feat: log regression metrics as parameters in Training class

- Added a method to persist computed regression metrics (MSE, MAE, R²) as MLflow parameters during model training, enhancing model evaluation and tracking.
- Updated the Training class to log the equation path if available, improving artifact management.

model_manager/sientia/reports.py

@@ -19,8 +19,8 @@ from evidently.metrics import (
 )
 from evidently.metrics.base_metric import generate_column_metrics
 from evidently.options import ColorOptions
-from evidently.report import Report
 from evidently.pipeline.column_mapping import ColumnMapping
+from evidently.report import Report
 
 COLOR_DISCRETE_SEQUENCE = (
     '#ed0400',
@@ -36,17 +36,18 @@ def load_html_from_file(file_path):
     with open(file_path, encoding='utf-8') as file:
         return file.read()
 
+
 def inject_content(main_html, section_id, content):
     soup = BeautifulSoup(main_html, 'html.parser')
     section = soup.find(id=section_id)
-    
+
     # Verifica se a seção foi encontrada E se ela é uma Tag (não uma string)
     if section and isinstance(section, Tag):
         section.clear()
         # Converte o conteúdo para um fragmento de BeautifulSoup e anexa
         new_content = BeautifulSoup(content, 'html.parser')
         section.append(new_content)
-        
+
     return str(soup)
 
 
@@ -68,7 +69,12 @@ class Reports:
     """
 
     def __init__(
-        self, reference_data: Any, current_data: Any, target_name: str, base_path: str | None = None, template_path: str | None = None
+        self,
+        reference_data: Any,
+        current_data: Any,
+        target_name: str,
+        base_path: str | None = None,
+        template_path: str | None = None,
     ) -> None:
         """
         Initializes an instance of the AigReport class.
@@ -151,7 +157,7 @@ class Reports:
 
             mapping.target = self.target_name
             mapping.prediction = 'prediction'
-            
+
             report = Report(metrics=metrics, options=self.options)
             report.run(
                 reference_data=self.ref_data,
@@ -247,10 +253,10 @@ class Reports:
         if output_dir and not os.path.exists(output_dir):
             os.makedirs(output_dir, exist_ok=True)
 
-        print(f"Output directory: {output_dir}")
-        print(f"Report path: {report_path}")
-        print(f"Base path: {self.base_path}")
-        print(f"Template path: {self.template_path}")
+        print(f'Output directory: {output_dir}')
+        print(f'Report path: {report_path}')
+        print(f'Base path: {self.base_path}')
+        print(f'Template path: {self.template_path}')
 
         # Load main HTML template
         main_html_path = os.path.join(self.template_path, 'header.html')