mirror of
https://github.com/MBombeck/HealthLog.git
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Marc-André Bombeck
2c88acc5f7
Local lab OCR reads a report photo on the device with tesseract.js, whose defaults load the worker, the WebAssembly core and the language data from cdn.jsdelivr.net. The production CSP allows workers and fetches only from this origin, so the engine could not load; where it did load (dev), the browser of anyone scanning a report contacted a third-party CDN. The worker, the three LSTM core builds and the deu and eng best_int language data (about 17 MB) are now copied from pinned packages into public/tesseract/ at prebuild and predev, and createWorker is pointed at them with the worker started from its URL rather than a blob. A test holds the options against the staged file list.
87 lines
3.2 KiB
TypeScript
87 lines
3.2 KiB
TypeScript
/**
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* v1.18.10 — in-browser (local) OCR for lab-report scans.
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*
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* Used by the TEXT-mode Lab-OCR path: a user whose AI provider cannot read
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* images (ChatGPT-OAuth/Codex, a text-only model) OCR's the photo HERE, in the
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* browser, and only the extracted TEXT is POSTed to `/api/labs/ocr/extract`.
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* The raw image never leaves the device.
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*
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* tesseract.js (WASM) is LAZY-loaded via `await import(...)` so the multi-MB
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* worker + WASM core + `deu+eng` traineddata land in the browser only when the
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* user actually scans in text mode — never at app boot, and never for the
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* higher-accuracy vision path. This mirrors the chart-defer discipline.
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*
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* Images only — tesseract.js cannot read PDFs, matching the vision path's
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* image-only constraint for non-Anthropic providers.
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*
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* Every engine file is served from this origin under `/tesseract/`, staged
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* from node_modules by `scripts/stage-tesseract-assets.mjs`. The library's
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* defaults fetch the worker, the WebAssembly core and the language data from
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* cdn.jsdelivr.net, which both sends the user's browser to a third party and
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* is refused by the production CSP. The worker is started from its URL, not
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* from a blob, so `worker-src 'self'` admits it.
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*/
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/** German + English: a German lab sheet needs `deu` for ä/ö/ü/ß; `eng` covers
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* the many English analyte names and units that appear on the same sheet. */
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const OCR_LANGS = "deu+eng";
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/** OEM 1 (LSTM only), the library default, spelled out because the staged
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* core builds and the `best_int` language data are the LSTM-only ones. */
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const OCR_OEM = 1;
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/** Same-origin engine paths; see `scripts/stage-tesseract-assets.mjs`. */
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export const LOCAL_OCR_ASSET_OPTIONS = {
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workerPath: "/tesseract/worker.min.js",
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corePath: "/tesseract/core",
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langPath: "/tesseract/lang",
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workerBlobURL: false,
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gzip: true,
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} as const;
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export class LocalOcrError extends Error {
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constructor(message: string) {
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super(message);
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this.name = "LocalOcrError";
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}
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}
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/**
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* OCR an image file entirely in the browser and return the extracted plain
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* text. Throws `LocalOcrError` when the engine fails to load or recognise.
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*
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* A fresh worker is created and terminated per call. The traineddata is
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* browser-cached after the first run, so the cost is paid once.
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*/
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export async function ocrImageToText(file: File): Promise<string> {
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// Lazy import — keeps tesseract.js out of the main bundle.
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let createWorker: typeof import("tesseract.js").createWorker;
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try {
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({ createWorker } = await import("tesseract.js"));
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} catch {
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throw new LocalOcrError("Failed to load the local OCR engine");
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}
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const worker = await createWorker(
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OCR_LANGS,
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OCR_OEM,
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LOCAL_OCR_ASSET_OPTIONS,
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);
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try {
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const {
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data: { text },
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} = await worker.recognize(file);
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const trimmed = text.trim();
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if (!trimmed) {
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throw new LocalOcrError("No text could be read from the image");
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}
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return trimmed;
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} catch (err) {
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if (err instanceof LocalOcrError) throw err;
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throw new LocalOcrError("Local OCR failed to read the image");
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} finally {
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// Free the WASM worker; the traineddata stays browser-cached.
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await worker.terminate().catch(() => {});
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}
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}
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