fix(ml): corrige le build MLflow (psycopg2), le garde-fou Makefile, la doc et la fuite de mot de passe

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)

docs/architecture/10-infra.md

@@ -155,7 +155,7 @@ du `docker-compose.yml` principal (réseau, volumes et démarrage séparés).
 
 | Service | Image | Points notables |
 |---|---|---|
-| `mlflow-db` | `postgres:16` | Stocke le tracking store MLflow. Mot de passe obligatoire via `MLFLOW_DB_PASSWORD` |
+| `mlflow-db` | `postgres:17` | Stocke le tracking store MLflow. Mot de passe obligatoire via `MLFLOW_DB_PASSWORD` |
 | `mlflow` | Construite depuis `ml/` | Expose l'UI et l'API MLflow sur `127.0.0.1:5000`. Artefacts sur volume `mlflow-artifacts`, tracking store sur `mlflow-db` |
 
 Portée actuelle : environnement de tracking et de registre de modèles pour le développement

ml/Dockerfile

@@ -1,5 +1,5 @@
 FROM python:3.14-slim
-RUN pip install --no-cache-dir --only-binary :all: mlflow==3.16.1 psycopg2-binary==2.9.10
+RUN pip install --no-cache-dir --only-binary :all: mlflow==3.16.1 psycopg2-binary==2.9.13
 RUN useradd --create-home --uid 1000 mlflow \
     && mkdir /mlartifacts \
     && chown mlflow /mlartifacts

ml/docker-compose.mlflow.yml

@@ -21,12 +21,11 @@ services:
       - "127.0.0.1:5000:5000"
     volumes:
       - mlflow-artifacts:/mlartifacts
-    command: >
+    environment:
-      mlflow server
+      MLFLOW_DB_PASSWORD: ${MLFLOW_DB_PASSWORD}
-      --host 0.0.0.0 --port 5000
+    entrypoint: [ "/bin/sh", "-c" ]
-      --backend-store-uri postgresql://mlflow:${MLFLOW_DB_PASSWORD}@mlflow-db:5432/mlflow
+    command:
-      --artifacts-destination /mlartifacts
+      - exec mlflow server --host 0.0.0.0 --port 5000 --backend-store-uri "postgresql://mlflow:$$MLFLOW_DB_PASSWORD@mlflow-db:5432/mlflow" --artifacts-destination /mlartifacts --serve-artifacts
-      --serve-artifacts
 
 volumes:
   mlflow-db-data: