dsh-deepseek-vision

In the DeepSeek Harness ecosystem, pure text programming models like the DeepSeek series natively lack image processing capabilities, limiting developers' applications in multimodal tasks. dsh-deepseek-vision, as a vision-language gateway plugin, cleverly addresses this by providing a lightweight routing layer that enables models to seamlessly handle image inputs, whether pasted in chat, returned from tools, or captured from browser screenshots.

The plugin's core capability lies in its intelligent routing mechanism: for models officially declared to support vision, images are directly forwarded to native endpoints; for others, a configurable vision model (default Qwen-VL) first converts the images into detailed text descriptions before passing them to DeepSeek for further processing. This process uses an in-process LRU cache, describing each image only once to avoid redundant billing, while maintaining session history invariants to ensure original images remain persisted unaffected. Installation and configuration follow official plugin mechanisms, allowing zero-code changes to swap vision models and compatibility with various OpenAI-style gateways.

This plugin is particularly suitable for users leveraging DeepSeek Harness for programming, AI development, or research, especially developers who need to occasionally process images without switching models or introducing complex dependencies. It does not inject additional tools or rely on local models, offering only the thinnest bridge to let users focus on core tasks while extending DeepSeek's multimodal capabilities. Whether you're a software engineer, AI researcher, or educator, if you want to integrate image understanding into your DeepSeek workflow, dsh-deepseek-vision provides a reliable and efficient solution.