graph O(1) neighbor lookup), per the
  evidence-based-claims rule.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

2026-06-29 10:03:02 -07:00

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Quick Start

Get Brainy running in under a minute.

1. Install

npm install @soulcraft/brainy

2. Initialize

import { Brainy, NounType, VerbType } from '@soulcraft/brainy'

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

That's it. Brainy auto-configures storage, loads the embedding model, and builds the indexes.

3. Add Knowledge

// Text is automatically embedded into 384-dim vectors
const reactId: string = await brain.add({
  data: 'React is a JavaScript library for building user interfaces',
  type: NounType.Concept,
  subtype: 'library',                                  // Sub-classification within Concept
  metadata: { category: 'frontend', year: 2013 }
})

const nextId: string = await brain.add({
  data: 'Next.js framework for React with server-side rendering',
  type: NounType.Concept,
  subtype: 'framework',
  metadata: { category: 'framework', year: 2016 }
})

type is one of Brainy's 42 stable NounTypes. subtype is your free-form sub-classification within that type — flat string, no hierarchy, indexed on the fast path. See Subtypes & Facets for the full guide.

4. Create Relationships

// Typed graph relationships
await brain.relate({
  from: nextId,
  to: reactId,
  type: VerbType.DependsOn
})

5. Query with Triple Intelligence

import type { Result } from '@soulcraft/brainy'

// All three search paradigms in one call
const results: Result[] = await brain.find({
  query: 'modern frontend frameworks',    // Vector similarity search
  where: { year: { greaterThan: 2015 } }, // Metadata filtering
  connected: { to: reactId, depth: 2 }   // Graph traversal
})

console.log(results[0].data)   // 'Next.js framework for React...'
console.log(results[0].score)  // 0.94

What Just Happened

Every entity you add() lives in three indexes simultaneously:

Index	What it stores	Query with
Vector	384-dim embedding of `data`	`find({ query: '...' })`
Metadata	All `metadata` fields	`find({ where: { ... } })`
Graph	Typed relationships from `relate()`	`find({ connected: { ... } })`

find() queries all three in parallel and fuses the results.

Natural Language Queries

Brainy understands 220+ natural language patterns:

// These all work without any configuration
await brain.find({ query: 'recent documents about machine learning' })
await brain.find({ query: 'articles created this week' })
await brain.find({ query: 'people who work at Anthropic' })

Next Steps

Triple Intelligence — understand how the query engine works
The Find System — advanced queries, operators, and graph traversal
API Reference — complete method documentation
Storage Adapters — filesystem, memory

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