AI cockpit aims at building a human control interface to AI systems. It is supposed to cover requirements from EU's AI act. More details can be found at https://www.kicockpit.eu/. All shared components necessary for this repo can be found here. There you also can find more info about all other activities & results of this project.

This section describes how to run this software on your machine.

The following components and tools are necessary to build & run AICockpit in your dev environment.

• Java JDK 21 or later
• Maven 3
• NodeJs (16.9.1) and NPM (8.3.2) - NodeJS Install
• Postgres (available for development via docker-compose scripts)
• using Keycloak is optional

Project needs a library from an AI cockpit Github repo and thus you need to adapt your Maven settings (usually located here ~/.m2/settings.xml). Following example of a complete settings.xml shows you necessary additions. Please note, that you need username/Github token replaced by values, from your user.

<settings xmlns="http://maven.apache.org/SETTINGS/1.0.0"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/SETTINGS/1.0.0
                      http://maven.apache.org/xsd/settings-1.0.0.xsd">

  <activeProfiles>
    <activeProfile>github</activeProfile>
  </activeProfiles>

  <profiles>
    <profile>
      <id>github</id>
      <repositories>
        <repository>
          <id>central</id>
          <url>https://repo1.maven.org/maven2</url>
        </repository>
        <repository>
            <id>github</id>
            <url>https://maven.pkg.github.com/starwit/vision-api</url>
            <snapshots>
                <enabled>true</enabled>
            </snapshots>
        </repository>
      </repositories>
    </profile>
  </profiles>

  <servers>
    <server>
      <id>github</id>
      <username>username</username>
      <password>TOKEN</password>
    </server>
  </servers>
</settings>

• mvn -B build-helper:parse-version versions:set -DnewVersion=${parsedVersion.majorVersion}.${parsedVersion.nextMinorVersion}.\0${parsedVersion.qualifier?} versions:commit
• mvn -B release:clean release:prepare -Darguments="-DskipTests"
• mvn -B release:clean
• mvn -B release:update-versions
• mvn versions:set -DremoveSnapshot
• changelog convetions: https://www.conventionalcommits.org/en/v1.0.0/

❗ Each step is executed from the project home directory.

1. go to the deployment folder and start the environment (database and keycloak) via docker-compose:

   cd deployment
   docker compose up

2. go to webclient/app and install the frontend applications dependencies

   cd webclient/app
   npm install

3. build the project

   mvn clean install -P frontend

4. start project

   java -jar application/target/application-0.0.1-SNAPSHOT.jar

   You can also run the main-class via Visual Studio Code.

• application can be reached under http://localhost:8081/ai-cockpit/
• swagger under http://localhost:8081/ai-cockpit/swagger-ui/
• If you are using keycloak:
  • default user/password is admin/admin
  • keycloak can be reached under http://localost:8081/auth

For debugging, you can start the frontend separately.

cd webclient/app
npm start

NPM server starts under localhost:3000/starwit/ by default

! If you are using the installation with keycloak, make sure you are logged in before first usage - just go to localhost:8081/starwit in your browser.

You can start the spring boot application in debug mode. See Spring Boot documentation for further details. The easiest way is, to use debug functionality integrated with your IDE like VS Code.

The database is available under localhost:3006

Username:starwit
Database:starwit
Password:starwit

PGAdmin is recommended to access database for development purpose. It can be deployed via docker-compose file.

If you want to start your application without keycloak, you need to change spring boot profile to dev in application\src\main\resources\application.properties.

spring.profiles.active=dev

or define env-variable

SPRING_PROFILES_ACTIVE=dev

Start the database without keycloak:

cd deployment
docker compose up

see https://github.com/starwit/ai-cockpit-deployment