Update app.py

app.py

@@ -1,7 +1,16 @@
+import subprocess
+import sys
+
+# Check if scikit-learn is installed, if not install it
+try:
+    import sklearn
+except ModuleNotFoundError:
+    subprocess.check_call([sys.executable, "-m", "pip", "install", "scikit-learn"])
+    import sklearn
+
 import gradio as gr
 import pandas as pd
 import pickle
-import sklearn
 
 # Load the pre-trained model
 with open('best_model.pkl', 'rb') as model_file:
@@ -50,18 +59,4 @@ interface = gr.Interface(
     inputs=[
         gr.Dropdown(['morning', 'afternoon', 'evening'], label="Time of Day"),
         gr.Dropdown(['mild', 'regular', 'strong'], label="Coffee Strength"),
-        gr.Dropdown(['unsweetened', 'lightly sweetened', 'sweet'], label="Sweetness Level"),
-        gr.Dropdown(['none', 'regular', 'skim', 'almond'], label="Milk Type"),
-        gr.Dropdown(['hot', 'iced', 'cold brew'], label="Coffee Temperature"),
-        gr.Dropdown(['yes', 'no'], label="Flavored Coffee"),
-        gr.Dropdown(['low', 'medium', 'high'], label="Caffeine Tolerance"),
-        gr.Dropdown(['Arabica', 'Robusta', 'blend'], label="Coffee Bean"),
-        gr.Dropdown(['small', 'medium', 'large'], label="Coffee Size"),
-        gr.Dropdown(['none', 'vegan', 'lactose-intolerant'], label="Dietary Preferences")
-    ],
-    outputs=gr.Textbox(label="Recommended Coffee Type"),
-    title="Coffee Type Recommendation"
-)
-
-if __name__ == "__main__":
-    interface.launch()
+        gr.Dropdown(['unsweetened', 'lightly sweetened',