Update app.py

app.py

@@ -46,21 +46,10 @@ if uploaded_file:
                 speaker = "Speaker 1" if idx % 2 == 0 else "Speaker 2"
                 diarized_transcript += f"{speaker}: {sentence}\n\n"
 
-            
-            # Static Session Context Recall
-            st.info("🔍 Loading previous session context...")
-            past_sessions = [
-                {"date": "2024-04-15", "coping": "walking", "emotion": "anxiety", "notes": "high workload"},
-                {"date": "2024-04-22", "coping": "journaling", "emotion": "stress", "notes": "difficulty sleeping"}
-            ]
-            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}"""
-
             # Summarization
             st.info("📋 Summarizing conversation...")
             summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-samsum")
-            summary = summarizer(prompt_input, max_length=256, min_length=60, do_sample=False)
+            summary = summarizer(raw_transcript, max_length=256, min_length=60, do_sample=False)
 
             # Emotion tagging
             st.info("🎭 Extracting emotional tones...")
@@ -68,7 +57,7 @@ if uploaded_file:
             emotion_scores = emotion_model(raw_transcript)
 
             # Layout with Tabs
-tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions", "📈 Trends"])
+            tab1, tab2, tab3 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions"])
 
             with tab1:
                 st.subheader("📝 Speaker-Simulated Transcript")
@@ -76,35 +65,9 @@ tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emoti
 
             with tab2:
                 st.subheader("📋 Contextual Summary")
-                
-            # Insight Tracking based on previous sessions
-            insights = []
-            if "music" in raw_transcript.lower():
-                if any("walking" in s["coping"] for s in past_sessions):
-                    insights.append("Patient previously mentioned walking as a helpful coping mechanism. This time, music is highlighted instead.")
-            if "sleep" in raw_transcript.lower():
-                insights.append("Sleep continues to be a recurring theme across sessions.")
-            final_output = f"{summary[0]['summary_text']}\n\nContextual Observations:\n" + "\n".join(insights)
-            st.write(final_output)
-    
+                st.write(summary[0]["summary_text"])
 
             with tab3:
-
-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)
                 st.subheader("💬 Emotional Insights (Overall)")
                 for emo in emotion_scores[0]:
                     st.write(f"{emo['label']}: {round(emo['score']*100, 2)}%")
@@ -162,3 +125,35 @@ with tab4:
     finally:
         if os.path.exists(audio_path):
             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)