Update app.py

app.py

@@ -7,9 +7,9 @@ import streamlit as st
 
 def get_POMFinder():
     # Get file paths
-    load_files = "Backend/" #pkg_resources.resource_listdir(__name__, 'Backend/')
-    DataBase_path = "Backend/POMFinder_443structures_100Dataset_per_Structure_xPDF_hypercube_sampling_Grmax_Name.h5" #pkg_resources.resource_filename(__name__, "Backend/"+load_files[0])
-    POMFinder_path = "Backend/XGBoost_443structures_100PDFperStructure_xPDF_hypercube_sampling_Grmax.model" #pkg_resources.resource_filename(__name__, "Backend/"+load_files[1])
+    load_files = "Backend/"
+    DataBase_path = "Backend/POMFinder_443structures_100Dataset_per_Structure_xPDF_hypercube_sampling_Grmax_Name.h5"
+    POMFinder_path = "Backend/XGBoost_443structures_100PDFperStructure_xPDF_hypercube_sampling_Grmax.model"
     # Import the Database    
     hf_name = h5py.File(DataBase_path, "r")
     y = hf_name.get('y')
@@ -88,7 +88,7 @@ def POMPredicter(POMFinder, Gr, y_onehotenc_cat):
 
 
 st.title('POMFinder')
-st.write('Welcome to POMFinder which is a tree-based supervised learning algorithm that can predict the polyoxometalate cluster from a Pair Distribution Function.
+st.write('Welcome to POMFinder which is a tree-based supervised learning algorithm that can predict the polyoxometalate cluster from a Pair Distribution Function.')
 st.write('Upload a PDF to use POMFinder to predict the structure.')
 
 # Define the file upload widget