3 Commits
Author SHA1 Message Date
grabowski 764764e07e feat: refuse silent v3->v2 downgrade; monthly retrain timer with staged promote
train_all() now raises RainUnavailableError when use_rain=True and the
Open-Meteo history cannot be loaded, instead of logging a warning and
writing gauge-only (v2) bundles over the deployed v3 set -- which is what
the 2026-09-01 server retrain did unnoticed. --no-rain remains the explicit
way to get v2. CLI exits 2 with a one-line error. Three tests cover the
guard, the opt-out, and the v3 happy path.

scripts/retrain.sh trains into models/.staging, refuses to promote unless
metrics.json shows hgb-v3+ and >=14 trained stations, then renames bundles
into place (previous generation kept in models/.previous). No API restart:
predict.py reloads by mtime on the hourly precompute.

water-monitor-retrain.{service,timer}: 1st of each month 03:30, Persistent,
OMP_NUM_THREADS=4, Nice=15, same sandbox as the API unit. install.sh now
does `uv sync` into .venv (one env rule; removes a stale venv/) and enables
the timer. water-monitor.service in the repo matched neither the deployed
unit nor the uv env; it now does (run.py --web-api, .venv, EnvironmentFile).
2026-09-11 21:37:11 +02:00
grabowski ab8a10dd75 Add install.sh and fix service unit placeholder
- scripts/install.sh: one-command hardened deploy (creates the water-monitor
  system user, deploys to /opt, builds a uv-managed venv, installs and enables
  the systemd unit). Idempotent; excludes .env/*.db/stations.json from sync so
  runtime state is preserved.
- Fix placeholder Documentation= URL in water-monitor.service.
- README: document the script as the primary systemd install path, with manual
  steps kept as a fallback.
2026-07-22 12:55:17 +07:00
grabowski af62cfef0b Initial commit: Northern Thailand Ping River Monitor v3.1.0
Security & Dependency Updates / Dependency Security Scan (push) Successful in 29s
Security & Dependency Updates / Docker Security Scan (push) Failing after 53s
Security & Dependency Updates / License Compliance (push) Successful in 13s
Security & Dependency Updates / Check for Dependency Updates (push) Successful in 19s
Security & Dependency Updates / Code Quality Metrics (push) Successful in 11s
Security & Dependency Updates / Security Summary (push) Successful in 7s
Features:
- Real-time water level monitoring for Ping River Basin (16 stations)
- Coverage from Chiang Dao to Nakhon Sawan in Northern Thailand
- FastAPI web interface with interactive dashboard and station management
- Multi-database support (SQLite, MySQL, PostgreSQL, InfluxDB, VictoriaMetrics)
- Comprehensive monitoring with health checks and metrics collection
- Docker deployment with Grafana integration
- Production-ready architecture with enterprise-grade observability

 CI/CD & Automation:
- Complete Gitea Actions workflows for CI/CD, security, and releases
- Multi-Python version testing (3.9-3.12)
- Multi-architecture Docker builds (amd64, arm64)
- Daily security scanning and dependency monitoring
- Automated documentation generation
- Performance testing and validation

 Production Ready:
- Type safety with Pydantic models and comprehensive type hints
- Data validation layer with range checking and error handling
- Rate limiting and request tracking for API protection
- Enhanced logging with rotation, colors, and performance metrics
- Station management API for dynamic CRUD operations
- Comprehensive documentation and deployment guides

 Technical Stack:
- Python 3.9+ with FastAPI and Pydantic
- Multi-database architecture with adapter pattern
- Docker containerization with multi-stage builds
- Grafana dashboards for visualization
- Gitea Actions for CI/CD automation
- Enterprise monitoring and alerting

 Ready for deployment to B4L infrastructure!
2025-08-12 15:40:24 +07:00