feat: add routed model training pipeline

src/lmpm/scripts/train.py

@@ -0,0 +1,36 @@
+"""Train every routed model from the external SQLite material dataset."""
+
+import argparse
+import json
+from pathlib import Path
+
+from lmpm.training.workflow import train_sqlite_database
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description="Train LMPM target models from a completed SQLite dataset."
+    )
+    parser.add_argument(
+        "database", type=Path, help="SQLite database with material_records"
+    )
+    parser.add_argument(
+        "artifact", type=Path, help="Destination .joblib model artifact"
+    )
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    bundle = train_sqlite_database(args.database, args.artifact)
+    report_path = args.artifact.with_suffix(".metrics.json")
+    report_path.write_text(
+        json.dumps(bundle.report(), ensure_ascii=False, indent=2) + "\n",
+        encoding="utf-8",
+    )
+    print(f"saved model artifact: {args.artifact}")
+    print(f"saved validation report: {report_path}")
+
+
+if __name__ == "__main__":
+    main()