pipeline {
    agent any
    environment {
        PATH = "/path/to/your/python/bin:${env.PATH}"
        SACRED_IGNORE_GIT = 'TRUE'
    }
    parameters {
        string(name: 'EPOCHS', defaultValue: '10', description: 'Liczba Epok')
    }
    stages {
        stage('Przygotowanie') {
            steps {
                sh 'pip install pandas tensorflow scikit-learn imbalanced-learn sacred pymongo mlflow'
            }
        }
        stage('Pobierz dane') {
            steps {
                script {
                    copyArtifacts(projectName: 's487187-create-dataset', fingerprintArtifacts: true)
                }
            }
        }
        stage('Trenuj model') {
            steps {
                script {
                    sh 'mlflow run . -P epochs=$EPOCHS'
                }
            }
        }
        stage('Zarchiwizuj model') {
            steps {
                sh '''
                    mkdir -p model
                    cp -r mlruns/* model/
                '''
                archiveArtifacts artifacts: 'model/**', fingerprint: true
            }
        }
    }
}