Update app.py

app.py

@@ -18,7 +18,7 @@ mapping = {
 }
 
 # Define the function for making predictions
-def salarybracket(age, workclass, education, marital_status, occupation, relationship, race, gender, native_country):
+def salarybracket(age, workclass, education, education_num, marital_status, occupation, relationship, race, gender, capital_gain, capital_loss, hours_per_week, native_country):
     # Get the value associated with the selected label
     workclass_value = next((v for k, v in mapping['workclass'].items() if k == workclass), None)
     education_value = next((v for k, v in mapping['education'].items() if k == education), None)
@@ -29,7 +29,7 @@ def salarybracket(age, workclass, education, marital_status, occupation, relatio
     gender_value = next((v for k, v in mapping['gender'].items() if k == gender), None)
     native_country_value = next((v for k, v in mapping['native_country'].items() if k == native_country), None)
     
-    inputs = np.array([[age, workclass_value, education_value, marital_status_value, occupation_value, relationship_value, race_value, gender_value, native_country_value]])
+    inputs = np.array([[age, workclass_value, education_value, education_num, marital_status_value, occupation_value, relationship_value, race_value, gender_value, capital_gain, capital_loss, hours_per_week, native_country_value]])
     prediction = model.predict(inputs)
     prediction_value = prediction[0][0]  # Assuming the prediction is a scalar
     result = "Income_bracket lesser than or equal to 50K ⬇️" if prediction_value <= 0.5 else "Income_bracket greater than 50K ⬆️"
@@ -49,12 +49,16 @@ salarybracket_ga = gr.Interface(fn=salarybracket,
                                     gr.Slider(17, 90, label="Age"),
                                     gr.Dropdown(dropdown_options['workclass'], label="Workclass"),
                                     gr.Dropdown(dropdown_options['education'], label="Education"),
+                                    gr.Number(1, 16, label="Education Num [1 to 16]"),
                                     gr.Dropdown(dropdown_options['marital_status'], label="Marital Status"),
                                     gr.Dropdown(dropdown_options['occupation'], label="Occupation"),
                                     gr.Dropdown(dropdown_options['relationship'], label="Relationship"),
                                     gr.Dropdown(dropdown_options['race'], label="Race"),
                                     gr.Dropdown(dropdown_options['gender'], label="Gender"),
-                                    gr.Dropdown(dropdown_options['native_country'], label="Native Country")
+                                    gr.Number(0, 99999, label="Capital Gain [0 to 99999]"),
+                                    gr.Number(0, 4356, label="Capital Loss [0 to 4356]"),
+                                    gr.Number(1, 99, label="Hours per Week [1 to 99]"),
+                                    gr.Dropdown(dropdown_options['native_country'], label="Native Country")                                        
                                 ],
                                 outputs="text",
                                 title="Salary Bracket Prediction",