pipeline {
    agent {
        docker {
            image 's444409-create-dataset'
        }
    }
    
    environment {
        NOTIFICATION_ADDRESS = 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
    }

    stages {
        stage('Get previousl trend') {
            steps {
                copyArtifacts projectName: 's444409-evaluate', selector: lastSuccessful(), optional: true
            }
        }
        stage('Evaluate model and write results to file') {
            steps {
                sh "python eval_model.py"
                script {
                    LOSS = sh(script: 'tail -1 evaluation_results.txt', returnStdout: true).trim()
                }
            }
        }
    }

    post {
        always {
            archiveArtifacts artifacts: 'evaluation_results', 
            onlyIfSuccessful: true
        }

        success {
            emailext body: "Evaluation results: RMSE:${LOSS}", subject: "${env.JOB_NAME}", to: "${env.NOTIFICATION_ADDRESS}"
        }

        failure {
            emailext body: 'FAILURE', subject: "${env.JOB_NAME}", to: "${env.NOTIFICATION_ADDRESS}"
        }
    }
}