Update app.py

app.py

@@ -14,7 +14,7 @@ from datetime import datetime
 st.set_page_config(page_title="Atma.ai - Session Summarizer + Export", layout="wide")
 
 st.title("🧠 Atma.ai – Advanced Mental Health Session Summarizer")
-st.markdown("Upload a therapy session audio (Tamil-English mix) to view the transcript, summary, emotional analysis, and export everything to Word!")
+    st.markdown("Upload a therapy session audio (Tamil-English mix) to view the transcript, summary, emotional analysis, and export everything to Word!")
 
 # Upload audio
 uploaded_file = st.file_uploader("🎙️ Upload audio file", type=["wav", "mp3", "m4a"])
@@ -58,21 +58,21 @@ if uploaded_file:
         ]
         rag_context = "\n".join([f"Session {i+1}: {s['coping']}, {s['emotion']}, {s['notes']}" for i, s in enumerate(past_sessions)])
         prompt_input = f"""Previous session context:\n{rag_context}\n\nCurrent session:\n{raw_transcript}"""
-        summary = summarizer(prompt_input, max_length=256, min_length=60, do_sample=False)
+            summary = summarizer(prompt_input, max_length=256, min_length=60, do_sample=False)
 
-        # Emotion tagging
-        st.info("🎭 Extracting emotional tones...")
-        emotion_model = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True)
-        emotion_scores = emotion_model(raw_transcript)
+            # Emotion tagging
+            st.info("🎭 Extracting emotional tones...")
+            emotion_model = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True)
+            emotion_scores = emotion_model(raw_transcript)
 
-        # Layout with Tabs
+            # Layout with Tabs
 
-        with tab1:
-            st.subheader("📝 Speaker-Simulated Transcript")
-            st.markdown(diarized_transcript, unsafe_allow_html=True)
+            with tab1:
+                st.subheader("📝 Speaker-Simulated Transcript")
+                st.markdown(diarized_transcript, unsafe_allow_html=True)
 
-        with tab2:
-            st.subheader("📋 Contextual Summary")
+            with tab2:
+                st.subheader("📋 Contextual Summary")
 
         # Insight Tracking based on previous sessions
         insights = []
@@ -85,26 +85,26 @@ if uploaded_file:
         final_output = f"{summary[0]['summary_text']}\n\nContextual Observations:\n" + "\n".join(insights)
         st.write(final_output)
 
-        with tab3:
-            st.subheader("💬 Emotional Insights (Overall)")
-            if 'emotion_scores' in locals():
-                for emo in emotion_scores[0]:
-                    st.write(f"{emo['label']}: {round(emo['score']*100, 2)}%")
-            else:
-                st.write("No emotional data to display.")
+            with tab3:
+                st.subheader("💬 Emotional Insights (Overall)")
+                if 'emotion_scores' in locals():
+                    for emo in emotion_scores[0]:
+                        st.write(f"{emo['label']}: {round(emo['score']*100, 2)}%")
+                else:
+                    st.write("No emotional data to display.")
+                
+            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]
             
-        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)
+                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)
 
             # Export Button
             st.subheader("📥 Export Session Report")
@@ -162,14 +162,14 @@ if uploaded_file:
 
 tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions", "📈 Trends"])
 
-with tab1:
+    with tab1:
     st.subheader("📝 Speaker-Simulated Transcript")
     if 'diarized_transcript' in locals():
         st.markdown(diarized_transcript, unsafe_allow_html=True)
     else:
         st.warning("Transcript not available.")
 
-with tab2:
+    with tab2:
     st.subheader("📋 Contextual Summary")
     if 'summary' in locals():
 
@@ -186,7 +186,7 @@ with tab2:
     else:
         st.warning("Summary not available.")
 
-with tab3:
+    with tab3:
     st.subheader("💬 Emotional Insights (Overall)")
     if 'emotion_scores' in locals():
         for emo in emotion_scores[0]:
@@ -194,7 +194,7 @@ with tab3:
     else:
         st.warning("No emotional data to display.")
 
-with tab4:
+    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]