Update app.py

app.py

@@ -2,10 +2,13 @@ import streamlit as st
 from transformers import pipeline
 import re
 
-# Load models
-emotion_classifier = pipeline("text-classification", model="bhadresh-savani/distilbert-base-uncased-emotion", top_k=1)
+# Load upgraded models
+emotion_classifier = pipeline(
+    "text-classification",
+    model="j-hartmann/emotion-english-distilroberta-base",
+    return_all_scores=True
+)
 intent_classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
-text_generator = pipeline("text2text-generation", model="declare-lab/flan-alpaca-base", max_new_tokens=200)
 
 # Candidate intents
 candidate_tasks = [
@@ -19,14 +22,18 @@ candidate_tasks = [
     "upgrade device"
 ]
 
-# Emotion scoring
-urgent_emotions = {"anger", "annoyance", "disgust", "frustration", "sadness"}
-moderate_emotions = {"confusion", "concern", "nervousness", "fear"}
+# Emotion categories (updated)
+urgent_emotions = {"anger", "frustration", "anxiety", "urgency", "afraid", "annoyed"}
+moderate_emotions = {"confused", "sad", "tired", "concerned"}
+
+def get_emotion_label(emotion_result):
+    sorted_emotions = sorted(emotion_result[0], key=lambda x: x['score'], reverse=True)
+    return sorted_emotions[0]['label']
 
 def get_emotion_score(emotion):
-    if emotion in urgent_emotions:
+    if emotion.lower() in urgent_emotions:
         return 1.0
-    elif emotion in moderate_emotions:
+    elif emotion.lower() in moderate_emotions:
         return 0.6
     else:
         return 0.2
@@ -73,7 +80,7 @@ def generate_reply(input_text, intent):
 
     return f"{opening} {solution} {closing}"
 
-# UI
+# Streamlit UI
 st.set_page_config(page_title="Customer Support Assistant", layout="centered")
 st.title("📞 Smart Customer Support Assistant (for Agents Only)")
 
@@ -85,10 +92,9 @@ if st.button("Analyze Message"):
     else:
         with st.spinner("Processing..."):
 
-            # Emotion detection
+            # Emotion detection (updated)
             emotion_result = emotion_classifier(user_input)
-            emotion_data = emotion_result[0][0] if isinstance(emotion_result[0], list) else emotion_result[0]
-            emotion_label = emotion_data['label']
+            emotion_label = get_emotion_label(emotion_result)
             emotion_score = get_emotion_score(emotion_label)
 
             # Intent detection