If you run a Python service that accepts user text, you already have the problem. Comments, chat messages, profile bios, support tickets and increasingly LLM output all arrive as strings that need a policy decision attached to them. This tutorial is a hands-on walkthrough of adding a content moderation API Python integration to a service you already ship: one POST request, a JSON body, and a boolean response you can branch on. No tuning loop, no score calibration, no model hosting.

Everything below uses the documented cloud API. The base URL is https://api.cautionlabs.com , the endpoint is POST /moderation , authentication is a bearer Cloud API key, and the request body has a single required field, text . If you want the conceptual overview before the Python specifics, adding moderation in an afternoon covers the shape of the product first.

Why Python teams reach for a moderation API

Moderation rarely shows up as its own project.…