Implement comprehensive conversation management system enabling AI agents like Claude Code to maintain infinite context and history. Provides semantic search, smart context retrieval, and automatic artifact linking using Brainy's existing Triple Intelligence infrastructure. Core Features: - ConversationManager API for message storage and retrieval - MCP protocol integration with 6 tools for Claude Code - Context ranking using semantic, temporal, and graph scoring - Neural clustering for theme discovery and deduplication - Virtual filesystem integration for code artifact linking - CLI commands for setup and management Zero new infrastructure required - uses existing Brainy features: - Storage via brain.add() with NounType.Message - Relationships via brain.relate() with VerbType.Precedes - Search via brain.find() with Triple Intelligence - Clustering via brain.neural() - Artifacts via brain.vfs() One-command setup: brainy conversation setup Version: 3.19.0 |
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| .. | ||
| api | ||
| architecture | ||
| augmentations | ||
| conversation | ||
| deployment | ||
| features | ||
| guides | ||
| vfs | ||
| API_DECISION_TREE.md | ||
| API_REFERENCE.md | ||
| CORE_API_PATTERNS.md | ||
| CREATING-AUGMENTATIONS.md | ||
| EXTENDING_STORAGE.md | ||
| FIND_SYSTEM.md | ||
| METADATA_CONTRACT_IMPLEMENTATION.md | ||
| MODEL_LOADING_QUICK_REFERENCE.md | ||
| NEURAL_API_PATTERNS.md | ||
| PERFORMANCE.md | ||
| QUICK-START.md | ||
| README.md | ||
| RELEASE-GUIDE.md | ||
| SCALING.md | ||
| troubleshooting.md | ||
| universal-display-augmentation.md | ||
| VALIDATION.md | ||
| ZERO_CONFIG.md | ||
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
Quick Links
Getting Started
- Quick Start Guide - Get up and running in minutes
- Enterprise for Everyone - No limits, no tiers, everything free
- Natural Language Queries - Query with plain English
Core Concepts
- Zero Configuration - Auto-adapts to any environment
- Noun-Verb Taxonomy - Revolutionary data model
- Triple Intelligence - Unified query system
- Architecture Overview - System design
API Documentation
- API Reference - Complete API documentation
- TypeScript Types - Type definitions
Advanced Topics
- Augmentations System - Enterprise plugins & neural import
- Storage Architecture - Storage adapter system
- Performance Tuning - Optimization guide
- Migration Guide - Upgrading from 1.x
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.add("Revolutionary AI Breakthrough", {
type: "article",
category: "technology",
rating: 4.8
})
const authorId = await brain.add("Dr. Sarah Chen", {
type: "person",
role: "researcher"
})
// Create relationships (verbs)
await brain.relate(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
- GitHub: github.com/brainy-org/brainy
- Issues: Report bugs or request features
- Discussions: Join the conversation
License
Brainy is MIT licensed. See LICENSE for details.