updated app.py and added models

app.py

@@ -507,10 +507,12 @@ def get_predictions(selected_variable, selected_industry, selected_campaign,
 
         
     # load model from S3
-    with tempfile.TemporaryFile() as fp:
-        s3_client.download_fileobj(Fileobj=fp, Bucket=bucket_name, Key=key)
-        fp.seek(0)
-        regr = joblib.load(fp)
+    # with tempfile.TemporaryFile() as fp:
+    #     s3_client.download_fileobj(Fileobj=fp, Bucket=bucket_name, Key=key)
+    #     fp.seek(0)
+    #     regr = joblib.load(fp)
+    model_file='/models/'+key
+    regr=joblib.load(model_file)
     
     email_body_dict = {}
     for _, r in training_dataset.iterrows():

models/modelCTA_ConversionRate.sav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a2055c6474bb535a4c983320e98dbed7260d220590b138abc01cb94f4f44e48
+size 1338343

models/modelCTA_MLP_CTOR.sav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e77c726a399f29c045939df3c6c43e7e42ebd939b99c33d568018d668aef8cfc
+size 166693

models/modelCTA_MLP_ConversionRate.sav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a82dce17fa71a767cf9eb05b1ced6d1c0fd0c8ffbd863bd39779b4418ac5725c
+size 166671