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dsh-chatgpt-codex

Model Inference Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install sudipnext/dsh-chatgpt-codex

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

Run dsh plugin install sudipnext/dsh-chatgpt-codex inside DeepSeek Harness to install the plugin; the source repository is hosted at https://github.com/sudipnext/dsh-chatgpt-codex .

About this plugin

DeepSeek Harness has no built-in ChatGPT OAuth on its main model route, so anyone who wants to call Codex-family models (GPT-5.6 Luna, Terra, Sol, and earlier) from DSH is currently limited to a one-shot subagent path or a separate OpenAI API key. dsh-chatgpt-codex closes that gap by wiring the ChatGPT credential flow and the Codex Responses streaming interface directly into the native DSH message-and-tool protocol with zero API keys and no pi-ai runtime dependency.

The plugin supports both browser PKCE callbacks and headless device-code login, handles automatic token refresh with cross-process rotation locks, and stores credentials atomically at 0600 under a dedicated DSH directory. On the response side it streams text, reasoning summaries, function calls, images, usage metrics, and finish reasons, while encrypted reasoning-item replay keeps multi-turn Codex sessions coherent. The bundled model catalog covers the current GPT-5.6 and GPT-5.5/5.4 families; actual availability depends on your ChatGPT subscription tier and workspace policy.

It is well suited for developers who want to use a ChatGPT subscription as their primary DSH model, particularly those working over SSH, inside Docker containers, or other headless setups where juggling extra API keys is unwanted friction.

Use Cases

  • Use Codex-family models as the primary DSH model without an OpenAI API key
  • Authenticate via device code in headless SSH or Docker environments
  • Maintain multi-turn Codex session coherence through encrypted reasoning replay

Best For

  • DSH users who prefer a ChatGPT subscription over an OpenAI API key
  • Developers working in headless environments like SSH or Docker
  • Teams integrating Codex models into their DSH workflow