when generating predictions disable the sidebar

ProtHGT_app.py

@@ -38,6 +38,8 @@ if 'submitted' not in st.session_state:
     st.session_state.submitted = False
 if 'previous_inputs' not in st.session_state:
     st.session_state.previous_inputs = None
+if 'generating_predictions' not in st.session_state:
+    st.session_state.generating_predictions = False
 
 with st.expander("🚀 Upcoming Features"):
     st.info("""
@@ -51,6 +53,9 @@ with st.expander("🚀 Upcoming Features"):
     """)
 
 with st.sidebar:
+
+    disabled = st.session_state.generating_predictions
+
     st.markdown("""
         <style>
         .title {
@@ -90,7 +95,8 @@ with st.sidebar:
     # Add protein selection methods
     selection_method = st.radio(
         "Choose input method:",
-        ["Use example query", "Search proteins", "Upload protein ID file"]
+        ["Use example query", "Search proteins", "Upload protein ID file"],
+        disabled=disabled
     )
 
     if selection_method == "Use example query":
@@ -98,7 +104,11 @@ with st.sidebar:
 
     elif selection_method == "Search proteins":
         # User enters search term
-        search_query = st.text_input("Start typing a protein ID (at least 3 characters)", "")
+        search_query = st.text_input(
+            "Start typing a protein ID (at least 3 characters)", 
+            "", 
+            disabled=disabled
+        )
 
         # Apply fuzzy search only if query length is >= 3
         filtered_proteins = []
@@ -107,27 +117,24 @@ with st.sidebar:
             matches = process.extract(
                 search_query.upper(), 
                 {p: p.upper() for p in available_proteins}, 
-                limit=50,
-                score_cutoff=50  # Optional: only include matches above 50% similarity
+                limit=50
             )
             filtered_proteins = [match[0] for match in matches]  # Show top 50 matches
 
-        # Multi-select for filtered results
         selected_proteins = st.multiselect(
             "Select proteins from search results",
             options=filtered_proteins,
             placeholder="Start typing to search...",
-            max_selections=100
+            max_selections=100,
+            disabled=disabled
         )
 
-        if selected_proteins:
-            st.write(f"Selected {len(selected_proteins)} proteins")
-
-    else:
+    else:  # Upload file option
         uploaded_file = st.file_uploader(
             "Upload a text file with UniProt IDs (one per line, max 100)*",
-            type=['txt']
-        )        
+            type=['txt'],
+            disabled=disabled
+        )
 
         if uploaded_file:
             protein_list = [line.strip() for line in uploaded_file.read().decode('utf-8').splitlines()]
@@ -174,6 +181,7 @@ with st.sidebar:
                     Currently, our system can only generate predictions for proteins that are already included in our knowledge graph. **Real-time retrieval of relationship data from external source databases is not yet supported.**  
                     We are actively working on integrating this capability in future updates. Stay tuned!
                     """)
+
     if selected_proteins:
         with st.expander("View Selected Proteins"):
             st.write(f"Total proteins selected: {len(selected_proteins)}")
@@ -216,7 +224,8 @@ with st.sidebar:
         selected_go_category = st.selectbox(
             "Select GO Category for predictions",
             options=list(go_category_options.keys()),
-            help="Choose which GO category to generate predictions for. Selecting 'All Categories' will generate predictions for all three categories."
+            help="Choose which GO category to generate predictions for. Selecting 'All Categories' will generate predictions for all three categories.",
+            disabled=disabled
         )
 
     st.warning("⚠️ Due to memory and computational constraints, the maximum number of proteins that can be processed at once is limited to 100 proteins. For larger datasets, please consider running the model locally using our GitHub repository.")
@@ -237,6 +246,7 @@ with st.sidebar:
             st.session_state.submitted = True
 
 if st.session_state.submitted:
+    st.session_state.generating_predictions = True
     with st.spinner("Generating predictions..."):
         # Generate predictions only if not already in session state
         if st.session_state.predictions_df is None:
@@ -286,12 +296,12 @@ if st.session_state.submitted:
 
             st.session_state.predictions_df = predictions_df
         
+        st.session_state.generating_predictions = False
         # Display and filter predictions
         st.success("Predictions generated successfully!")
         st.markdown("### Filter and View Predictions")
         
         # Create filters
-        st.markdown("### Filter Predictions")
         col1, col2, col3, col4 = st.columns(4)  # Changed to 4 columns
         
         with col1: