# Copier en .env (gitignore) et renseigner les secrets.
# A sourcer avant de lancer les scripts : set -a; source .env; set +a

# --- MLflow (serveur de la VM, basic auth) ---
MLFLOW_TRACKING_URI=https://mlflow.192-168-122-143.nip.io
MLFLOW_TRACKING_USERNAME=admin
MLFLOW_TRACKING_PASSWORD=change-me
MLFLOW_EXPERIMENT_NAME=tp02_electricity_consumption

# --- CA interne ENI MLOps (les clients Python n'utilisent pas le store systeme par defaut) ---
REQUESTS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt
AWS_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt

# --- S3 Garage : artefacts MLflow (TP03) ---
# Necessaire pour log_model (upload de l'artefact) ET pour le chargement du modele
# par l'API (download depuis s3://mlflow-artifacts). Cle S3 "mlflow" (RWO sur le bucket).
AWS_ACCESS_KEY_ID=GKxxxxxxxxxxxxxxxxxxxxxxxx
AWS_SECRET_ACCESS_KEY=change-me
MLFLOW_S3_ENDPOINT_URL=https://garage.192-168-122-143.nip.io

# --- Import du package lab ---
PYTHONPATH=/home/user/tp