How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces
AI Summary
An AI coding agent built a 3D Gaussian splat gallery of Paris monuments by directly chaining two Hugging Face Spaces: an image generation Space and a 3D reconstruction Space. Utilizing plain-text agents.md instructions provided by Gradio Spaces, the agent handled asset generation, format conversion, compression, and Three.js UI integration with minimal human guidance.
Key Takeaways
- Gradio Spaces now expose a plain-text agents.md file containing full invocation schemas, templates, and auth hints.
- The pipeline chained an image generation Space with VAST-AI/TripoSplat for single-image 3D Gaussian splat reconstruction.
- The coding agent performed crucial post-processing, including coordinate flipping, Three.js viewer assembly, and .ksplat compression.
Why it matters
Demonstrates the practical realization of the 'building-block economy' for multimedia AI, where agents can automatically discover, integrate, and chain open-weights models and hosted services using standardized endpoint documentation like agents.md, completely removing manual SDK and integration overhead.
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