Update app.py

app.py

@@ -20,8 +20,8 @@ from sklearn.metrics import accuracy_score
 
 
 # Suppress TensorFlow warnings
-os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
-os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
+os.environ["CUDA_VISIBLE_DEVICES"] = "-1"  # No GPU available, use CPU only
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"    # Suppress TensorFlow logging
 
 # Download necessary NLTK resources
 nltk.download("punkt")
@@ -59,7 +59,7 @@ def load_data():
         tr = pd.read_csv("Testing.csv")
     except FileNotFoundError:
         raise RuntimeError("Data files not found. Please ensure `Training.csv` and `Testing.csv` are uploaded correctly.")
-    
+
     disease_dict = {
         'Fungal infection': 0, 'Allergy': 1, 'GERD': 2, 'Chronic cholestasis': 3, 'Drug Reaction': 4,
         'Peptic ulcer diseae': 5, 'AIDS': 6, 'Diabetes': 7, 'Gastroenteritis': 8, 'Bronchial Asthma': 9,
@@ -71,11 +71,12 @@ def load_data():
         'Hypoglycemia': 32, 'Osteoarthritis': 33, 'Arthritis': 34
     }
 
+    # Replace prognosis values with numerical categories
     df.replace({'prognosis': disease_dict}, inplace=True)
-    df = df.infer_objects(copy=False)
+    df = df.infer_objects()  # Removed 'copy=False' argument
 
     tr.replace({'prognosis': disease_dict}, inplace=True)
-    tr = tr.infer_objects(copy=False)
+    tr = tr.infer_objects()  # Removed 'copy=False' argument
 
     return df, tr, disease_dict