Update app.py

app.py

@@ -3,15 +3,15 @@ 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')
 
-# pred = model1.predict([[1],[2],[3],[4],[5],[6]])
-# print(pred[0])
-
+title = "SHIPMENT PRICING PREDICTION(PREDICT PACK PRICE AND UNIT PRICE"
 
 def greed(Measure,Line_Item_Quantity,Line_Item_Value,Weight,Freight_Cost,Line_Item_Insurance):
     input_array=np.array([[Measure,Line_Item_Quantity,Line_Item_Value,Weight,Freight_Cost,Line_Item_Insurance]])
@@ -19,16 +19,13 @@ def greed(Measure,Line_Item_Quantity,Line_Item_Value,Weight,Freight_Cost,Line_It
     pred2=model2.predict(input_array)
     return pred1,pred2
 
-# print(greed(1,2,3,4,5,6))
-# model=gr.outputs(greed(1,2,3,4,5,6))
+
+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=["number","number"],
+    outputs=[output1,output2],
 )
 demo.launch(share=True)
-
-# print(model)
-
-# gr.outputs.