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dsh-vision

Model Inference Updated 2026.08.24

Run the following command in DeepSeek Harness:

dsh plugin install Terry12138qy/dsh-vision

Paste the following prompt into your AI chat to install this plugin:

To install the dsh-vision plugin in DeepSeek Harness, run the command: dsh plugin install Terry12138qy/dsh-vision, or visit the full source address https://github.com/Terry12138qy/dsh-vision for detailed instructions.

About this plugin

DeepSeek Harness models often lack native vision capabilities, which restricts their utility in multimodal tasks. The dsh-vision plugin elegantly solves this by giving models "eyes" to see and describe images, enabling them to process visual inputs. Users simply provide an image path or URL, and the plugin leverages Alibaba Cloud's qwen3.5-omni-plus multimodal large model to generate Chinese descriptions. If the primary model fails due to quota exhaustion or rate limits, it automatically switches to Zhipu's glm-4.6v-flash as a backup, ensuring reliable performance.

At its core, dsh-vision streamlines image understanding: it converts images to base64, calls APIs for text descriptions, and returns results, allowing DeepSeek Harness to seamlessly integrate vision features. Whether handling local files or online images, it works efficiently across various use cases.

This plugin is ideal for developers working with DeepSeek Harness, AI enthusiasts, and researchers who need models to comprehend visual content. From document processing and image analysis to creative applications, dsh-vision offers a straightforward way to add vision capabilities, expanding the model's application boundaries with minimal setup and reliable multimodal AI support.

Use Cases

  • Process local image files and automatically generate Chinese text descriptions.
  • Analyze image URLs to obtain content summaries for automation tasks.
  • Integrate vision capabilities into DeepSeek Harness tools to extend model applications.

Best For

  • Developers and engineers using DeepSeek Harness.
  • AI researchers and enthusiasts needing image recognition features.
  • Professionals involved in document processing or content creation.