Update app.py

app.py

@@ -1,6 +1,5 @@
 import gradio as gr
 import pandas as pd
-import numpy as np
 import joblib, os
 
 script_dir = os.path.dirname(os.path.abspath(__file__))
@@ -11,13 +10,14 @@ model_path = os.path.join(script_dir, 'toolkit', 'Random Forest Classifier.jobli
 pipeline = joblib.load(pipeline_path)
 model = joblib.load(model_path)
 
-# Update predict function to handle new parameters
+# Load the heart.csv data
+heart_data_path = os.path.join(script_dir, 'heart.csv')
+heart_df = pd.read_csv(heart_data_path)
+
+# Define the predict function
 def predict(age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal):
     # Create a dataframe with the input data
-
-  input_df = pd.read_csv("heart.csv") 
-'''    
- input_df = pd.DataFrame({
+    input_df = pd.DataFrame({
         'age': [age],
         'sex': [sex],
         'cp': [cp],
@@ -32,7 +32,7 @@ def predict(age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak,
         'ca': [ca],
         'thal': [thal]
     })
- '''
+
     # Process input data using the pipeline
     X_processed = pipeline.transform(input_df)