Merge pull request #2799 from bluewave-labs/develop

Merging Develop into Master - Dec 2nd, 2025

Author: HarshP4585

.env.dev

@@ -2,9 +2,9 @@
 # NOTE: Please do not change the BACKEND_PORT
 BACKEND_PORT=3000
 BACKEND_URL=http://localhost:3000
-FRONTEND_PORT=8082
-FRONTEND_URL=http://localhost:8082
-ALLOWED_ORIGINS=["http://localhost:5173", "http://localhost:8082", "http://localhost:3000"]
+FRONTEND_PORT=5173
+FRONTEND_URL=http://localhost:5173
+HOST=localhost
 BIAS_AND_FAIRNESS_PORT=8000
 NODE_ENV=development
 

.env.prod

@@ -4,7 +4,7 @@ BACKEND_PORT=3000
 BACKEND_URL=http://localhost:3000 # localhost needs to be replaced by ip
 FRONTEND_PORT=8080
 FRONTEND_URL=http://localhost:8080 # localhost needs to be replaced by ip
-ALLOWED_ORIGINS=["http://localhost:5173", "http://localhost:8080", "http://localhost:3000"] # localhost needs to be replaced by ip
+HOST=localhost
 BIAS_AND_FAIRNESS_PORT=8000
 NODE_ENV=production
 # NOTE: Please do not change this unless the database is hosted on a different server and you want to use SSL for the connection

.gitignore

@@ -25,4 +25,5 @@ agent-output.md
 FILE_MANAGER_WORKFLOW.md
 SYSTEM_DESIGN_FILE_MANAGER.md
 SYSTEM_DESIGN_EMAIL_NOTIFICATION.md
-FILE_STORAGE_ARCHITECTURE.md
+FILE_STORAGE_ARCHITECTURE.md
+Authentication_Authorization_Workflow_Documentation.md

BiasAndFairnessModule/run_full_evaluation.py

@@ -252,7 +252,7 @@ def _run_metric(metric_name: str, y_true: np.ndarray, y_pred: np.ndarray,
         race_value = convert_metric_to_float(race_result, metric_name)
         all_results[f"{metric_name}_race"] = race_value
 
-        print(f"      ✅ {metric_name}: sex={sex_value:.4f}, race={race_value:.4f}")
+        print(f"      ✅ {metric_name}: computed for sex and race (values not logged for privacy)")
 
     except Exception as e:
         print(f"      ❌ {metric_name}: Error - {str(e)}")
@@ -388,7 +388,7 @@ def _print_pipeline_summary(comprehensive_results: dict, clean_results: dict):
     if fairness_values:
         max_disparity_sex = max(fairness_values.values())
         max_metric_sex = max(fairness_values, key=fairness_values.get)
-        print(f"   Highest sex-based disparity: {max_metric_sex} = {max_disparity_sex:.4f}")
+        print(f"   Sex-based disparities detected. (Metric name and value omitted for privacy.)")
 
     fairness_values_race = {k: v for k, v in comprehensive_results['fairness_metrics'].items() 
                            if v is not None and 'race' in k}

BiasAndFairnessModule/src/eval_engine/results_summarizer.py

@@ -60,7 +60,7 @@ def summarize_results(results_path: str = 'artifacts/evaluation_results.json') -
     eo_sex = results['fairness']['equalized_odds_sex']
     eo_race = results['fairness']['equalized_odds_race']
 
-    print(f"   Equalized Odds (Sex): {eo_sex:.3f}")
+    print("   Equalized Odds (Sex): See assessment below")
     if abs(eo_sex) < 0.1:
         print("     ✅ Good: Similar true positive and false positive rates")
     elif abs(eo_sex) < 0.2: