Upload app.py

app.py

@@ -1,15 +1,17 @@
-
 import gradio as gr
 from joblib import load
 import pandas as pd
 
+
+
 dv , model = load("train_model.joblib")
 
 
+
 # creating a predict function to be passed into gradio UI
 def predict(age, job, marital, education, default, housing,
             loan, contact, month,day_of_week,campaign,pdays,
-            previous,poutcome,cons_price_idx,cons_conf_idx,emp_var_rate):
+            previous,poutcome,emp_var_rate,cons_price_idx,cons_conf_idx):
   
     customer = {
         'age': age,
@@ -26,9 +28,10 @@ def predict(age, job, marital, education, default, housing,
         'pdays': pdays,
         'previous': previous,
         'poutcome': poutcome,
+        'emp_var_rate': emp_var_rate,
         'cons_price_idx': cons_price_idx,
         'cons_conf_idx': cons_conf_idx,
-        'emp_var_rate': emp_var_rate
+        
     }
     
     print(customer)
@@ -45,37 +48,38 @@ def predict(age, job, marital, education, default, housing,
     
     return str(prediction)
 
-age = gr.inputs.Slider(minimum=1,default = 35, maximum=100, label = 'age') #default=data['age'].mean()
-job = gr.inputs.Dropdown(choices=["housemaid", "services","admin.","blue-collar","technician",
-                                 "retired","management","unemployed","self-employed","unknown",
-                                  "entrepreneur","student"],label = 'job')
-marital = gr.inputs.Dropdown(choices=["married", "single","divorced","unknown"],label = 'marital')
-education = gr.inputs.Dropdown(choices=["basic.4y", "high.school","basic.6y","basic.9y","professional.course",
-                                 "unknown","university.degree","illiterate"],label = 'education')
-default = gr.inputs.Dropdown(choices=["yes", "no","unknown"],label = 'default')
-housing = gr.inputs.Dropdown(choices=["yes", "no","unknown"],label = 'housing')
-loan = gr.inputs.Dropdown(choices=["yes", "no","unknown"],label = 'loan')
-contact = gr.inputs.Dropdown(choices=["telephone", "cellular"],label = 'contact')
-month = gr.inputs.Dropdown(choices=['may', 'jun', 'jul', 'aug', 'oct', 'nov', 'dec',
-                                    'mar', 'apr','sep'],label = 'month')
-day_of_week = gr.inputs.Dropdown(choices=['mon', 'tue', 'wed', 'thu', 'fri'],label = 'day_of_week')
-campaign = gr.inputs.Slider(minimum=1,default = 2, maximum=56, label = 'campaign') 
-pdays = gr.inputs.Slider(minimum=0,default = 0, maximum=27, label = 'pdays') 
-previous = gr.inputs.Slider(minimum=0,default = 0, maximum=7, label = 'previous') 
-poutcome = gr.inputs.Dropdown(choices=["nonexistent", "failure","success"],label = 'poutcome')
-cons_price_idx = gr.inputs.Slider(minimum=92,default = 94, maximum=95, label = 'cons_price_idx')
-cons_conf_idx = gr.inputs.Slider(minimum=-51,default = -42, maximum=-27, label = 'cons_conf_idx')
-emp_var_rate = gr.inputs.Slider(minimum=4964,default = 5191, maximum=5228, label = 'emp_var_rate')
 
 
 
+age = gr.inputs.Slider(minimum=1,default = 35, maximum=100, step=1,label = 'Age') #default=data['age'].mean()
+job = gr.inputs.Dropdown(choices=["Housemaid", "Services","Admin.","Blue-Collar","Technician",
+                                 "Retired","Management","Unemployed","Self-Employed","Unknown",
+                                  "Entrepreneur","Student"],label = 'Job')
+marital = gr.inputs.Dropdown(choices=["Married", "Single","Divorced","Unknown"],label = 'Marital')
+education = gr.inputs.Dropdown(choices=["Basic.4y", "High.School","Basic.6y","Basic.9y","Professional.Course",
+                                 "Unknown","University.Degree","Illiterate"],label = 'Education')
+default = gr.inputs.Radio(["Yes", "No","Unknown"],label = 'Default',type="index")
+housing = gr.inputs.Radio(choices=["Yes", "No","Unknown"],label = 'Housing',type="index")
+loan = gr.inputs.Radio(["Yes", "No","Unknown"],type="index",label = 'Loan')
+contact = gr.inputs.Radio(["Telephone", "Cellular"],type = "index",label = 'Contact')
+month = gr.inputs.Dropdown(choices=['Mar', 'Apr','May', 'Jun', 'Jul', 'Aug','Sep','Oct', 'Nov', 'Dec'],label = 'Month')
+day_of_week = gr.inputs.Dropdown(choices=['Mon', 'Tue', 'Wed', 'Thu', 'Fri'],label = 'Day of Week')
+campaign = gr.inputs.Slider(minimum=1,default = 2, maximum=56, step = 1,label = 'Campaign') 
+pdays = gr.inputs.Slider(minimum=0,default = 0, maximum=27, step = 1,label = 'Last Contact(in days)') 
+previous = gr.inputs.Slider(minimum=0,default = 0, maximum=7, step = 1,label = 'Previous Contacts') 
+poutcome = gr.inputs.Radio(["Nonexistent", "Failure","Success"],label = 'Previous Outcome',type="index")
+emp_var_rate = gr.inputs.Slider(minimum=-3,default = 1, maximum=1,step= 1, label = 'Employment Variation Rate')
+cons_price_idx = gr.inputs.Slider(minimum=92,default = 94, maximum=95,step = 1, label = 'Consumer Price Index ')
+cons_conf_idx = gr.inputs.Slider(minimum=-51,default = -42, maximum=-27, step = 1, label = 'Consumer Confidence Index')
+
+
 
 
 iface = gr.Interface(predict,[age, job, marital, education, default, housing,
             loan, contact, month,day_of_week,campaign,pdays,
-            previous,poutcome,cons_price_idx,cons_conf_idx,emp_var_rate],
+            previous,poutcome,emp_var_rate,cons_price_idx,cons_conf_idx],
              outputs = "number",
-            interpretation="default"
+            interpretation="default",verbose = True
              )
 iface.launch(share=True)