# Azure AI Contentsafety Py

> Azure AI 内容安全 Python SDK。用于检测文本和图像中的有害内容，支持多级别严重性分类。触发词：内容安全、内容审核、有害内容检测、文本审核、图像审核、Azure Content Safety、内容过滤、仇恨言论检测、暴力内容检测、自残检测、色情内容检测

- Skill: `kscz0000/azure-ai-contentsafety-py` (Agent Skill)
- Install (CLI): `npx skillmds@latest add kscz0000/azure-ai-contentsafety-py`
- Raw SKILL.md: https://api.skillmd.com/api/skills/kscz0000/azure-ai-contentsafety-py/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-py

---


# Azure AI Content Safety SDK for Python

检测应用程序中的有害用户生成内容和 AI 生成内容。

## 安装

```bash
pip install azure-ai-contentsafety
```

## 环境变量

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

## 身份认证

### API 密钥

```python
from azure.ai.contentsafety import ContentSafetyClient
from azure.core.credentials import AzureKeyCredential
import os

client = ContentSafetyClient(
    endpoint=os.environ["CONTENT_SAFETY_ENDPOINT"],
    credential=AzureKeyCredential(os.environ["CONTENT_SAFETY_KEY"])
)
```

### Entra ID

```python
from azure.ai.contentsafety import ContentSafetyClient
from azure.identity import DefaultAzureCredential

client = ContentSafetyClient(
    endpoint=os.environ["CONTENT_SAFETY_ENDPOINT"],
    credential=DefaultAzureCredential()
)
```

## 分析文本

```python
from azure.ai.contentsafety import ContentSafetyClient
from azure.ai.contentsafety.models import AnalyzeTextOptions, TextCategory
from azure.core.credentials import AzureKeyCredential

client = ContentSafetyClient(endpoint, AzureKeyCredential(key))

request = AnalyzeTextOptions(text="Your text content to analyze")
response = client.analyze_text(request)

# 检查每个类别
for category in [TextCategory.HATE, TextCategory.SELF_HARM, 
                 TextCategory.SEXUAL, TextCategory.VIOLENCE]:
    result = next((r for r in response.categories_analysis 
                   if r.category == category), None)
    if result:
        print(f"{category}: severity {result.severity}")
```

## 分析图像

```python
from azure.ai.contentsafety import ContentSafetyClient
from azure.ai.contentsafety.models import AnalyzeImageOptions, ImageData
from azure.core.credentials import AzureKeyCredential
import base64

client = ContentSafetyClient(endpoint, AzureKeyCredential(key))

# 从文件
with open("image.jpg", "rb") as f:
    image_data = base64.b64encode(f.read()).decode("utf-8")

request = AnalyzeImageOptions(
    image=ImageData(content=image_data)
)

response = client.analyze_image(request)

for result in response.categories_analysis:
    print(f"{result.category}: severity {result.severity}")
```

### 从 URL 分析图像

```python
from azure.ai.contentsafety.models import AnalyzeImageOptions, ImageData

request = AnalyzeImageOptions(
    image=ImageData(blob_url="https://example.com/image.jpg")
)

response = client.analyze_image(request)
```

## 文本黑名单管理

### 创建黑名单

```python
from azure.ai.contentsafety import BlocklistClient
from azure.ai.contentsafety.models import TextBlocklist
from azure.core.credentials import AzureKeyCredential

blocklist_client = BlocklistClient(endpoint, AzureKeyCredential(key))

blocklist = TextBlocklist(
    blocklist_name="my-blocklist",
    description="Custom terms to block"
)

result = blocklist_client.create_or_update_text_blocklist(
    blocklist_name="my-blocklist",
    options=blocklist
)
```

### 添加黑名单项

```python
from azure.ai.contentsafety.models import AddOrUpdateTextBlocklistItemsOptions, TextBlocklistItem

items = AddOrUpdateTextBlocklistItemsOptions(
    blocklist_items=[
        TextBlocklistItem(text="blocked-term-1"),
        TextBlocklistItem(text="blocked-term-2")
    ]
)

result = blocklist_client.add_or_update_blocklist_items(
    blocklist_name="my-blocklist",
    options=items
)
```

### 使用黑名单分析

```python
from azure.ai.contentsafety.models import AnalyzeTextOptions

request = AnalyzeTextOptions(
    text="Text containing blocked-term-1",
    blocklist_names=["my-blocklist"],
    halt_on_blocklist_hit=True
)

response = client.analyze_text(request)

if response.blocklists_match:
    for match in response.blocklists_match:
        print(f"Blocked: {match.blocklist_item_text}")
```

## 严重性级别

文本分析默认返回 4 个严重性级别（0、2、4、6）。如需 8 个级别（0-7）：

```python
from azure.ai.contentsafety.models import AnalyzeTextOptions, AnalyzeTextOutputType

request = AnalyzeTextOptions(
    text="Your text",
    output_type=AnalyzeTextOutputType.EIGHT_SEVERITY_LEVELS
)
```

## 有害内容类别

| 类别 | 描述 |
|----------|-------------|
| `Hate` | 基于身份的攻击（种族、宗教、性别等） |
| `Sexual` | 色情内容、两性关系、身体部位 |
| `Violence` | 身体伤害、武器、伤害行为 |
| `SelfHarm` | 自残、自杀、饮食失调 |

## 严重性等级

| 级别 | 文本范围 | 图像范围 | 含义 |
|-------|------------|-------------|---------|
| 0 | 安全 | 安全 | 无有害内容 |
| 2 | 低 | 低 | 轻微提及 |
| 4 | 中 | 中 | 中等内容 |
| 6 | 高 | 高 | 严重内容 |

## 客户端类型

| 客户端 | 用途 |
|--------|---------|
| `ContentSafetyClient` | 分析文本和图像 |
| `BlocklistClient` | 管理自定义黑名单 |

## 最佳实践

1. **使用黑名单**处理特定领域的词汇
2. **设置严重性阈值**以适应您的使用场景
3. **处理多个类别**——内容可能以多种方式有害
4. **使用 halt_on_blocklist_hit**实现立即拒绝
5. **记录分析结果**用于审计和改进
6. **考虑 8 级严重性模式**以获得更精细的控制
7. **预审核 AI 输出**后再展示给用户

## 使用场景
本技能适用于执行概述中描述的工作流或操作。

## 限制
- 仅当任务明确符合上述范围时使用本技能。
- 输出不能替代特定环境的验证、测试或专家审查。
- 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。