Most LangGraph content stops at the notebook. You build a cute ReAct loop, it answers one question, and the article ends before the hard part: how do you actually serve this thing, swap models without a rewrite, and see what it's doing when it misbehaves? This post walks through a small but production-shaped LangGraph deployment: a RAG ReAct agent that exposes an OpenAI-compatible HTTP API , so any OpenAI client (Open WebUI, the openai SDK, LibreChat) can talk to it unchanged, r...