| import gradio as gr | |
| import pickle | |
| import sklearn | |
| import pandas as pd | |
| regions = ['southwest', 'southeast', 'northwest', 'northeast'] | |
| def predict(age,sex,bmi,children,smoker,region): | |
| loaded_model = pickle.load(open("insurance_predict.pkl", 'rb')) | |
| p = loaded_model.predict(pd.DataFrame(data={'age':[int(age)],'sex':[sex],'bmi':[int(bmi)],'children':[int(children)],'smoker':[smoker],'region':[region]})) | |
| sp = str(p).split(".") | |
| p = sp[0][1:]+'.'+sp[1][:2] | |
| return gr.Textbox.update("{0}$💵".format(p)) | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| gr.Markdown("# 📄 Premium insurance price prediction\nPredict how much a client should be charged for getting medical insurance at your company 🏢") | |
| with gr.Box(): | |
| with gr.Row(): | |
| sex = gr.Dropdown(['male','female'],label='Sex',value='male',interactive=True) | |
| smoker = gr.Dropdown(['no','yes'],label='Is smoker?',value='no',interactive=True) | |
| age = gr.Slider(minimum=18,maximum=100,value=18,label='age',interactive=True,step=1) | |
| children = gr.Slider(minimum=0,maximum=10,value=0,label='No. of children',interactive=True,step=1) | |
| with gr.Row(): | |
| bmi = gr.Slider(minimum=15,maximum=100,value=18,label='BMI',interactive=True,step=1) | |
| region = gr.Dropdown(regions,label='From which region?',value='southwest',interactive=True) | |
| with gr.Row(): | |
| temp = gr.Textbox("...",label='Price prediction 📈',interactive=False) | |
| btn = gr.Button(value="Predict") | |
| btn.click(predict, inputs=[age,sex,bmi,children,smoker,region], outputs=temp) | |
| demo.launch() |