Moderation

Send text, images or both to POST /v1/moderations and NagaAI returns a verdict per input: whether any category tripped, and a score for each category. Use it to screen user messages before they reach a chat model, or model output before it reaches a user. The endpoint follows the OpenAI Moderations format, and the OpenAI SDK works unchanged. Choose a model whose operations include moderation in GET /v1/models.

Check a message

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.naga.ac/v1", api_key=os.environ["NAGA_API_KEY"])

result = client.moderations.create(
    model="omni-moderation-latest",
    input="I will hurt you if you post that again.",
)

verdict = result.results[0]
if verdict.flagged:
    hits = [name for name, hit in verdict.categories.model_dump().items() if hit]
    print("Blocked:", ", ".join(hits))
else:
    print("Allowed")

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.naga.ac/v1", apiKey: process.env.NAGA_API_KEY });

const result = await client.moderations.create({
  model: "omni-moderation-latest",
  input: "I will hurt you if you post that again.",
});

const verdict = result.results[0];
if (verdict.flagged) {
  const hits = Object.entries(verdict.categories).filter(([, hit]) => hit).map(([name]) => name);
  console.log("Blocked:", hits.join(", "));
} else {
  console.log("Allowed");
}

curl https://api.naga.ac/v1/moderations \
  -H "Authorization: Bearer $NAGA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "omni-moderation-latest", "input": "I will hurt you if you post that again."}'

Each entry of results has flagged, categories and category_scores. The response below is shortened to two categories:

{
  "id": "modr-8f3a2c71",
  "model": "omni-moderation-latest",
  "results": [
    {
      "flagged": true,
      "categories": {"violence": true, "harassment": false},
      "category_scores": {"violence": 0.91, "harassment": 0.12},
      "category_applied_input_types": {"violence": ["text"], "harassment": ["text"]}
    }
  ]
}

Check text and images together

model is required. input is a string, a list of strings, or a list of text and image_url parts. Parts in one list are judged together as a single input. An image is an https URL or a data: URI.

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.naga.ac/v1", api_key=os.environ["NAGA_API_KEY"])

result = client.moderations.create(
    model="omni-moderation-latest",
    input=[
        {"type": "text", "text": "Look what I found on the way home"},
        {"type": "image_url", "image_url": {"url": "https://docs.naga.ac/static/img/playground-chat.png"}},
    ],
)

verdict = result.results[0]
print(verdict.flagged, verdict.category_applied_input_types)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.naga.ac/v1", apiKey: process.env.NAGA_API_KEY });

const result = await client.moderations.create({
  model: "omni-moderation-latest",
  input: [
    { type: "text", text: "Look what I found on the way home" },
    { type: "image_url", image_url: { url: "https://docs.naga.ac/static/img/playground-chat.png" } },
  ],
});

const verdict = result.results[0];
console.log(verdict.flagged, verdict.category_applied_input_types);

omni-moderation-latest also returns category_applied_input_types, which says whether text, an image or both triggered each category. Other models, such as mistral-moderation, have their own category set, so read categories from the response instead of hard-coding names.

Billing

NagaAI charges each image_url part as a flat 250 input tokens, and text by its token count. The response carries no usage field, so read the charge in your activity log. See Balance, metrics and logs.

Troubleshooting

400 `model_not_found`

The model does not exist or has no moderation operation. Check its operations in GET /v1/models.

400 with `Failed to read the file` or `Failed to validate the image`

NagaAI downloads each image URL before it moderates, and the download failed or the file is not an image. Check that the URL is public and loads in a browser, or send the image as a data: URI.

400 with `too large`

The image is over the size limit the message names. Send a smaller image.

Get started

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Product

Check a message

Check text and images together

Billing

Troubleshooting

400 `model_not_found`

400 with `Failed to read the file` or `Failed to validate the image`

400 with `too large`

​Check a message

​Check text and images together

​Billing

​Troubleshooting

​400 model_not_found

​400 with Failed to read the file or Failed to validate the image

​400 with too large

Check a message

Check text and images together

Billing

Troubleshooting

400 `model_not_found`

400 with `Failed to read the file` or `Failed to validate the image`

400 with `too large`