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dsh-llm-databricks

Model Inference Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install zhuchengde0214-ctrl/dsh-llm-databricks

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

Run dsh plugin install zhuchengde0214-ctrl/dsh-llm-databricks inside your DeepSeek Harness workspace to install the bundle; the source lives at https://github.com/zhuchengde0214-ctrl/dsh-llm-databricks .

About this plugin

If you have conversation models—Claude, GPT, Gemini, Llama, DeepSeek, or others—already served behind a Databricks AI Gateway and want to call them from DeepSeek Harness the same way you would a local endpoint, dsh-llm-databricks was built for exactly that. It installs as a fully standalone bundle, touches neither the Harness core nor node_modules, and plugs in exclusively through the public LLM, settings, and credentials seams, so you are up and running the moment configuration is in place.

Use Cases

  • Your Databricks Workspace already serves Claude, GPT, or DeepSeek via AI Gateway and you want to call them from Harness without patching core or node_modules
  • A single workspace exposes MLflow Chat Completions, OpenAI Responses, and Anthropic Messages simultaneously; declare one provider route per protocol to unify access
  • You need the bearer token kept strictly in the credentials service—never in settings files or logs—while still hitting HTTPS-gated endpoints

Best For

  • Databricks Workspace administrators who have already wired up AI Gateway model endpoints
  • Application teams running DeepSeek Harness that want cloud-served models without managing local inference
  • Platform engineers with strict security, audit, and credential-isolation requirements for LLM call chains