Update app.py

app.py

@@ -1,12 +1,17 @@
 #!pip install gradio --upgrade  # Upgrade to the latest version of Gradio
+#!pip install huggingface_hub joblib
 
 import gradio as gr
 import pandas as pd
 import joblib
 from huggingface_hub import hf_hub_download
+import os
 
-# Your Hugging Face token
-token = "token"
+# Load the Hugging Face token from the environment variable
+token = os.getenv("HF_TOKEN")
+
+if token is None:
+    raise ValueError("Hugging Face token not found. Please set the 'HF_TOKEN' environment variable.")
 
 # Download the model and scaler from the Hugging Face Hub using the token
 model_path = hf_hub_download(repo_id="rama0519/DiabeticLogistic123", filename="logistic_regression_model.joblib", use_auth_token=token)
@@ -53,7 +58,6 @@ def predict_diabetes(pregnancies, glucose, blood_pressure, skin_thickness, insul
     return prediction_text
 
 # Create the Gradio interface
-# Use gr.Slider to allow for setting min and max values
 interface = gr.Interface(
     fn=predict_diabetes,
     inputs=[
@@ -72,4 +76,4 @@ interface = gr.Interface(
 )
 
 # Launch the interface
-interface.launch()
+interface.launch()