QuickStart: Analyze text content

บทความ
23/01/2568

Get started with the Content Safety Studio, REST API, or client SDKs to do basic text moderation. The Azure AI Content Safety service provides you with AI algorithms for flagging objectionable content. Follow these steps to try it out.

For more information on text moderation, see the Harm categories concept page. For API input limits, see the Input requirements section of the Overview.

ข้อควรระวัง

The sample data and code may contain offensive content. User discretion is advised.

Prerequisites

An Azure subscription - Create one for free
Once you have your Azure subscription, create a Content Safety resource in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, supported region (see Region availability), and supported pricing tier. Then select Create.
- The resource takes a few minutes to deploy. After it finishes, Select go to resource. In the left pane, under Resource Management, select Subscription Key and Endpoint. The endpoint and either of the keys are used to call APIs.
cURL installed

Analyze text content

The following section walks through a sample request with cURL. Paste the command below into a text editor, and make the following changes.

Replace <endpoint> with the endpoint URL associated with your resource.
Replace <your_subscription_key> with one of the keys that come with your resource.
Optionally, replace the "text" field in the body with your own text you'd like to analyze.

เคล็ดลับ

Text size and granularity

See Input requirements for maximum text length limitations.

shell

curl --location --request POST '<endpoint>/contentsafety/text:analyze?api-version=2024-09-01' \
--header 'Ocp-Apim-Subscription-Key: <your_subscription_key>' \
--header 'Content-Type: application/json' \
--data-raw '{
  "text": "I hate you",
  "categories": ["Hate", "Sexual", "SelfHarm", "Violence"],
  "blocklistNames": ["string"],
  "haltOnBlocklistHit": true,
  "outputType": "FourSeverityLevels"
}'

The below fields must be included in the url:

Name	Required	Description	Type
API Version	Required	This is the API version to be checked. The current version is: api-version=2024-09-01. Example: `<endpoint>/contentsafety/text:analyze?api-version=2024-09-01`	String

The parameters in the request body are defined in this table:

Name	Required	Description	Type
text	Required	This is the raw text to be checked. Other non-ascii characters can be included.	String
categories	Optional	This is assumed to be an array of category names. See the Harm categories guide for a list of available category names. If no categories are specified, all four categories are used. We use multiple categories to get scores in a single request.	String
blocklistNames	Optional	Text blocklist Name. Only support following characters: `0-9 A-Z a-z - . _ ~`. You could attach multiple list names here.	Array
haltOnBlocklistHit	Optional	When set to `true`, further analyses of harmful content won't be performed in cases where blocklists are hit. When set to `false`, all analyses of harmful content will be performed, whether or not blocklists are hit.	Boolean
outputType	Optional	`"FourSeverityLevels"` or `"EightSeverityLevels"`. Output severities in four or eight levels, the value can be `0,2,4,6` or `0,1,2,3,4,5,6,7`.	String

See the following sample request body:

JSON

{
  "text": "I hate you",
  "categories": ["Hate", "Sexual", "SelfHarm", "Violence"],
  "blocklistNames": ["array"],
  "haltOnBlocklistHit": false,
  "outputType": "FourSeverityLevels"
}

Open a command prompt window, paste in the edited cURL command, and run it.

Output

You should see the text moderation results displayed as JSON data in the console output. For example:

JSON

{
  "blocklistsMatch": [
    {
      "blocklistName": "string",
      "blocklistItemId": "string",
      "blocklistItemText": "string"
    }
  ],
  "categoriesAnalysis": [
    {
      "category": "Hate",
      "severity": 2
    },
    {
      "category": "SelfHarm",
      "severity": 0
    },
    {
      "category": "Sexual",
      "severity": 0
    },
    {
      "category": "Violence",
      "severity": 0
    }
  ]
}

The JSON fields in the output are defined here:

Name	Description	Type
categoriesAnalysis	Each output class that the API predicts. Classification can be multi-labeled. For example, when a text sample is run through the text moderation model, it could be classified as both sexual content and violence. Harm categories	String
Severity	The higher the severity of input content, the larger this value is.	Integer

Reference documentation | Library source code | Package (NuGet) | Samples

Prerequisites

An Azure subscription - Create one for free
The Visual Studio IDE with workload .NET desktop development enabled. Or if you don't plan on using Visual Studio IDE, you need the current version of .NET Core.
Once you have your Azure subscription, create a Content Safety resource in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, supported region (see Region availability), and supported pricing tier. Then select Create.
- The resource takes a few minutes to deploy. After it finishes, Select go to resource. In the left pane, under Resource Management, select Subscription Key and Endpoint. The endpoint and either of the keys are used to call APIs.

Set up application

Create a new C# application.

Visual Studio IDE
CLI

Open Visual Studio, and under Get started select Create a new project. Set the template filters to C#/All Platforms/Console. Select Console App (command-line application that can run on .NET on Windows, Linux and macOS) and choose Next. Update the project name to ContentSafetyQuickstart and choose Next. Select .NET 6.0 or above, and choose Create to create the project.

Install the client SDK

Once you've created a new project, install the client SDK by right-clicking on the project solution in the Solution Explorer and selecting Manage NuGet Packages. In the package manager that opens select Browse, and search for Azure.AI.ContentSafety. Select Install.

In a console window (such as cmd, PowerShell, or Bash), use the dotnet new command to create a new console app with the name content-safety-quickstart. This command creates a simple "Hello World" C# project with a single source file: Program.cs.

dotnet

dotnet new console -n content-safety-quickstart

Change your directory to the newly created app folder. You can build the application with:

dotnet

dotnet build

The build output should contain no warnings or errors.

คอนโซล

...
Build succeeded.
  0 Warning(s)
  0 Error(s)
...

Install the client SDK

Within the application directory, install the Computer Vision client SDK for .NET with the following command:

dotnet

dotnet add package Azure.AI.ContentSafety

Create environment variables

In this example, you'll write your credentials to environment variables on the local machine running the application.

To set the environment variable for your key and endpoint, open a console window and follow the instructions for your operating system and development environment.

To set the CONTENT_SAFETY_KEY environment variable, replace YOUR_CONTENT_SAFETY_KEY with one of the keys for your resource.
To set the CONTENT_SAFETY_ENDPOINT environment variable, replace YOUR_CONTENT_SAFETY_ENDPOINT with the endpoint for your resource.

ข้อสำคัญ

Use API keys with caution. Don't include the API key directly in your code, and never post it publicly. If you use an API key, store it securely in Azure Key Vault. For more information about using API keys securely in your apps, see API keys with Azure Key Vault.

For more information about AI services security, see Authenticate requests to Azure AI services.

Windows
Linux

คอนโซล

setx CONTENT_SAFETY_KEY 'YOUR_CONTENT_SAFETY_KEY'

คอนโซล

setx CONTENT_SAFETY_ENDPOINT 'YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, you might need to restart any running programs that will read the environment variables, including the console window.

Bash

export CONTENT_SAFETY_KEY='YOUR_CONTENT_SAFETY_KEY'

Bash

export CONTENT_SAFETY_ENDPOINT='YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, run source ~/.bashrc from your console window to make the changes effective.

Analyze text content

From the project directory, open the Program.cs file that was created previously. Paste in the following code:

using System;
using Azure.AI.ContentSafety;

namespace Azure.AI.ContentSafety.Dotnet.Sample
{
  class ContentSafetySampleAnalyzeText
  {
    public static void AnalyzeText()
    {
      // retrieve the endpoint and key from the environment variables created earlier
      string endpoint = Environment.GetEnvironmentVariable("CONTENT_SAFETY_ENDPOINT");
      string key = Environment.GetEnvironmentVariable("CONTENT_SAFETY_KEY");

      ContentSafetyClient client = new ContentSafetyClient(new Uri(endpoint), new AzureKeyCredential(key));

      string text = "Your input text";

      var request = new AnalyzeTextOptions(text);

      Response<AnalyzeTextResult> response;
      try
      {
          response = client.AnalyzeText(request);
      }
      catch (RequestFailedException ex)
      {
          Console.WriteLine("Analyze text failed.\nStatus code: {0}, Error code: {1}, Error message: {2}", ex.Status, ex.ErrorCode, ex.Message);
          throw;
      }

      Console.WriteLine("\nAnalyze text succeeded:");
      Console.WriteLine("Hate severity: {0}", response.Value.CategoriesAnalysis.FirstOrDefault(a => a.Category == TextCategory.Hate)?.Severity ?? 0);
      Console.WriteLine("SelfHarm severity: {0}", response.Value.CategoriesAnalysis.FirstOrDefault(a => a.Category == TextCategory.SelfHarm)?.Severity ?? 0);
      Console.WriteLine("Sexual severity: {0}", response.Value.CategoriesAnalysis.FirstOrDefault(a => a.Category == TextCategory.Sexual)?.Severity ?? 0);
      Console.WriteLine("Violence severity: {0}", response.Value.CategoriesAnalysis.FirstOrDefault(a => a.Category == TextCategory.Violence)?.Severity ?? 0);

    }
    static void Main()
    {
        AnalyzeText();
    }
  }
}

Replace "Your input text" with the text content you'd like to use.

เคล็ดลับ

Text size and granularity

See Input requirements for maximum text length limitations.

Visual Studio IDE
CLI

Build and run the application by selecting Start Debugging from the Debug menu at the top of the IDE window (or press F5).

Build and run the application from your application directory with these commands:

dotnet

dotnet build
dotnet run

Reference documentation | Library source code | Package (PyPI) | Samples |

Prerequisites

An Azure subscription - Create one for free
Once you have your Azure subscription, create a Content Safety resource in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, supported region (see Region availability), and supported pricing tier. Then select Create.
- The resource takes a few minutes to deploy. After it finishes, Select go to resource. In the left pane, under Resource Management, select Subscription Key and Endpoint. The endpoint and either of the keys are used to call APIs.
Python 3.x
- Your Python installation should include pip. You can check if you have pip installed by running pip --version on the command line. Get pip by installing the latest version of Python.

Create environment variables

In this example, you'll write your credentials to environment variables on the local machine running the application.

To set the environment variable for your key and endpoint, open a console window and follow the instructions for your operating system and development environment.

To set the CONTENT_SAFETY_KEY environment variable, replace YOUR_CONTENT_SAFETY_KEY with one of the keys for your resource.
To set the CONTENT_SAFETY_ENDPOINT environment variable, replace YOUR_CONTENT_SAFETY_ENDPOINT with the endpoint for your resource.

ข้อสำคัญ

For more information about AI services security, see Authenticate requests to Azure AI services.

Windows
Linux

คอนโซล

setx CONTENT_SAFETY_KEY 'YOUR_CONTENT_SAFETY_KEY'

คอนโซล

setx CONTENT_SAFETY_ENDPOINT 'YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, you might need to restart any running programs that will read the environment variables, including the console window.

Bash

export CONTENT_SAFETY_KEY='YOUR_CONTENT_SAFETY_KEY'

Bash

export CONTENT_SAFETY_ENDPOINT='YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, run source ~/.bashrc from your console window to make the changes effective.

Analyze text content

The following section walks through a sample request with the Python SDK.

Open a command prompt, navigate to your project folder, and create a new file named quickstart.py.
Run this command to install the Azure AI Content Safety library:

คอนโซล
```
pip install azure-ai-contentsafety
```

Copy the following code into quickstart.py:

Python

import os
from azure.ai.contentsafety import ContentSafetyClient
from azure.core.credentials import AzureKeyCredential
from azure.core.exceptions import HttpResponseError
from azure.ai.contentsafety.models import AnalyzeTextOptions, TextCategory

def analyze_text():
    # analyze text
    key = os.environ["CONTENT_SAFETY_KEY"]
    endpoint = os.environ["CONTENT_SAFETY_ENDPOINT"]

    # Create an Azure AI Content Safety client
    client = ContentSafetyClient(endpoint, AzureKeyCredential(key))

    # Contruct request
    request = AnalyzeTextOptions(text="Your input text")

    # Analyze text
    try:
        response = client.analyze_text(request)
    except HttpResponseError as e:
        print("Analyze text failed.")
        if e.error:
            print(f"Error code: {e.error.code}")
            print(f"Error message: {e.error.message}")
            raise
        print(e)
        raise

    hate_result = next(item for item in response.categories_analysis if item.category == TextCategory.HATE)
    self_harm_result = next(item for item in response.categories_analysis if item.category == TextCategory.SELF_HARM)
    sexual_result = next(item for item in response.categories_analysis if item.category == TextCategory.SEXUAL)
    violence_result = next(item for item in response.categories_analysis if item.category == TextCategory.VIOLENCE)

    if hate_result:
        print(f"Hate severity: {hate_result.severity}")
    if self_harm_result:
        print(f"SelfHarm severity: {self_harm_result.severity}")
    if sexual_result:
        print(f"Sexual severity: {sexual_result.severity}")
    if violence_result:
        print(f"Violence severity: {violence_result.severity}")

if __name__ == "__main__":
    analyze_text()

Replace "Your input text" with the text content you'd like to use.

เคล็ดลับ

Text size and granularity

See Input requirements for maximum text length limitations.
Then run the application with the python command on your quickstart file.

คอนโซล
```
python quickstart.py
```

Reference documentation | Library source code | Artifact (Maven) | Samples

Prerequisites

An Azure subscription - Create one for free
The current version of the Java Development Kit (JDK)
The Gradle build tool, or another dependency manager.
Once you have your Azure subscription, create a Content Safety resource in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, supported region (see Region availability), and supported pricing tier. Then select Create.
- The resource takes a few minutes to deploy. After it finishes, Select go to resource. In the left pane, under Resource Management, select Subscription Key and Endpoint. The endpoint and either of the keys are used to call APIs.

Set up application

Create a new Gradle project.

In a console window (such as cmd, PowerShell, or Bash), create a new directory for your app, and navigate to it.

คอนโซล

mkdir myapp && cd myapp

Run the gradle init command from your working directory. This command will create essential build files for Gradle, including build.gradle.kts, which is used at runtime to create and configure your application.

คอนโซล

gradle init --type basic

When prompted to choose a DSL, select Kotlin.

From your working directory, run the following command to create a project source folder:

คอนโซล

mkdir -p src/main/java

Navigate to the new folder and create a file called ContentSafetyQuickstart.java.

Install the client SDK

This quickstart uses the Gradle dependency manager. You can find the client library and information for other dependency managers on the Maven Central Repository.

Locate build.gradle.kts and open it with your preferred IDE or text editor. Then copy in the following build configuration. This configuration defines the project as a Java application whose entry point is the class ContentSafetyQuickstart. It imports the Azure AI Vision library.

Kotlin

plugins {
    java
    application
}
application { 
    mainClass.set("ContentSafetyQuickstart")
}
repositories {
    mavenCentral()
}
dependencies {
    implementation(group = "com.azure", name = "azure-ai-contentsafety", version = "1.0.0")
}

Create environment variables

In this example, you'll write your credentials to environment variables on the local machine running the application.

To set the environment variable for your key and endpoint, open a console window and follow the instructions for your operating system and development environment.

To set the CONTENT_SAFETY_KEY environment variable, replace YOUR_CONTENT_SAFETY_KEY with one of the keys for your resource.
To set the CONTENT_SAFETY_ENDPOINT environment variable, replace YOUR_CONTENT_SAFETY_ENDPOINT with the endpoint for your resource.

ข้อสำคัญ

For more information about AI services security, see Authenticate requests to Azure AI services.

Windows
Linux

คอนโซล

setx CONTENT_SAFETY_KEY 'YOUR_CONTENT_SAFETY_KEY'

คอนโซล

setx CONTENT_SAFETY_ENDPOINT 'YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, you might need to restart any running programs that will read the environment variables, including the console window.

Bash

export CONTENT_SAFETY_KEY='YOUR_CONTENT_SAFETY_KEY'

Bash

export CONTENT_SAFETY_ENDPOINT='YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, run source ~/.bashrc from your console window to make the changes effective.

Analyze text content

Open ContentSafetyQuickstart.java in your preferred editor or IDE and paste in the following code. Replace <your text sample> with the text content you'd like to use.

เคล็ดลับ

Text size and granularity

See Input requirements for maximum text length limitations.

Java

import com.azure.ai.contentsafety.ContentSafetyClient;
import com.azure.ai.contentsafety.ContentSafetyClientBuilder;
import com.azure.ai.contentsafety.models.AnalyzeTextOptions;
import com.azure.ai.contentsafety.models.AnalyzeTextResult;
import com.azure.ai.contentsafety.models.TextCategoriesAnalysis;
import com.azure.core.credential.KeyCredential;
import com.azure.core.util.Configuration;


public class ContentSafetyQuickstart {
    public static void main(String[] args) {

        // get endpoint and key from environment variables
        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();

        AnalyzeTextResult response = contentSafetyClient.analyzeText(new AnalyzeTextOptions("<your text sample>"));

        for (TextCategoriesAnalysis result : response.getCategoriesAnalysis()) {
            System.out.println(result.getCategory() + " severity: " + result.getSeverity());
        }
    }
}

Navigate back to the project root folder, and build the app with:

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gradle build

Then, run it with the gradle run command:

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gradle run

Output

คอนโซล

Hate severity: 0
SelfHarm severity: 0
Sexual severity: 0
Violence severity: 0

Reference documentation | Library source code | Package (npm) | Samples |

Prerequisites

An Azure subscription - Create one for free
The current version of Node.js
Once you have your Azure subscription, create a Content Safety resource in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, supported region (see Region availability), and supported pricing tier. Then select Create.
- The resource takes a few minutes to deploy. After it finishes, Select go to resource. In the left pane, under Resource Management, select Subscription Key and Endpoint. The endpoint and either of the keys are used to call APIs.

Set up application

Create a new Node.js application. In a console window (such as cmd, PowerShell, or Bash), create a new directory for your app, and navigate to it.

คอนโซล

mkdir myapp && cd myapp

Run the npm init command to create a node application with a package.json file.

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npm init

Install the client SDK

Install the @azure-rest/ai-content-safety npm package:

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npm install @azure-rest/ai-content-safety

Also install the dotenv module to use environment variables:

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npm install dotenv

Your app's package.json file will be updated with the dependencies.

Create environment variables

In this example, you'll write your credentials to environment variables on the local machine running the application.

To set the environment variable for your key and endpoint, open a console window and follow the instructions for your operating system and development environment.

To set the CONTENT_SAFETY_KEY environment variable, replace YOUR_CONTENT_SAFETY_KEY with one of the keys for your resource.
To set the CONTENT_SAFETY_ENDPOINT environment variable, replace YOUR_CONTENT_SAFETY_ENDPOINT with the endpoint for your resource.

ข้อสำคัญ

For more information about AI services security, see Authenticate requests to Azure AI services.

Windows
Linux

คอนโซล

setx CONTENT_SAFETY_KEY 'YOUR_CONTENT_SAFETY_KEY'

คอนโซล

setx CONTENT_SAFETY_ENDPOINT 'YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, you might need to restart any running programs that will read the environment variables, including the console window.

Bash

export CONTENT_SAFETY_KEY='YOUR_CONTENT_SAFETY_KEY'

Bash

export CONTENT_SAFETY_ENDPOINT='YOUR_CONTENT_SAFETY_ENDPOINT'

After you add the environment variables, run source ~/.bashrc from your console window to make the changes effective.

Analyze text content

Create a new file in your directory, index.js. Open it in your preferred editor or IDE and paste in the following code. Replace <your text sample> with the text content you'd like to use.

เคล็ดลับ

Text size and granularity

See Input requirements for maximum text length limitations.

JavaScript

const ContentSafetyClient = require("@azure-rest/ai-content-safety").default,
  { isUnexpected } = require("@azure-rest/ai-content-safety");
const { AzureKeyCredential } = require("@azure/core-auth");

// Load the .env file if it exists
require("dotenv").config();

async function main() {
    // get endpoint and key from environment variables
    const endpoint = process.env["CONTENT_SAFETY_ENDPOINT"];
    const key = process.env["CONTENT_SAFETY_KEY"];
    
    const credential = new AzureKeyCredential(key);
    const client = ContentSafetyClient(endpoint, credential);
    
    // replace with your own sample text string 
    const text = "<your sample text>";
    const analyzeTextOption = { text: text };
    const analyzeTextParameters = { body: analyzeTextOption };
    
    const result = await client.path("/text:analyze").post(analyzeTextParameters);
    
    if (isUnexpected(result)) {
        throw result;
    }
    
    for (let i = 0; i < result.body.categoriesAnalysis.length; i++) {
    const textCategoriesAnalysisOutput = result.body.categoriesAnalysis[i];
    console.log(
      textCategoriesAnalysisOutput.category,
      " severity: ",
      textCategoriesAnalysisOutput.severity
    );
  }
}

main().catch((err) => {
    console.error("The sample encountered an error:", err);
});

Run the application with the node command on your quickstart file.

คอนโซล

node index.js

Output

คอนโซล

Hate severity:  0
SelfHarm severity:  0
Sexual severity:  0
Violence severity:  0

Clean up resources

If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.

Harm categories
Configure filters for each category and test on datasets using Content Safety Studio, export the code and deploy.

แหล่งทรัพยากรเพิ่มเติม

เอกสาร

Harm categories in Azure AI Content Safety - Azure AI services

Learn about the different content moderation flags and severity levels that the Azure AI Content Safety service returns.
Quickstart: Analyze image content - Azure AI services

Get started using Azure AI Content Safety to analyze image content for objectionable material.
Quickstart: Custom categories (preview) - Azure AI services

Use the custom categories API to create your own content categories and train the Content Safety model for your use case.
Use blocklists for text moderation - Azure AI services

Learn how to customize text moderation in Azure AI Content Safety by using your own list of blocklistItems.
Quickstart: Content Safety Studio - Azure AI services

Learn how to get started with the Content Safety service using Content Safety Studio in your browser.
Frequently asked questions - Azure AI Content Safety - Azure AI services

Get answers to frequently asked questions about Azure AI Content Safety.
Language support - Azure AI Content Safety - Azure AI services

This is a list of natural languages that the Azure AI Content Safety API supports.
Azure AI Content Safety documentation - Quickstarts, Tutorials, API Reference - Azure AI services

The cloud-based Azure AI Content Safety API provides developers with access to advanced algorithms for processing images and text and flagging content that is potentially offensive, risky, or otherwise undesirable.

การฝึกอบรม

โมดูล

Use AI responsibly with Azure AI Content Safety - Training

As the amount of user-generated online content increases, so does the need to ensure harmful material is moderated effectively. Azure AI Content Safety resource includes features to help organizations moderate and manage both user-generated and AI-generated content.

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ลงทะเบียนตอนนี้

แชร์ผ่าน

QuickStart: Analyze text content

Prerequisites

Analyze text content

Output

Prerequisites

Set up application

Install the client SDK

Install the client SDK

Create environment variables

Analyze text content

Prerequisites

Create environment variables

Analyze text content

Prerequisites

Set up application

Install the client SDK

Create environment variables

Analyze text content

Output

Prerequisites

Set up application

Install the client SDK

Create environment variables

Analyze text content

Output

Clean up resources

คำติชม

แหล่งทรัพยากรเพิ่มเติม

แชร์ผ่าน

QuickStart: Analyze text content

Prerequisites

Analyze text content

Output

Prerequisites

Set up application

Install the client SDK

Create environment variables

Analyze text content

Prerequisites

Create environment variables

Analyze text content

Prerequisites

Set up application

Install the client SDK

Create environment variables

Analyze text content

Output

Prerequisites

Set up application

Install the client SDK

Create environment variables

Analyze text content

Output

Clean up resources

Related content

คำติชม

แหล่งทรัพยากรเพิ่มเติม