Update app.py

app.py

@@ -119,7 +119,7 @@ if tabs =='Chat':
     st.write("Get visualizations and analysis from our Gemini powered agent")
         
         # Read the CSV file
-    df = pd.read_csv(uploaded_file)
+    #df = pd.read_csv(uploaded_file)
 
         # Display the data
     with st.expander("Preview"):
@@ -145,20 +145,21 @@ elif tabs == 'Reports':
     st.write("Filtering Options")
     branch_names = df['Branch_Name'].unique().tolist()
     product_names = df['Description'].unique().tolist()
-    selected_branch = st.selectbox('Select Branch Name', ['All'] + branch_names)
-    selected_product = st.selectbox('Select Product', ['All'] + product_names)
+    selected_branches = st.multiselect('Select Branch(es) Name', branch_names, default=branch_names)
+    selected_products = st.multiselect('Select product(s) Name', product_names, default=product_names)
 
 # Button to apply filters
     if st.button('Apply Filters and Generate report'):
+        df = pd.read_csv(uploaded_file)
         filtered_df = df.copy()
     
     # Apply Branch Name Filter
-    if selected_branch != 'All':
-        filtered_df = filtered_df[filtered_df['Branch_Name'] == selected_branch]
+    if selected_branches:
+        filtered_df = filtered_df[filtered_df['Branch_Name'].isin(selected_branches)]
     
     # Apply Description Filter
-    if selected_product != 'All':
-        filtered_df = filtered_df[filtered_df['Description'] == selected_product]
+    if selected_products:
+        filtered_df = filtered_df[filtered_df['Product_Name'].isin(selected_products)]
     
     # Display filtered DataFrame
         st.write("Filtered DataFrame")