Update app.py

app.py

@@ -10,7 +10,7 @@ toxicity_pipeline = pipeline("text-classification", model="martin-ha/toxic-comme
 
 EMO_THRESHOLD = 0.05  # include even lower confidence emotions
 
-# Expanded emotion mapping
+# Expanded emotion mapping with special cases
 EMOTION_MAPPING = {
     "joy": {
         "underlying": ["Relief", "Contentment", "Pride", "Love", "Gratitude", "Hope"],
@@ -41,9 +41,28 @@ EMOTION_MAPPING = {
         "underlying": ["Accomplishment", "Self-worth", "Achievement"],
         "recommendation": "Celebrate your success while staying humble.",
         "polarity": 1
+    },
+    "anxiety": {
+        "underlying": ["Worry", "Unease", "Apprehension", "Nervousness"],
+        "recommendation": "Try box breathing (4-4-4-4) and focus on preparation.",
+        "polarity": -1
+    },
+    "excitement": {
+        "underlying": ["Anticipation", "Eagerness", "Enthusiasm"],
+        "recommendation": "Channel this energy into planning and goal-setting!",
+        "polarity": 1
     }
 }
 
+# Special emotion triggers
+SPECIAL_EMOTION_TRIGGERS = {
+    "anxious": {"emotion": "anxiety", "confidence": 0.8},
+    "thrilled": {"emotion": "excitement", "confidence": 0.9},
+    "devastated": {"emotion": "grief", "confidence": 0.85},
+    "overjoyed": {"emotion": "elation", "confidence": 0.95},
+    "apprehensive": {"emotion": "wariness", "confidence": 0.75}
+}
+
 def create_visualization(emotions):
     fig, ax = plt.subplots(figsize=(8,5))
     colors = ['#4CAF50' if EMOTION_MAPPING.get(e, {}).get('polarity', 0) > 0 
@@ -60,16 +79,31 @@ def create_visualization(emotions):
     plt.close()
     return f'<img src="data:image/png;base64,{base64.b64encode(buf.read()).decode("utf-8")}">'
 
+def detect_special_emotions(text):
+    special_emotions = {}
+    text_lower = text.lower()
+    
+    for trigger, data in SPECIAL_EMOTION_TRIGGERS.items():
+        if trigger in text_lower:
+            emotion = data["emotion"]
+            # Only add if not already detected or if our confidence is higher
+            if data["confidence"] > special_emotions.get(emotion, 0):
+                special_emotions[emotion] = data["confidence"]
+    
+    return special_emotions
+
 def analyze_text(text):
-    # Emotion detection
+    # Detect special cases first
+    special_emotions = detect_special_emotions(text)
+    
+    # Original emotion detection
     emo_results = emotion_pipeline(text, top_k=None)
     emotions = {e["label"].lower(): e["score"] for e in emo_results if e["score"] > EMO_THRESHOLD}
     
-    # Manual override for specific emotions
-    if "disappointment" in text.lower():
-        emotions["disappointment"] = max(emotions.get("disappointment", 0), 0.7)
-    if "pride" in text.lower():
-        emotions["pride"] = max(emotions.get("pride", 0), 0.8)
+    # Merge with special cases (keeping higher confidence)
+    for emo, score in special_emotions.items():
+        if score > emotions.get(emo, 0):
+            emotions[emo] = score
     
     # Generate detailed analysis
     details = ""
@@ -108,7 +142,10 @@ def analyze_text(text):
     elif negative_emotions and not positive_emotions:
         final_rec = "Consider reaching out for support if these feelings persist."
     elif positive_emotions and negative_emotions:
-        final_rec = "You're experiencing mixed emotions. Acknowledge both sides - celebrate the positive while addressing the negative."
+        if "anxiety" in negative_emotions and "excitement" in positive_emotions:
+            final_rec = "This exciting change comes with natural nerves. Make lists of what you can control to ease anxiety."
+        else:
+            final_rec = "You're experiencing mixed emotions. Acknowledge both sides - celebrate the positive while addressing the negative."
     else:
         final_rec = "The emotional tone is neutral or complex."
     
@@ -127,9 +164,9 @@ iface = gr.Interface(
     title="Advanced Emotion Analyzer",
     description="Detects complex emotional states including underlying emotions and provides balanced recommendations.",
     examples=[
-        ["I'm proud of my work but disappointed with the recognition"],
-        ["I feel joyful yet anxious about the future"],
-        ["This situation makes me both hopeful and fearful"]
+        ["I'm thrilled about my promotion but anxious about the increased responsibilities"],
+        ["I feel overjoyed yet apprehensive about the future"],
+        ["This situation makes me both hopeful and devastated"]
     ]
 )