SIENTIAPDE-1273

Update requirements and enhance metrics and data handling

- Updated the sientia-dataops-library dependency version in requirements.txt to 1.5.3.
- Added new metrics for model analysis, including lag, count, and error count in metrics.py.
- Implemented a new method for formatting transformed data in gates.py.
- Enhanced MLFlowRepository with methods to load artifact dataframes and calculate model metrics, including drift and performance metrics.
- Updated the prediction process to handle transformed data and ensure proper execution of related activities in format_and_export_prediction.py and prediction_process.py.

laborious/metrics.py

@@ -169,3 +169,22 @@ MODEL_WRITE_ERROR_COUNT = Counter(
     'Number of errors writing to the model',
     SIENTIA_CORE_LABELS,
 )
+
+MODEL_ANALYZE_LAG = Histogram(
+    'laborious_model_analyze_lag',
+    'Lag between the start and end of analyze operations',
+    SIENTIA_CORE_LABELS,
+    buckets=[0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0],
+)
+
+MODEL_ANALYZE_COUNT = Counter(
+    'laborious_model_analyze_count',
+    'Number of analyze operations',
+    SIENTIA_CORE_LABELS,
+)
+
+MODEL_ANALYZE_ERROR_COUNT = Counter(
+    'laborious_model_analyze_error_count',
+    'Number of errors during analyze operations',
+    SIENTIA_CORE_LABELS,
+)