brainy/docs
David Snelling ef8f35ec2a FINAL: Correct API documentation after comprehensive audit
Key findings from audit:
- Code implementation is CORRECT (uses greaterThan, lessThan, etc.)
- Only documentation showed wrong MongoDB-style operators
- Neural API is complete and functional
- All features preserved, just better organized

This commit establishes the final, correct API documentation.
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architecture CHECKPOINT: Brainy 2.0 API refactor - pre-fixes state 2025-08-25 09:52:32 -07:00
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Brainy Documentation

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

📊 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 { BrainyData } from 'brainy'

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

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

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

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

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

Documentation Structure

docs/
├── README.md                    # This file
├── guides/                      # User guides
│   ├── getting-started.md      # Quick start guide
│   ├── natural-language.md     # NLP query guide
│   └── performance.md          # Performance tuning
├── architecture/               # Technical architecture
│   ├── overview.md            # System overview
│   ├── noun-verb-taxonomy.md  # Data model
│   ├── triple-intelligence.md # Query system
│   └── storage.md             # Storage layer
└── api/                       # API documentation
    ├── README.md              # API overview
    ├── brainy-data.md        # Main class
    └── types.md              # TypeScript types

Community

License

Brainy is MIT licensed. See LICENSE for details.