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dsh-custom-provider-reasoning

Model Inference Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install 534119219/dsh-custom-provider-reasoning

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

Install this plugin in DeepSeek Harness by running the command `dsh plugin install 534119219/dsh-custom-provider-reasoning`. Source: https://github.com/534119219/dsh-custom-provider-reasoning

About this plugin

In DeepSeek Harness, users of custom model providers often encounter a limitation: the composer model selector only displays reasoning effort options for models with pre-defined metadata, leaving custom routes without this crucial control. This gap prevents users from fine-tuning the inference behavior of powerful models like DeepSeek V4, even though they can freely add custom providers.

This plugin bridges that gap by automatically injecting reasoningEfforts metadata into each eligible model, enabling options like Off, Low, Medium, and High in the model chooser. It ensures these selections are effectively transmitted to the backend. Additionally, it intelligently fills in missing maxTokens and contextWindow parameters to avoid output truncation and manages protocol-specific compatibility settings, such as thinkingFormat and supportsDeveloperRole, to prevent errors from unsupported roles or format mismatches across different API protocols.

Designed for developers and researchers using custom model providers, especially those needing to adjust inference depth for performance or cost optimization, this plugin works seamlessly after installation. It empowers custom routes with the same reasoning effort control as built-in providers, streamlining development workflows and enhancing the usability of advanced models in the DeepSeek Harness ecosystem.

Use Cases

  • When custom model providers' models lack reasoning effort options in the composer selector.
  • When custom route models need auto-filled maxTokens and contextWindow to prevent output truncation.
  • When switching between different API protocols requires auto-management of compatibility settings like thinkingFormat or supportsDeveloperRole.

Best For

  • Developers using custom model providers who need fine-grained control over inference depth.
  • Researchers relying on the composer model selector for model inference testing.
  • Operations staff deploying models in multi-protocol environments who require endpoint compatibility assurance.