Update app.py

app.py

@@ -1,7 +1,40 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+loaded_model="xgboost-model.pkl"
+def predict_death_event(age,	anaemia,	creatinine_phosphokinase	,diabetes	,ejection_fraction,	high_blood_pressure	,platelets	,serum_creatinine,	serum_sodium,	sex	,smoking	,time):
+   input=[[age,	anaemia,	creatinine_phosphokinase	,diabetes	,ejection_fraction,	high_blood_pressure	,platelets	,serum_creatinine,	serum_sodium,	sex	,smoking	,time]]
+   result=loaded_model.predict(input)
+   
+   if result[0]==1:
+      return 'Positive'
+   else:
+      return 'Negative'
+   return result
+
+
+
+title = "Patient Survival Prediction"
+description = "Predict survival of patient with heart failure, given their clinical record"
+
+out_response = gr.components.Textbox(type="text", label='Death_event')
+
+iface = gr.Interface(fn=predict_death_event,      
+        inputs=[
+        gr.Slider(18, 100, value=20, label="Age"),
+        gr.Slider(0, 1, value=1, label="anaemia"),
+        gr.Slider(100, 2000, value=20,  label="creatinine_phosphokinase"),
+        gr.Slider(0, 1, value=1, label="diabetes"),
+        gr.Slider(18, 100, value=20, label="ejection_fraction"),
+        gr.Slider(0, 1, value=1, label="high_blood_pressure"),
+        gr.Slider(18, 400000, value=20, label="platelets"),
+        gr.Slider(1, 10, value=20, label="serum_creatinine"),
+        gr.Slider(100, 200, value=20, label="serum_sodium"),
+        gr.Slider(0, 1, value=1, label="sex"),
+        gr.Slider(0, 1, value=1, label="smoking"),
+        gr.Slider(1, 10, value=20, label="time"),
+        ],
+    outputs = [out_response])
+iface.launch()
+
+
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()