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Azure AI Content Safety

Free

Moderate content using Azure's AI capabilities in Java.

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Free · Opens the source repo

What Azure AI Content Safety does

The Azure AI Content Safety SDK for Java provides developers with the tools to create content moderation applications that can analyze text and images for harmful content. This SDK is particularly useful for applications that require user-generated content to be monitored for safety, ensuring that harmful or inappropriate material is flagged before it reaches users. With the SDK, developers can integrate content safety features directly into their Java applications, leveraging Azure's powerful AI capabilities.

The SDK supports various harm categories, including hate speech, sexual content, violence, and self-harm, allowing developers to tailor their applications to specific moderation needs. The severity of detected content is classified on a scale, enabling nuanced responses based on the level of risk associated with the content. This is crucial for applications in sensitive environments where user safety is paramount.

Developers can easily create clients to interact with the Azure AI Content Safety service, using either API keys or Azure's DefaultAzureCredential for authentication. The SDK provides straightforward methods for analyzing text and images, as well as managing blocklists to prevent specific terms or phrases from being displayed. This functionality is essential for maintaining community standards and ensuring a safe user experience.

Overall, the Azure AI Content Safety SDK is designed for developers looking to implement content moderation solutions efficiently, making it a valuable tool for any application that interacts with user-generated content.

When to use it

Use this SDK when building applications that require moderation of user-generated content, such as social media platforms, forums, or any interactive environments.

When not to use it

This SDK may not be suitable for applications that do not involve user-generated content or where content moderation is not a concern.

What you can build with it

Social Media Application

Integrate the SDK to moderate comments and posts, ensuring harmful content is filtered before publication.

Online Forum

Use the SDK to analyze user submissions for inappropriate language, maintaining a safe community environment.

Content Sharing Platform

Implement the SDK to check images and text for safety, preventing the sharing of harmful content.

How to install Azure AI Content Safety

View source

1. Install with the skills CLI

npx skills add sickn33/agentic-awesome-skills/azure-ai-contentsafety-java --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by sickn33

Azure AI Content Safety SDK for Java

Build content moderation applications using the Azure AI Content Safety SDK for Java.

Installation

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-ai-contentsafety</artifactId>
    <version>1.1.0-beta.1</version>
</dependency>

Client Creation

With API Key

import com.azure.ai.contentsafety.ContentSafetyClient;
import com.azure.ai.contentsafety.ContentSafetyClientBuilder;
import com.azure.ai.contentsafety.BlocklistClient;
import com.azure.ai.contentsafety.BlocklistClientBuilder;
import com.azure.core.credential.KeyCredential;

String endpoint = System.getenv("CONTENT_SAFETY_ENDPOINT");
String key = System.getenv("CONTENT_SAFETY_KEY");

ContentSafetyClient contentSafetyClient = new ContentSafetyClientBuilder()
    .credential(new KeyCredential(key))
    .endpoint(endpoint)
    .buildClient();

BlocklistClient blocklistClient = new BlocklistClientBuilder()
    .credential(new KeyCredential(key))
    .endpoint(endpoint)
    .buildClient();

With DefaultAzureCredential

import com.azure.identity.DefaultAzureCredentialBuilder;

ContentSafetyClient client = new ContentSafetyClientBuilder()
    .credential(new DefaultAzureCredentialBuilder().build())
    .endpoint(endpoint)
    .buildClient();

Key Concepts

Harm Categories

CategoryDescription
HateDiscriminatory language based on identity groups
SexualSexual content, relationships, acts
ViolencePhysical harm, weapons, injury
Self-harmSelf-injury, suicide-related content

Severity Levels

  • Text: 0-7 scale (default outputs 0, 2, 4, 6)
  • Image: 0, 2, 4, 6 (trimmed scale)

Core Patterns

Analyze Text

import com.azure.ai.contentsafety.models.*;

AnalyzeTextResult result = contentSafetyClient.analyzeText(
    new AnalyzeTextOptions("This is text to analyze"));

for (TextCategoriesAnalysis category : result.getCategoriesAnalysis()) {
    System.out.printf("Category: %s, Severity: %d%n",
        category.getCategory(),
        category.getSeverity());
}

Analyze Text with Options

AnalyzeTextOptions options = new AnalyzeTextOptions("Text to analyze")
    .setCategories(Arrays.asList(
        TextCategory.HATE,
        TextCategory.VIOLENCE))
    .setOutputType(AnalyzeTextOutputType.EIGHT_SEVERITY_LEVELS);

AnalyzeTextResult result = contentSafetyClient.analyzeText(options);

Analyze Text with Blocklist

AnalyzeTextOptions options = new AnalyzeTextOptions("I h*te you and want to k*ll you")
    .setBlocklistNames(Arrays.asList("my-blocklist"))
    .setHaltOnBlocklistHit(true);

AnalyzeTextResult result = contentSafetyClient.analyzeText(options);

if (result.getBlocklistsMatch() != null) {
    for (TextBlocklistMatch match : result.getBlocklistsMatch()) {
        System.out.printf("Blocklist: %s, Item: %s, Text: %s%n",
            match.getBlocklistName(),
            match.getBlocklistItemId(),
            match.getBlocklistItemText());
    }
}

Analyze Image

import com.azure.ai.contentsafety.models.*;
import com.azure.core.util.BinaryData;
import java.nio.file.Files;
import java.nio.file.Paths;

// From file
byte[] imageBytes = Files.readAllBytes(Paths.get("image.png"));
ContentSafetyImageData imageData = new ContentSafetyImageData()
    .setContent(BinaryData.fromBytes(imageBytes));

AnalyzeImageResult result = contentSafetyClient.analyzeImage(
    new AnalyzeImageOptions(imageData));

for (ImageCategoriesAnalysis category : result.getCategoriesAnalysis()) {
    System.out.printf("Category: %s, Severity: %d%n",
        category.getCategory(),
        category.getSeverity());
}

Analyze Image from URL

ContentSafetyImageData imageData = new ContentSafetyImageData()
    .setBlobUrl("https://example.com/image.jpg");

AnalyzeImageResult result = contentSafetyClient.analyzeImage(
    new AnalyzeImageOptions(imageData));

Blocklist Management

Create or Update Blocklist

import com.azure.core.http.rest.RequestOptions;
import com.azure.core.http.rest.Response;
import com.azure.core.util.BinaryData;
import java.util.Map;

Map<String, String> description = Map.of("description", "Custom blocklist");
BinaryData resource = BinaryData.fromObject(description);

Response<BinaryData> response = blocklistClient.createOrUpdateTextBlocklistWithResponse(
    "my-blocklist", resource, new RequestOptions());

if (response.getStatusCode() == 201) {
    System.out.println("Blocklist created");
} else if (response.getStatusCode() == 200) {
    System.out.println("Blocklist updated");
}

Add Block Items

import com.azure.ai.contentsafety.models.*;
import java.util.Arrays;

List<TextBlocklistItem> items = Arrays.asList(
    new TextBlocklistItem("badword1").setDescription("Offensive term"),
    new TextBlocklistItem("badword2").setDescription("Another term")
);

AddOrUpdateTextBlocklistItemsResult result = blocklistClient.addOrUpdateBlocklistItems(
    "my-blocklist",
    new AddOrUpdateTextBlocklistItemsOptions(items));

for (TextBlocklistItem item : result.getBlocklistItems()) {
    System.out.printf("Added: %s (ID: %s)%n",
        item.getText(),
        item.getBlocklistItemId());
}

List Blocklists

PagedIterable<TextBlocklist> blocklists = blocklistClient.listTextBlocklists();

for (TextBlocklist blocklist : blocklists) {
    System.out.printf("Blocklist: %s, Description: %s%n",
        blocklist.getName(),
        blocklist.getDescription());
}

Get Blocklist

TextBlocklist blocklist = blocklistClient.getTextBlocklist("my-blocklist");
System.out.println("Name: " + blocklist.getName());

List Block Items

PagedIterable<TextBlocklistItem> items = 
    blocklistClient.listTextBlocklistItems("my-blocklist");

for (TextBlocklistItem item : items) {
    System.out.printf("ID: %s, Text: %s%n",
        item.getBlocklistItemId(),
        item.getText());
}

Remove Block Items

List<String> itemIds = Arrays.asList("item-id-1", "item-id-2");

blocklistClient.removeBlocklistItems(
    "my-blocklist",
    new RemoveTextBlocklistItemsOptions(itemIds));

Delete Blocklist

blocklistClient.deleteTextBlocklist("my-blocklist");

Error Handling

import com.azure.core.exception.HttpResponseException;

try {
    contentSafetyClient.analyzeText(new AnalyzeTextOptions("test"));
} catch (HttpResponseException e) {
    System.out.println("Status: " + e.getResponse().getStatusCode());
    System.out.println("Error: " + e.getMessage());
    // Common codes: InvalidRequestBody, ResourceNotFound, TooManyRequests
}

Environment Variables

CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com/
CONTENT_SAFETY_KEY=<your-api-key>

Best Practices

  1. Blocklist Delay: Changes take ~5 minutes to take effect
  2. Category Selection: Only request needed categories to reduce latency
  3. Severity Thresholds: Typically block severity >= 4 for strict moderation
  4. Batch Processing: Process multiple items in parallel for throughput
  5. Caching: Cache blocklist results where appropriate

Trigger Phrases

  • "content safety Java"
  • "content moderation Azure"
  • "analyze text safety"
  • "image moderation Java"
  • "blocklist management"
  • "hate speech detection"
  • "harmful content filter"

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Frequently asked questions about Azure AI Content Safety

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