Update app.py
Browse files
app.py
CHANGED
@@ -121,28 +121,27 @@ else:
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with input_container:
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if user_message:
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st.session_state.entered_text.append(user_message)
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st.session_state.messages.append({"role": "user", "content": user_message})
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with st.chat_message("user"):
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st.write(user_message)
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# Define rewards
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if user_sentiment in ["Positive", "Moderately Positive"]:
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if mood_trend == "increased":
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reward = +1
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mood_trend_symbol = " ⬆️"
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@@ -151,8 +150,8 @@ with input_container:
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mood_trend_symbol = ""
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else: # decreased
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reward = -0.2
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mood_trend_symbol = " ⬇️"
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if mood_trend == "increased":
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reward = +1
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mood_trend_symbol = " ⬆️"
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@@ -165,20 +164,19 @@ with input_container:
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print(
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f"mood_trend - sentiment - reward: {mood_trend} - {user_sentiment} - 🛑{reward}🛑"
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)
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with st.chat_message("ai"):
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st.markdown(llm_reponse_with_quesiton)
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# Update data to memory
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st.session_state.user_sentiment = user_sentiment
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st.session_state.mood_trend = mood_trend
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st.session_state.mood_trend_symbol = mood_trend_symbol
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# Convert the response to speech
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speech_fp = text_to_speech(response)
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# Play the speech
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with input_container:
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if user_message:
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st.session_state.entered_text.append(user_message)
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st.session_state.messages.append({"role": "user", "content": user_message})
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# Display the user's message
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with st.chat_message("user"):
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st.write(user_message)
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# Process the user's message and generate a response
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with st.spinner("Processing..."):
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response = generate_response(user_message)
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st.session_state.past.append(user_message)
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st.session_state.messages.append({"role": "ai", "content": response})
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# Detect sentiment
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user_sentiment = chatbot.detect_sentiment(user_message)
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# Update mood history / mood_trend
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chatbot.update_mood_history()
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mood_trend = chatbot.check_mood_trend()
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# Define rewards
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if user_sentiment in ["Positive", "Moderately Positive"]:
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if mood_trend == "increased":
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reward = +1
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mood_trend_symbol = " ⬆️"
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mood_trend_symbol = ""
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else: # decreased
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reward = -0.2
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mood_trend_symbol = " ⬇️"
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else:
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if mood_trend == "increased":
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reward = +1
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mood_trend_symbol = " ⬆️"
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print(
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f"mood_trend - sentiment - reward: {mood_trend} - {user_sentiment} - 🛑{reward}🛑"
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)
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# Update Q-values
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chatbot.update_q_values(user_sentiment, reward, user_sentiment)
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# Display the AI's response
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with st.chat_message("ai"):
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st.markdown(llm_reponse_with_quesiton)
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st.session_state.user_sentiment = user_sentiment
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st.session_state.mood_trend = mood_trend
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st.session_state.mood_trend_symbol = mood_trend_symbol
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# Convert the response to speech
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speech_fp = text_to_speech(response)
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# Play the speech
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