Update app.py

app.py

@@ -13,10 +13,10 @@ loaded_model = pickle.load(open("h22_xgb.pkl", 'rb'))
 explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
 
 # Create the main function for server
-def main_func(ValueDiversity,AdequateResources,Voice,GrowthAdvancement,Workload,WorkLifeBalance):
-    new_row = pd.DataFrame.from_dict({'ValueDiversity':ValueDiversity,'AdequateResources':AdequateResources,
-              'Voice':Voice,'GrowthAdvancement':GrowthAdvancement,'Workload':Workload,
-              'WorkLifeBalance':WorkLifeBalance}, orient = 'index').transpose()
+def main_func(age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, oldpeak, slp, caa, thall):
+    new_row = pd.DataFrame.from_dict({'age':age,'sex':sex,
+              'cp':cp,'trtbps':trtbps,'chol':chol,
+              'fbs':fbs, 'restecg':restecg, 'thalachh':thalachh, 'exng':exng, 'oldpeak':oldpeak, 'slp':slp, 'caa':caa, 'thall':thall}, orient = 'index').transpose()
     
     prob = loaded_model.predict_proba(new_row)
     
@@ -46,12 +46,18 @@ with gr.Blocks(title=title) as demo:
     gr.Markdown("""---""")
     gr.Markdown(description2)
     gr.Markdown("""---""")
-    ValueDiversity = gr.Slider(label="ValueDiversity Score", minimum=1, maximum=5, value=4, step=1)
-    AdequateResources = gr.Slider(label="AdequateResources Score", minimum=1, maximum=5, value=4, step=1)
-    Voice = gr.Slider(label="Voice Score", minimum=1, maximum=5, value=4, step=1)
-    GrowthAdvancement = gr.Slider(label="GrowthAdvancement Score", minimum=1, maximum=5, value=4, step=1)
-    Workload = gr.Slider(label="Workload Score", minimum=1, maximum=5, value=4, step=1)
-    WorkLifeBalance = gr.Slider(label="WorkLifeBalance Score", minimum=1, maximum=5, value=4, step=1)
+    age = gr.Slider(label="age Score", minimum=15, maximum=90, value=40, step=5)
+    sex = gr.Slider(label="sex Score", minimum=0, maximum=1, value=1, step=1)
+    cp = gr.Slider(label="cp Score", minimum=1, maximum=5, value=4, step=1)
+    chol = gr.Slider(label="chol Score", minimum=1, maximum=5, value=4, step=1)
+    fbs = gr.Slider(label="fbs Score", minimum=1, maximum=5, value=4, step=1)
+    restecg = gr.Slider(label="restecg Score", minimum=1, maximum=5, value=4, step=1)
+    thalachh = gr.Slider(label="thalachh Score", minimum=1, maximum=5, value=4, step=1)
+    exng = gr.Slider(label="exng Score", minimum=1, maximum=5, value=4, step=1)
+    oldpeak = gr.Slider(label="oldpeak Score", minimum=1, maximum=5, value=4, step=1)
+    slp = gr.Slider(label="slp Score", minimum=1, maximum=5, value=4, step=1)
+    caa = gr.Slider(label="caa Score", minimum=1, maximum=5, value=4, step=1)
+    thall = gr.Slider(label="thall Score", minimum=1, maximum=5, value=4, step=1)
     submit_btn = gr.Button("Analyze")
 
     with gr.Column(visible=True) as output_col:
@@ -60,11 +66,11 @@ with gr.Blocks(title=title) as demo:
 
     submit_btn.click(
         main_func,
-        [ValueDiversity,AdequateResources,Voice,GrowthAdvancement,Workload,WorkLifeBalance],
-        [label,local_plot], api_name="Employee_Turnover"
+        [age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, oldpeak, slp, caa, thall],
+        [label,local_plot], api_name="Heart_Predictor"
     )
     
     gr.Markdown("### Click on any of the examples below to see how it works:")
-    gr.Examples([[4,4,4,4,5,5], [5,4,5,4,4,4]], [ValueDiversity,AdequateResources,Voice,GrowthAdvancement,Workload,WorkLifeBalance], [label,local_plot], main_func, cache_examples=True)
+    gr.Examples([[24,0,3,5,6,8,4,4,4,4,5,5,6], [5,2,3,4,2,3,3,4,2,4,5,4,4,4]], [age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, oldpeak, slp, caa, thall], [label,local_plot], main_func, cache_examples=True)
 
 demo.launch()