dsh-tool-ocr

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Local image text recognition for DeepSeek Harness models without vision input, backed by the standalone newbee-ocr (nbocr) engine over PP-OCRv6 models. Fully out-of-tree: depends only on published dsh base packages.

Features

Quick start

1. Install the engine — grab nbocr from the newbee-ocr-cli releases (one-line installer or prebuilt archive):

curl -LsSf https://github.com/zibo-chen/newbee-ocr-cli/releases/latest/download/newbee_ocr_cli-installer.sh | sh
# Windows PowerShell: irm https://github.com/zibo-chen/newbee-ocr-cli/releases/latest/download/newbee_ocr_cli-installer.ps1 | iex

2. Install the plugin

dsh plugin --profile web add dsh-tool-ocr
# or: cd ~/.dsh/profiles/web && pnpm add dsh-tool-ocr

3. Mount it in your profile's cordis.patch.yml:

- insert:
    - id: ocr
      name: 'dsh-tool-ocr'
      inject: [tools, subprocess, systemPrompt]
      config:
        command: 'C:/path/to/nbocr.exe'   # required — the nbocr executable

That's it — restart dsh, then point the model at an image: ocr { path: "C:/screenshot.png" }. To tune recognition (language, model tier, limits), open Settings → Plugins → Plugin config and edit the OCR card; changes apply on save, no restart needed. command is the only field that must come from the composition.

Image inputs

• path works on every dsh build: the model reads the file from disk.
• attachment_id needs a build that admits images for text-only models (e.g. the dsh fork with api-gateway.allowImagePlaceholder: true): images enter the session, the llm layer substitutes [image attachment <id>] text, and the model hands the id to ocr.

Configuration

Tool usage

ocr { path | attachment_id, action?, include_boxes?, table?, max_text_chars? }

status probes readiness without engine work; check runs a real end-to-end 1x1 probe.

Development

pnpm typecheck   # tsc --noEmit
pnpm test        # vitest
pnpm lint        # oxlint

Real-engine smoke (skipped unless both env vars are set):

NBOCR_BIN=/path/to/nbocr OCR_E2E_IMAGE=/path/to/image.png pnpm test

License

MIT