Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import streamlit as st
 import plotly.graph_objects as go
 from transformers import pipeline
@@ -56,7 +57,7 @@ if uploaded_file:
             emotion_scores = emotion_model(raw_transcript)
 
             # Layout with Tabs
-            tab1, tab2, tab3 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions"])
+            tab1, tab2, tab3 = tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions", "📈 Trends"])
 
             with tab1:
                 st.subheader("📝 Speaker-Simulated Transcript")
@@ -67,7 +68,21 @@ if uploaded_file:
                 st.write(summary[0]["summary_text"])
 
             with tab3:
-                st.subheader("💬 Emotional Insights (Overall)")
+                
+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 = go.Figure()
+    fig.add_trace(go.Scatter(x=session_dates, y=anxiety_scores, mode='lines+markers', name='Anxiety'))
+    fig.add_trace(go.Scatter(x=session_dates, y=sadness_scores, mode='lines+markers', name='Sadness'))
+    fig.update_layout(title='Emotional Trends', xaxis_title='Date', yaxis_title='Score (%)')
+    st.plotly_chart(fig)
+
+st.subheader("💬 Emotional Insights (Overall)")
                 for emo in emotion_scores[0]:
                     st.write(f"{emo['label']}: {round(emo['score']*100, 2)}%")
 
@@ -124,28 +139,3 @@ if uploaded_file:
     finally:
         if os.path.exists(audio_path):
             os.remove(audio_path)
-
-# --- Post-processing UI Layout ---
-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")
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(x=session_dates, y=anxiety_scores, mode='lines+markers', name='Anxiety'))
-    fig.add_trace(go.Scatter(x=session_dates, y=sadness_scores, mode='lines+markers', name='Sadness'))
-    fig.update_layout(title='Emotional Trends', xaxis_title='Date', yaxis_title='Score (%)')
-    st.plotly_chart(fig)