docling.rs-cuda

CUDA (NVIDIA GPU) build of docling.rs for Node.js / Bun — Linux x64 only. Same JavaScript API, GPU-accelerated PDF/image ML pipeline (RT-DETR layout, TableFormer, OCR): measured 1.5–2.1× on multi-page digital PDFs and up to 8.7× on very large documents vs CPU.

The npm tarball is a few KB of JavaScript; the CUDA native addon and the ONNX Runtime CUDA provider libraries (hundreds of MB — past npm's practical size limits) are downloaded by a postinstall script from this project's GitHub release that matches the package version, and verified against the release's sha256 manifest.

npm install docling.rs-cuda
# or keep `require('docling.rs')` working unchanged via an npm alias:
npm install docling.rs@npm:docling.rs-cuda

Requirements:

• Linux x64, glibc ≥ 2.38 (Ubuntu 24.04+ / Debian 13+ era — inherited from the CUDA ONNX Runtime binaries, same floor as the docling-rs-cuda Python wheel)
• CUDA 12 + cuDNN 9 installed on the system (the download ships the ONNX Runtime provider, not the CUDA toolkit)
• network access to github.com at install time — or set DOCLING_RS_NPM_CUDA_URL to a mirror base URL / local directory holding the same release assets (air-gapped installs)

A GPU build defaults to DOCLING_RS_EP=auto: GPU when one is usable, CPU fallback when not. DOCLING_RS_EP=cuda forces the GPU (fail loudly), DOCLING_RS_EP=cpu forces CPU. Everything else — API, model downloads, docs — is identical to docling.rs; see its README.