Upload app.py

app.py

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+
+import pickle
+import gradio as gr
+import numpy as np
+
+model=pickle.load(open('model1.pkl','rb'))
+
+a1= gr.Number(label='Unit of Measure (Per Pack)')
+a2= gr.Number(label='Line Item Quantity')
+a3= gr.Number(label='Line Item Value')
+a4= gr.Number(label='Weight (Kilograms)')
+a5= gr.Number(label='Freight Cost (USD)')
+a6= gr.Number(label='Line Item Insurance (USD)')
+
+def predict_pack_price(a1,a2,a3,a4,a5,a6):
+    input_array=np.array([[a1,a2,a3,a4,a5,a6]])
+    pred=model.predict(input_array)
+    print(pred)
+    return pred
+
+# def predict_unit_price(a1,a2,a3,a4,a5,a6):
+#     input_array=np.array([[a1,a2,a3,a4,a5,a6]])
+#     pred=clf2.predict(input_array)
+#     return pred
+
+# outputs1=gr.outputs.Textbox()
+# outputs2=gr.outputs.Textbox()
+demo1 =gr.Interface(fn=predict_pack_price,inputs=['number','number','number','number','number','number'],outputs='number',description='PACK PRICE')
+# demo2 =gr.Interface(fn=predict_unit_price,inputs=[a1,a2,a3,a4,a5,a6],outputs=outputs2,description="UNIT PRICE")
+
+demo1.launch(share=True)