Update app.py

app.py

@@ -49,48 +49,58 @@ id2label = {
 # Source: https://blog.jcharistech.com/2021/01/21/how-to-save-uploaded-files-to-directory-in-streamlit-apps/
 
 # Store uploaded file temporarily in directory to get file path (necessary for processing)
-def save_uploadedfile(upl_file):
-     with open(os.path.join("tempDir",upl_file.name),"wb") as f:
-         f.write(upl_file.getbuffer())
-     return st.success("Saved File:{} to tempDir".format(upl_file.name))
+# def save_uploadedfile(upl_file):
+#      with open(os.path.join("tempDir",upl_file.name),"wb") as f:
+#          f.write(upl_file.getbuffer())
+#      return st.success("Saved File:{} to tempDir".format(upl_file.name))
+
+# if uploaded_file is not None: 
+#     # Save the file 
+#     file_details = {"FileName": uploaded_file.name, "FileType": uploaded_file.type}
+#     save_uploadedfile(uploaded_file)
+
+#     #Get the file path
+
+file = st.file_uploader("File upload", type=["pdf"])
 
 if uploaded_file is not None: 
-    # Save the file 
-    file_details = {"FileName": uploaded_file.name, "FileType": uploaded_file.type}
-    save_uploadedfile(uploaded_file)
 
-    #Get the file path
-    
+    # Retrieve the file name 
+    with tempfile.NamedTemporaryFile(mode="wb") as temp:
+        bytes_data = files.getvalue()
+        temp.write(bytes_data)
+        print(temp.name)
 
-par_list = get_paragraphs(uploaded_file)
+#     # Process file
+#     par_list = get_paragraphs(uploaded_file)
 
-### Make predictions 
-preds = vg_model(par_list)
+# ### Make predictions 
+# preds = vg_model(par_list)
 
-# Get label names 
-preds_list = preds.tolist()
+# # Get label names 
+# preds_list = preds.tolist()
 
-predictions_names=[]
+# predictions_names=[]
 
-# loop through each prediction
-for ele in preds_list:
-  try:
-    index_of_one = ele.index(1)
-  except ValueError:
-    index_of_one = "NA" 
-  if index_of_one != "NA": 
-    name  = id2label[index_of_one]
-  else: 
-    name = "NA"
-    predictions_names.append(name)
+# # loop through each prediction
+# for ele in preds_list:
+#   try:
+#     index_of_one = ele.index(1)
+#   except ValueError:
+#     index_of_one = "NA" 
+#   if index_of_one != "NA": 
+#     name  = id2label[index_of_one]
+#   else: 
+#     name = "NA"
+#     predictions_names.append(name)
 
-# Combine the paragraphs and labels to a dataframe 
-df_predictions = pd.DataFrame({'Paragraph': par_list, 'Prediction': predictions_names})
+# # Combine the paragraphs and labels to a dataframe 
+# df_predictions = pd.DataFrame({'Paragraph': par_list, 'Prediction': predictions_names})
 
-# Drop all "Other" and "NA" predictions
-filtered_df = df[df['Prediction'].isin(['Other', 'NA'])]
+# # Drop all "Other" and "NA" predictions
+# filtered_df = df[df['Prediction'].isin(['Other', 'NA'])]
 
 
-#####################################
-st.write(df)  
+# #####################################
+# st.write(df)