How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces
An AI coding agent built a working interactive 3D web gallery of 6 Paris monuments by chaining two existing Hugging Face Spaces on its own, with no person writing the integration code. Hugging Face engineer Mishig Davaadorj published the walkthrough on June 9, 2026, showing the agent generate images with Ideogram 4, convert each into a 3D Gaussian splat with VAST-AI TripoSplat, and assemble a browser viewer. It worked because each Space ships a plain-text agents.md file telling any agent exactly how to call it.
Key Takeaways
- I never opened an image generator.
- But the same forces are hitting multimedia AI .
The hard part of using a state-of-the-art image model, a video model, a TTS model, or a 3D reconstruction model was never the model.
- As of now, every Gradio Space also exposes a plain-text that tells an agent exactly how to call it: returns everything needed in one shot: the schema URL, the call and poll templates, how to upload files, and the auth hint: No client library.
- It noticed TripoSplat outputs are Y-down and flipped them upright, auto-framed each monument, compressed the files to (~3× smaller, so they load fast), built a Three.js viewer with a scroll-to-switch and drag-to-rotate UI, and deployed the whole thing as a static Space.
The only human inputs were taste-level: "make it zoomed out," "replace the obelisk with something better for splatting," "the transition lingers too long."
- Once this pipeline existed, spinning up entirely new galleries cost about one sentence each.
A Blog post by Mishig Davaadorj on Hugging Face Back to Articles How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces Community Article Published June 9, 2026 Upvote 20 +14 Mishig Davaadorj mishig Follow An agent built a 3D Paris gallery from two Hugging Face Spaces. I asked a coding agent to build a beautiful website showcasing the monuments of Paris as 3D Gaussian splats. I never opened an image generator.
I never touched a 3D reconstruction tool. The agent produced every asset (the images and the 3D splats) by calling two Hugging Face Spaces directly, then wired them into a cinematic viewer. Here's the result, live as a static Space: 👉 mishig/monuments-de-paris This post is about how that's possible now, and why I think it's a preview of how a lot of multimedia software gets built from here on.
The building-block economy comes for multimedia Mitchell Hashimoto recently described a shift he calls the building block economy : the most effective path to software is no longer a polished monolith, but small, well-documented components that others (increasingly agents ) can assemble. His key observation: AI is okay at building everything from scratch, but it is really good at gluing together proven pieces. That thesis has mostly been told with code libraries.
For more details please read the original article at Hugging Face.
Continue Learning
Comments
Comments appear only after moderation. Your email identifies your submission to the moderator and is never displayed here.
No approved comments yet.