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.

input-sample.md

@@ -32,7 +32,7 @@ mc cp input_dataset.csv suse/model-training/training-sample-dataset-1001.csv
 
 ##### Temporal input payload sample
 
-Keys match `TrainModelParams.from_dict` in `model_manager/utils/models/train_model_params.py`: every field passed to `_check_none` must be present; `model_metadata` must be non-empty for `validate_business_rules()`. Omit optional keys (`date_column`, `date_format`, `random_state`, `val_file_name`, `model_id`) when defaults or `None` apply.
+Keys match `TrainModelParams.from_dict` in `model_manager/utils/models/train_model_params.py`: every field passed to `_check_none` must be present, including **`date_column`**; `model_metadata` must be non-empty for `validate_business_rules()`. You may omit **`date_format`** (defaults to `yyyy-MM-dd HH:mm:ss`). Omit optional keys (`random_state`, `val_file_name`, `model_id`) when defaults or `None` apply.
 
 ```json
 {
@@ -43,6 +43,7 @@ Keys match `TrainModelParams.from_dict` in `model_manager/utils/models/train_mod
   "file_name": "training-sample-dataset-1001.csv",
   "line_separator": ",",
   "decimal_separator": ".",
+  "date_column": "timestamp",
   "train_size": 80,
   "shuffle": true,
   "random_state": 42,