> Move your app from direct OpenAI to Modelux in 3 lines. # Migrating from OpenAI If your app already uses the OpenAI SDK, you can point it at Modelux with three changes — no other code modifications needed. ## 1. Add OpenAI as a provider in Modelux In the dashboard, add your existing OpenAI API key as a provider. Modelux will use that key to proxy requests — you keep your existing OpenAI account, billing, and rate limits. ## 2. Create a Modelux API key Create a project, then generate an API key scoped to it. Copy the `mlx_sk_...` value. ## 3. Update your client config Change two lines in your app: ```diff from openai import OpenAI client = OpenAI( - api_key=os.environ["OPENAI_API_KEY"], + base_url="https://api.modelux.ai/v1", + api_key=os.environ["MODELUX_API_KEY"], ) ``` That's it. Your existing `client.chat.completions.create(...)` calls work unchanged. Model names like `gpt-4o-mini` are routed to OpenAI through your credentials. ## What you get for free Just by routing through Modelux, with zero other code changes: - **Full request logs** with searchable traces - **Per-request cost tracking** - **Latency percentiles** by model - **Team-level analytics** if multiple apps share one org ## Next steps Once traffic is flowing, you can add value without further code changes: - **Add a fallback chain** to improve reliability — create a routing config `@production` that falls back from `gpt-4o-mini` to `claude-haiku-4-5`, then update your app to call `model="@production"` instead of `gpt-4o-mini`. - **Set a monthly budget** with auto-downgrade to cap your spend. - **Enable the replay simulator** to test changes against historical traffic. ## Streaming still works Streaming responses pass through unchanged: ```python stream = client.chat.completions.create( model="@production", messages=[...], stream=True, ) for chunk in stream: print(chunk.choices[0].delta.content or "", end="") ```