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# import pickle
import gradio as gr
import numpy as np
import xgboost as xgb
model1=xgb.XGBRegressor()
model2=xgb.XGBRegressor()
model1.load_model('model1.json')
model2.load_model('model2.json')
def greed(Unit_of_Measure,Line_Item_Quantity,Line_Item_Value,Weight_kg,Freight_Cost,Line_Item_Insurance):
input_array=np.array([[Unit_of_Measure,Line_Item_Quantity,Line_Item_Value,Weight_kg,Freight_Cost,Line_Item_Insurance]])
pred1=model1.predict(input_array)
pred2=model2.predict(input_array)
pred1=float(np.asarray(pred1))
pred2=float(np.asarray(pred2))
return pred1,pred2
output1=gr.outputs.Textbox(label='Pack price')
output2=gr.outputs.Textbox(label='Unit price')
demo = gr.Interface(
fn=greed,
inputs=[gr.inputs.Number(),gr.inputs.Number(),gr.inputs.Number(),gr.inputs.Number(),gr.inputs.Number(),gr.inputs.Number()],
outputs=[output1,output2],description='SHIPMENT PRICING PREDICTION')
demo.launch(share=True)
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