Update ai-core-orchestration-consumption-opt.md

I321506 · I321506 · commit 1348ce62eab4 · 2025-05-23T13:22:39.000+08:00
diff --git a/tutorials/ai-core-orchestration-consumption-opt/ai-core-orchestration-consumption-opt.md b/tutorials/ai-core-orchestration-consumption-opt/ai-core-orchestration-consumption-opt.md
@@ -9,7 +9,7 @@ author_profile: https://github.com/I321506
 ---
 
 # Leveraging Orchestration Capabilities to Enhance Responses
-<!-- description -->  In this tutorial, we will explore advanced orchestration capabilities available in the Gen AI Hub, including features such as Data Masking and Content Filtering.
+<!-- description -->  In this tutorial, we will explore optional orchestration capabilities available in the Gen AI Hub, such as Data Masking and Content Filtering.
 
 ## You will learn
 - Inference of GenAI models using orchestration along with Data Masking and Content Filtering features
@@ -79,7 +79,7 @@ By the end of this tutorial
 
 [OPTION BEGIN [AI Launchpad]]
 
-**In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional advanced modules to enhance data privacy and refine response quality. These enhancements include: 
+**In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional modules to enhance data privacy and refine response quality. These enhancements include: 
 
   -	**Data Masking**: Hiding sensitive information like phone numbers, organizational details, or personal identifiers. 
   -	**Content Filtering**: Screening for categories such as hate speech, self-harm, explicit content, and violence to ensure safe and relevant responses. 
@@ -97,13 +97,13 @@ By the end of this tutorial
 
 [OPTION BEGIN [Python SDK]]
 
-- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional advanced modules to enhance data privacy and refine response quality. These enhancements include: 
+- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional modules to enhance data privacy and refine response quality. These enhancements include: 
 
     -	**Data Masking**: Hiding sensitive information like phone numbers, organizational details, or personal identifiers. 
 
     -	**Content Filtering**: Screening for categories such as hate speech, self-harm, explicit content, and violence to ensure safe and relevant responses.
 
-- Here, we extend the use case introduced in Previous Tutorial, where orchestration was executed without incorporating data masking or content filtering. Here, we will include these advanced modules to improve data privacy, security, and response quality. 
+- Here, we extend the use case introduced in Previous Tutorial, where orchestration was executed without incorporating data masking or content filtering. Here, we will include these modules to improve data privacy, security, and response quality. 
 
 **NOTE** : If you are continuing with the same notebook from the previous tutorial, skip steps 1 and 2. Otherwise, create a new notebook using the already deployed orchestration URL to access the Harmonized API. 
 
@@ -127,13 +127,13 @@ print(cv_content)
 
 [OPTION BEGIN [JavaScript SDK]]
 
-- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional advanced modules to enhance data privacy and refine response quality. These enhancements include: 
+- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional modules to enhance data privacy and refine response quality. These enhancements include: 
 
     -	**Data Masking**: Hiding sensitive information like phone numbers, organizational details, or personal identifiers. 
 
     -	**Content Filtering**: Screening for categories such as hate speech, self-harm, explicit content, and violence to ensure safe and relevant responses.
 
-- Here, we extend the use case introduced in Previous Tutorial, where orchestration was executed without incorporating data masking or content filtering. Here, we will include these advanced modules to improve data privacy, security, and response quality. 
+- Here, we extend the use case introduced in Previous Tutorial, where orchestration was executed without incorporating data masking or content filtering. Here, we will include these modules to improve data privacy, security, and response quality. 
 
 **NOTE** : If you are continuing with the same project from the previous tutorial, skip steps 1 and 2. Otherwise, create a new project using the already deployed orchestration URL to access the Harmonized API.
 
@@ -154,13 +154,13 @@ const cvContent = await readFile('path/to/cv.txt', 'utf-8');
 
 [OPTION BEGIN [Java SDK]]
 
-- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional advanced modules to enhance data privacy and refine response quality. These enhancements include: 
+- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional modules to enhance data privacy and refine response quality. These enhancements include: 
 
     -	**Data Masking**: Hiding sensitive information like phone numbers, organizational details, or personal identifiers. 
 
     -	**Content Filtering**: Screening for categories such as hate speech, self-harm, explicit content, and violence to ensure safe and relevant responses.
 
-- Here, we extend the use case introduced in Previous Tutorial, where orchestration was executed without incorporating data masking or content filtering. Here, we will include these advanced modules to improve data privacy, security, and response quality. 
+- Here, we extend the use case introduced in Previous Tutorial, where orchestration was executed without incorporating data masking or content filtering. Here, we will include these modules to improve data privacy, security, and response quality. 
 
 **NOTE** : If you are continuing with the same project from the previous tutorial, skip steps 1 and 2. Otherwise, create a new Java Maven project using the already deployed orchestration URL to access the Harmonized API. Please find detailed information on orchestration configuration and deployment in the previous tutorial or in  our [documentation](https://sap.github.io/ai-sdk/docs/java/overview-cloud-sdk-for-ai-java). 
 
@@ -191,15 +191,15 @@ System.out.println(cvContent);
 
 [OPTION BEGIN [Bruno]]
 
-- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional advanced modules to enhance data privacy and refine response quality. These enhancements include: 
+- **In this tutorial**, we will build upon the orchestration framework introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html). The focus will shift from basic orchestration to leveraging optional modules to enhance data privacy and refine response quality. These enhancements include: 
 
     -	**Data Masking**: Hiding sensitive information like phone numbers, organizational details, or personal identifiers. 
 
     -	**Content Filtering**: Screening for categories such as hate speech, self-harm, explicit content, and violence to ensure safe and relevant responses.
 
-- Here, we extend the use case introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html), where orchestration was executed without incorporating data masking or content filtering. Here, we will include these advanced modules to improve data privacy, security, and response quality. 
+- Here, we extend the use case introduced in [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html), where orchestration was executed without incorporating data masking or content filtering. Here, we will include these modules to improve data privacy, security, and response quality. 
 
-**Bruno Setup** : If you have already completed the environment setup, configuration, and deployment as described in the [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html), you can directly proceed to the Data Masking Configuration. If you're new to this, please follow the steps in the [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html) to set up your environment, configure, and deploy the orchestration before proceeding with the advanced modules.  
+**Bruno Setup** : If you have already completed the environment setup, configuration, and deployment as described in the [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html), you can directly proceed to the Data Masking Configuration. If you're new to this, please follow the steps in the [Tutorial](https://developers.sap.com/tutorials/ai-core-orchestration-consumption.html) to set up your environment, configure, and deploy the orchestration before proceeding with the modules.  
 
 [OPTION END]
 
@@ -938,7 +938,7 @@ The **Content Filtering** Module allows screening of both input and output conte
 ![img](img/image023.png)
 
 **Conclusion** :  
-Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of advanced modules like data masking and content filtering to enhance privacy and ensure response quality.  
+Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of modules like data masking and content filtering to enhance privacy and ensure response quality.  
 
 While this tutorial used a resume screening use case, the same principles can be applied to other use cases. You can customize the Data Masking and Content Filtering settings based on your specific requirements to handle sensitive or categorized data effectively.  
 
@@ -982,7 +982,7 @@ with open("model_responses.txt", "w") as file:
 - A **model_responses.txt** file will be generated, containing outputs from all the models used.
 
 **Conclusion** :  
-Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of advanced modules like data masking and content filtering to enhance privacy and ensure response quality.  
+Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of modules like data masking and content filtering to enhance privacy and ensure response quality.  
 
 While this tutorial used a resume screening use case, the same principles can be applied to other use cases. You can customize the Data Masking and Content Filtering settings based on your specific requirements to handle sensitive or categorized data effectively.  
 
@@ -1066,7 +1066,7 @@ modelResponses.map(response => {
 - A **model_responses.txt** file will be generated, containing outputs from all the models used.
 
 **Conclusion** :  
-Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of advanced modules like data masking and content filtering to enhance privacy and ensure response quality.  
+Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of modules like data masking and content filtering to enhance privacy and ensure response quality.  
 
 While this tutorial used a resume screening use case, the same principles can be applied to other use cases. You can customize the Data Masking and Content Filtering settings based on your specific requirements to handle sensitive or categorized data effectively.  
 
@@ -1140,7 +1140,7 @@ createFileFromResponses(responses);
 - A **model_responses.txt** file will be generated, containing outputs from all the models used.
 
 **Conclusion** :  
-Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of advanced modules like data masking and content filtering to enhance privacy and ensure response quality.  
+Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of modules like data masking and content filtering to enhance privacy and ensure response quality.  
 
 While this tutorial used a resume screening use case, the same principles can be applied to other use cases. You can customize the Data Masking and Content Filtering settings based on your specific requirements to handle sensitive or categorized data effectively.  
 
@@ -1157,7 +1157,7 @@ By incorporating these optional modules, you can tailor your Response to meet or
 By following these steps, you can successfully mask sensitive data and apply content filtering while consuming the deployed model.
 ![img](img/content_filtering.png)
 **Conclusion** :  
-Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of advanced modules like data masking and content filtering to enhance privacy and ensure response quality.  
+Once the orchestration completes, you can observe that the output is now more refined, with sensitive information masked and inappropriate content filtered. This demonstrates the power of modules like data masking and content filtering to enhance privacy and ensure response quality.  
 
 While this tutorial used a resume screening use case, the same principles can be applied to other use cases. You can customize the Data Masking and Content Filterin settings based on your specific requirements to handle sensitive or categorized data effectively.  
 
