Create app.py

app.py

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+import gradio as gr
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+
+from pycaret.regression import *
+
+# Set display results
+pd.options.display.float_format = '{:,.4f}'.format
+%config InlineBackend.figure_format = 'retina'
+
+def predict_cvr(xyz_campaign_id, gender, age, Impressions, Clicks, 
+                Total_Conversion, interest): #สร้าง function predict_cvr โดยภายใน function คือ ส่วนของ input data
+  path = "/content/drive/MyDrive/KAG_conversion_data.csv" #Import development ไฟล์ที่เป็น .csv
+  df = pd.read_csv(path) #อ่านไฟล์ csv
+  df.drop(["ad_id", "fb_campaign_id", "Spent","Approved_Conversion"],axis=1, inplace = True) #drop columns ทิ้ง
+  df = pd.DataFrame.from_dict({'xyz_campaign_id': [xyz_campaign_id], 'gender': [gender], 'age': [age], 'Impressions': [Impressions], 'Clicks': [Clicks], 
+                               'Total_Conversion': [Total_Conversion], 'interest': [interest]}) #แปลงเป็น dataframe
+  df["xyz_campaign_id"].replace({916:"campaign_a",936:"campaign_b",1178:"campaign_c"}, inplace=True) #แทนที่ด้วยชื่อ campaign
+  pred = cvr_saved.predict(df).tolist()[0] #เมื่่อถูกทำนายแล้ว มันจะส่งกลับคืนค่าเข้าไปใน pred
+  return 'Conversion Rate : '+str(pred) #function predict_cvr จะส่ง output ออกมาเป็น "Conversion Rate : pred"
+  
+xyz_campaign_id = gr.inputs.Dropdown(['campaign_a', 'campaign_b', 'campaign_c'], label="xyz_campaign_id")
+gender = gr.inputs.Dropdown(['M', 'F'], label = "gender")
+age = gr.inputs.Dropdown(['30-34', '35-39', '40-44', '45-49'], label = "age")
+Impressions = gr.inputs.Slider(minimum=100,maximum=1000000,step=100,label =  "Impressions")
+Clicks = gr.inputs.Slider(minimum=1,maximum=500,step=1, label = "Clicks")
+Total_Conversion = gr.inputs.Slider(minimum=1,maximum=100,step= 1, label = "Total_Conversion") 
+interest = gr.inputs.Slider(minimum=1,maximum=114,step= 1, label = "interest")
+
+gr.Interface(predict_cvr, inputs =[xyz_campaign_id, gender, age, Impressions, Clicks, 
+                Total_Conversion, interest],
+             outputs="label",
+             title = "Facebook Ads Conversions Prediction Web App",
+             theme = "dark-peach",
+             capture_session=True).launch(debug=True);