Microsoft Azure AI Contentsafety TS

Azure AI Content Safety REST SDK for TypeScript

Analyze text and images for harmful content with customizable blocklists.

Installation

npm install @azure-rest/ai-content-safety @azure/identity @azure/core-auth

Environment Variables

CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com
CONTENT_SAFETY_KEY=<api-key>
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication

Important: This is a REST client. ContentSafetyClient is a function, not a class.

API Key

import ContentSafetyClient from "@azure-rest/ai-content-safety";
import { AzureKeyCredential } from "@azure/core-auth";

const client = ContentSafetyClient(
  process.env.CONTENT_SAFETY_ENDPOINT!,
  new AzureKeyCredential(process.env.CONTENT_SAFETY_KEY!)
);

DefaultAzureCredential

import ContentSafetyClient from "@azure-rest/ai-content-safety";
import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes
// const credential = new ManagedIdentityCredential();

const client = ContentSafetyClient(
  process.env.CONTENT_SAFETY_ENDPOINT!,
  credential
);

Analyze Text

import ContentSafetyClient, { isUnexpected } from "@azure-rest/ai-content-safety";

const result = await client.path("/text:analyze").post({
  body: {
    text: "Text content to analyze",
    categories: ["Hate", "Sexual", "Violence", "SelfHarm"],
    outputType: "FourSeverityLevels"  // or "EightSeverityLevels"
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

for (const analysis of result.body.categoriesAnalysis) {
  console.log(`${analysis.category}: severity ${analysis.severity}`);
}

Analyze Image

Base64 Content

import { readFileSync } from "node:fs";

const imageBuffer = readFileSync("./image.png");
const base64Image = imageBuffer.toString("base64");

const result = await client.path("/image:analyze").post({
  body: {
    image: { content: base64Image }
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

for (const analysis of result.body.categoriesAnalysis) {
  console.log(`${analysis.category}: severity ${analysis.severity}`);
}

Blob URL

const result = await client.path("/image:analyze").post({
  body: {
    image: { blobUrl: "https://storage.blob.core.windows.net/container/image.png" }
  }
});

Blocklist Management

Create Blocklist

const result = await client
  .path("/text/blocklists/{blocklistName}", "my-blocklist")
  .patch({
    contentType: "application/merge-patch+json",
    body: {
      description: "Custom blocklist for prohibited terms"
    }
  });

if (isUnexpected(result)) {
  throw result.body;
}

console.log(`Created: ${result.body.blocklistName}`);

Add Items to Blocklist

const result = await client
  .path("/text/blocklists/{blocklistName}:addOrUpdateBlocklistItems", "my-blocklist")
  .post({
    body: {
      blocklistItems: [
        { text: "prohibited-term-1", description: "First blocked term" },
        { text: "prohibited-term-2", description: "Second blocked term" }
      ]
    }
  });

if (isUnexpected(result)) {
  throw result.body;
}

for (const item of result.body.blocklistItems ?? []) {
  console.log(`Added: ${item.blocklistItemId}`);
}

Analyze with Blocklist

const result = await client.path("/text:analyze").post({
  body: {
    text: "Text that might contain blocked terms",
    blocklistNames: ["my-blocklist"],
    haltOnBlocklistHit: false
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

// Check blocklist matches
if (result.body.blocklistsMatch) {
  for (const match of result.body.blocklistsMatch) {
    console.log(`Blocked: "${match.blocklistItemText}" from ${match.blocklistName}`);
  }
}

List Blocklists

const result = await client.path("/text/blocklists").get();

if (isUnexpected(result)) {
  throw result.body;
}

for (const blocklist of result.body.value ?? []) {
  console.log(`${blocklist.blocklistName}: ${blocklist.description}`);
}

Delete Blocklist

await client.path("/text/blocklists/{blocklistName}", "my-blocklist").delete();

Harm Categories

Severity Levels

Output Types:

• FourSeverityLevels (default): Returns 0, 2, 4, 6
• EightSeverityLevels: Returns 0-7

Content Moderation Helper

import ContentSafetyClient, { 
  isUnexpected, 
  TextCategoriesAnalysisOutput 
} from "@azure-rest/ai-content-safety";

interface ModerationResult {
  isAllowed: boolean;
  flaggedCategories: string[];
  maxSeverity: number;
  blocklistMatches: string[];
}

async function moderateContent(
  client: ReturnType<typeof ContentSafetyClient>,
  text: string,
  maxAllowedSeverity = 2,
  blocklistNames: string[] = []
): Promise<ModerationResult> {
  const result = await client.path("/text:analyze").post({
    body: { text, blocklistNames, haltOnBlocklistHit: false }
  });

  if (isUnexpected(result)) {
    throw result.body;
  }

  const flaggedCategories = result.body.categoriesAnalysis
    .filter(c => (c.severity ?? 0) > maxAllowedSeverity)
    .map(c => c.category!);

  const maxSeverity = Math.max(
    ...result.body.categoriesAnalysis.map(c => c.severity ?? 0)
  );

  const blocklistMatches = (result.body.blocklistsMatch ?? [])
    .map(m => m.blocklistItemText!);

  return {
    isAllowed: flaggedCategories.length === 0 && blocklistMatches.length === 0,
    flaggedCategories,
    maxSeverity,
    blocklistMatches
  };
}

API Endpoints

Key Types

import ContentSafetyClient, {
  isUnexpected,
  AnalyzeTextParameters,
  AnalyzeImageParameters,
  TextCategoriesAnalysisOutput,
  ImageCategoriesAnalysisOutput,
  TextBlocklist,
  TextBlocklistItem
} from "@azure-rest/ai-content-safety";

Best Practices

1. Always use isUnexpected() - Type guard for error handling
2. Set appropriate thresholds - Different categories may need different severity thresholds
3. Use blocklists for domain-specific terms - Supplement AI detection with custom rules
4. Log moderation decisions - Keep audit trail for compliance
5. Handle edge cases - Empty text, very long text, unsupported image formats