add extra columns for feedback functionality

app.py

@@ -10,18 +10,19 @@ import uuid
 import logging
 import traceback
 from pathlib import Path
-from typing import List, Dict, Any
 from collections import Counter
+from typing import List, Dict, Any, Optional
+
 
-import streamlit as st
-from langchain_core.messages import HumanMessage, AIMessage
 import pandas as pd
+import streamlit as st
 import plotly.express as px
+from langchain_core.messages import HumanMessage, AIMessage
 
 from multi_agent_chatbot import get_multi_agent_chatbot
 from smart_chatbot import get_chatbot as get_smart_chatbot
-from src.reporting.feedback_schema import create_feedback_from_dict
 from src.reporting.snowflake_connector import save_to_snowflake
+from src.reporting.feedback_schema import create_feedback_from_dict
 from src.config.paths import (
     IS_DEPLOYED,
     PROJECT_DIR,
@@ -98,6 +99,8 @@ st.markdown("""
         color: #1f77b4;
         text-align: center;
         margin-bottom: 1rem;
+        width: 100%;
+        display: block;
     }
     
     .subtitle {
@@ -105,54 +108,8 @@ st.markdown("""
         color: #666;
         text-align: center;
         margin-bottom: 2rem;
-    }
-    
-    .example-questions-header {
-        text-align: center;
-        margin-bottom: 1rem;
-    }
-    
-    .example-questions-description {
-        text-align: center;
-        color: #666;
-        margin-bottom: 2rem;
-    }
-    
-    /* Hide ALL default Streamlit text input help messages about Enter key */
-    /* This is the key one - hides "Press Enter to apply" message inside input field */
-    div[data-testid="InputInstructions"],
-    span[data-testid="InputInstructions"],
-    *[data-testid="InputInstructions"] {
-        display: none !important;
-        visibility: hidden !important;
-        opacity: 0 !important;
-        height: 0 !important;
-        width: 0 !important;
-        overflow: hidden !important;
-        position: absolute !important;
-        left: -9999px !important;
-    }
-    
-    /* Also hide other potential locations */
-    div[data-testid="stTextInput"] + div > small,
-    div[data-testid="stTextInput"] ~ div > small,
-    div[data-testid="stTextInputContainer"] + div > small,
-    div[data-testid="stTextInputContainer"] ~ div > small,
-    div[data-baseweb="input"] + div > small,
-    div[data-baseweb="input"] ~ div > small {
-        display: none !important;
-        visibility: hidden !important;
-        opacity: 0 !important;
-        height: 0 !important;
-        overflow: hidden !important;
-    }
-    
-    /* Custom help text for input */
-    .input-help-text {
-        font-size: 0.85rem;
-        color: #666;
-        margin-top: 0.25rem;
-        text-align: left;
+        width: 100%;
+        display: block;
     }
     
     .session-info {
@@ -304,6 +261,114 @@ def serialize_documents(sources):
     
     return serialized
 
+
+def extract_transcript(messages: List[Any]) -> List[Dict[str, str]]:
+    """Extract transcript from messages - only user and bot messages, no extra metadata"""
+    transcript = []
+    for msg in messages:
+        if isinstance(msg, HumanMessage):
+            transcript.append({
+                "role": "user",
+                "content": str(msg.content) if hasattr(msg, 'content') else str(msg)
+            })
+        elif isinstance(msg, AIMessage):
+            transcript.append({
+                "role": "assistant",
+                "content": str(msg.content) if hasattr(msg, 'content') else str(msg)
+            })
+    return transcript
+
+
+def build_retrievals_structure(rag_retrieval_history: List[Dict[str, Any]], messages: List[Any]) -> List[Dict[str, Any]]:
+    """Build retrievals structure from retrieval history"""
+    retrievals = []
+    
+    for entry in rag_retrieval_history:
+        # Get the user message that triggered this retrieval
+        # The entry has conversation_up_to which includes messages up to that point
+        conversation_up_to = entry.get("conversation_up_to", [])
+        
+        # Find the last user message in conversation_up_to (this is the trigger)
+        user_message_trigger = ""
+        for msg_dict in reversed(conversation_up_to):
+            if msg_dict.get("type") == "HumanMessage":
+                user_message_trigger = msg_dict.get("content", "")
+                break
+        
+        # Fallback: if not found in conversation_up_to, get from actual messages
+        # This handles edge cases where conversation_up_to might be incomplete
+        if not user_message_trigger:
+            # Find which retrieval this is (0-indexed)
+            retrieval_idx = rag_retrieval_history.index(entry)
+            # The user message that triggered this retrieval is at position (retrieval_idx * 2)
+            # because each retrieval is preceded by: user message, bot response, user message, ...
+            # But we need to account for the fact that the first retrieval happens after the first user message
+            user_msgs = [msg for msg in messages if isinstance(msg, HumanMessage)]
+            if retrieval_idx < len(user_msgs):
+                user_message_trigger = str(user_msgs[retrieval_idx].content)
+            elif user_msgs:
+                # Fallback to last user message
+                user_message_trigger = str(user_msgs[-1].content)
+        
+        # Get retrieved documents and truncate content to 100 chars
+        docs_retrieved = entry.get("docs_retrieved", [])
+        retrieved_docs = []
+        for doc in docs_retrieved:
+            doc_copy = doc.copy()
+            # Truncate content to 100 characters (keep all other fields)
+            if "content" in doc_copy:
+                doc_copy["content"] = doc_copy["content"][:100]
+            retrieved_docs.append(doc_copy)
+        
+        retrievals.append({
+            "retrieved_docs": retrieved_docs,
+            "user_message_trigger": user_message_trigger
+        })
+    
+    return retrievals
+
+
+def build_feedback_score_related_retrieval_docs(
+    is_feedback_about_last_retrieval: bool,
+    messages: List[Any],
+    rag_retrieval_history: List[Dict[str, Any]]
+) -> Optional[Dict[str, Any]]:
+    """Build feedback_score_related_retrieval_docs structure"""
+    if not rag_retrieval_history:
+        return None
+    
+    # Get the relevant retrieval entry
+    if is_feedback_about_last_retrieval:
+        relevant_entry = rag_retrieval_history[-1]
+    else:
+        # If feedback is about all retrievals, use the last one as default
+        relevant_entry = rag_retrieval_history[-1]
+    
+    # Get conversation up to that point
+    conversation_up_to = relevant_entry.get("conversation_up_to", [])
+    
+    # Convert to transcript format (role/content)
+    conversation_up_to_point = []
+    for msg_dict in conversation_up_to:
+        if msg_dict.get("type") == "HumanMessage":
+            conversation_up_to_point.append({
+                "role": "user",
+                "content": msg_dict.get("content", "")
+            })
+        elif msg_dict.get("type") == "AIMessage":
+            conversation_up_to_point.append({
+                "role": "assistant",
+                "content": msg_dict.get("content", "")
+            })
+    
+    # Get retrieved docs with full content (not truncated)
+    retrieved_docs = relevant_entry.get("docs_retrieved", [])
+    
+    return {
+        "conversation_up_to_point": conversation_up_to_point,
+        "retrieved_docs": retrieved_docs
+    }
+
 def extract_chunk_statistics(sources: List[Any]) -> Dict[str, Any]:
     """Extract statistics from retrieved chunks."""
     if not sources:
@@ -483,7 +548,7 @@ def display_chunk_statistics_table(stats: Dict[str, Any], title: str = "Retrieva
         return
     
     # Wrap in styled container
-    # st.markdown('<div class="retrieval-distribution-container">', unsafe_allow_html=True)
+    st.markdown('<div class="retrieval-distribution-container">', unsafe_allow_html=True)
     
     st.subheader(f"📊 {title}")
     
@@ -600,7 +665,7 @@ def main():
         st.session_state.reset_conversation = False
         st.rerun()
 
-    # Header - centered
+    # Header - fully center aligned
     st.markdown('<h1 class="main-header">🤖 Intelligent Audit Report Chatbot</h1>', unsafe_allow_html=True)
     st.markdown('<p class="subtitle">Ask questions about audit reports. Use the sidebar filters to narrow down your search!</p>', unsafe_allow_html=True)
     
@@ -627,21 +692,15 @@ def main():
             
             2. **Leave filters empty** to search across all data
             
-            3. **Type your question** in the chat and click "Send"
+            3. **Type your question** in the chat input at the bottom
             
-            4. **Choose sample questions from the bottom of the page**
+            4. **Click "Send"** to submit your question
             
             #### 💡 Tips
             
             - Use specific questions for better results
             - Combine multiple filters for precise searches
-            - Check the "Retrieved Documents" tab to get various insights
-            
-            #### 💬 Feedback Section
-            
-            - Rate your experience (1-5 stars)
-            - Provide optional text feedback
-            - Located at the bottom of the page
+            - Check the "Retrieved Documents" tab to see source material
             
             #### ⚠️ Important
             
@@ -666,13 +725,11 @@ def main():
                 help="Choose specific reports to search. When enabled, all other filters are ignored."
             )
         st.markdown('</div>', unsafe_allow_html=True)
-
-        st.markdown('---')
         
         # Determine if filename filter is active
         filename_mode = len(selected_filenames) > 0
         # Sources filter
-        # st.markdown('<div class="filter-section">', unsafe_allow_html=True)
+        st.markdown('<div class="filter-section">', unsafe_allow_html=True)
         st.markdown('<div class="filter-title">📊 Sources</div>', unsafe_allow_html=True)
         selected_sources = st.multiselect(
             "Select sources:",
@@ -767,67 +824,6 @@ def main():
                 label_visibility="collapsed",
                 value=default_value if default_value else None
             )
-            
-            # Use JavaScript to specifically target and hide "Press Enter to apply" message
-            st.markdown("""
-            <script>
-                (function() {
-                    // Hide InputInstructions element (contains "Press Enter to apply")
-                    function hideInputInstructions() {
-                        // Target the specific Streamlit element
-                        const instructions = document.querySelector('[data-testid="InputInstructions"]');
-                        if (instructions) {
-                            instructions.style.display = 'none';
-                            instructions.style.visibility = 'hidden';
-                            instructions.style.opacity = '0';
-                            instructions.style.height = '0';
-                            instructions.style.width = '0';
-                            instructions.style.overflow = 'hidden';
-                            instructions.style.position = 'absolute';
-                            instructions.style.left = '-9999px';
-                        }
-                        
-                        // Also search for any text containing "Press Enter" or "apply" inside input containers
-                        const allElements = document.querySelectorAll('*');
-                        allElements.forEach(el => {
-                            const text = el.textContent || el.innerText || '';
-                            if ((text.toLowerCase().includes('press enter') || 
-                                 text.toLowerCase().includes('enter to') ||
-                                 text.toLowerCase().includes('to apply')) &&
-                                (el.tagName === 'SPAN' || el.tagName === 'DIV' || el.tagName === 'SMALL')) {
-                                const style = window.getComputedStyle(el);
-                                const fontSize = parseFloat(style.fontSize);
-                                // Hide if it's small text (likely help text)
-                                if (fontSize < 14 || el.hasAttribute('data-testid')) {
-                                    el.style.display = 'none';
-                                    el.style.visibility = 'hidden';
-                                    el.style.height = '0';
-                                    el.style.overflow = 'hidden';
-                                }
-                            }
-                        });
-                    }
-                    
-                    // Run immediately and after delays to catch dynamic elements
-                    hideInputInstructions();
-                    setTimeout(hideInputInstructions, 50);
-                    setTimeout(hideInputInstructions, 100);
-                    setTimeout(hideInputInstructions, 500);
-                    
-                    // Observe for new elements added by Streamlit
-                    const observer = new MutationObserver(function(mutations) {
-                        hideInputInstructions();
-                    });
-                    observer.observe(document.body, { childList: true, subtree: true, attributes: true });
-                })();
-            </script>
-            """, unsafe_allow_html=True)
-            
-            # # Show custom help text below input - this replaces the default "Press Enter" message
-            # st.markdown(
-            #     "<div class='input-help-text'>💡 Press the <strong>Send</strong> button to submit your question</div>",
-            #     unsafe_allow_html=True
-            # )
         
         with col2:
             send_button = st.button("Send", key="send_button", use_container_width=True)
@@ -930,8 +926,7 @@ def main():
                 # Count unique filenames
                 unique_filenames = set()
                 for doc in sources:
-                    metadata = getattr(doc, 'metadata', {})
-                    filename = metadata.get('filename', 'Unknown')
+                    filename = getattr(doc, 'metadata', {}).get('filename', 'Unknown')
                     unique_filenames.add(filename)
                 
                 st.markdown(f"**Found {len(sources)} document chunks from {len(unique_filenames)} unique documents (showing top 20):**")
@@ -986,44 +981,6 @@ def main():
                 st.info("No documents were retrieved for the last query.")
         else:
             st.info("No documents have been retrieved yet. Start a conversation to see retrieved documents here.")
-        
-        # Display retrieval history stats
-        st.markdown("---")
-        if st.session_state.rag_retrieval_history:
-            st.markdown("#### 📊 Retrieval History")
-            st.markdown(f"This conversation has **{len(st.session_state.rag_retrieval_history)}** retrieval entries.")
-            
-            with st.expander(f"View {len(st.session_state.rag_retrieval_history)} retrieval entries", expanded=False):
-                for idx, entry in enumerate(st.session_state.rag_retrieval_history, 1):
-                    with st.expander(f"Entry {idx}: {entry.get('rag_query_expansion', 'N/A')[:50]}...", expanded=False):
-                        st.markdown(f"**Query:** {entry.get('rag_query_expansion', 'N/A')}")
-                        st.markdown(f"**Documents Retrieved:** {len(entry.get('docs_retrieved', []))}")
-                        
-                        # Show conversation up to this point
-                        conversation = entry.get('conversation_up_to', [])
-                        if conversation:
-                            st.markdown("**Conversation Context:**")
-                            for msg in conversation[-3:]:  # Show last 3 messages
-                                role = msg.get('type', 'unknown')
-                                content = msg.get('content', '')[:200] + "..." if len(msg.get('content', '')) > 200 else msg.get('content', '')
-                                if role == 'human':
-                                    st.markdown(f"- **You:** {content}")
-                                elif role == 'ai':
-                                    st.markdown(f"- **Bot:** {content}")
-                        
-                        # Show retrieved documents summary
-                        docs = entry.get('docs_retrieved', [])
-                        if docs:
-                            st.markdown("**Retrieved Documents:**")
-                            for doc_idx, doc in enumerate(docs[:5], 1):  # Show first 5
-                                doc_meta = doc.get('metadata', {})
-                                filename = doc_meta.get('filename', 'Unknown')[:50]
-                                st.markdown(f"{doc_idx}. {filename}")
-                            if len(docs) > 5:
-                                st.markdown(f"... and {len(docs) - 5} more documents")
-        else:
-            st.markdown("---")
-            st.info("📊 Retrieval history will appear here after you start asking questions.")
     
     # Feedback Dashboard Section
     st.markdown("---")
@@ -1085,17 +1042,39 @@ def main():
                     print("=" * 80)
                     st.write("🔍 **Debug: Feedback Data Being Submitted:**")
                     
+                    # Extract transcript from messages
+                    transcript = extract_transcript(st.session_state.messages)
+                    
+                    # Build retrievals structure
+                    retrievals = build_retrievals_structure(
+                        st.session_state.rag_retrieval_history.copy() if st.session_state.rag_retrieval_history else [],
+                        st.session_state.messages
+                    )
+                    
+                    # Build feedback_score_related_retrieval_docs
+                    feedback_score_related_retrieval_docs = build_feedback_score_related_retrieval_docs(
+                        is_feedback_about_last_retrieval,
+                        st.session_state.messages,
+                        st.session_state.rag_retrieval_history.copy() if st.session_state.rag_retrieval_history else []
+                    )
+                    
+                    # Preserve old retrieved_data format for backward compatibility
+                    retrieved_data_old_format = st.session_state.rag_retrieval_history.copy() if st.session_state.rag_retrieval_history else []
+                    
                     # Create feedback data dictionary
                     feedback_dict = {
                         "open_ended_feedback": open_ended_feedback,
                         "score": feedback_score,
                         "is_feedback_about_last_retrieval": is_feedback_about_last_retrieval,
-                        "retrieved_data": st.session_state.rag_retrieval_history.copy() if st.session_state.rag_retrieval_history else [],
                         "conversation_id": st.session_state.conversation_id,
                         "timestamp": time.time(),
                         "message_count": len(st.session_state.messages),
                         "has_retrievals": has_retrievals,
-                        "retrieval_count": len(st.session_state.rag_retrieval_history)
+                        "retrieval_count": len(st.session_state.rag_retrieval_history) if st.session_state.rag_retrieval_history else 0,
+                        "transcript": transcript,
+                        "retrievals": retrievals,
+                        "feedback_score_related_retrieval_docs": feedback_score_related_retrieval_docs,
+                        "retrieved_data": retrieved_data_old_format  # Preserved old column
                     }
                     
                     print(f"📝 FEEDBACK SUBMISSION: Score={feedback_score}, Retrievals={len(st.session_state.rag_retrieval_history) if st.session_state.rag_retrieval_history else 0}")
@@ -1137,19 +1116,18 @@ def main():
                         # Ensure parent directory exists before writing
                         feedback_file.parent.mkdir(parents=True, mode=0o777, exist_ok=True)
                         
-                        # Save to local file
+                        # Save to local file first
                         print(f"💾 FEEDBACK SAVE: Saving to local file: {feedback_file}")
                         with open(feedback_file, 'w') as f:
                             json.dump(feedback_data, f, indent=2, default=str)
                         
                         print(f"✅ FEEDBACK SAVE: Local file saved successfully")
-                        st.success("✅ Thank you for your feedback! It has been saved locally.")
-                        st.balloons()
                         
                         # Save to Snowflake if enabled and credentials available
                         logger.info("🔄 FEEDBACK SAVE: Starting Snowflake save process...")
                         logger.info(f"📊 FEEDBACK SAVE: feedback_obj={'exists' if feedback_obj else 'None'}")
                         
+                        snowflake_success = False
                         try:
                             snowflake_enabled = os.getenv("SNOWFLAKE_ENABLED", "false").lower() == "true"
                             logger.info(f"🔍 SNOWFLAKE CHECK: enabled={snowflake_enabled}")
@@ -1160,36 +1138,39 @@ def main():
                                         logger.info("📤 SNOWFLAKE UI: Attempting to save feedback to Snowflake...")
                                         print("📤 SNOWFLAKE UI: Attempting to save feedback to Snowflake...")
                                         
-                                        if save_to_snowflake(feedback_obj):
+                                        snowflake_success = save_to_snowflake(feedback_obj)
+                                        if snowflake_success:
                                             logger.info("✅ SNOWFLAKE UI: Successfully saved to Snowflake")
                                             print("✅ SNOWFLAKE UI: Successfully saved to Snowflake")
-                                            st.success("✅ Feedback also saved to Snowflake!")
                                         else:
                                             logger.warning("⚠️ SNOWFLAKE UI: Save failed")
                                             print("⚠️ SNOWFLAKE UI: Save failed")
-                                            st.warning("⚠️ Snowflake save failed, but local save succeeded")
                                     except Exception as e:
                                         logger.error(f"❌ SNOWFLAKE UI ERROR: {e}")
                                         print(f"❌ SNOWFLAKE UI ERROR: {e}")
                                         traceback.print_exc()
-                                        st.warning(f"⚠️ Could not save to Snowflake: {e}")
+                                        snowflake_success = False
                                 else:
                                     logger.warning("⚠️ SNOWFLAKE UI: Skipping (feedback object not created)")
                                     print("⚠️ SNOWFLAKE UI: Skipping (feedback object not created)")
-                                    st.warning("⚠️ Skipping Snowflake save (feedback object not created)")
+                                    snowflake_success = False
                             else:
                                 logger.info("💡 SNOWFLAKE UI: Integration disabled")
                                 print("💡 SNOWFLAKE UI: Integration disabled")
-                                st.info("💡 Snowflake integration disabled (set SNOWFLAKE_ENABLED=true to enable)")
-                        except NameError as e:
-                            traceback.print_exc()
-                            logger.error(f"❌ NameError in Snowflake save: {e}")
-                            print(f"❌ NameError in Snowflake save: {e}")
-                            st.warning(f"⚠️ Snowflake save error: {e}")
+                                # If Snowflake is disabled, consider it successful (local save only)
+                                snowflake_success = True
+                        
                         except Exception as e:
                             logger.error(f"❌ Exception in Snowflake save: {type(e).__name__}: {e}")
                             print(f"❌ Exception in Snowflake save: {type(e).__name__}: {e}")
-                            st.warning(f"⚠️ Snowflake save error: {e}")
+                            snowflake_success = False
+                        
+                        # Only show success if Snowflake save succeeded (or if Snowflake is disabled)
+                        if snowflake_success:
+                            st.success("✅ Thank you for your feedback! It has been saved successfully.")
+                            st.balloons()
+                        else:
+                            st.warning("⚠️ Feedback saved locally, but Snowflake save failed. Please check logs.")
                         
                         # Mark feedback as submitted to prevent resubmission
                         st.session_state.feedback_submitted = True
@@ -1225,16 +1206,30 @@ def main():
                     # Scroll to conversation - this is handled by the auto-scroll at bottom
                     pass
     
+    # Display retrieval history stats
+    if st.session_state.rag_retrieval_history:
+        st.markdown("---")
+        st.markdown("#### 📊 Retrieval History")
+        
+        with st.expander(f"View {len(st.session_state.rag_retrieval_history)} retrieval entries", expanded=False):
+            for idx, entry in enumerate(st.session_state.rag_retrieval_history, 1):
+                st.markdown(f"**Retrieval #{idx}**")
+                
+                # Display the actual RAG query
+                rag_query_expansion = entry.get("rag_query_expansion", "No query available")
+                st.code(rag_query_expansion, language="text")
+                
+                # Display summary stats
+                st.json({
+                    "conversation_length": len(entry.get("conversation_up_to", [])),
+                    "documents_retrieved": len(entry.get("docs_retrieved", []))
+                })
+                st.markdown("---")
+    
     # Example Questions Section
     st.markdown("---")
-    st.markdown(
-        "<h3 class='example-questions-header'>💡 Example Questions</h3>",
-        unsafe_allow_html=True
-    )
-    st.markdown(
-        "<p class='example-questions-description'>Click on any question below to use it, or modify the editable examples:</p>",
-        unsafe_allow_html=True
-    )
+    st.markdown("### 💡 Example Questions")
+    st.markdown("Click on any question below to use it, or modify the editable examples:")
     
     # Initialize example question state
     if 'custom_question_1' not in st.session_state:
@@ -1257,53 +1252,56 @@ def main():
     
     st.markdown("---")
     
-    # Questions 2 & 3: Editable examples (collapsible, side by side)
-    with st.expander("#### ✏️ Customizable Questions (Edit and use)", expanded=False):
-        # Place questions side by side
-        col1, col2 = st.columns(2)
-        
-        # Question 2
-        with col1:
-            st.markdown("**Question 2:**")
-            custom_q1 = st.text_area(
-                "Edit question 2:",
-                value=st.session_state.custom_question_1,
-                height=100,
-                key="edit_question_2",
-                help="Modify this question to fit your needs, then click 'Use This Question'",
-                label_visibility="collapsed"
-            )
-            if st.button("📋 Use Question 2", key="use_custom_1", use_container_width=True):
-                if custom_q1.strip():
-                    st.session_state.pending_question = custom_q1.strip()
-                    st.session_state.custom_question_1 = custom_q1.strip()
-                    st.session_state.input_counter = (st.session_state.get('input_counter', 0) + 1) % 1000
-                    st.rerun()
-                else:
-                    st.warning("Please enter a question first!")
-            st.caption("💡 Tip: Add specific details like dates, names, or amounts to get more precise answers")
-            st.info("💡 **Filter to apply:** Select District(s) and Year(s) from sidebar panel")
-        
-        # Question 3
-        with col2:
-            st.markdown("**Question 3:**")
-            custom_q2 = st.text_area(
-                "Edit question 3:",
-                value=st.session_state.custom_question_2,
-                height=100,
-                key="edit_question_3",
-                help="Modify this question to fit your needs, then click 'Use This Question'",
-                label_visibility="collapsed"
-            )
-            if st.button("📋 Use Question 3", key="use_custom_2", use_container_width=True):
-                if custom_q2.strip():
-                    st.session_state.pending_question = custom_q2.strip()
-                    st.session_state.custom_question_2 = custom_q2.strip()
-                    st.session_state.input_counter = (st.session_state.get('input_counter', 0) + 1) % 1000
-                    st.rerun()
-                else:
-                    st.warning("Please enter a question first!")
-            st.caption("💡 Tip: Use specific terms from the documents (e.g., 'PDM', 'SACCOs', 'FY 2022/23')")
+    # Questions 2 & 3: Editable examples
+    st.markdown("#### ✏️ Customizable Questions (Edit and use)")
+    
+    # Question 2
+    # st.markdown("**Question 2:**")
+    custom_q1 = st.text_area(
+        "Edit question 2:",
+        value=st.session_state.custom_question_1,
+        height=80,
+        key="edit_question_2",
+        help="Modify this question to fit your needs, then click 'Use This Question'"
+    )
+    col1, col2 = st.columns([1, 4])
+    with col1:
+        if st.button("📋 Use Question 2", key="use_custom_1", use_container_width=True):
+            if custom_q1.strip():
+                st.session_state.pending_question = custom_q1.strip()
+                st.session_state.custom_question_1 = custom_q1.strip()
+                st.session_state.input_counter = (st.session_state.get('input_counter', 0) + 1) % 1000
+                st.rerun()
+            else:
+                st.warning("Please enter a question first!")
+    with col2:
+        st.caption("💡 Tip: Add specific details like dates, names, or amounts to get more precise answers")
+    
+    st.info("💡 **Filter to apply:** Select District(s) and Year(s) sidebar panel before asking this question.")
+
+    st.markdown("---")
+    
+    # Question 3
+    # st.markdown("**Question 3:**")
+    custom_q2 = st.text_area(
+        "Edit question 3:",
+        value=st.session_state.custom_question_2,
+        height=80,
+        key="edit_question_3",
+        help="Modify this question to fit your needs, then click 'Use This Question'"
+    )
+    col1, col2 = st.columns([1, 4])
+    with col1:
+        if st.button("📋 Use Question 3", key="use_custom_2", use_container_width=True):
+            if custom_q2.strip():
+                st.session_state.pending_question = custom_q2.strip()
+                st.session_state.custom_question_2 = custom_q2.strip()
+                st.session_state.input_counter = (st.session_state.get('input_counter', 0) + 1) % 1000
+                st.rerun()
+            else:
+                st.warning("Please enter a question first!")
+    with col2:
+        st.caption("💡 Tip: Use specific terms from the documents (e.g., 'PDM', 'SACCOs', 'FY 2022/23')")
     
 
     # Store selected question for next render (handled in input section above)
@@ -1316,5 +1314,32 @@ def main():
     </script>
     """, unsafe_allow_html=True)
 
+
 if __name__ == "__main__":
+    # Check if running in Streamlit context
+    try:
+        from streamlit.runtime.scriptrunner import get_script_run_ctx
+        if get_script_run_ctx() is None:
+            # Not in Streamlit runtime - show helpful message
+            print("=" * 80)
+            print("⚠️  WARNING: This is a Streamlit app!")
+            print("=" * 80)
+            print("\nPlease run this app using:")
+            print("  streamlit run app.py")
+            print("\nNot: python app.py")
+            print("\nThe app will not function correctly when run with 'python app.py'")
+            print("=" * 80)
+            import sys
+            sys.exit(1)
+    except ImportError:
+        # Streamlit not installed or not in Streamlit context
+        print("=" * 80)
+        print("⚠️  WARNING: This is a Streamlit app!")
+        print("=" * 80)
+        print("\nPlease run this app using:")
+        print("  streamlit run app.py")
+        print("\nNot: python app.py")
+        print("=" * 80)
+        import sys
+        sys.exit(1)
     main()