DeepSeek Harness (DSH) is an agent testing toolkit released by DeepSeek for developers. Built on a plugin‑first architecture, it supports custom configuration for large‑language models, tool integrations and agent workflows. It delivers visual debugging via local web UI, making it suitable for building AI assistants, chat‑bots and virtual agent prototypes. This guide targets Windows operating systems and introduces two distinct deployment approaches: the official npx web‑based quick start for ad‑hoc testing, and the community‑maintained dsh‑launcher desktop launcher for long‑term daily usage without repeated command‑line input.

Prerequisite Environment: Install Node.js and npm

DSH depends on Node.js runtime. Before any installation steps, you must set up this environment. The LTS 24.x release is the recommended version for stable operation.

Verify Local Installation Status

Press Win + R, input cmd to open command prompt, then run the two commands below to validate runtime availability.

node -v
npm -v

Successful output sample:

v24.19.0
11.17.0
  • If valid version numbers appear, your environment is ready and you can move directly to the installation phase.
  • When “not an internal command” error occurs, download Node.js LTS installer from official website. Check Add to PATH during installation wizard to configure system environment variables automatically. Restart command‑line terminal after installation completes and run verification commands again.

Option One: Official Web UI Quick‑Start via Native npx

This deployment method requires zero permanent local installation packages. It pulls runtime resources on‑demand and spins up web service instantly, best suited for short‑term testing and quick validation of agent logic.

Step 1: Copy Official Launch Command

Navigate to DeepSeek Harness official website https://www.deepseek.com/harness/. Copy the one‑click startup command displayed on the right‑hand section of the webpage.

npx @deepseek‑ai/dsh web

Step 2: Execute Startup Command Inside Command Prompt

Open cmd terminal under any working directory and paste the command. The execution workflow follows these stages:

  1. The terminal prompts to install dependency package @deepseek‑ai/dsh 0.1.0‑rc.6. Type y and confirm installation.
  2. Deprecation warning node‑domexception may pop up. This warning can safely be ignored and will not block normal runtime.
  3. After dependency download completes, local web service boots up. The terminal outputs access address: http://127.0.0.1:3080.
C:\Users\wang‑zhip>npx @deepseek‑ai/dsh web
Need to install the following packages:
@deepseek‑ai/dsh@0.1.0‑rc.6
Ok to proceed? (y) y
npm warn deprecated node‑domexception@1.0.0: Use your platform's native DOMException instead
web: http://127.0.0.1:3080

Step 3: Access DSH Visual Panel Through Browser

Copy http://127.0.0.1:3080 and open it in your browser to enter the main graphical interface of DeepSeek Harness. All agent configuration, plugin management and debugging work can be completed on this web page.

Step 4: Configure DeepSeek API Credentials (Mandatory)

Without valid API key configuration, DSH cannot invoke large‑model inference. Follow these configuration steps:

  1. Click settings icon on top‑right corner, select Models tab on left sidebar.
  2. Select DeepSeek provider entry and click Edit.
  3. Paste your DeepSeek API secret key into input box and click Save.
How to Obtain DeepSeek API Key
  1. Visit DeepSeek open platform https://platform.deepseek.com/, log‑in with mobile number or WeChat account.
  2. Locate API Keys in left‑side navigation bar, click Create API Key.
  3. Assign custom name for this key, copy and store credential immediately after creation. The full secret string displays only once and cannot be retrieved later.
  4. New accounts receive free trial inference quota. You may recharge balance after trial resources are exhausted.

Step 5: Select Working Directory and Conduct Functional Testing

After API key saving finishes, choose a local project folder as working directory. DSH will read local project files in this folder, enabling end‑to‑end testing for model invocation, plugin execution and custom agent workflows.

Important note for npx web mode: every time you start work you need to re‑run the npx command within cmd terminal. Service will shut down immediately once you close the command‑line window.

Option Two: dsh‑launcher Desktop Launcher — Command‑Free Solution for Long‑Term Use

The native npx web solution requires manual terminal startup every session, creating friction for developers running repeated agent experiments. Community open‑source project dsh‑launcher delivers a desktop launcher. After one‑time installation, you can launch DSH by double‑clicking desktop icon without typing npx instructions repeatedly.

Step 1: Download Installation Package

  1. Access open‑source repository: https://github.com/Ruler4396/dsh‑launcher
  2. Navigate to Releases page on repository right sidebar.
  3. Download Windows installation MSI package from asset list and complete installation wizard.

Core Advantages of Desktop Launcher

  1. Double‑click desktop shortcut to spin up DSH local service; browser UI pops‑up automatically.
  2. Background process management, no need to keep cmd terminal window open. Port 3080 service persists in background.
  3. Eliminates repetitive npx command input, perfectly fits frequent daily agent development, debugging and iteration.

Common Troubleshooting for DeepSeek Harness

1. Slow or Failed npx Dependency Download

Network instability often causes npm package download timeout. Switch npm registry mirror source within cmd terminal before installation:

npm config set registry https://registry.npmmirror.com

After setting mirror source, retry npx startup command for faster dependency acquisition.

2. Cannot Open Web Page at 127.0.0.1:3080

  • Confirm command‑line terminal has not been closed. In npx web mode, closing cmd kills the whole backend service.
  • Check whether port 3080 is occupied by other local software. If port conflict occurs, modify DSH startup port parameter and use alternative port number.

3. API Key Saved But Model Invocation Fails

  • Double‑check API key string for extra whitespace or line breaks. Extra invisible characters will trigger authentication failures.
  • Verify your DeepSeek platform account still has available inference quota. Empty balance will result in API call rejection.
  • Restart DSH service to force reload model provider configuration after credential updates.

4. Node.js Runtime Version Too Low

DSH requires Node.js version 22 or higher. Version 24 LTS remains the most stable recommendation. Download latest LTS release from official Node.js website and reinstall runtime environment.

5. Desktop Launcher Installation Failure

Make sure you download the correct Windows x64 MSI installer from Releases tag. Outdated Windows system versions may lack runtime dependencies and block installation.

Multi‑Provider Model Integration Considerations

DSH supports adding custom model providers beyond official DeepSeek endpoints. In real‑world agent development scenarios, developers often need to switch between multiple LLM back‑ends for capability comparison, load balancing and cost control. A unified API gateway simplifies multi‑model access management. Treerouter can consolidate different model endpoints under one uniform interface, reducing repeated configuration overhead when testing agents across various LLMs.

Summary

Two deployment patterns serve different developer requirements.

  • For occasional testing and quick proof‑of‑concept work: choose official npx web deployment. No permanent local installation, start with one single command.
  • For continuous agent development, frequent debugging and long‑running workflows: select dsh‑launcher desktop launcher. It removes command‑line operations and improves daily developer experience.

Regardless of which solution you adopt, two prerequisites are mandatory: properly configured Node.js runtime environment and valid model provider API credentials. DSH plugin‑oriented architecture enables rapid iteration for agent prototypes, which greatly lowers the threshold for custom agent development.

Learn more：https://treerouter.com