Upload app.py

app.py

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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')
+
+# pred = model1.predict([[1],[2],[3],[4],[5],[6]])
+# print(pred[0])
+
+
+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]])
+    pred1=model1.predict(input_array)
+    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))
+
+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"],
+)
+demo.launch(share=True)
+
+# print(model)
+
+# gr.outputs.