ONNX Runtime Web Loader¶

OpenMedKit web includes an ONNX Runtime Web loader for local token-classification artifacts. It selects the strongest available execution path at runtime:

1. WebGPU when navigator.gpu is available
2. wasm with SIMD and threads when cross-origin isolation and SharedArrayBuffer are available
3. single-threaded wasm as the conservative fallback

The threaded wasm path requires the application to serve pages with Cross-Origin-Opener-Policy: same-origin and Cross-Origin-Embedder-Policy: require-corp. Without those headers, browsers hide SharedArrayBuffer; the loader falls back to single-threaded wasm instead of reaching for a remote runtime.

import {
  loadOrtWebTokenClassificationPipeline,
  deidentify,
} from "@openmed/openmedkit-web";

const pipeline = await loadOrtWebTokenClassificationPipeline({
  modelPath: "/models/openmed-pii/onnx/model.onnx",
  assetPath: "/models/openmed-pii/onnxruntime/",
  tokenize: tokenizeClinicalNote,
  decode: decodeTokenClassificationOutputs,
});

const result = await deidentify(
  "Patient Casey Example called 212-555-0198.",
  { pipeline, detector: "ort-web" },
);

modelPath and assetPath must point to local or offline paths such as /models/..., ./models/..., ../models/..., or file://.... HTTP(S), protocol-relative, data:, and blob: paths are rejected so tests and browser bundles do not silently fetch PHI-processing assets from a CDN.

Session construction is cached by model path, wasm asset path, backend choice, and session options. Repeated calls reuse the same InferenceSession, while callers that need isolation can pass their own cache: new Map().

For tests, pass a small runtime object through runtime and explicit capabilities. That lets Node exercise WebGPU, threaded wasm, and basic wasm selection without installing browser APIs or downloading ONNX Runtime assets.