Merge pull request #11027 from exec-astraea/fix-new-string-behavior-link

Fixed the link to new-string-behavior setting

Author: MarkvanMents

content/en/docs/deployment/general/populate-user-type.md

@@ -38,9 +38,9 @@ There are several approaches to classify users as `Internal` or `External`, rang
 
 The simplest method to set the `UserType` is by using the Identity and Access Management (IAM) modules, which require only configuration without the need to develop a microflow. This approach leverages a connection with an Identity Provider (IdP) to classify users. The primary benefit of IdP-based classification is its efficiency, as it typically only requires configuration within the existing IAM modules. Mendix offers you the following IAM modules:
 
-* [OIDC](https://docs.mendix.com/appstore/modules/oidc/)
-* [SCIM](https://docs.mendix.com/appstore/modules/scim/)
-* [SAML](https://docs.mendix.com/appstore/modules/saml/)
+* [OIDC](/appstore/modules/oidc/)
+* [SCIM](/appstore/modules/scim/)
+* [SAML](/appstore/modules/saml/)
 
 Alternatively, you can build a custom microflow as described in the [Populating UserType for Existing Users of an App](#using-microflow) section below.
 

content/en/docs/deployment/mendix-cloud-deploy/behavior-of-app.md

@@ -62,7 +62,7 @@ Therefore, do not assume that an established WebSocket connection will remain op
 
 ## Move to Kubernetes
 
-* Only [supported Mendix versions](https://docs.mendix.com/releasenotes/studio-pro/lts-mts/) are able to move to Kubernetes.
+* Only [supported Mendix versions](/releasenotes/studio-pro/lts-mts/) are able to move to Kubernetes.
 * The platform configures `CF_INSTANCE_INDEX=0` for 1 of the instances to define a leader instance and to make [Community Commons](/appstore/modules/community-commons-function-library/) function `GetCFInstanceIndex` partially backwards compatible. The leader instance will return `0` while all follower instances will return `-1`. We advise stopping the use of the `GetCFInstanceIndex` function as it is specific to Cloud Foundry.
 * If your model is using the [SAML module](https://marketplace.mendix.com/link/component/1174), these versions are compatible with Kubernetes:
     * Mendix 9 – Version 3.6.19 and higher.

content/en/docs/deployment/on-premises-design/linux/linux.md

@@ -7,7 +7,7 @@ aliases:
     - /developerportal/deploy/unix-like/
 ---
 
-{{% alert color="warning" %}} Linux deployment is only supported on Debian 10 (buster) for the [Mendix Runtime version 9, 10, and 11](https://docs.mendix.com/releasenotes/studio-pro/lts-mts/).  We will not add support for any other versions of the Mendix Runtime. Consider using the [Portable App Distribution for Linux](/developerportal/deploy/linux-pad/) option instead. {{% /alert %}}
+{{% alert color="warning" %}} Linux deployment is only supported on Debian 10 (buster) for the [Mendix Runtime version 9, 10, and 11](/releasenotes/studio-pro/lts-mts/).  We will not add support for any other versions of the Mendix Runtime. Consider using the [Portable App Distribution for Linux](/developerportal/deploy/linux-pad/) option instead. {{% /alert %}}
 
 ## Introduction
 

content/en/docs/marketplace/genai/how-to/create-single-agent.md

@@ -47,7 +47,7 @@ Before building an agent in your app, make sure your scenario meets the followin
 
 * Basic understanding of Function Calling and Prompt Engineering: learn about [Function Calling](/appstore/modules/genai/function-calling/) and [Prompt Engineering](/appstore/modules/genai/get-started/#prompt-engineering) to use them within the Mendix ecosystem.
 
-* Optional Prerequisites: Basic understanding of the [Model Context Protocol](https://modelcontextprotocol.io/docs/getting-started/intro) and the available Mendix modules—[MCP Server module](https://docs.mendix.com/appstore/modules/genai/mcp-modules/mcp-server/) and [MCP Client module](https://docs.mendix.com/appstore/modules/genai/mcp-modules/mcp-client/).
+* Optional Prerequisites: Basic understanding of the [Model Context Protocol](https://modelcontextprotocol.io/docs/getting-started/intro) and the available Mendix modules—[MCP Server module](/appstore/modules/genai/mcp-modules/mcp-server/) and [MCP Client module](/appstore/modules/genai/mcp-modules/mcp-client/).
 
 ## Agent Use Case
 
@@ -312,7 +312,7 @@ Connect an MCP server as a tool source through a consumed MCP service document a
     * **Credentials microflow** (optional): set this when authentication is required.
     * **Protocol version**: select the protocol that matches your MCP server
 
-    For more details regarding protocol version and authentication, refer to the [technical documentation](https://docs.mendix.com/appstore/modules/genai/genai-for-mx/agent-editor/#define-mcp).
+    For more details regarding protocol version and authentication, refer to the [technical documentation](/appstore/modules/genai/genai-for-mx/agent-editor/#define-mcp).
 
 3. In the consumed MCP service document, click **List tools** to verify the connection.
 

content/en/docs/marketplace/genai/how-to/integrate_function_calling.md

@@ -55,7 +55,7 @@ Selecting the infrastructure for integrating GenAI into your Mendix application
 * Your Own Connector: Optionally, if you prefer a custom connector, you can integrate your chosen infrastructure. However, this document focuses on the Mendix Cloud GenAI, OpenAI, and Amazon Bedrock connectors, as they offer comprehensive support and ease of use to get started.
 
 {{% alert color="info" %}}
-Not all models support function calling. Ensure that your preferred GenAI provider is set up in your Mendix app and that a compatible model is available. Mendix provides an [overview of models and their capabilities](https://docs.mendix.com/appstore/modules/genai/#models).
+Not all models support function calling. Ensure that your preferred GenAI provider is set up in your Mendix app and that a compatible model is available. Mendix provides an [overview of models and their capabilities](/appstore/modules/genai/#models).
 {{% /alert %}}
 
 ### Customizing Microflows {#microflows}

content/en/docs/marketplace/genai/mendix-cloud-genai/_index.md

@@ -24,7 +24,7 @@ There are three different types of resources:
 ## Getting started
 
 1. Learn about GenAI Resource Packs and how to acquire them in the [Mendix Cloud GenAI Resource Packs](/appstore/modules/genai/mx-cloud-genai/resource-packs/) document.
-2. Once you have access to GenAI resources, log in to the [Mendix Cloud GenAI portal](https://genai.home.mendix.com/) to generate access keys for your resources. This portal provides an overview of all the resources you have access to and you can also request new GenAI Resources there. For more information, see [Navigate through the Mendix Cloud GenAI Portal](https://docs.mendix.com/appstore/modules/genai/mx-cloud-genai/Navigate-MxGenAI/).
+2. Once you have access to GenAI resources, log in to the [Mendix Cloud GenAI portal](https://genai.home.mendix.com/) to generate access keys for your resources. This portal provides an overview of all the resources you have access to and you can also request new GenAI Resources there. For more information, see [Navigate through the Mendix Cloud GenAI Portal](/appstore/modules/genai/mx-cloud-genai/Navigate-MxGenAI/).
 3. Use a starter app containing the [Mendix Cloud GenAI Connector](https://marketplace.mendix.com/link/component/239449) (for example, the [BlankGenAI starter app](https://marketplace.mendix.com/link/component/227934)) or implement the connector in the Mendix application according to its documentation. Once you have imported access key in its configuration overview, you are connected to Mendix Cloud GenAI and can access available resources within your application. 
 
 ## Relevant Sources

content/en/docs/marketplace/genai/reference-guide/agent-editor.md

@@ -102,7 +102,7 @@ To use the Agent Editor functionalities in your app, you must perform the follow
 6. Deploy the agent to cloud environments.
 7. Improve the agent in the next iterations.
 
-For a step by step tutorial, check out the [create your first agent](https://docs.mendix.com/appstore/modules/genai/how-to/howto-single-agent/#define-agent-editor) documentation.
+For a step by step tutorial, check out the [create your first agent](/appstore/modules/genai/how-to/howto-single-agent/#define-agent-editor) documentation.
 
 ### Defining the Model {#define-model}
 
@@ -234,13 +234,13 @@ When configuring the action, select the Agent document so that the right agent i
 
 Optionally, you can pass a `Request` object to set request-level values, and a `FileCollection` object with files to send along with the user message to make use of vision or document chat capabilities. Support for files and images depends on the underlying large language model. Refer to the documentation of the specific connector.
 
-The output is a `GenAICommons.Response` object, aligned with the GenAI Commons and Agent Commons domain models and actions, which can be used for further logic. Additionally, all agents created via the Agent Editor extension are seamlessly integrated with other Mendix offerings, such as the [Token consumption monitor](https://docs.mendix.com/appstore/modules/genai/genai-for-mx/conversational-ui/#snippet-token-monitor) or the [Traceability](https://docs.mendix.com/appstore/modules/genai/genai-for-mx/conversational-ui/#traceability) feature from [ConversationalUI](https://docs.mendix.com/appstore/modules/genai/genai-for-mx/conversational-ui/).
+The output is a `GenAICommons.Response` object, aligned with the GenAI Commons and Agent Commons domain models and actions, which can be used for further logic. Additionally, all agents created via the Agent Editor extension are seamlessly integrated with other Mendix offerings, such as the [Token consumption monitor](/appstore/modules/genai/genai-for-mx/conversational-ui/#snippet-token-monitor) or the [Traceability](/appstore/modules/genai/genai-for-mx/conversational-ui/#traceability) feature from [ConversationalUI](/appstore/modules/genai/genai-for-mx/conversational-ui/).
 
 ### Deploying the Agent to Cloud Environments {#deploy-agent}
 
 Agents created with the Agent Editor are documents in the app model. This means they are packaged and deployed together with the rest of the app whenever a deployment is performed.
 
-Environment-specific flexibility is provided through constants. Values such as the model key, knowledge base key, or custom MCP endpoint can be overridden per app environment during the deployment process. For details, see [Environment Details: Constants](https://docs.mendix.com/developerportal/deploy/environments-details/#constants).
+Environment-specific flexibility is provided through constants. Values such as the model key, knowledge base key, or custom MCP endpoint can be overridden per app environment during the deployment process. For details, see [Environment Details: Constants](/developerportal/deploy/environments-details/#constants).
 
 Agents created in Studio Pro (using Agent Editor) are visible in the Agent Commons UI, but they are not editable there.
 

content/en/docs/marketplace/genai/reference-guide/external-platforms/snowflake-cortex.md

@@ -47,7 +47,7 @@ The [Snowflake showcase app](https://marketplace.mendix.com/link/component/22584
 
     For more information, see [How to Use Marketplace Content](/appstore/use-content/).
 
-2. In Studio Pro, in the [App Explorer](https://docs.mendix.com/refguide/app-explorer/), go to **Showcase_AI_RESTSQLAPI** > **Pages**.
+2. In Studio Pro, in the [App Explorer](/refguide/app-explorer/), go to **Showcase_AI_RESTSQLAPI** > **Pages**.
 
     This section contains the following pages: 
 

content/en/docs/marketplace/platform-supported-content/modules/aws/amazon-bedrock.md

@@ -312,7 +312,7 @@ Prompt templates address this constraint by allowing you to include orchestratio
 
 For a deeper understanding of prompt templates and their implementation, refer to the [Amazon documentation on prompt templates](https://docs.aws.amazon.com/bedrock/latest/userguide/kb-test-config.html#kb-test-config-sysprompt), which provides comprehensive guidance on their usage and best practices.
 
-For more information about how to structure your prompts, see [Prompt engineering](https://docs.mendix.com/appstore/modules/genai/prompt-engineering/).
+For more information about how to structure your prompts, see [Prompt engineering](/appstore/modules/genai/prompt-engineering/).
 
 #### Chatting with History {#retrieve-and-generate-with-history}
 

content/en/docs/marketplace/platform-supported-content/modules/databricks-edc.md

@@ -13,7 +13,7 @@ This how-to describes the steps required to enable your app to use the External
 
 ## Prerequisites
 
-For some general information on how to use bring your own JDBC driver with the external database connector, read [External Database Connector: Configure for Any Database](https://docs.mendix.com/appstore/modules/external-database-connector/#byod).
+For some general information on how to use bring your own JDBC driver with the external database connector, read [External Database Connector: Configure for Any Database](/appstore/modules/external-database-connector/#byod).
 
 ## Configuring the Connection Between Your Mendix App and Databricks