Update app.py

app.py

@@ -13,10 +13,10 @@ loaded_model = pickle.load(open("heart_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)
     
@@ -29,7 +29,7 @@ def main_func(ValueDiversity,AdequateResources,Voice,GrowthAdvancement,Workload,
     local_plot = plt.gcf()
     plt.close()
     
-    return {"Leave": float(prob[0][0]), "Stay": 1-float(prob[0][0])}, local_plot
+    return {"Low Change": float(prob[0][0]), "High Chance": 1-float(prob[0][0])}, local_plot
 
 # Create the UI
 title = "**Heart Attack Predictor & Interpreter** 🪐"
@@ -48,12 +48,20 @@ 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=4, step=1)
+    sex = gr.Slider(label="sex Score", minimum=1, maximum=5, value=4, step=1)
+    cp = gr.Slider(label="cp Score", minimum=1, maximum=5, value=4, step=1)
+    trtbps = gr.Slider(label="GrowthAdvancement 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)
+    thalacch = gr.Slider(label="thalacch 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:
@@ -62,11 +70,11 @@ 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([[24,0,4,4,4,4,5,5,1,2,3], [24,0,4,4,3,2,5,5,1,2,3]], [age,sex,cp,trtbps,chol,fbs,restecg,thalachh,exng,oldpeak,slp,caa,thall], [label,local_plot], main_func, cache_examples=True)
 
 demo.launch()