Update app.py

app.py

@@ -3,6 +3,7 @@ import joblib
 import pandas as pd
 import datasets
 import json
+import numpy as np
 
 # Load the model
 pipe = joblib.load("./model.pkl")
@@ -32,18 +33,44 @@ outputs = [gr.Dataframe(row_count=(2, "dynamic"), col_count=(1, "fixed"), label=
     #predictions = pipe.predict(data)
     #return pd.DataFrame(predictions, columns=["Depression"])
 
+#code to fix missing columns with na
+#def infer(inputs):
+    #data = pd.DataFrame(inputs, columns=headers)
+    # Add missing columns with default values (e.g., 0)
+    #for col in all_headers:
+        #if col not in data.columns:
+            #data[col] = 0
+    # Ensure the order of columns matches the training data
+    #data = data[all_headers]
+    #predictions = pipe.predict(data)
+    #return pd.DataFrame(predictions, columns=["Depression"])
+
+
 def infer(inputs):
     data = pd.DataFrame(inputs, columns=headers)
+    
+    # Replace empty strings with NaN
+    data = data.replace('', np.nan)
+    
     # Add missing columns with default values (e.g., 0)
     for col in all_headers:
         if col not in data.columns:
             data[col] = 0
+    
     # Ensure the order of columns matches the training data
     data = data[all_headers]
+    
+    # Fill NaN values with default values (e.g., 0)
+    data = data.fillna(0)
+    
+    # Convert all data to float
+    data = data.astype(float)
+    
     predictions = pipe.predict(data)
     return pd.DataFrame(predictions, columns=["Depression"])
 
 
+
 gr.Interface(
     fn=infer,
     inputs=inputs,