[Unit]
Description=Retrain the Ping River flood forecast models
Documentation=https://git.b4l.co.th/B4L/Northern-Thailand-Ping-River-Monitor/-/blob/master/docs/FLOOD_FORECASTING.md
After=network-online.target
Wants=network-online.target

[Service]
Type=oneshot
User=water-monitor
Group=water-monitor
WorkingDirectory=/opt/thailand-water-monitor
EnvironmentFile=/opt/thailand-water-monitor/.env
# Same interpreter as water-monitor.service -- the uv-managed .venv.
# scripts/retrain.sh trains into models/.staging, refuses to promote anything
# that is not a rain-enabled (hgb-v3) set covering the expected stations, then
# renames the bundles into place. The API reloads them on its next hourly
# precompute; no restart, so a failed run leaves the old models serving.
ExecStart=/bin/bash /opt/thailand-water-monitor/scripts/retrain.sh
# HistGradientBoosting is CPU-bound; cap threads so training cannot starve
# the API (docs/FLOOD_FORECASTING.md section 6 measured 4 as the sweet spot).
Environment=OMP_NUM_THREADS=4
Environment=PYTHONPATH=/opt/thailand-water-monitor
Environment=PYTHONUNBUFFERED=1
Nice=15
IOSchedulingClass=idle
# 15 stations at ~50 s each plus data load: 12 min observed on 2026-09-12.
TimeoutStartSec=45min

# Same sandbox as the API unit.
NoNewPrivileges=true
PrivateTmp=true
ProtectSystem=strict
ProtectHome=true
ReadWritePaths=/opt/thailand-water-monitor
CapabilityBoundingSet=

StandardOutput=journal
StandardError=journal
SyslogIdentifier=water-monitor-retrain