# Azure AI Contentsafety Java > 使用 Azure AI Content Safety SDK for Java 构建内容审核应用程序。触发词：内容安全Java、Azure内容审核、文本安全分析、图像审核Java、黑名单管理、仇恨言论检测、有害内容过滤 - Skill: `kscz0000/azure-ai-contentsafety-java` (Agent Skill) - Install (CLI): `npx skillmds@latest add kscz0000/azure-ai-contentsafety-java` - Raw SKILL.md: https://api.skillmd.com/api/skills/kscz0000/azure-ai-contentsafety-java/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: kscz0000 (https://skillmd.com/u/kscz0000) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/kscz0000/azure-ai-contentsafety-java --- # Azure AI Content Safety SDK for Java 使用 Azure AI Content Safety SDK for Java 构建内容审核应用程序。 ## 安装 ```xml com.azure azure-ai-contentsafety 1.1.0-beta.1 ``` ## 创建客户端 ### 使用 API 密钥 ```java 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(); ``` ### 使用 DefaultAzureCredential ```java import com.azure.identity.DefaultAzureCredentialBuilder; ContentSafetyClient client = new ContentSafetyClientBuilder() .credential(new DefaultAzureCredentialBuilder().build()) .endpoint(endpoint) .buildClient(); ``` ## 核心概念 ### 危害类别 | 类别 | 描述 | |----------|-------------| | Hate（仇恨） | 基于身份群体的歧视性语言 | | Sexual（性内容） | 性内容、关系、行为 | | Violence（暴力） | 身体伤害、武器、损伤 | | Self-harm（自残） | 自伤、自杀相关内容 | ### 严重程度级别 - 文本：0-7 级（默认输出 0、2、4、6） - 图像：0、2、4、6（精简级别） ## 核心模式 ### 分析文本 ```java 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()); } ``` ### 带选项分析文本 ```java AnalyzeTextOptions options = new AnalyzeTextOptions("Text to analyze") .setCategories(Arrays.asList( TextCategory.HATE, TextCategory.VIOLENCE)) .setOutputType(AnalyzeTextOutputType.EIGHT_SEVERITY_LEVELS); AnalyzeTextResult result = contentSafetyClient.analyzeText(options); ``` ### 使用黑名单分析文本 ```java 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()); } } ``` ### 分析图像 ```java import com.azure.ai.contentsafety.models.*; import com.azure.core.util.BinaryData; import java.nio.file.Files; import java.nio.file.Paths; // 从文件读取 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()); } ``` ### 从 URL 分析图像 ```java ContentSafetyImageData imageData = new ContentSafetyImageData() .setBlobUrl("https://example.com/image.jpg"); AnalyzeImageResult result = contentSafetyClient.analyzeImage( new AnalyzeImageOptions(imageData)); ``` ## 黑名单管理 ### 创建或更新黑名单 ```java 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 description = Map.of("description", "Custom blocklist"); BinaryData resource = BinaryData.fromObject(description); Response 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"); } ``` ### 添加黑名单项 ```java import com.azure.ai.contentsafety.models.*; import java.util.Arrays; List 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()); } ``` ### 列出黑名单 ```java PagedIterable blocklists = blocklistClient.listTextBlocklists(); for (TextBlocklist blocklist : blocklists) { System.out.printf("Blocklist: %s, Description: %s%n", blocklist.getName(), blocklist.getDescription()); } ``` ### 获取黑名单 ```java TextBlocklist blocklist = blocklistClient.getTextBlocklist("my-blocklist"); System.out.println("Name: " + blocklist.getName()); ``` ### 列出黑名单项 ```java PagedIterable items = blocklistClient.listTextBlocklistItems("my-blocklist"); for (TextBlocklistItem item : items) { System.out.printf("ID: %s, Text: %s%n", item.getBlocklistItemId(), item.getText()); } ``` ### 移除黑名单项 ```java List itemIds = Arrays.asList("item-id-1", "item-id-2"); blocklistClient.removeBlocklistItems( "my-blocklist", new RemoveTextBlocklistItemsOptions(itemIds)); ``` ### 删除黑名单 ```java blocklistClient.deleteTextBlocklist("my-blocklist"); ``` ## 错误处理 ```java 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()); // 常见错误码：InvalidRequestBody、ResourceNotFound、TooManyRequests } ``` ## 环境变量 ```bash CONTENT_SAFETY_ENDPOINT=https://.cognitiveservices.azure.com/ CONTENT_SAFETY_KEY= ``` ## 最佳实践 1. **黑名单延迟**：更改约需 5 分钟生效 2. **类别选择**：仅请求所需类别以降低延迟 3. **严重程度阈值**：严格审核通常拦截严重程度 >= 4 的内容 4. **批量处理**：并行处理多项以提高吞吐量 5. **缓存**：在适当场景缓存黑名单结果 ## 触发词 - "content safety Java" - "content moderation Azure" - "analyze text safety" - "image moderation Java" - "blocklist management" - "hate speech detection" - "harmful content filter" ## 何时使用 此技能适用于执行概述中描述的工作流或操作。 ## 限制 - 仅当任务明确匹配上述范围时使用此技能。 - 不要将输出视为环境特定验证、测试或专家审查的替代品。 - 如果缺少必需的输入、权限、安全边界或成功标准，请停止并请求澄清。