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VisionFlow Documentation
Complete documentation for VisionFlow - enterprise-grade multi-agent knowledge graphing
reference
2026-02-11

VisionFlow Documentation

Enterprise-grade multi-agent knowledge graphing with 3D visualization, semantic reasoning, and GPU-accelerated physics. This documentation follows the Diataxis framework for maximum discoverability.

Quick Start

Get running in 5 minutes:

  1. Installation - Docker or native setup
  2. First Graph - Create your first visualization
  3. Navigation Guide - Master the 3D interface

Documentation by Role

New Users - Getting started with VisionFlow

Your Learning Path

Step Document Time
1 What is VisionFlow? 10 min
2 Installation 15 min
3 First Graph 20 min
4 Navigation Guide 15 min
5 Configuration 10 min

Next Steps

Developers - Building and extending VisionFlow

Onboarding Path

Priority Document Focus
High Developer Journey Codebase learning path
High Development Setup IDE and environment
High Project Structure Code organisation
Medium Architecture Overview System design
Medium Adding Features Development workflow
Standard Testing Guide Unit, integration, E2E

By Technology

API Reference

Architects - System design and patterns

Architecture Path

Document Focus
Architecture Overview Complete system architecture
Technology Choices Stack rationale
System Overview Architectural blueprint
Hexagonal CQRS Ports and adapters
Data Flow End-to-end pipeline
Integration Patterns System integration

Deep Dives

Hexagonal Architecture Ports

Operators - Deployment and operations

Operations Path

Document Purpose
Deployment Guide Production deployment
Docker Compose Container orchestration
Operator Runbook Operations playbook
Configuration Environment variables
Security Authentication and secrets
Telemetry Observability

Infrastructure

Data Operations

Documentation Structure

graph TB
    subgraph Entry["Entry Points"]
        README["README.md"]
        OVERVIEW["getting-started/overview.md"]
    end

    subgraph Learning["Learning (Tutorials)"]
        T1["Installation"]
        T2["First Graph"]
        T3["Neo4j Quick Start"]
    end

    subgraph Tasks["Task-Oriented (Guides)"]
        G1["Features"]
        G2["Developer"]
        G3["Infrastructure"]
        G4["Operations"]
    end

    subgraph Understanding["Understanding (Explanations)"]
        E1["Architecture"]
        E2["Ontology"]
        E3["Physics"]
    end

    subgraph Lookup["Lookup (Reference)"]
        R1["API"]
        R2["Database"]
        R3["Protocols"]
    end

    README --> Learning
    README --> Tasks
    README --> Understanding
    README --> Lookup
    OVERVIEW --> Learning

    Learning --> Tasks
    Tasks --> Understanding
    Understanding --> Lookup

    style README fill:#4A90E2,color:#fff
    style Learning fill:#7ED321,color:#fff
    style Tasks fill:#F5A623,color:#000
    style Understanding fill:#BD10E0,color:#fff
    style Lookup fill:#9013FE,color:#fff
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Quick Links

Task Document
Install VisionFlow Installation
Create first graph First Graph
Deploy AI agents Agent Orchestration
Query Neo4j Neo4j Integration
Add a feature Adding Features
Set up XR/VR Vircadia XR Guide
Understand architecture Architecture Overview
Learn the codebase Developer Journey
Deploy to production Deployment Guide
Configure environment Configuration
Fix issues Troubleshooting
Write tests Testing Guide
Use REST API REST API
Use WebSocket API WebSocket API
Optimise performance GPU Optimisations
Secure the app Security Guide

Documentation Categories

Tutorials (Learning-Oriented)

Step-by-step lessons for beginners.

Tutorial Time Description
Installation 10 min Docker and native setup
First Graph 15 min Create your first visualisation
Neo4j Quick Start 20 min Query the graph database

Concepts (Understanding-Oriented)

Core mental models and foundational knowledge.

Concept Description
Core Concepts Overview of VisionFlow mental models
Physics Engine Force-directed graph simulation
Actor Model Concurrent actor-based patterns
Hexagonal Architecture Ports and adapters design

Guides (Task-Oriented)

Practical instructions for specific goals.

Core Features (8 guides)
AI Agent System (6 guides)
Developer Guides (8 guides)
Infrastructure and Operations (15 guides)

Explanations (Understanding-Oriented)

Deep dives into architecture and design.

System Architecture (20+ documents)
GPU and Physics (8 documents)
Ontology and Reasoning (11 documents)

Reference (Information-Oriented)

Technical specifications and APIs.

API Documentation (8 references)
Database and Protocols (6 references)
System Status (5 references)

Getting Help

Issue Type Resource
Documentation gaps GitHub Issues with documentation label
Technical problems Troubleshooting Guide
Infrastructure issues Infrastructure Troubleshooting
Developer setup Development Setup
Feature requests GitHub Discussions

Documentation Stats

Category Count
Tutorials 5
How-To Guides 81
Explanation 72
Reference 46
Other (diagrams, research) 38
Total 242 markdown files
  • Framework: Diataxis (Tutorials, How-To, Explanation, Reference)
  • Last Updated: 2026-02-11
  • Verified: Links checked, Mermaid diagrams validated

Maintained by DreamLab AI Documentation Team