Update app.py

app.py

@@ -26,9 +26,7 @@ final_chain = mdl.create_final_chain()
 # Define states and actions
 states = [
     "Negative",
-    "Moderately Negative",
     "Neutral",
-    "Moderately Positive",
     "Positive",
 ]
 
@@ -79,10 +77,6 @@ if "messages" not in st.session_state:
     st.session_state.messages = []
 if "user_sentiment" not in st.session_state:
     st.session_state.user_sentiment = "Neutral"
-if "mood_trend" not in st.session_state:
-    st.session_state.mood_trend = "Unchanged"
-if "mood_trend_symbol" not in st.session_state:
-    st.session_state.mood_trend_symbol = ""
 
 # Layout of input/response containers
 
@@ -136,39 +130,7 @@ with input_container:
             
             # Detect sentiment
             user_sentiment = chatbot.detect_sentiment(user_message)
-            
-            # Update mood history / mood_trend
-            chatbot.update_mood_history()
-            mood_trend = chatbot.check_mood_trend()
-
-            # Define rewards
-            if user_sentiment in ["Positive", "Moderately Positive"]:
-                if mood_trend == "increased":
-                        reward = +1
-                        mood_trend_symbol = " ⬆️"
-                elif mood_trend == "unchanged":
-                        reward = +0.8
-                        mood_trend_symbol = ""    
-                else:  # decreased
-                        reward = -0.2
-                        mood_trend_symbol = " ⬇️"            
-            else:
-                 if mood_trend == "increased":
-                        reward = +1
-                        mood_trend_symbol = " ⬆️"
-                 elif mood_trend == "unchanged":
-                        reward = -0.2
-                        mood_trend_symbol = ""   
-                 else:  # decreased
-                        reward = -1
-                        mood_trend_symbol = " ⬇️"      
-    
-            print(f"mood_trend - sentiment - reward: {mood_trend} - {user_sentiment} - 🛑{reward}🛑")    
-    
-
-            # Update Q-values
-            chatbot.update_q_values(user_sentiment, reward, user_sentiment)
-            
+
             # Display the AI's response
             with st.chat_message("ai"):
                 st.markdown(response)