updated

app.py

@@ -5,6 +5,7 @@ from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
 from sklearn.ensemble import RandomForestClassifier
 import joblib
+import re
 
 # Load and preprocess data
 def load_and_preprocess_data(filename):
@@ -38,8 +39,8 @@ joblib.dump(label_encoders, "label_encoders.pkl")
 
 # Prediction function
 def predict_colleges(category, gender, rank, region):
-    if not isinstance(rank, (int, float)) or rank < 0:
-        return "Invalid Rank: Please enter a valid positive number."
+    if not isinstance(rank, (int, float)) or rank < 0 or not re.match(r'^\d+$', str(rank)):
+        return "Invalid Rank: Please enter a valid positive integer without symbols."
     
     # Load label encoders
     label_encoders = joblib.load("label_encoders.pkl")
@@ -77,7 +78,7 @@ demo = gr.Interface(
     inputs=[
         gr.Dropdown(choices=["OC", "BC", "SC", "ST"], label="Category"),
         gr.Radio(choices=["Male", "Female"], label="Gender"),
-        gr.Number(label="Rank", precision=0),  # Restrict to whole numbers only
+        gr.Textbox(label="Rank", type="number"),  # Restrict to number input
         gr.Dropdown(choices=["AU", "SV"], label="Region")
     ],
     outputs=gr.Dataframe(headers=["College Name", "Branch"]),
@@ -85,4 +86,4 @@ demo = gr.Interface(
     description="Enter your details to predict all possible colleges and branches based on your rank."
 )
 
-demo.launch()
+demo.launch()