Update analyzing.py

analyzing.py

@@ -543,23 +543,13 @@ if 'parsed_responses' not in st.session_state:
     st.session_state['parsed_responses'] = None
 
 # Load dataset
-data_path = 'uap_files_embeds.h5'
+data_path = 'parsed_files_distance_embeds.h5'
 
 my_dataset = st.file_uploader("Upload Parsed DataFrame", type=["csv", "xlsx"])
-# if st.session_state['parsed_responses'] is not None:
-#     #use_parsed_data = st.checkbox('Analyze recently parsed dataset')
-#     #if use_parsed_data:
-#     parsed = st.session_state.get('parsed_responses', pd.DataFrame()).copy() # this will overwrite the parsed_responses variable
-#     filtered_data = filter_dataframe(parsed)
-#     st.dataframe(filtered_data)
 if my_dataset is not None:
-#     try:
-#         data = pd.read_csv(my_dataset) if my_dataset.type == "text/csv" else pd.read_excel(my_dataset)
-#         filtered_data = filter_dataframe(data)
-#         st.dataframe(filtered_data)
-#     except Exception as e:
-#         st.error(f"An error occurred while reading the file: {e}")
-# #if 'parsed_responses' not in st.session_state:
+    
+    if parsed: # save space by cleaning default dataset
+        parsed = None
     try:
         if my_dataset.type == "text/csv":
             data = pd.read_csv(my_dataset)
@@ -575,7 +565,7 @@ if my_dataset is not None:
     except Exception as e:
         st.error(f"An error occurred while reading the file: {e}")
 else:
-    parsed = load_data(data_path).drop(columns=['embeddings']).head(10000)
+    parsed = load_data(data_path).drop(columns=['embeddings'])
     parsed_responses = filter_dataframe(parsed)
     st.session_state['parsed_responses'] = parsed_responses
     st.dataframe(parsed_responses)