Update app.py

app.py

@@ -41,7 +41,7 @@ def preprocess_input(short_description, impact, priority, category, urgency):
         input_data[column] = label_encoders[column].fit_transform(input_data[column])
     short_description = input_data['short_description'].iloc[0].lower()
     # Tokenize text data
-    sequences = tokenizer.texts_to_sequences(short_description)
+    sequences = tokenizer.texts_to_sequences([short_description])
     print("Short description",input_data['short_description'].iloc[0])
     print("Sequence",sequences)
     if not sequences:
@@ -55,8 +55,9 @@ def preprocess_input(short_description, impact, priority, category, urgency):
     # Normalize numerical features
     numerical_features = input_data[['impact', 'priority', 'category', 'urgency', 'sentiment_score']]
     scaler = StandardScaler()
-    scaled_numerical_features = scaler.fit_transform(numerical_features)
     
+    scaled_numerical_features = scaler.fit_transform(numerical_features)
+
     # Prepare the final input features
     X_input = np.concatenate([padded_sequences, scaled_numerical_features], axis=1)
     return X_input, input_data['sentiment_score'].iloc[0]