azure-ai-contentsafety-java
Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.
- License 许可
- MIT
- 所属仓库
- microsoft/skills
- 最近更新
- 2026-11-12
- Stars
- ★ 3.2k
- Forks
- 365
01 前言 Front Matter
- name
- azure-ai-contentsafety-java
- license
- MIT
- metadata
- { "author": "Microsoft", "package": "com.azure:azure-ai-contentsafety", "version": "1.0.0" }
- description
- Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.
02 资源文件 2
- 许可证LICENSE.txt11.1 KB
- 参考文档references/examples.md17.0 KB
03 SKILL.md 正文
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.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;
TokenCredential credential = new DefaultAzureCredentialBuilder()
.requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
.build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();
ContentSafetyClient client = new ContentSafetyClientBuilder()
.credential(credential)
.endpoint(endpoint)
.buildClient();
Key Concepts
Harm Categories
| Category | Description |
|---|---|
| Hate | Discriminatory language based on identity groups |
| Sexual | Sexual content, relationships, acts |
| Violence | Physical harm, weapons, injury |
| Self-harm | Self-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/ # Required for all auth methods
CONTENT_SAFETY_KEY=<your-api-key> # Only required for AzureKeyCredential auth
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
Best Practices
- Blocklist Delay: Changes take ~5 minutes to take effect
- Category Selection: Only request needed categories to reduce latency
- Severity Thresholds: Typically block severity >= 4 for strict moderation
- Batch Processing: Process multiple items in parallel for throughput
- 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"
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