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Update app.py
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app.py
CHANGED
@@ -9,15 +9,14 @@ client = Groq(api_key=groq_api_key)
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# Function to fetch personalized advice using Groq API
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def get_personalized_advice(user_data):
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"""Fetch personalized advice
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query = f"""
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Based on the following
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- Anxiety level: {user_data['anxiety_level']}
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- Self-esteem: {user_data['self_esteem']}
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- Mental health history: {user_data['mental_health_history']}
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- Stress level: {user_data['stress_level']}
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-
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Please provide professional, personalized mental health advice tailored to these responses.
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"""
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try:
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@@ -27,11 +26,11 @@ def get_personalized_advice(user_data):
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)
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return response.choices[0].message.content
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except Exception as e:
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st.error(f"Error fetching advice
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return None
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def stress_level_to_string(stress_level):
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"""Convert
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if stress_level == 0:
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return "Low"
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elif stress_level == 1:
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@@ -39,10 +38,10 @@ def stress_level_to_string(stress_level):
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else:
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return "High"
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# Chatbot interface
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def chatbot_interface():
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st.title("π
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st.write("
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# Initialize session state
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if 'step' not in st.session_state:
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@@ -63,29 +62,30 @@ def chatbot_interface():
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# Step 0: Welcome message and initial question
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if st.session_state.step == 0:
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st.write("Bot:
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st.
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next_step_button = st.button("Start Assessment")
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clear_button = st.button("Clear All")
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if
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next_step()
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if clear_button:
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clear_data()
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# Step 1: Ask for anxiety level
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elif st.session_state.step == 1:
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st.write("Bot: On a scale
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anxiety_level = st.slider("Anxiety Level", 1, 10, 5)
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-
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next_step()
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# Step 2: Ask for self-esteem
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elif st.session_state.step == 2:
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st.write("Bot: On a scale from 1 to 10, how would you rate your current self-esteem?")
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self_esteem = st.slider("Self-esteem Level", 1, 10, 5)
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-
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next_step()
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# Step 3: Ask for mental health history
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@@ -96,30 +96,36 @@ def chatbot_interface():
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["None", "Minor Issues", "Moderate Issues", "Severe Issues"]
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)
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st.session_state.user_data['mental_health_history'] = mental_health_history
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# Step 4: Ask for stress level
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elif st.session_state.step == 4:
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st.write("Bot: On a scale from 0 to 2, how would you rate your current stress level?")
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stress_level = st.radio("Stress Level
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st.session_state.user_data['stress_level'] = stress_level
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-
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# Step 5:
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elif st.session_state.step == 5:
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st.write("Bot: Thank you for providing the information
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user_data = st.session_state.user_data
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st.write(f"Bot:
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st.subheader("π Professional Well-being Advice:")
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advice = get_personalized_advice(user_data)
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if advice:
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st.write(f"Bot: {advice}")
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else:
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st.write("Bot:
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-
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# Option to restart
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restart_button = st.button("Start Over")
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clear_button = st.button("Clear All")
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if restart_button:
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# Function to fetch personalized advice using Groq API
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def get_personalized_advice(user_data):
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"""Fetch personalized advice based on user data."""
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query = f"""
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Based on the following student's responses:
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- Anxiety level: {user_data['anxiety_level']}
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- Self-esteem: {user_data['self_esteem']}
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- Mental health history: {user_data['mental_health_history']}
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- Stress level: {user_data['stress_level']}
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Provide professional, personalized mental health advice.
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"""
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try:
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)
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return response.choices[0].message.content
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except Exception as e:
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st.error(f"Error fetching advice: {str(e)}")
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return None
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def stress_level_to_string(stress_level):
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"""Convert stress level to string representation."""
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if stress_level == 0:
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return "Low"
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elif stress_level == 1:
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else:
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return "High"
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# Chatbot interface
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def chatbot_interface():
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st.title("π Student Health and Stress Chatbot")
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st.write("Hello! Iβm here to assist you in assessing your well-being and provide helpful advice. Let's get started! π")
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# Initialize session state
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if 'step' not in st.session_state:
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# Step 0: Welcome message and initial question
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if st.session_state.step == 0:
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st.write("Bot: Welcome to the Student Health and Stress Assessment. Let's start with some simple questions.")
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start_button = st.button("Start Assessment")
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clear_button = st.button("Clear All")
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if start_button:
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next_step()
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if clear_button:
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clear_data()
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# Step 1: Ask for anxiety level
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elif st.session_state.step == 1:
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st.write("Bot: On a scale of 1 to 10, how would you rate your current anxiety level?")
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anxiety_level = st.slider("Anxiety Level", 1, 10, 5)
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st.session_state.user_data['anxiety_level'] = anxiety_level
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next_step_button = st.button("Next")
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if next_step_button:
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next_step()
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# Step 2: Ask for self-esteem
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elif st.session_state.step == 2:
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st.write("Bot: On a scale from 1 to 10, how would you rate your current self-esteem?")
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self_esteem = st.slider("Self-esteem Level", 1, 10, 5)
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st.session_state.user_data['self_esteem'] = self_esteem
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next_step_button = st.button("Next")
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if next_step_button:
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next_step()
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# Step 3: Ask for mental health history
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["None", "Minor Issues", "Moderate Issues", "Severe Issues"]
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)
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st.session_state.user_data['mental_health_history'] = mental_health_history
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next_step_button = st.button("Next")
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if next_step_button:
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next_step()
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# Step 4: Ask for stress level
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elif st.session_state.step == 4:
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st.write("Bot: On a scale from 0 to 2, how would you rate your current stress level?")
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stress_level = st.radio("Stress Level", [0, 1, 2])
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st.session_state.user_data['stress_level'] = stress_level
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next_step_button = st.button("Next")
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if next_step_button:
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next_step()
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# Step 5: Provide personalized advice based on responses
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elif st.session_state.step == 5:
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st.write("Bot: Thank you for providing the information! Here's a summary of your responses:")
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user_data = st.session_state.user_data
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st.write(f"Bot: Your Anxiety Level: {user_data['anxiety_level']}")
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st.write(f"Bot: Your Self-Esteem Level: {user_data['self_esteem']}")
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st.write(f"Bot: Mental Health History: {user_data['mental_health_history']}")
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st.write(f"Bot: Your Stress Level: {stress_level_to_string(user_data['stress_level'])}")
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st.subheader("π Personalized Mental Health Advice:")
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advice = get_personalized_advice(user_data)
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if advice:
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st.write(f"Bot: {advice}")
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else:
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st.write("Bot: I'm unable to retrieve personalized advice at the moment, but feel free to try again later.")
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# Option to restart or clear data
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restart_button = st.button("Start Over")
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clear_button = st.button("Clear All")
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if restart_button:
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