Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import streamlit as st
 import matplotlib.pyplot as plt
 from transformers import pipeline
@@ -127,33 +126,34 @@ if uploaded_file:
             os.remove(audio_path)
 
 # --- Post-processing UI Layout ---
-tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions", "📈 Trends"])
-
-with tab1:
-    st.subheader("📝 Transcript")
-    st.markdown(diarized_transcript, unsafe_allow_html=True)
-
-with tab2:
-    st.subheader("📋 Contextual Summary")
-    st.write(final_output)
-
-with tab3:
-    st.subheader("💬 Emotional Insights (Overall)")
-    for emo in emotion_scores[0]:
-        st.write(f"{emo['label']}: {round(emo['score']*100, 2)}%")
-
-with tab4:
-    st.subheader("📈 Emotional Trends Over Time")
-
-    session_dates = ["2024-04-01", "2024-04-08", "2024-04-15", "2024-04-22"]
-    anxiety_scores = [70, 65, 55, 40]
-    sadness_scores = [30, 20, 25, 15]
-
-    fig, ax = plt.subplots()
-    ax.plot(session_dates, anxiety_scores, label='Anxiety', marker='o')
-    ax.plot(session_dates, sadness_scores, label='Sadness', marker='o')
-    ax.set_title("Emotional Trends Over Time")
-    ax.set_ylabel("Score (%)")
-    ax.set_xlabel("Session Date")
-    ax.legend()
-    st.pyplot(fig)
+if 'diarized_transcript' in locals() and 'final_output' in locals() and 'emotion_scores' in locals():
+    tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions", "📈 Trends"])
+
+    with tab1:
+        st.subheader("📝 Transcript")
+        st.markdown(diarized_transcript, unsafe_allow_html=True)
+
+    with tab2:
+        st.subheader("📋 Contextual Summary")
+        st.write(final_output)
+
+    with tab3:
+        st.subheader("💬 Emotional Insights (Overall)")
+        for emo in emotion_scores[0]:
+            st.write(f"{emo['label']}: {round(emo['score']*100, 2)}%")
+
+    with tab4:
+        st.subheader("📈 Emotional Trends Over Time")
+
+        session_dates = ["2024-04-01", "2024-04-08", "2024-04-15", "2024-04-22"]
+        anxiety_scores = [70, 65, 55, 40]
+        sadness_scores = [30, 20, 25, 15]
+
+        fig, ax = plt.subplots()
+        ax.plot(session_dates, anxiety_scores, label='Anxiety', marker='o')
+        ax.plot(session_dates, sadness_scores, label='Sadness', marker='o')
+        ax.set_title("Emotional Trends Over Time")
+        ax.set_ylabel("Score (%)")
+        ax.set_xlabel("Session Date")
+        ax.legend()
+        st.pyplot(fig)