Update app.py

app.py

@@ -1136,41 +1136,59 @@ elif page == "Therapists":
 elif page == "Insights":
     st.subheader("Insights")
 
-    session_titles = [session["title"] for session in st.session_state['sessions']]
-    selected_session_title = st.selectbox("Select a session", session_titles)
-
-    if selected_session_title:
-        selected_session = next(session for session in st.session_state['sessions'] if session["title"] == selected_session_title)
-        print(f"Selected session for insights: {selected_session}")  # Debug statement
-
-        if selected_session and 'messages' in selected_session:
-            st.write(f"Messages: {selected_session['messages']}")
-            conversation_summary, mood_df = generate_insights(selected_session)
-
-            st.markdown("### Conversation Summary")
-            st.write(conversation_summary)
-
-            if not mood_df.empty:
-                st.markdown("### Mood Analysis")
-                fig, ax = plt.subplots()   
-                ax.pie(mood_df['Count'], labels=mood_df['Mood'], autopct='%1.1f%%', startangle=90, colors=['#4CAF50', '#FFC107', '#F44336'])
-                ax.axis('equal')
-                st.pyplot(fig)
-
-                st.markdown("### Mood Over Time")
-                mood_timeline = pd.Series([msg.content.lower() for msg in selected_session['messages'] if isinstance(msg, HumanMessage)]).apply(
-                    lambda x: 1 if any(word in x for word in ['happy', 'good', 'great', 'awesome']) else (
-                        0 if any(word in x for word in ['okay', 'fine', 'alright', 'normal']) else -1
+    # Check if sessions exist in the state
+    if 'sessions' in st.session_state and st.session_state['sessions']:
+        # Extract session titles
+        session_titles = [session["title"] for session in st.session_state['sessions']]
+        selected_session_title = st.selectbox("Select a session", session_titles)
+
+        if selected_session_title:
+            # Find the selected session by title
+            selected_session = next(
+                (session for session in st.session_state['sessions'] if session["title"] == selected_session_title), None
+            )
+
+            if selected_session and 'messages' in selected_session:
+                # Display the messages
+                st.write(f"Messages: {selected_session['messages']}")
+                
+                # Call your generate_insights function (ensure this function returns the required values)
+                conversation_summary, mood_df = generate_insights(selected_session)
+
+                st.markdown("### Conversation Summary")
+                st.write(conversation_summary)
+
+                if not mood_df.empty:
+                    st.markdown("### Mood Analysis")
+                    fig, ax = plt.subplots()   
+                    ax.pie(mood_df['Count'], labels=mood_df['Mood'], autopct='%1.1f%%', startangle=90, colors=['#4CAF50', '#FFC107', '#F44336'])
+                    ax.axis('equal')
+                    st.pyplot(fig)
+
+                    # Mood over time plot
+                    st.markdown("### Mood Over Time")
+                    mood_timeline = pd.Series(
+                        [msg.content.lower() for msg in selected_session['messages'] if isinstance(msg, HumanMessage)]
+                    ).apply(
+                        lambda x: 1 if any(word in x for word in ['happy', 'good', 'great', 'awesome']) else (
+                            0 if any(word in x for word in ['okay', 'fine', 'alright', 'normal']) else -1
+                        )
                     )
-                )
-                mood_timeline.index = pd.to_datetime(mood_timeline.index, unit='s')
-                mood_timeline_df = mood_timeline.reset_index()
-                mood_timeline_df.columns = ['Time', 'Mood']
-                st.line_chart(mood_timeline_df.set_index('Time'))
+                    
+                    # If there's no timestamp, create a simple timeline based on message indices
+                    mood_timeline.index = pd.date_range(start='2023-01-01', periods=len(mood_timeline), freq='T')
+
+                    mood_timeline_df = mood_timeline.reset_index()
+                    mood_timeline_df.columns = ['Time', 'Mood']
+
+                    st.line_chart(mood_timeline_df.set_index('Time'))
+                else:
+                    st.write("No mood data to display.")
             else:
-                st.write("No mood data to display.")
-        else:
-            st.write("No messages to summarize.")
+                st.write("No messages to summarize.")
+    else:
+        st.write("No sessions found.")
+
 
 
 elif page == "How to use?":