Update app.py

app.py

@@ -11,26 +11,26 @@ def salarybracket(age, workclass, education, education_num, marital_status, occu
     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"
-    return f"Income_bracket Prediction: {prediction_value} \n\nResult: {result}"
+    return f"Result: {result}"
 
     
 # Create the Gradio interface
 salarybracket_ga = gr.Interface(fn=salarybracket, 
                                inputs = [
-                                            gr.Number(13.0, 84.0, label="Age: [13 to 84]"),
-                                            gr.Number(1.0, 28.0, label="workclass: [1 to 28]"),
-                                            gr.Number(10.0, 32.0, label="education: [10 to 32]"),
-                                            gr.Number(0.0, 11.0, label="education_num: [0 to 11]"),
-                                            gr.Number(0.0, 1.0, label="marital_status: [0 or 1]"),
-                                            gr.Number(0.0, 37.0, label="occupation: [0 to 37]"),
-                                            gr.Number(0.0, 37.0, label="relationship: [0 to 37]"),
-                                            gr.Number(0.0, 1.0, label="race: [0 or 1]"),
-                                            gr.Number(0.0, 30.0, label="gender: [0 to 30]"),
-                                            gr.Number(0.0, 1.0, label="capital_gain: [0 or 1]"),
-                                            gr.Number(0.0, 19.0, label="capital_loss: [0.0  19.0]"),
-                                            gr.Number(0.0, 1.0, label="hours_per_week: [0 or 1]"),
-                                            gr.Number(0.0, 1.0, label="native_country: [0 or 1]"),
-                                        ],
+                                            gr.Number(17, 90, label="Age [17 to 90]"),
+                                            gr.Number(0, 8, label="Workclass [0 to 8]"),
+                                            gr.Number(0, 15, label="Education [0 to 15]"),
+                                            gr.Number(1, 16, label="Education Num [1 to 16]"),
+                                            gr.Number(0, 6, label="Marital Status [0 to 6]"),
+                                            gr.Number(0, 14, label="Occupation [0 to 14]"),
+                                            gr.Number(0, 5, label="Relationship [0 to 5]"),
+                                            gr.Number(0, 4, label="Race [0 to 4]"),
+                                            gr.Number(0, 1, label="Gender [0 to 1]"),
+                                            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.Number(0, 40, label="Native Country [0 to 40]"),
+                                        ]
                                 outputs="text", title="Salary Bracket Prediction", 
                                examples = [
                                             [75,0,0,6,6,0,2,1,0,0,0,1,3,0,0],