Build LEGO CAD models in LDraw with an agent

Have an agent plan, generate, and check an LDraw LEGO model from a text brief.

Done with ChatGPTClaudeยท Advanced

What they did
A developer set up a Dockerized web app with docs that let ChatGPT and Claude agents turn a prompt into LDraw source. The agent first reads the instructions, lays out a parts plan and submodels, then writes a plan file and Python generators that produce the LDraw file. It uses part search, collision and gap checks, and headless rendering, then repeats the render-and-fix loop until it thinks the model is done.
How it went
The process can produce the LDraw source, multiple viewers, and a GLB file that can be edited in Blender. The author says large accurate builds usually need the expensive high-end models, and generation is slow; spaceships perform poorly, and VR use on Meta Quest 3 has several problems.
Tips
Expect to spend time on iteration, and use the validation tools rather than trusting the first pass. If there is no TypeSafe API key, part lookup falls back to text search, which can lower model quality; the Docker image also needs about 5 GB of disk space.

Try it yourself with Claude Code

You are helping me create an LDraw LEGO model. First read the project instructions and then make a clear build plan for [object] using real LDraw part numbers and colors, including any needed submodels. Do not place bricks by hand; instead, write the files and scripts that generate the model. After each generation pass, check for collisions, gaps, and parts that float or intersect, and render a preview for review. Pause and ask for my approval before any final export or other irreversible step. When I confirm, produce the final [.ldr or .mpd] file, a parts list, and any export files you can generate.

Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.

Read the original on github.com โ†—

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