Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import os
 import streamlit as st
 import tempfile
@@ -42,6 +41,9 @@ def get_emotion_classifier():
 
 def perform_emotion_detection(text):
     try:
+        if not text or len(text.strip()) < 3:
+            return {}, "neutral", {}, "NEUTRAL"
+            
         emotion_classifier = get_emotion_classifier()
         emotion_results = emotion_classifier(text)[0]
         
@@ -61,20 +63,60 @@ def perform_emotion_detection(text):
                             "embarrassment", "fear", "grief", "nervousness", "remorse", "sadness"]
         neutral_emotions = ["confusion", "curiosity", "realization", "surprise", "neutral"]
         
-        emotions_dict = {result['label']: result['score'] for result in emotion_results}
-        top_emotion = max(emotions_dict, key=emotions_dict.get)
+        # Fix 1: Create a clean emotions dictionary from results
+        emotions_dict = {}
+        for result in emotion_results:
+            emotions_dict[result['label']] = result['score']
+        
+        # Fix 2: Filter out very low scores (below threshold)
+        filtered_emotions = {k: v for k, v in emotions_dict.items() if v > 0.05}
+        
+        # If filtered dictionary is empty, fall back to original
+        if not filtered_emotions:
+            filtered_emotions = emotions_dict
+        
+        # Fix 3: Make sure we properly find the top emotion
+        top_emotion = max(filtered_emotions, key=filtered_emotions.get)
+        top_score = filtered_emotions[top_emotion]
         
+        # Fix 4: More robust sentiment assignment
         if top_emotion in positive_emotions:
             sentiment = "POSITIVE"
         elif top_emotion in negative_emotions:
             sentiment = "NEGATIVE"
         else:
-            sentiment = "NEUTRAL"
+            # If the top emotion is neutral but there are strong competing emotions, use them
+            competing_emotions = sorted(filtered_emotions.items(), key=lambda x: x[1], reverse=True)[:3]
             
+            # Check if there's a close second non-neutral emotion
+            if len(competing_emotions) > 1:
+                if (competing_emotions[0][0] in neutral_emotions and 
+                    competing_emotions[1][0] not in neutral_emotions and
+                    competing_emotions[1][1] > 0.7 * competing_emotions[0][1]):
+                    # Use the second strongest emotion instead
+                    top_emotion = competing_emotions[1][0]
+                    if top_emotion in positive_emotions:
+                        sentiment = "POSITIVE"
+                    elif top_emotion in negative_emotions:
+                        sentiment = "NEGATIVE"
+                    else:
+                        sentiment = "NEUTRAL"
+                else:
+                    sentiment = "NEUTRAL"
+            else:
+                sentiment = "NEUTRAL"
+            
+        # Log for debugging
+        print(f"Text: {text[:50]}...")
+        print(f"Top 3 emotions: {sorted(filtered_emotions.items(), key=lambda x: x[1], reverse=True)[:3]}")
+        print(f"Selected top emotion: {top_emotion} ({filtered_emotions.get(top_emotion, 0):.3f})")
+        print(f"Sentiment determined: {sentiment}")
+        
         return emotions_dict, top_emotion, emotion_map, sentiment
     except Exception as e:
         st.error(f"Emotion detection failed: {str(e)}")
-        return {}, "unknown", {}, "UNKNOWN"
+        print(f"Exception in emotion detection: {str(e)}")
+        return {}, "neutral", {}, "NEUTRAL"
 
 # Sarcasm Detection Function
 @st.cache_resource
@@ -86,6 +128,9 @@ def get_sarcasm_classifier():
 
 def perform_sarcasm_detection(text):
     try:
+        if not text or len(text.strip()) < 3:
+            return False, 0.0
+            
         sarcasm_classifier = get_sarcasm_classifier()
         result = sarcasm_classifier(text)[0]
         is_sarcastic = result['label'] == "LABEL_1"
@@ -254,7 +299,6 @@ def custom_audio_recorder():
             audioRecorder.streamBeingCaptured = null;
         }
     }
-
     var isRecording = false;
     var recordButton = document.getElementById('record-button');
     var audioElement = document.getElementById('audio-playback');
@@ -292,7 +336,6 @@ def custom_audio_recorder():
                 });
         }
     }
-
     document.addEventListener('DOMContentLoaded', function() {
         recordButton = document.getElementById('record-button');
         audioElement = document.getElementById('audio-playback');
@@ -301,13 +344,11 @@ def custom_audio_recorder():
         recordButton.addEventListener('click', toggleRecording);
     });
     </script>
-
     <div class="audio-recorder-container">
         <button id="record-button" class="record-button">Start Recording</button>
         <audio id="audio-playback" controls style="display:block; margin-top:10px;"></audio>
         <input type="hidden" id="audio-data" name="audio-data">
     </div>
-
     <style>
     .audio-recorder-container {
         display: flex;
@@ -340,8 +381,16 @@ def custom_audio_recorder():
 
 # Function to display analysis results
 def display_analysis_results(transcribed_text):
+    # Fix 5: Add debugging to track what's happening
+    st.session_state.debug_info = st.session_state.get('debug_info', [])
+    st.session_state.debug_info.append(f"Processing text: {transcribed_text[:50]}...")
+    
     emotions_dict, top_emotion, emotion_map, sentiment = perform_emotion_detection(transcribed_text)
     is_sarcastic, sarcasm_score = perform_sarcasm_detection(transcribed_text)
+    
+    # Add results to debug info
+    st.session_state.debug_info.append(f"Top emotion: {top_emotion}, Sentiment: {sentiment}")
+    st.session_state.debug_info.append(f"Sarcasm: {is_sarcastic}, Score: {sarcasm_score:.3f}")
 
     st.header("Transcribed Text")
     st.text_area("Text", transcribed_text, height=150, disabled=True, help="The audio converted to text.")
@@ -380,6 +429,17 @@ def display_analysis_results(transcribed_text):
         else:
             st.write("No emotions detected.")
 
+    # Fix 6: Add debug expander for troubleshooting
+    with st.expander("Debug Information", expanded=False):
+        st.write("Debugging information for troubleshooting:")
+        for i, debug_line in enumerate(st.session_state.debug_info[-10:]):
+            st.text(f"{i+1}. {debug_line}")
+        if emotions_dict:
+            st.write("Raw emotion scores:")
+            for emotion, score in sorted(emotions_dict.items(), key=lambda x: x[1], reverse=True):
+                if score > 0.01:  # Only show non-negligible scores
+                    st.text(f"{emotion}: {score:.4f}")
+
     with st.expander("Analysis Details", expanded=False):
         st.write("""
         **How this works:**
@@ -416,6 +476,10 @@ def process_base64_audio(base64_data):
 
 # Main App Logic
 def main():
+    # Fix 7: Initialize session state for debugging
+    if 'debug_info' not in st.session_state:
+        st.session_state.debug_info = []
+    
     tab1, tab2 = st.tabs(["📁 Upload Audio", "🎙️ Record Audio"])
     
     with tab1:
@@ -487,4 +551,4 @@ def main():
     show_model_info()
 
 if __name__ == "__main__":
-    main()
+    main()