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How to Install DeepSeek Harness on Ubuntu and Connect a Local Model

Run DeepSeek Harness on Ubuntu with its npm quick start, then configure a compatible local model endpoint or use Ollama’s launcher.
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On Ubuntu, the documented quick start for DeepSeek Harness is to install Node.js and run npx @deepseek-ai/dsh web. Then connect a model through the Harness provider settings, or use Ollama’s documented ollama launch dsh integration. A local address alone does not guarantee local inference: use a model actually hosted on your machine and the API protocol that server supports.

Before you start

DeepSeek Harness is an open-source agent harness from DeepSeek AI, currently in developer preview. Its official README warns: “DeepSeek Harness is in developer preview and iterating rapidly. THERE WILL BE COMPATIBILITY-BREAKING CHANGES.” Check the current README before installing because commands and setup details may change.

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  • You need Node.js for the npm quick start. The README does not specify an Ubuntu release or a Node.js installation method.
  • The official setup sources do not state minimum hardware requirements.
  • No special physical accessory or paid service is established as necessary for the basic setup.

Install and launch the Harness on Ubuntu

  1. Install Node.js using a method appropriate for your Ubuntu release.
  2. Open a terminal and run npx @deepseek-ai/dsh web.
  3. When the server starts, open http://127.0.0.1:3080 in a browser on the same machine. This is the default Web UI address in the README.

The documented command launches the Web UI; it does not itself select or download a local model. For an explicit self-hosted provider, configure the endpoint and model details in the Harness.

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Connect a self-hosted model through provider settings

In the Harness Web UI, open the Models page and add or configure a provider. The official provider guide describes these fields:

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  • Provider ID: the identifier for this provider configuration.
  • Base URL: the API base URL exposed by your local model server. Use the value that server documents; there is no single universal local-model URL.
  • API protocol: choose the protocol implemented by the endpoint. The guide lists OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages.
  • Credential: supply the key or credential expected by the endpoint. Some local servers may not require one, but the Harness still needs a compatible credential configuration for its provider setup.
  • Model ID: enter the exact model identifier the endpoint accepts.

Save the provider and select its configured model for use. A local server can still fail to connect if its base URL is wrong, its API protocol differs from the selected option, or a gateway does not support the expected API behavior.

Use Ollama’s documented launcher instead

If Ollama is your local model server, its integration documentation provides a direct launcher:

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ollama launch dsh

To choose a model explicitly, pass its name with --model:

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ollama launch dsh --model <model>

Use the model identifier available in your Ollama setup in place of <model>. The integration also supports configuring without starting the Harness:

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ollama launch dsh --config

Check the selected model’s location before assuming inference is local. Ollama’s integration page demonstrates both a local model and a cloud model; selecting a cloud model sends inference to a cloud service rather than keeping it on the Ubuntu machine.

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Choose the setup path that fits

Path Best fit What to keep in mind
Harness npm launch plus custom provider You want to enter and manage the provider endpoint, protocol, credential, and model ID yourself. The local server must expose an API compatible with the selected protocol.
Ollama integration launcher You use Ollama and want its documented Harness launch and model-selection flow. Choose a genuinely local model if local inference is the goal; the integration can also show cloud models.

The official setup sources do not establish comparative model quality, hardware benchmarks, or minimum system requirements, so those cannot be inferred from the install route.

Troubleshoot provider and model errors

  • Credential missing: store the key through the Models page or provide the environment variable referenced by the provider guide, as appropriate for the provider.
  • Unknown model: select a model already configured in the Harness or add the exact model ID accepted by the endpoint.
  • Model list is empty or discovery fails: some endpoints use listing formats the Harness does not support. Enter the model ID manually instead.
  • Requests fail despite a reachable server: verify the base URL and API protocol, then check whether any gateway between the Harness and server supports that protocol.

These fixes address configuration mismatches; they do not establish that a particular server or model is compatible with every Harness version.

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