Merge branch 'development' into 9.24.32-rn

Author: MariaShaposhnikova

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

@@ -25,9 +25,12 @@ Amazon Bedrock is a fully managed service that makes foundation models (FMs) fro
 
 The Amazon Bedrock connector requires Mendix Studio Pro version 9.24.2 or above.
 
-To authenticate with Amazon Web Service (AWS), you must also install and configure the [AWS Authentication connector version 3.0.0 or higher](https://marketplace.mendix.com/link/component/120333). It is crucial for the Amazon Bedrock connector to function correctly. For more information about installing and configuring the AWS Authentication connector, see [AWS Authentication](/appstore/modules/aws/aws-authentication/).
+To authenticate with Amazon Web Service (AWS), you must install and configure the [AWS Authentication connector version 3.0.0 or higher](https://marketplace.mendix.com/link/component/120333). It is crucial for the Amazon Bedrock connector to function correctly. For more information about installing and configuring the AWS Authentication connector, see [AWS Authentication](/appstore/modules/aws/aws-authentication/).
+
+You must have the latest [GenAI Commons](/appstore/modules/genai/commons/) version, available in the [GenAI for Mendix](https://marketplace.mendix.com/link/component/227931) bundle. To make integration of generative AI capabilities as easy as possible, the Amazon Bedrock connector depends on the generic domain model and operations provided by the GenAI Commons module.
+
+To ensure that your app can connect to Bedrock, you must also install and configure the [Encryption module](/appstore/modules/encryption/#configuration). 
 
-You must also install the [GenAI Commons version 2.0.0 or higher](/appstore/modules/genai/commons/). To make integration of generative AI capabilities as easy as possible, the Amazon Bedrock connector depends on the generic domain model and operations provided by the GenAI Commons module.
 
 ### Licensing and Cost
 
@@ -105,7 +108,7 @@ You can follow a similar approach to implement any of the other operations in **
 
 ### Chatting with Large Language Models using the ChatCompletions Operation
 
-A common use case of the Amazon Bedrock Connector is the development of chatbots and chat solutions. The **ChatCompletions (without history / with history)** operations offer an easy way to connect to most of the text-generation models available on Amazon Bedrock. The ChatCompletions operations are built on top of Bedrock's Converse API, allowing you to talk to different models without the need of a model-specific implementation. For more information on the ChatCompletion operations, see [GenAI Commons: Chat Completions](/appstore/modules/genai/commons/#text-files-operations).
+A common use case of the Amazon Bedrock Connector is the development of chatbots and chat solutions. The **ChatCompletions (without history / with history)** operations offer an easy way to connect to most of the text-generation models available on Amazon Bedrock. The ChatCompletions operations are built on top of Bedrock's Converse API, allowing you to talk to different models without the need of a model-specific implementation. For more information on the ChatCompletion operations, see [GenAI Commons: Chat Completions](/appstore/modules/genai/commons/#genai-generate).
 
 For an overview of supported models and model-specific capabilities and limitations, see [Amazon Bedrock Converse API](https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html#conversation-inference-supported-models-features) in the AWS documentation.
 

content/en/docs/appstore/use-content/platform-supported-content/modules/database-connector-mx10.md

@@ -31,6 +31,12 @@ If you need to connect to other database types, check out the [Database Connecto
 
 ### Features {#features}
 
+{{% alert color="info" %}}
+
+From [Studio Pro 10.19](/releasenotes/studio-pro/10.19/), you can connect to any database by using the Java dependency specified by the user for the respective database. For more information, see the [Configure for Any Database](#byod) section below.
+
+{{</alert>}}
+
 This connector supports connections to the following database types:
 
 * Microsoft SQL
@@ -39,8 +45,6 @@ This connector supports connections to the following database types:
 * Oracle
 * Snowflake – GA support from [Studio Pro 10.12](/releasenotes/studio-pro/10.12/) (Beta versions are available from [Studio Pro 10.10](/releasenotes/studio-pro/10.10/)). For more information, see [Configure the External Database Connector for Snowflake](/appstore/modules/snowflake/external-database-connector/)
 
-If you are looking for another database type, follow the prompt to request support your database when you open the database connection wizard.
-
 This connector supports the following statements:
 
 * `SELECT`
@@ -210,3 +214,45 @@ To connect to PostgreSQL when the application is running in Mendix Cloud, follow
 1. To configure SSL-based authentication in Mendix Cloud, add a CA certificate and client certificate for server configuration and the selected SSL mode. For more details, see the [Running in the Cloud](/howto/integration/use-a-client-certificate/#running-in-the-cloud) section of *Use a Client Certificate*.
 2. After the client certificate has been added, double-click the client certificate and add the value `ClientCertificateIdentifier` to `Use Client Certificate for specific services`. This must match the value provided for the constant `ClientCertificateIdentifier`.
 3. Add the required values to the constants created for DBSource, DBUsername, DBPassword, and ClientCertificateIdentifier.
+
+## Configure for Any Database {#byod}
+
+### Prerequisites 
+
+* Ensure you have the appropriate Java Database Connectivity (JDBC) JAR file for the specific database.
+* Gather the external connection details, including login credentials and the JDBC connection string.
+
+### Connect to the Database
+
+1. Open the module settings and add the JDBC JAR File.
+   
+   * Alternatively, place the downloaded JAR file in the userlib folder of your application.
+
+2. Run the app with the latest version of the External Database Connector. 
+
+3. Create a New External Database Connection.
+4. Open the connection settings and under Database Type, select **Other**.
+5. Enter the login credentials and JDBC connection string.
+6. Click **Test Connection** to ensure the database connection is successful.
+7. Click **Save** to save the connection details. 
+
+### Configure Database Schema Information 
+
+The Browse Database Schema tab might not display a comprehensive overview of all available schemas for certain databases. You can customize this behavior using the Configure option. To do so, follow these steps:
+
+1. Open the **App** menu and select **Deploy for Eclipse**.
+2. Extend the class MxQueryBasedSchemaInfoProvider.
+3. Override the following methods based on your requirements:
+    * getTableMetaDataQuery
+    * getViewMetaDataQuery
+    * getProcedureMetaDataQuery
+    * getFunctionMetaDataQuery
+4. Use the provided example, MxDb2SchemaInfoProvider for IBM Db2, for a better understanding of how to customize the schema information.
+
+### Running Queries and Handling Query Responses
+
+Execute queries as you would with supported databases, and retrieve responses in the associated entity. Refer to the documentation of your specific JDBC library for detailed syntax and execution options.
+
+{{% alert color="info" %}}
+By default, autocommit is set to false for design time queries.
+{{% /alert %}}

content/en/docs/appstore/use-content/platform-supported-content/modules/genai/Mx GenAI Connector.md

@@ -8,7 +8,7 @@ weight: 60
 
 ## Introduction
 
-The Mendix Cloud GenAI connector (delivered as part of [GenAI for Mendix](https://marketplace.mendix.com/link/component/227931)) lets you utilize Mendix Cloud GenAI resource packs directly within your Mendix application. It allows you to integrate generative AI by dragging and dropping common operations from its toolbox.
+The Mendix Cloud GenAI connector (delivered as part of [GenAI for Mendix](https://marketplace.mendix.com/link/component/227931)) lets you utilize Mendix Cloud GenAI resource packs directly within your Mendix application. It allows you to integrate generative AI by dragging and dropping common operations from its toolbox. Feel free to contact [genai-resource-packs@mendix.com](mailto:genai-resource-packs@mendix.com) to learn more.
 
 ### Typical Use Cases
 
@@ -74,7 +74,7 @@ To use this connector, you need configuration keys to authenticate to the Mendix
 
 ## Installation
 
-Add the [Dependencies](#dependencies) listed above from the Marketplace. On the Marketplace, the Mendix Cloud GenAI connector is bundled inside of [GenAI for Mendix](https://marketplace.mendix.com/link/component/227931) which also contains GenAI commons operations and logic. To import this module into your app, follow the instructions in the [Use Marketplace Content](/appstore/use-content/).
+Add the [dependencies](#dependencies) listed above from the Marketplace. On the Marketplace, the Mendix Cloud GenAI connector is bundled inside of the [GenAI for Mendix](https://marketplace.mendix.com/link/component/227931) which also contains GenAI commons operations and logic. To import this module into your app, follow the instructions in the [Use Marketplace Content](/appstore/use-content/).
 
 ## Configuration {#configuration}
 

content/en/docs/appstore/use-content/platform-supported-content/modules/genai/_index.md

@@ -10,7 +10,7 @@ description: "Describes the general properties and common concepts of generative
 With the Mendix GenAI capabilities, you can create engaging, intelligent experiences with a variety of AI models and your own data.
 
 {{% alert color="info" %}}
-These pages cover modules that integrate with third-party generative AI tools. For running pre-trained Machine Learning (ML) models using the Mendix Runtime, please see the [Machine Learning Kit](/refguide/machine-learning-kit/).
+These pages cover modules that integrate with generative AI tools. For running pre-trained Machine Learning (ML) models using the Mendix Runtime, please see the [Machine Learning Kit](/refguide/machine-learning-kit/).
 {{% /alert %}}
 
 ### Typical Use Cases
@@ -47,14 +47,15 @@ To help you get started, the following sections list the available GenAI compone
 |-------------------|---------------------------------------------------|----------------------------------|------------|
 | [AI Bot Starter App](https://marketplace.mendix.com/link/component/227926) | Lets you kick-start the development of enterprise-grade AI chatbot experiences. For example, you can use it to create your own private enterprise-ready ChatGPT-like app. | Starter App | 10.12 |
 | [Blank GenAI App](https://marketplace.mendix.com/link/component/227934) | Start from scratch to create a new application with GenAI capabilities and without any dependencies. | Starter App | 10.12 |
-| [GenAI Showcase App](https://marketplace.mendix.com/link/component/220475) | Understand what you can build with generative AI. Understand how to implement the OpenAI and Amazon Bedrock connectors and how to integrate them with the Conversational UI module. |Showcase App | 9.24.2 |
+| [GenAI Showcase App](https://marketplace.mendix.com/link/component/220475) | Understand what you can build with generative AI. Understand how to implement the Mendix Cloud GenAI, OpenAI, and Amazon Bedrock connectors and how to integrate them with the Conversational UI module. |Showcase App | 9.24.2 |
 | [RFP Assistant Starter App / Questionnaire Assistant Starter App](https://marketplace.mendix.com/link/component/235917) | The RFP Assistant Starter App and the Questionnaire Assistant Starter App leverage historical RFPs (or question-answer pairs) and a continuously updated knowledge base to generate and assist in editing responses to RFPs, offering a time-saving alternative to manually finding similar responses and enhancing the knowledge management process.  | Starter App | 9.24.2 |
-| [Support Assistant Starter App](https://marketplace.mendix.com/link/component/231035) | Learn how to combine common GenAI patterns, such as function calling and RAG to build your support assistant. Connect it to a model like Anthropic Claude or Amazon Titan via Amazon Bedrock or use an (Azure) OpenAI subscription.  | Starter App | 10.12 |
-| [Conversational UI](/appstore/modules/genai/conversational-ui/) | Create a Conversational UI for a new or existing app. | UI Module | 9.24.2 |
-| [OpenAI Connector](/appstore/modules/genai/openai/) | Connect to Azure OpenAI. | Connector Module | 9.24.2 |
-| [Amazon Bedrock Connector](/appstore/modules/genai/bedrock/) | Connect to Amazon Bedrock. Use Retrieve & Generate or Bedrock agents. | Connector Module | 9.24.2 |
+| [Support Assistant Starter App](https://marketplace.mendix.com/link/component/231035) | Learn how to combine common GenAI patterns, such as function calling and RAG to build your support assistant. Connect it to a model like Anthropic Claude via Mendix Cloud GenAI or Amazon Bedrock or use an (Azure) OpenAI subscription.  | Starter App | 10.12 |
+| [GenAI For Mendix](https://marketplace.mendix.com/link/component/227931) |[GenAI Commons](/appstore/modules/genai/commons/): Common capabilities that allow all GenAI connectors to be integrated with the other modules. You can also implement your own connector based on this. | Common Module | 9.24.2 |
+| |[Conversational UI](/appstore/modules/genai/conversational-ui/): Create a Conversational UI for a new or existing app. | UI Module | 9.24.2 |
+| |[Mendix Cloud GenAI Connector](/appstore/modules/genai/MxGenAI/): Connect to Mendix Cloud and utilize Mendix Cloud GenAI resource packs directly within your Mendix application. | Connector Module | 9.24.2 |
+| [OpenAI Connector](/appstore/modules/genai/openai/) | Connect to (Azure) OpenAI. | Connector Module | 9.24.2 |
+| [Amazon Bedrock Connector](/appstore/modules/aws/amazon-bedrock/) | Connect to Amazon Bedrock. Use Retrieve and Generate or Bedrock agents. | Connector Module | 9.24.2 |
 | [PgVector Knowledge Base](/appstore/modules/genai/pgvector/) | Manage and interact with a PostgreSQL *pgvector* Knowledge Base. | Connector Module | 9.24.2 |
-| [GenAI Commons](/appstore/modules/genai/commons/) | Common capabilities that allow all GenAI connectors to be integrated with the other modules. You can also implement your connector based on this. | Common Module | 9.24.2 |
 | [Snowflake Showcase App](https://marketplace.mendix.com/link/component/225845) | Learn how to implement the Cortex functionalities in your app. | Showcase App | 10.12 |
 
 ### Available Models {#models}
@@ -63,32 +64,31 @@ Mendix connectors offer direct support for the following models:
 
 | Architecture | Models | Category | Input | Output | Additional capabilities |
 |--------------|---------------------|---------------------|-------------------|-----------|-------------------------|
+| Mendix Cloud GenAI | Anthropic Claude 3.5 Sonnet | Chat Completions | text, image, document | text | Function calling |
+| | Cohere Embed English, Cohere Embed Multilingual | Embeddings | text | embeddings | |
 | Azure / OpenAI | gpt-3.5-turbo | Chat completions | text | text | Function calling |
 | | gpt-4, gpt-4-turbo, gpt-4o, gpt-4o mini | Chat completions | text, image | text | Function calling |
 | | DALL·E 2, DALL·E 3 | Image generation | text | image | |
 | | text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large     | Embeddings | text | embeddings| |
-| Amazon Bedrock | Amazon Titan Text G1 - Express, Amazon Titan Text G1 - Lite, Amazon Titan Text G1 - Premier | Chat Completions | text | text | Document Chat (except Titan Premier) |
+| Amazon Bedrock | Amazon Titan Text G1 - Express, Amazon Titan Text G1 - Lite, Amazon Titan Text G1 - Premier | Chat Completions | text, document (except Titan Premier) | text | |
 | | AI21 Jamba-Instruct | Chat Completions | text | text |  |
 | | AI21 Labs Jurassic-2 (Text) | Chat Completions | text | text |  |
-| | Amazon Nova Pro, Amazon Nova Lite | Chat Completion | text | text | Function calling, Document Chat |
+| | Amazon Nova Pro, Amazon Nova Lite | Chat Completion | text, image, document | text | Function calling |
 | | Amazon Titan Image Generator G1 | Image generation | text | image | |
 | | Amazon Titan Embeddings Text v2 | Embeddings | text | embeddings| |
-| | Anthropic Claude v2.0, Anthropic Claude v2.1| Chat Completions | text | text | Document Chat |
-| | Anthropic Claude v3 Sonnet, Anthropic Claude v3 Haiku, Anthropic Claude v3 Opus | Chat Completions | text, image | text | Function calling, Document Chat |
-| | Anthropic Claude v3.5 Sonnet, Anthropic Claude v3.5 Sonnet v2 | Chat Completions | text, image | text | Function calling, Document Chat |
-| | Cohere Command | Chat Completions | text | text | Document Chat |
+| | Anthropic Claude 2.0, Anthropic Claude 2.1| Chat Completions | text, document | text | |
+| | Anthropic Claude 3 Sonnet, Anthropic Claude 3.5 Sonnet, Anthropic Claude 3.5 Sonnet v2, Anthropic Claude 3 Haiku, Anthropic Claude 3 Opus | Chat Completions | text, image, document | text | Function calling |
+| | Cohere Command | Chat Completions | text, document | text | |
 | | Cohere Command Light | Chat Completions | text | text | |
-| | Cohere Command R, Cohere Command R+ | Chat Completions | text | text | Function calling, Document Chat |
+| | Cohere Command R, Cohere Command R+ | Chat Completions | text, document | text | Function calling |
 | | Cohere Embed English, Cohere Embed Multilingual | Embeddings | text | embeddings | |
-| | Meta Llama 2, MetaLlama 3| Chat Completions | text | text | Document Chat |
-| | Meta Llama 3.1| Chat Completions | text | text | Function calling, Document Chat |
-| | Mistral AI Instruct | Chat Completions | text | text | Document Chat |
-| | Mistral Large, Mistral Large 2 | Chat Completions | text | text | Function calling, Document Chat |
+| | Meta Llama 2, MetaLlama 3| Chat Completions | text, document | text | |
+| | Meta Llama 3.1| Chat Completions | text, document | text | Function calling |
+| | Mistral AI Instruct | Chat Completions | text. document | text | |
+| | Mistral Large, Mistral Large 2 | Chat Completions | text, document | text | Function calling |
 | | Mistral Small | Chat Completions | text | text | Function calling |
-| Mendix Cloud GenAI | Anthropic Claude v3.5 Sonnet | Chat Completions | text, image | text | Function calling, Document Chat |
-| | Cohere Embed English, Cohere Embed Multilingual | Embeddings | text | embeddings | |
 
-For more details on limitations and supported model capabilities for the Bedrock Converse API used in the ChatCompletions operations, see [Supported models and model features](https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html#conversation-inference-supported-models-features) in the AWS documentation.
+For more details on limitations and supported model capabilities for the Bedrock Converse API used in the ChatCompletions operations, see [Supported models and model features](https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference-supported-models-features.html) in the AWS documentation.
 
 The available showcase applications offer implementation inspiration for many of the listed models.