feat: require date_column in training parameters and update documentation

- Made `date_column` a required field in `TrainModelParams`, ensuring it must be present in the input data.
- Updated related documentation in `input-sample.md`, `README.md`, and various test scenarios to reflect the change in requirement.
- Adjusted the handling of `date_format` to default to `yyyy-MM-dd HH:mm:ss` if omitted, enhancing usability.
- Refined test scenarios to include new examples and ensure compliance with the updated parameter structure.

These changes improve the robustness of the model training workflow and clarify the expectations for input data.

e2e/test_cleanup_files_workflow.py

@@ -4,18 +4,17 @@ End-to-end tests for CleanupFiles workflow.
 Covers scenarios 3.x: cleanup of temporary local directories.
 """
 
-import os
-import shutil
-import tempfile
-
 import pytest
-import pytest_asyncio
 from temporalio.testing import WorkflowEnvironment
 from temporalio.worker import Worker
 
 from e2e.helpers import make_workflow_id, start_and_await_workflow
 from model_manager.workflows.cleanup_files import CleanupFiles
 
+# Matches Cleanup.dir_timestamp_pattern: name_YYYYMMDD_HHMMSS_microseconds
+_STALE_DIR_OLD = 'stale_run_20200102_030405_000001'
+_STALE_DIR_OLDER = 'stale_run_20191231_235959_999999'
+
 
 @pytest.mark.asyncio
 @pytest.mark.integration
@@ -59,9 +58,9 @@ async def test_scenario_3_1_2_cleanup_removes_old_temp_dirs(
     reports_dir = tmp_path / 'reports_temp'
     reports_dir.mkdir()
 
-    # Create two stale run directories
-    stale1 = reports_dir / 'run-1234567890'
-    stale2 = reports_dir / 'run-9876543210'
+    # Create two stale run directories (names must match cleanup activity regex)
+    stale1 = reports_dir / _STALE_DIR_OLD
+    stale2 = reports_dir / _STALE_DIR_OLDER
     stale1.mkdir()
     stale2.mkdir()
     (stale1 / 'model.pkl').write_bytes(b'fake-model-data')