Update app.py

app.py

@@ -4,6 +4,10 @@ from joblib import load
 from tensorflow.keras.models import load_model
 import tensorflow as tf
 import pickle
+import pandas as pd  # Ensure pandas is imported for DataFrame operations
+
+# Load dataset
+df = pd.read_csv('your_dataset.csv')  # Replace with the correct path to your dataset
 
 # Load the LabelEncoder and ColumnTransformer before prediction
 with open('label_encoder.pkl', 'rb') as f:
@@ -108,10 +112,8 @@ def predict_dosage(gender, race, age, height, weight, diabetes, simvastatin, ami
 # Launch Gradio app
 gr.Interface(
     fn=predict_dosage,
-    inputs=[
-        input_Gender, input_Race, input_Age, input_Height, input_Weight,
-        input_Diabetes, input_Simvastatin, input_Amiodarone,
-        input_INR_reported, input_Cyp2C9_genotypes, input_VKORC1_genotypes, input_model
-    ],
+    inputs=[input_Gender, input_Race, input_Age, input_Height, input_Weight,
+            input_Diabetes, input_Simvastatin, input_Amiodarone,
+            input_INR_reported, input_Cyp2C9_genotypes, input_VKORC1_genotypes, input_model],
     outputs=[output_warfarin_dosage]
 ).launch(debug=True)