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self-evolving-router-dsh

Model Inference Updated 2026.09.15

Run the following command in DeepSeek Harness:

dsh plugin install sra-research/self-evolving-router-dsh

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

Run dsh plugin install sra-research/self-evolving-router-dsh in your terminal to add the plugin; the source repository is available at https://github.com/sra-research/self-evolving-router-dsh .

About this plugin

In a DeepSeek Harness model-inference pipeline, routing decides which model instance or backend each request is sent to. self-evolving-router-dsh is an inference-routing plugin built for exactly this concern: instead of treating the routing policy as a fixed, hand-written configuration, it adopts a self-evolving approach that lets the routing logic adapt over time based on runtime feedback signals.

If you are building a multi-model or multi-backend inference service on DeepSeek Harness and want your routing decisions to evolve in response to load, latency, or quality signals rather than requiring constant manual re-tuning, this plugin offers a lightweight, MIT-licensed path forward. Maintained by the sra-research team, it stays focused on the inference-scheduling niche and suits engineering teams already working within the Harness ecosystem who need more dynamic routing behavior.

Use Cases

  • Dynamically adjusting inference routing based on real-time load across multiple models
  • Replacing static routing configurations to reduce manual tuning in inference pipelines
  • Introducing adaptive scheduling strategies for inference requests in DeepSeek Harness

Best For

  • Engineering teams building inference services on DeepSeek Harness
  • Developers needing multi-backend dynamic routing without manual rule upkeep
  • Platform architects prioritizing flexible and continuously evolving inference scheduling