Update app.py

app.py

@@ -179,7 +179,35 @@ def hbdscan_tranform(df_transformed):
     return df_transformed
 
 # Shared inputs
-inputs = [
+ann_inputs = [
+    gr.Slider(18, 90, step=1, label="Age"),
+    gr.Dropdown(["Male", "Female"], label="Gender"),
+    gr.Dropdown(["Private", "Self-emp-not-inc", "Self-emp-inc", "Federal-gov", "Local-gov", "State-gov", "Without-pay", "Never-worked"], label="Workclass"),
+    gr.Dropdown(["Preschool", "1st-4th", "5th-6th", "7th-8th", "9th", "10th", "11th", "12th", "HS-grad", "Some-college", "Assoc-voc", "Assoc-acdm", "Bachelors", "Masters", "Doctorate", "Prof-school"], label="Education"),
+    gr.Dropdown(["Married-civ-spouse", "Divorced", "Never-married", "Separated", "Widowed", "Married-spouse-absent", "Married-AF-spouse"], label="Marital Status"),
+    gr.Dropdown(["Tech-support", "Craft-repair", "Other-service", "Sales", "Exec-managerial", "Prof-specialty", "Handlers-cleaners", "Machine-op-inspct", "Adm-clerical", "Farming-fishing", "Transport-moving", "Priv-house-serv", "Protective-serv", "Armed-Forces"], label="Occupation"),
+    gr.Dropdown(["Wife", "Husband", "Own-child", "Not-in-family", "Other-relative", "Unmarried"], label="Relationship"),
+    gr.Dropdown(["White", "Black", "Asian-Pac-Islander", "Amer-Indian-Eskimo", "Other"], label="Race"),
+    gr.Slider(0, 100000, step=100, label="Capital Gain"),
+    gr.Slider(0, 5000, step=50, label="Capital Loss"),
+    gr.Slider(1, 60, step=1, label="Hours Per Week"),
+    gr.Dropdown(["United-States", "Canada", "Mexico", "Other"], label="Native Country")
+]
+rf_inputs = [
+    gr.Slider(18, 90, step=1, label="Age"),
+    gr.Dropdown(["Male", "Female"], label="Gender"),
+    gr.Dropdown(["Private", "Self-emp-not-inc", "Self-emp-inc", "Federal-gov", "Local-gov", "State-gov", "Without-pay", "Never-worked"], label="Workclass"),
+    gr.Dropdown(["Preschool", "1st-4th", "5th-6th", "7th-8th", "9th", "10th", "11th", "12th", "HS-grad", "Some-college", "Assoc-voc", "Assoc-acdm", "Bachelors", "Masters", "Doctorate", "Prof-school"], label="Education"),
+    gr.Dropdown(["Married-civ-spouse", "Divorced", "Never-married", "Separated", "Widowed", "Married-spouse-absent", "Married-AF-spouse"], label="Marital Status"),
+    gr.Dropdown(["Tech-support", "Craft-repair", "Other-service", "Sales", "Exec-managerial", "Prof-specialty", "Handlers-cleaners", "Machine-op-inspct", "Adm-clerical", "Farming-fishing", "Transport-moving", "Priv-house-serv", "Protective-serv", "Armed-Forces"], label="Occupation"),
+    gr.Dropdown(["Wife", "Husband", "Own-child", "Not-in-family", "Other-relative", "Unmarried"], label="Relationship"),
+    gr.Dropdown(["White", "Black", "Asian-Pac-Islander", "Amer-Indian-Eskimo", "Other"], label="Race"),
+    gr.Slider(0, 100000, step=100, label="Capital Gain"),
+    gr.Slider(0, 5000, step=50, label="Capital Loss"),
+    gr.Slider(1, 60, step=1, label="Hours Per Week"),
+    gr.Dropdown(["United-States", "Canada", "Mexico", "Other"], label="Native Country")
+]
+hbd_inputs = [
     gr.Slider(18, 90, step=1, label="Age"),
     gr.Dropdown(["Male", "Female"], label="Gender"),
     gr.Dropdown(["Private", "Self-emp-not-inc", "Self-emp-inc", "Federal-gov", "Local-gov", "State-gov", "Without-pay", "Never-worked"], label="Workclass"),
@@ -197,7 +225,7 @@ inputs = [
 # Interfaces for each model
 ann_interface = gr.Interface(
     fn=predict_ann,
-    inputs=inputs,
+    inputs=ann_inputs,
     outputs="text",
     title="Artificial Neural Network",
     description="Predict income using an Artificial Neural Network."
@@ -205,7 +233,7 @@ ann_interface = gr.Interface(
 
 rf_interface = gr.Interface(
     fn=predict_rf,
-    inputs=inputs,
+    inputs=rf_inputs,
     outputs="text",
     title="Random Forest",
     description="Predict income using a Random Forest model."
@@ -213,17 +241,15 @@ rf_interface = gr.Interface(
 
 hb_interface = gr.Interface(
     fn=predict_hb,
-    inputs=inputs,
+    inputs=hbd_inputs,
     outputs="text",
     title="HDBScan Clustering",
     description="Predict income using a HDBScan Clustering model."
 )
 
-
 interface = gr.TabbedInterface(
     [ann_interface, rf_interface, hb_interface],
     ["ANN Model", "Random Forest Model", "HDBScan Model"]
 )
 
-
 interface.launch()