app

app.py

@@ -25,14 +25,22 @@ def update(array_value):
     validation_target_data = validation_data[['Attrition']]
     reg = LinearRegression().fit(validation_input_data, validation_target_data)
     # In future pass data through array_value parameter
-    prediction_value = reg.predict(np.array([[2,2,1,3,1,2,0,1,40,1]]))
-    return f"Prediction : {prediction_value}!"
+    if array_value == "2,2,1,3,1,2,0,1,40,1":
+        prediction_value = reg.predict(np.array([[2,2,1,3,1,2,0,1,40,1]]))
+        return f"Prediction : {prediction_value}!"
+    if array_value == "0,0,0,3,0,2,0,1,2,1":
+        prediction_value = reg.predict(np.array([[2,2,1,3,1,2,0,1,40,1]]))
+        return f"Prediction : {prediction_value}!"
+
+inputs = [
+        gr.Dropdown(["2,2,1,3,1,2,0,1,40,1", "0,0,0,3,0,2,0,1,2,1"], label="Prediction Scenario:")
+    ]
 
 with gr.Blocks() as demo:
     gr.Markdown("*** Employee Experience Prediction ***")
     gr.Markdown("[EmployeeExperience, HealthBenefitsSatisfaction, SalarySatisfaction, Designation, HealthConscious, EmployeeFeedbackSentiments, Education, Gender, HoursOfTrainingAttendedLastYear, InternalJobMovement, Attrition]")
     with gr.Row():
-        inp = gr.Textbox(placeholder="Enter Employee Experience Data")
+        inp = inputs
         out = gr.Textbox()
     btn = gr.Button("Run")
     btn.click(fn=update, inputs=inp, outputs=out)