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dsh-math-input

v0.1.0xiaxi626 / dsh-math-input489f50a221

InstallableBundlesUI & client pluginsCommunity · Topic auto-analysisWeb UI

Overview

dsh-math-input

Zero-token offline math input for DeepSeek Harness: handwriting recognition, screenshot OCR, LaTeX editor, and inline LaTeX rendering.

README / EN

Package documentation

Registry summary

Zero-token offline math input for DeepSeek Harness: handwriting recognition, screenshot OCR, LaTeX editor, and inline LaTeX rendering.

dsh.pub verifies the pinned bundle contract, runtime facts, and distribution semantics. The complete README remains in the source repository.

Read the full README on GitHub

LIMITATIONS

Known limitations

- **Model download**: first recognition triggers a ~7.2 MB download (encoder 3.4 MB + decoder 4.0 MB + vocab 4 KB); subsequent loads use IndexedDB cache. - **WebGPU auto-fallback**: when `webgpu` is selected but the browser doesn't support it (requires Chrome 113+), the engine automatically falls back to `wasm`. - **SharedArrayBuffer**: ONNX Runtime Web uses multi-threaded WASM when `Cross-Origin-Opener-Policy: same-origin` and `Cross-Origin-Embedder-Policy: require-corp` headers are present. Without them, it falls back to single-threaded — recognition still works but is slower. - **Handwritten vs printed**: the CoMER model is trained on the CROHME handwritten math expression dataset and optimized for handwriting. Screenshot OCR of printed formulas may underperform. - **Browser compatibility**: requires a modern browser with WebAssembly SIMD support. Chrome / Edge recommended; Firefox mostly works; Safari has limited support. - **Zero-token guarantee**: the plugin never calls `ctx.llm` — all recognition runs locally in the browser, with zero API costs.