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OpenAI Codex + MLflow AI Gateway

Route OpenAI Codex through the MLflow AI Gateway to get centralized tracing and observability, while each developer authenticates with their own OpenAI subscription.

Prerequisites

MLflow server running with a SQL backend (mlflow server --port 5000)
Codex installed (npm install -g @openai/codex)

Step 1: Create an OpenAI Endpoint

Navigate to the AI Gateway tab at http://localhost:5000/#/gateway and click OpenAI Codex in the quick start. Then click "create" to create an endpoint. The endpoint name is pre-filled as codex — you can change it, but make sure to use the same name in the next step.

Step 2: Run Codex

Configure Codex to point to the gateway base URL and run it.

bash

codex --config 'openai_base_url="http://localhost:5000/gateway/proxy/codex/v1"'

For a persistent setup, add the same value to ~/.codex/config.toml:

toml

openai_base_url = "http://localhost:5000/gateway/proxy/codex/v1

Note that you need to authenticate with your API key instead of ChatGPT subscription.

What You Get

Every session is captured as an MLflow trace. Open the Logs tab in the MLflow UI to inspect inputs, outputs, token usage, and latency for every request.