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MuleSoft Inference
Getting Started

Getting Started

Use the Connector in Your Project

Application Requirements

Java Development Kit (JDK)

The application using the MuleSoft Inference Connector can use Java Development Kit (JDK) 8, 11 and 17.

MuleSoft Runtime

The application using the MuleSoft Inference Connector requires a Mule Runtime >= 4.3.

Option 1: Maven Central Repository

Maven Central (opens in a new tab)

Edit File pom.xml

💡

The MAC Project connectors are constantly updated, and the version is regularly changed. Make sure to replace {version} with the latest release from Maven Central (opens in a new tab).

Copy and paste the following Maven Dependency into your Mule application pom file.

pom.xml
<dependency>
    <groupId>io.github.mulesoft-ai-chain-project</groupId>
    <artifactId>mule4-inference-connector</artifactId>
    <version>{version}</version>
    <classifier>mule-plugin</classifier>
</dependency>

Option 2: Local Maven Repository

Build Requirements

Before you start, ensure you have the following prerequisites:

  • Java Development Kit (JDK) 8, 11, and 17
  • Apache Maven
  • MuleSoft Anypoint Studio

Download the MuleSoft Inference Connector

Clone the MuleSoft Inference Connector repository from GitHub:

git clone https://github.com/MuleSoft-AI-Chain-Project/mule-inference-connector.git
cd mule-inference-connector

Install the Connector with Java 8

mvn clean install -DskipTests -Dgpg.skip

Installing with Java 11, 17, 21, 22, etc.

Step 1

export MAVEN_OPTS="--add-opens=java.base/java.util=ALL-UNNAMED --add-opens=java.base/java.net=ALL-UNNAMED --add-opens=java.base/java.util.regex=ALL-UNNAMED --add-opens=java.base/java.lang.reflect=ALL-UNNAMED --add-opens=java.base/java.lang=ALL-UNNAMED --add-opens=java.xml/javax.xml.namespace=ALL-UNNAMED"

Step 2

 
For Java 11
mvn clean install -Dmaven.test.skip=true -DskipTests -Dgpg.skip -Djdeps.multiRelease=11
 
For Java 17
mvn clean install -Dmaven.test.skip=true -DskipTests -Dgpg.skip -Djdeps.multiRelease=17
 
For Java 21
mvn clean install -Dmaven.test.skip=true -DskipTests -Dgpg.skip -Djdeps.multiRelease=21
 
For Java 22
mvn clean install -Dmaven.test.skip=true -DskipTests -Dgpg.skip -Djdeps.multiRelease=22

Edit File pom.xml

💡

The MAC Project connectors are constantly updated, and the version is regularly changed. Make sure to replace {version} with the latest release from our GitHub repository (opens in a new tab).

Add the following dependency to your pom.xml file:

pom.xml
<dependency>
  <groupId>com.mulesoft.connectors</groupId>
  <artifactId>mule4-inference-connector</artifactId>
  <version>{version}</version>
  <classifier>mule-plugin</classifier>
</dependency>

Connector Configuration

The MuleSoft Inference connector can be easily configured. Go to the Global Elements in your MuleSoft project, and create a new configuration. In the Connector Configuration, you will find the MuleSoft Inference configuration. Select it and press OK.

Tools Use AI Service

Inference Support

MuleSoft Inference supports different Inference Offerings:

Select the Inference type of your choice from the Inference Type dropdown field.

Tools Use AI Service

API Key

Provide the API Key for the Inference provider. Also check the tab Inference Parameters for additional properties for the inference provider.

Model Name

After choosing the LLM provider, the available and supported models are listed in the model name dropdown.

Temperature, Top P and Max Token

Temperature is a number between 0 and 2, with a default value of 0.7. The temperature is used to control the randomness of the output. When you set it higher, you'll get more random outputs. When you set it lower, towards 0, the values are more deterministic. Top P specifies the cumulative probability score threshold that the tokens must reach. Max Token defines the number of LLM Token to be used when generating a response. This parameter helps control the usage and costs when engaging with LLMs.

Connector OverviewSupported Operations