Create tapp.py

appStore/tapp.py

@@ -0,0 +1,49 @@
+# set path
+import glob, os, sys; 
+sys.path.append('../utils')
+
+#import needed libraries
+import seaborn as sns
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+import streamlit as st
+from st_aggrid import AgGrid
+from utils.tapp_classifier import load_tappClassifier, tapp_classification 
+import logging
+logger = logging.getLogger(__name__)
+from utils.config import get_classifier_params
+from io import BytesIO
+import xlsxwriter
+import plotly.express as px
+from pandas.api.types import (
+    is_categorical_dtype,
+    is_datetime64_any_dtype,
+    is_numeric_dtype,
+    is_object_dtype,
+    is_list_like)
+
+# Declare all the necessary variables
+tapp_classifier_identifier = 'tapp'
+param1  = get_classifier_params(tapp_classifier_identifier)
+
+def app():
+    ### Main app code ###
+    with st.container():
+        if 'key0' in st.session_state:
+            df = st.session_state.key0
+
+            #load Classifiers
+            classifier = load_tappClassifier(classifier_name=param1['model_name'])
+            st.session_state['{}_classifier'.format(tapp_classifier_identifier)] = classifier
+            
+            if len(df) > 100:
+                warning_msg = ": This might take sometime, please sit back and relax."
+            else:
+                warning_msg = ""
+                
+            df = tapp_classification(haystack_doc=df,
+                                    threshold= param1['threshold'])
+            st.dataframe(df)
+
+            st.session_state.key1 = df