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dsh-openai-gateway

Model Inference Updated 2026.08.24

Run the following command in DeepSeek Harness:

dsh plugin install backrooms-yrc/dsh-openai-gateway

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

To install this plugin in DeepSeek Harness, run the command: dsh plugin install backrooms-yrc/dsh-openai-gateway. The plugin source code is available at https://github.com/backrooms-yrc/dsh-openai-gateway.

About this plugin

Integrating a DeepSeek Harness Agent into existing OpenAI-based workflows can be challenging, as the native Web UI is not designed for programmatic access. The dsh-openai-gateway solves this by exposing your DeepSeek Harness as a standard OpenAI-compatible API server. This allows any OpenAI SDK client—be it IDE plugins, automation scripts, or tools like Raycast—to seamlessly drive your Agent with just a base URL and API key.

At its heart, the plugin maps each API request to a real Agent session complete with tools and a workspace, rather than acting as a mere LLM proxy. It supports both streaming and non-streaming responses and offers flexible session modes: a stateless default for quick, isolated calls, and sticky sessions for maintaining context across requests, ideal for complex, multi-turn tasks. Authentication and listening are handled independently, ensuring secure separation from the dsh Web UI and allowing you to expose endpoints as needed.

This gateway is perfect for AI application developers, research engineers, or tool enthusiasts who want to infuse their workflows with intelligent Agent capabilities. It caters especially to those familiar with the OpenAI ecosystem who wish to leverage the unique toolchain and session management of DeepSeek Harness. With minimal configuration, you can bridge a powerful local Agent to the global API standard, unlocking broader integration possibilities.

Use Cases

  • Call local DeepSeek Harness Agent via OpenAI SDK.
  • Integrate smart code assistants in IDEs or editors.
  • Automate Agent-based task processing with scripts.

Best For

  • AI developers needing to integrate Agents into existing workflows.
  • Research engineers using OpenAI toolchains.
  • Tool enthusiasts looking to extend local Agent capabilities.