Upload predict.py with huggingface_hub

predict.py

@@ -29,17 +29,40 @@ base_models = components['base_models']
 meta_model = components['meta_model']
 threshold = components.get('threshold_stacked', 0.5)
 
+import argparse
+
+# Parse arguments
+parser = argparse.ArgumentParser(description='Stroke Risk Predictor')
+parser.add_argument('--gender', type=str, default='Male', choices=['Male', 'Female'], help='Gender')
+parser.add_argument('--age', type=float, default=75, help='Age of the patient')
+parser.add_argument('--hypertension', type=int, default=1, choices=[0, 1], help='0: No, 1: Yes')
+parser.add_argument('--heart_disease', type=int, default=1, choices=[0, 1], help='0: No, 1: Yes')
+parser.add_argument('--ever_married', type=str, default='Yes', choices=['Yes', 'No'], help='Ever married?')
+parser.add_argument('--work_type', type=str, default='Private', 
+                    choices=['Private', 'Self-employed', 'Govt_job', 'children', 'Never_worked'], help='Work type')
+parser.add_argument('--Residence_type', type=str, default='Urban', choices=['Urban', 'Rural'], help='Residence type')
+parser.add_argument('--avg_glucose_level', type=float, default=220.5, help='Average glucose level')
+parser.add_argument('--bmi', type=float, default=30.1, help='Body Mass Index')
+parser.add_argument('--smoking_status', type=str, default='formerly smoked', 
+                    choices=['formerly smoked', 'never smoked', 'smokes', 'Unknown'], help='Smoking status')
+
+args = parser.parse_args()
+
+print("\nModel Input:")
+for arg, value in vars(args).items():
+    print(f"  {arg}: {value}")
+
 patient = pd.DataFrame([{
-    'gender': 'Male', # one of ['Male', 'Female'] # Other was dropped
-    'age': 75,
-    'hypertension': 1,
-    'heart_disease': 1,
-    'ever_married': 'Yes', # one of ['Yes', 'No']
-    'work_type': 'Private', # one of ['Private', 'Self-employed', 'Govt_job', 'Children', 'Never_worked']   
-    'Residence_type': 'Urban', # one of ['Urban', 'Rural']
-    'avg_glucose_level': 220.5,
-    'bmi': 30.1,
-    'smoking_status': 'formerly smoked' # one of ['formerly smoked', 'never smoked', 'smokes']
+    'gender': args.gender,
+    'age': args.age,
+    'hypertension': args.hypertension,
+    'heart_disease': args.heart_disease,
+    'ever_married': args.ever_married,
+    'work_type': args.work_type,
+    'Residence_type': args.Residence_type,
+    'avg_glucose_level': args.avg_glucose_level,
+    'bmi': args.bmi,
+    'smoking_status': args.smoking_status
 }])
 
 # 1. Preprocess