Spaces:
Sleeping
Sleeping
| import joblib | |
| import gradio as gr | |
| import pandas as pd | |
| from models import HealthInsurance | |
| def load_data(): | |
| global _model | |
| global _column_transformer | |
| global _bins_annual_premium_type | |
| _model = joblib.load(filename = 'parameters/random_forrest.gz') | |
| _column_transformer = joblib.load(filename = 'parameters/column_transformer.joblib') | |
| _bins_annual_premium_type = joblib.load(filename = 'parameters/bins_annual_premium_type.joblib') | |
| def predict(df): | |
| health_insurance = HealthInsurance(_model,_column_transformer, | |
| _bins_annual_premium_type) | |
| df_predicted = health_insurance.predict(df) | |
| return df_predicted[['score','previously_insured', | |
| 'annual_premium','vintage','gender', | |
| 'age','region_code','policy_sales_channel', | |
| 'driving_license','vehicle_age', | |
| 'vehicle_damage']] | |
| def create_input_table(): | |
| return gr.Dataframe(headers = ['previously_insured', | |
| 'annual_premium','vintage','gender', | |
| 'age','region_code','policy_sales_channel', | |
| 'driving_license','vehicle_age', | |
| 'vehicle_damage'], | |
| datatype = ['number','number','number','str','number', | |
| 'number','number','number','str','str'], | |
| row_count= 1, | |
| col_count= (10,'fixed'), | |
| type = 'pandas', | |
| label = 'Input') | |
| def create_output_table(): | |
| return gr.Dataframe(headers = ['score','previously_insured', | |
| 'annual_premium','vintage','gender', | |
| 'age','region_code','policy_sales_channel', | |
| 'driving_license','vehicle_age', | |
| 'vehicle_damage'], | |
| type = 'pandas', | |
| label = 'Output', | |
| wrap = True, | |
| interactive =False) | |
| def create_file_object(): | |
| return gr.File(label = 'File upload', | |
| type = 'bytes') | |
| def convert_file_to_pandas(file): | |
| df = pd.read_excel(io = file) | |
| return df | |
| def build_interface(): | |
| with gr.Blocks() as interface: | |
| file_object = create_file_object() | |
| input_table = create_input_table() | |
| output_table = create_output_table() | |
| greet_btn = gr.Button("Submit") | |
| greet_btn.click(fn=predict, inputs=input_table, outputs=output_table) | |
| file_object.change(fn = convert_file_to_pandas, | |
| inputs = file_object, | |
| outputs = input_table) | |
| interface.launch() | |
| if __name__ == "__main__": | |
| load_data() | |
| build_interface() |