upgraded code with newer version of gradio

app.py

@@ -1,74 +1,53 @@
 import gradio as gr
 import pickle
-from sklearn import preprocessing
 import pandas as pd
 
+# Load the trained model
 filename = 'knn_model.sav'
-
 loaded_model = pickle.load(open(filename, 'rb'))
 
-
-
+# Helper functions for input transformations
 def hptension(hp):
-  if hp == 'yes':
-      return 1
-  else:
-      return 0
+    return 1 if hp == 'yes' else 0
 
 def ht_dis(ht):
-  if ht == 'yes':
-      return 1
-  else:
-      return 0
-    
+    return 1 if ht == 'yes' else 0
 
 def gender_select(gen):
-  if gen == 'male':
-      return 1
-  else:
-      return 0
-    
+    return 1 if gen == 'male' else 0
+
 def age_group_selector(age_grp):
-  if age_grp == '0-16': return 0
-  elif age_grp =='17-32': return 1
-  elif age_grp =='33-48': return 2
-  elif age_grp =='49-64': return 3
-  else: return 4
-  
+    age_map = {'0-16': 0, '17-32': 1, '33-48': 2, '49-64': 3, '64+': 4}
+    return age_map.get(age_grp, 0)
 
 def smoker_cat(smoke):
-  if smoke == 'formerly smoked': return 0
-  elif smoke =='never smoked': return 1
-  elif smoke =='smokes': return 2
-  else: return 3
-
-
-def predict_insurance(input_gender,input_age_group,input_hypertension,input_heart_disease,input_avg_glucose_level,input_bmi,input_smoking_status):
-    
-    input_gender,input_age_group,input_hypertension,input_heart_disease,input_avg_glucose_level,input_bmi,input_smoking_status = input_gender,input_age_group,input_hypertension,input_heart_disease,input_avg_glucose_level,input_bmi,input_smoking_status
-
-    series = {'gender': [gender_select(input_gender)],
-            'age_band': [age_group_selector(input_age_group)],
-          'hypertension': [hptension(input_hypertension)],
-          'heart_disease': [ht_dis(input_heart_disease)],
-          'avg_glucose_level': [input_avg_glucose_level /272],
-          'bmi': [input_bmi/49],
-          'smoking_status': [smoker_cat(input_smoking_status)],
-           }
+    smoke_map = {'formerly smoked': 0, 'never smoked': 1, 'smokes': 2, 'Prefer not to say': 3}
+    return smoke_map.get(smoke, 3)
+
+# Prediction function
+def predict_insurance(input_gender, input_age_group, input_hypertension, input_heart_disease, input_avg_glucose_level, input_bmi, input_smoking_status):
+    # Prepare the input data
+    series = {
+        'gender': [gender_select(input_gender)],
+        'age_band': [age_group_selector(input_age_group)],
+        'hypertension': [hptension(input_hypertension)],
+        'heart_disease': [ht_dis(input_heart_disease)],
+        'avg_glucose_level': [input_avg_glucose_level / 272],
+        'bmi': [input_bmi / 49],
+        'smoking_status': [smoker_cat(input_smoking_status)],
+    }
 
     vector = pd.DataFrame(series)
 
+    # Perform prediction
     result = loaded_model.predict(vector)
-    if result[0] == 1:
-      return "Risk of having stroke is high"
-    else:
-      return "Risk of having stroke is low"
+    return "Risk of having stroke is high" if result[0] == 1 else "Risk of having stroke is low"
 
+# CSS to hide footer and markdown elements
 css = """
 footer {display:none !important}
 .output-markdown{display:none !important}
 footer {visibility: hidden} 
-
 .gr-button-lg {
     z-index: 14;
     width: 113px;
@@ -107,25 +86,41 @@ footer {visibility: hidden}
     transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;
     box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important;
 }
-
 """
 
-with gr.Blocks(title="Brain Stroke Prediction | Data Science Dojo", css = css) as demo:
+# Gradio app layout
+with gr.Blocks(title="Brain Stroke Prediction | Data Science Dojo", css=css) as demo:
     with gr.Row():
-        input_gender = gr.Radio(["male", "female"],label="Gender")
-        input_hypertension = gr.Radio(["yes", "no"],label="Hypertension")
-        input_heart_disease = gr.Radio(["yes", "no"],label="Heart disease")
+        input_gender = gr.Radio(["male", "female"], label="Gender")
+        input_hypertension = gr.Radio(["yes", "no"], label="Hypertension")
+        input_heart_disease = gr.Radio(["yes", "no"], label="Heart Disease")
+    
     with gr.Row():
-        input_age_group = gr.Dropdown(['0-16','17-32','33-48','49-64','64+'],label='Age Group')
-        input_smoking_status = gr.Dropdown(['formerly smoked', 'never smoked', 'smokes', 'Prefer not to say'],label='Smoker')
+        input_age_group = gr.Dropdown(['0-16', '17-32', '33-48', '49-64', '64+'], label='Age Group')
+        input_smoking_status = gr.Dropdown(['formerly smoked', 'never smoked', 'smokes', 'Prefer not to say'], label='Smoker')
+
     with gr.Row():
-        input_avg_glucose_level =  gr.Slider(0, 270,label='Average Glucose Level')
+        input_avg_glucose_level = gr.Slider(0, 270, label='Average Glucose Level')
+
     with gr.Row():
-        input_bmi =  gr.Slider(0, 45,label='BMI Range')
+        input_bmi = gr.Slider(0, 45, label='BMI Range')
+
     with gr.Row():
-        stroke = gr.Textbox(label='Chances of stroke')
-    btn_ins = gr.Button(value="Submit")
-    btn_ins.click(fn=predict_insurance, inputs=[input_gender,input_age_group,input_hypertension,input_heart_disease,
-                                                input_avg_glucose_level,input_bmi,input_smoking_status], outputs=[stroke])
+        stroke = gr.Textbox(label='Chances of Stroke', interactive=False)
 
-demo.launch()
+    btn_ins = gr.Button(value="Submit")
+    btn_ins.click(
+        fn=predict_insurance,
+        inputs=[
+            input_gender,
+            input_age_group,
+            input_hypertension,
+            input_heart_disease,
+            input_avg_glucose_level,
+            input_bmi,
+            input_smoking_status,
+        ],
+        outputs=[stroke]
+    )
+
+demo.launch(debug=True)