Classify unsafe text and image inputs with the OpenAI-compatible moderations API

Moderations

LLMGateway supports the OpenAI-compatible /v1/moderations endpoint for text and multimodal safety classification.

Use it when you want to:

Screen user prompts before they reach a model
Review generated output before displaying it
Apply the same moderation API shape you already use with OpenAI clients

For the full request and response schema, see the API reference.

Endpoint

POST https://api.llmgateway.io/v1/moderations

Authenticate with your LLMGateway API key:

-H "Authorization: Bearer $LLM_GATEWAY_API_KEY"

Supported Inputs

The input field accepts:

A single string
An array of strings
An array of multimodal content items with text and image_url

The default model is omni-moderation-latest.

curl

Single text input

curl -X POST "https://api.llmgateway.io/v1/moderations" \
  -H "Authorization: Bearer $LLM_GATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "I want to harm someone."
  }'

Multiple text inputs

curl -X POST "https://api.llmgateway.io/v1/moderations" \
  -H "Authorization: Bearer $LLM_GATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "omni-moderation-latest",
    "input": [
      "This is a harmless sentence.",
      "I want to attack somebody."
    ]
  }'

Multimodal input

curl -X POST "https://api.llmgateway.io/v1/moderations" \
  -H "Authorization: Bearer $LLM_GATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": [
      {
        "type": "text",
        "text": "Check this image for violent content."
      },
      {
        "type": "image_url",
        "image_url": {
          "url": "https://example.com/image.png"
        }
      }
    ]
  }'

OpenAI SDK

import OpenAI from "openai";

const client = new OpenAI({
	baseURL: "https://api.llmgateway.io/v1",
	apiKey: process.env.LLM_GATEWAY_API_KEY,
});

const response = await client.moderations.create({
	model: "omni-moderation-latest",
	input: "I want to harm someone.",
});

console.log(response.results[0]?.flagged);

Response Shape

The response follows the standard OpenAI moderation format:

{
	"id": "modr-123",
	"model": "omni-moderation-latest",
	"results": [
		{
			"flagged": true,
			"categories": {
				"violence": true,
				"self_harm": false
			},
			"category_scores": {
				"violence": 0.98,
				"self_harm": 0.01
			}
		}
	]
}

When To Use This Instead Of Chat Content Filtering

Use /v1/moderations when you want an explicit moderation decision in your own application flow.

If you want moderation to happen automatically as part of model requests, use LLMGateway content filtering on /v1/chat/completions instead.

Moderations

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