The Composer in DeepSeek Harness (DSH) defaults to plain text input. When formulas are required for model reasoning, manual LaTeX input is usually needed, which is cumbersome and error-prone. dsh-math-input provides DSH with zero-token consumption offline math input capabilities, supporting handwriting recognition, screenshot OCR, and LaTeX editing. All inference is performed in the browser.

Plugin Overview

dsh-math-input is a DeepSeek Harness plugin that provides zero-token consumption offline math input capabilities. The plugin is maintained by xiaxi626, is licensed under MIT, and is a model reasoning tool.

Core Capabilities

The plugin mainly provides the following features:

  • Handwriting recognition: Based on the CoMER ONNX model, it supports input via mouse, touch, or stylus.
  • Screenshot OCR: Extracts LaTeX from images and supports pasting with Ctrl+V or uploading a file.
  • LaTeX editor: Provides a symbol palette to easily insert Greek letters and math templates.
  • Inline rendering: Entering \[ ... \] renders the formula.
  • Zero consumption and offline: All inference is performed in the browser, does not rely on remote APIs, and does not consume tokens.

Installation and Activation

Before installing, ensure the following environment requirements are met:

  • DeepSeek Harness version >= 0.1.1-rc.2
  • Node.js version >= 20.0.0
  • The browser supports SharedArrayBuffer and WebGPU (Chrome or Edge is recommended)

Run the following command to install:

dsh plugin --profile web add github:xiaxi626/dsh-math-input

After successful installation, restart the DSH Web process, and a + button will appear on the left side of the input line.

Typical Usage

Click the + button on the left side of the input line to open the menu, then select the corresponding feature:

  1. Handwritten input

    • Click “Handwritten input” and draw the formula on the canvas.
    • Pause for about 1.5 seconds (adjustable in settings) to trigger automatic recognition.
    • After the preview is generated, click “Confirm and Insert,” and the formula is added to the Composer in the form \[ ... \].

  2. Screenshot OCR

    • Click “Screenshot and Recognize.”
    • Press Ctrl+V to paste an image, or click “Upload File.”
    • The plugin automatically extracts LaTeX; insert it after confirmation.

  3. LaTeX editor

    • Click “LaTeX Syntax Editor,” and the panel expands.
    • Use the symbol palette (Greek letters, fractions, radicals, etc.) to insert code.
    • Preview it in real time on the right, then click “Insert” to write the formula.

  4. Inline rendering

    • Enter \[x^2 + y^2 = r^2\] in the Composer, and the system will automatically render it as a formula.

Notes and Limitations

  • Dependency environment: The first recognition will download a model of about 7.2 MB (cached in IndexedDB); subsequent loads use the cache.
  • Browser support: A modern browser that supports WebAssembly SIMD is required. If WebGPU is selected but not supported, the engine will automatically fall back to WASM.
  • Cache cleanup: The cache in IndexedDB is not cleared automatically; you must manually delete the math-handwrite-models database in browser developer tools.
  • Recognition accuracy: The CoMER model is optimized for handwritten formulas; printed formulas or complex layouts may not be recognized well.
  • Security: When relying on SharedArrayBuffer, the Cross-Origin-Opener-Policy and Cross-Origin-Embedder-Policy headers must be set.

Summary

With this plugin, developers can quickly input high-quality mathematical formulas without consuming tokens, improving development and debugging efficiency. For more details, refer to the plugin catalog page or the GitHub repository.