pipeline {
    agent any
    parameters {
        buildSelector(
            name: 'BUILD_SELECTOR',
            defaultSelector: lastSuccessful(),
            description: 'A build to take the artifacts from'
        )
    }
    stages {
        stage('Copy artifacts') {
            steps {
                script {
                    copyArtifacts(
                        projectName: 'z-s487179-create-dataset',
                        selector: buildParameter('BUILD_SELECTOR'),
                        target: './ML'
                    )
                }
            }
        }
        stage('Run training and save model') {
            steps {
                    script {
                    sh 'ls -l'
                    docker.image('docker-image').inside {
                        dir('./ML') {
                            sh 'ls -l'
                            sh 'python3 ./model_train.py'
                            archiveArtifacts 'model.pt'
                        }
                    }
                }
            }
        }
    }
}