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plug

A DeepSeek Harness plugin that converts pasted, dropped, or imported images into text through an external vision model before sending the result to a text-only model.

VisionUI & ProductivityTerminal & TUIDeveloper Tools
0GitHub Stars0ForksUpdated2026-08-15

Install

$ dsh plugin --profile <name> add github:qing9835/plug#<commit>

Plugin Overview & Capabilities

AI-assisted organization based on the public repository snapshot. The content must be grounded in source evidence and does not replace compatibility or security verification.

source-grounded
dsh-eyes is an installable DSH bundle with host and client components. It intercepts image input in the conversation UI, sends images to an OpenAI-compatible vision endpoint through its bundled bridge, and automatically submits the resulting text description to the main model.

Key Capabilities

  • Installs through the DSH CLI as a persistent bundle plugin.
  • Captures pasted, dropped, and imported images in the chat input.
  • Provides image preview and configuration controls in the input UI.
  • Calls external OpenAI-compatible vision endpoints to describe, inspect, or OCR images.
  • Supports image validation, optional cropping, resizing, JPEG conversion, and base64 encoding.
  • Supports retry handling for selected transient errors and configured backup models.
  • Includes a separate Python stdio MCP bridge for compatible MCP clients.

Useful For

  • Letting a text-only DSH model work from screenshots or local images via textual descriptions.
  • Extracting text from images before sending it to a chat model.
  • Inspecting images with a configured external vision model.
  • Adding image-input translation to a DSH conversation workflow.

Who It Fits

  • DeepSeek Harness users running text-only models.
  • Users with access to an OpenAI-compatible vision endpoint.
  • Developers who want to use the included MCP bridge with DSH or another MCP client.

Documented Limitations

  • Requires setup of the bundled Python bridge environment and configuration of a vision model endpoint.
  • Vision analysis depends on an external OpenAI-compatible endpoint, model, and potentially an API key.
  • The MCP bridge cannot process an image that has already been rejected by the host chat message gate; the UI interception plugin addresses that input path.
  • The dynamic-plugin variant is session-scoped and must be defined again after a process restart; the bundle variant is the persistent option.
  • The README cautions that vision conclusions about layout issues should be cross-checked with OCR and source code.

DSH Compatibility

Version-specific runtime evidence collected by DSH Plugin. A missing result means we have not tested that combination yet.

Not tested yetNo runtime compatibility tests have been published yet.

Security Signals

Objective signals discovered from package metadata and source inspection. These are not a guarantee that a plugin is safe.

Dependency Counts

package.json declares 3 runtime, 0 development, 0 peer, and 0 optional dependencies.

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Dsh Bundle Declared

package.json declares DSH bundle metadata.

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License Declared

GitHub reports the repository license as MIT.

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Package Manifest Available

A root package.json was captured and can be inspected by the registry.

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Source Available

Public GitHub source metadata is available for this registry snapshot.

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Source & Registry Notes

Public provenance, Registry classification, and the latest source check for this entry, kept separate from runtime verification.

Source repository
qing9835/plug
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
d104d24 · 2026-08-15

This project is independently indexed from public source information. DSH Plugin is not affiliated with DeepSeek or the plugin author. Always check the author repository before installation.

Repository Activity

GitHub stars
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Last commit
2026-08-15
Last release
No release detected
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