PMML + Quarkus example

Description

A simple PMML service

Demonstrates PMML on Kogito capabilities, including REST interface code generation.

Installing and Running

Prerequisites

You will need:

• Java 17+ installed
• Environment variable JAVA_HOME set accordingly
• Maven 3.9.6+ installed

When using native image compilation, you will also need:

• GraalVM 19.3.1 installed
• Environment variable GRAALVM_HOME set accordingly
• Note that GraalVM native image compilation typically requires other packages (glibc-devel, zlib-devel and gcc) to be installed too. You also need ‘native-image’ installed in GraalVM (using ‘gu install native-image’). Please refer to GraalVM installation documentation for more details.

Compile and Run in Local Dev Mode

mvn clean compile quarkus:dev

Package and Run in JVM mode

mvn clean package
java -jar target/quarkus-app/quarkus-run.jar

or on Windows

mvn clean package
java -jar target\quarkus-app\quarkus-run.jar

Package and Run using Local Native Image

Note that this requires GRAALVM_HOME to point to a valid GraalVM installation

mvn clean package -Pnative

To run the generated native executable, generated in target/, execute

./target/pmml-quarkus-example-runner

Note: This does not yet work on Windows, GraalVM and Quarkus should be rolling out support for Windows soon.

OpenAPI (Swagger) documentation

Specification at swagger.io

You can take a look at the OpenAPI definition - automatically generated and included in this service - to determine all available operations exposed by this service. For easy readability you can visualize the OpenAPI definition file using a UI tool like for example available Swagger UI.

In addition, various clients to interact with this service can be easily generated using this OpenAPI definition.

When running in either Quarkus Development or Native mode, we also leverage the Quarkus OpenAPI extension that exposes Swagger UI that you can use to look at available REST endpoints and send test requests.

Example Usage

Once the service is up and running, you can use the following example to interact with the service.

POST /Regression

Given inputs:

{
  "fld1":3.0, 
  "fld2":2.0, 
  "fld3":"y"
}

Curl command (using the JSON object above):

curl -X POST -H 'Accept: application/json' -H 'Content-Type: application/json' -d '{"fld1":3.0, "fld2":2.0, "fld3":"y"}' http://localhost:8080/Testregression/LinReg

or on Windows:

curl -X POST -H "Accept: application/json" -H "Content-Type: application/json" -d "{"fld1":3.0, "fld2":2.0, "fld3":"y"}" http://localhost:8080/Testregression/LinReg

Example response:

{
  "fld4":52.5
}

POST /Tree

Given inputs:

{
  "temperature":30.0, 
  "humidity": 10.0 
}

Curl command (using the JSON object above):

curl -X POST -H 'Accept: application/json' -H 'Content-Type: application/json' -d '{"temperature":30.0, "humidity":10.0}' http://localhost:8080/Testtree/SampleMine

or on Windows:

curl -X POST -H "Accept: application/json" -H "Content-Type: application/json" -d "{"temperature":30.0, "humidity":10.0}" http://localhost:8080/Testtree/SampleMine

Example response:

{
  "decision":"sunglasses"
}

POST /Scorecard

Given inputs:

{
  "input1":5.0, 
  "input2":-10.0
}

Curl command (using the JSON object above):

curl -X POST -H 'Accept: application/json' -H 'Content-Type: application/json' -d '{"input1":5.0, "input2":-10.0}' http://localhost:8080/Testscorecard/SimpleScorecard

or on Windows:

curl -X POST -H "Accept: application/json" -H "Content-Type: application/json" -d "{"input1":5.0, "input2":-10.0}" http://localhost:8080/Testscorecard/SimpleScorecard

Example response:

{
  "score":-15.0
}

POST /MiningModel

Given inputs:

{"residenceState":"AP",
                "validLicense":true,
                "occupation":"ASTRONAUT",
                "categoricalY":"classA",
                "categoricalX":"red",
                "variable":6.6,
                "age":25.0
}

Curl command (using the JSON object above):

curl -X POST -H 'Accept: application/json' -H 'Content-Type: application/json' -d '{"residenceState":"AP", "validLicense":true, "occupation":"ASTRONAUT", "categoricalY":"classA", "categoricalX":"red", "variable":6.6, "age":25.0}' http://localhost:8080/Testminingmodel/PredicatesMining

or on Windows:

curl -X POST -H "Accept: application/json" -H "Content-Type: application/json" -d "{"residenceState":"AP", "validLicense":true, "occupation":"ASTRONAUT", "categoricalY":"classA", "categoricalX":"red", "variable":6.6, "age":25.0}" http://localhost:8080/Testminingmodel/PredicatesMining

Example response:

{
  "categoricalResult":1.381666666666666
}