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README.md

title Tutorials
description A guided learning path that takes you from understanding VisionClaw to running it, building your first 3D knowledge graph, and promoting a note into the formal ontology.
category tutorial
difficulty-level beginner

Tutorials

VisionClaw Docs · Tutorials

These four tutorials form a single learning path. Work through them in order: each one assumes what the previous one taught. You start by understanding what VisionClaw is, install and run the stack, build a graph you can walk around, then enrich that graph by promoting a plain note into the formal ontology. No prior knowledge of RDF, CUDA, or actor systems is required — every step is explained as you reach it. There is no separate database to set up; the graph store is an embedded Oxigraph triple store running in-process inside the Rust backend.

By the end you can point VisionClaw at your own notes, navigate the result in 3D, and govern how concepts become first-class ontology classes.

Learning path

# Tutorial What you learn Time
1 What is VisionClaw? The mental model — what each part does and where your data flows, no commands typed ~10 min
2 Installation System requirements, Docker Compose setup, and optional NVIDIA GPU acceleration ~20 min
3 Build Your First Graph Start the stack, load notes from GitHub or JSON, navigate the 3D space, and enable GPU physics 15–45 min
4 Promote a Note to the Ontology Turn a Markdown page into a governed OWL class with SHACL validation and PROV-O provenance ~30 min

Before you begin

  • Docker Engine with the Compose plugin (or Docker Desktop)
  • 8 GB RAM minimum, 16 GB recommended
  • A modern WebGL browser (Chrome, Firefox, or Safari, current release)
  • Optional: an NVIDIA GPU with CUDA for the 55x physics speedup — VisionClaw runs without it on CPU

Tutorial 2 covers each of these in detail, including how to verify your setup.

Where to go next

Once you have finished the path:

  • Pick a task from the How-To Guides — deployment, agent orchestration, REST API usage, XR setup.
  • Understand the design in Explanation — architecture, the physics engine, the ontology pipeline.
  • Look things up in the Reference — REST and WebSocket APIs, the binary protocol, configuration, and the agents catalogue.

See also