mint UI + mood detection

app.py

@@ -65,11 +65,29 @@ mental_health_keywords = [ # we implement a list of keywords to ensure chatbot o
     "focus", "concentrate", "concentration"
 ]
 
+def detect_mood(message):
+    text = message.lower()
+
+    if any(word in text for word in ["stress", "stressed", "overwhelmed", "burnout", "pressure", "finals", "exam"]):
+        return "😟 Stressed / Overwhelmed"
+    elif any(word in text for word in ["anxiety", "anxious", "panic", "worried", "worry", "nervous", "fear", "scared"]):
+        return "😰 Anxious"
+    elif any(word in text for word in ["sad", "lonely", "depressed", "crying", "numb", "hopeless", "down", "upset"]):
+        return "😢 Sad / Low"
+    elif any(word in text for word in ["angry", "anger", "mad", "frustrated", "annoyed", "irritated"]):
+        return "😠 Angry / Frustrated"
+    elif any(word in text for word in ["happy", "excited", "proud", "grateful", "confident"]):
+        return "😊 Positive"
+    else:
+        return "🙂 General Support"
+
 def respond(message, history):
 
     if not any(word in message.lower() for word in mental_health_keywords):
         return "I'm mainly here to support teen mental wellness. Try asking me about stress, anxiety, school pressure, friendships, emotions, sleep, or coping strategies."
 
+    mood = detect_mood(message)
+    
     relevant_chunk = get_top_chunk(message)
     print("Retrieved chunk:", relevant_chunk) # we are using this line to test RAG system (the terminal will show what knowledge chunk chatbot used)
     
@@ -107,7 +125,7 @@ User question:
         max_tokens=400 # allow longer responses
     )
 
-    return response.choices[0].message.content.strip()
+    return f"Detected Mood: {mood}\n\n" + response.choices[0].message.content.strip()
 
 custom_css = """
 body {