Merge pull request #123 from ineszang/feat/entrainement-du-modele

feat(ml): enregistrer le modèle dans le MLflow Model Registry

Makefile

@@ -20,6 +20,8 @@ PG_USER := $(or $(strip $(call env-val,POSTGRES_USER)),enervision)
 PG_PASSWORD := $(or $(strip $(call env-val,POSTGRES_PASSWORD)),change_me)
 PG_DB := $(or $(strip $(call env-val,POSTGRES_DB)),enervision)
 PG_PORT := $(or $(strip $(call env-val,POSTGRES_PORT)),5433)
+ml-env-val = $(shell sed -n 's/^$(1)=//p' ml/.env 2>/dev/null | tail -1)
+ML_ENV_DB_PASSWORD := $(call ml-env-val,MLFLOW_DB_PASSWORD)
 AIRFLOW_PORT := $(or $(strip $(call env-val,AIRFLOW_PORT)),8080)
 MAILPIT_UI_PORT := $(or $(strip $(call env-val,MAILPIT_UI_PORT)),8025)
 ML_DATABASE_URL ?= postgresql+psycopg://$(PG_USER):$(PG_PASSWORD)@localhost:$(PG_PORT)/$(PG_DB)
@@ -35,7 +37,7 @@ DEMO_NOW ?= 2024-12-31T00:00:00Z
         lint format typecheck test test-cov test-integration check \
         openapi docker-build db-up db-down db-reset db-logs db-psql db-wait db-ensure-airflow \
         migrate bootstrap-admin services-up demo-data demo-data-force \
-        ml-lint ml-typecheck ml-test ml-check ml-train ml-score detect-alerts recommendations \
+        ml-lint ml-typecheck ml-test ml-check ml-train ml-score mlflow-up detect-alerts recommendations \
         airflow-lint airflow-test airflow-check airflow-up airflow-down airflow-logs \
         tls-selfsigned tls-acme tls-renew stack-up stack-down stack-logs
 
@@ -118,6 +120,14 @@ ml-train: ## Entraine le modele LightGBM. CSV=chemin optionnel, sinon lit ML_DAT
 ml-score: ## Score le prochain pas horaire et l'ecrit dans `prediction`. CSV= et NOW= optionnels
 	cd $(ML) && uv run python -m enervision_ml.score $(if $(CSV),--csv $(CSV),) $(if $(NOW),--now $(NOW),)
 
+mlflow-up: ## Démarre le serveur MLflow (tracking + registry) en conteneur. ml/.env requis
+	@test -n "$(strip $(ML_ENV_DB_PASSWORD))" \
+		|| { echo "MLFLOW_DB_PASSWORD absente de ml/.env (copier ml/.env.example)"; exit 1; }
+	@echo "$(ML_ENV_DB_PASSWORD)" | grep -qE '^[A-Za-z0-9]+$$' \
+		|| { echo "MLFLOW_DB_PASSWORD doit contenir uniquement lettres et chiffres (interpolee dans l'URI postgresql://)"; exit 1; }
+	cd $(ML) && docker compose -f docker-compose.mlflow.yml up -d --build
+	@echo "mlflow   -> http://localhost:5000"
+
 detect-alerts: ## Détecte les alertes internes depuis les lectures en base. SITE= et NOW= optionnels
 	cd $(BACKEND) && uv run python -m app.detection.internal_alerts $(if $(SITE),--site-id $(SITE),) $(if $(NOW),--now $(NOW),)