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import streamlit as st
from groq import Groq
# Groq API Key (replace with your actual API key)
groq_api_key = "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"
# Initialize Groq client
client = Groq(api_key=groq_api_key)
# Function to fetch personalized advice using Groq API
def get_personalized_advice(user_data):
"""Fetch personalized advice using the Groq API based on user data."""
query = f"Based on the user's data: anxiety level: {user_data['anxiety_level']}, self esteem: {user_data['self_esteem']}, mental health history: {user_data['mental_health_history']}, stress level: {user_data['stress_level']}, provide personalized mental health advice."
try:
response = client.chat.completions.create(
messages=[{"role": "user", "content": query}],
model="llama-3.3-70b-versatile",
)
return response.choices[0].message.content
except Exception as e:
st.error(f"Error fetching advice from Groq: {str(e)}")
return None
# Function for chatbot interaction with professional styling
def chatbot_interface():
st.set_page_config(page_title="π Student Well-being Chatbot", layout="centered")
st.title("π Student Well-being Chatbot")
st.write("Welcome! I'm here to help you with well-being advice tailored to your current state.")
# Styling the sidebar for improved UX
st.sidebar.title("Student Well-being")
st.sidebar.write("The well-being questionnaire will guide you through assessing your mental health and providing personalized advice.")
# Initialize session state
if 'step' not in st.session_state:
st.session_state.step = 0
st.session_state.user_data = {}
def next_step():
st.session_state.step += 1
def show_input_error(message="Please provide a valid input."):
st.error(message)
return False
# Step 0: Welcome message and initial question
if st.session_state.step == 0:
st.write("Bot: Hi there! I'm here to assist you with your well-being. Let's get started! π")
st.markdown("<hr>", unsafe_allow_html=True)
next_step_button = st.button("Start Chat", key="start_button", help="Click to start the well-being questionnaire.")
if next_step_button:
next_step()
# Step 1: Ask for anxiety level with slider
elif st.session_state.step == 1:
st.write("Bot: On a scale of 1 to 10, how would you rate your anxiety level?")
anxiety_level = st.slider("Your Anxiety Level:", min_value=1, max_value=10, value=5, step=1, help="Rate your anxiety from 1 (low) to 10 (high).")
st.session_state.user_data['anxiety_level'] = anxiety_level
next_step()
# Step 2: Ask for self-esteem with slider
elif st.session_state.step == 2:
st.write("Bot: On a scale of 1 to 10, how would you rate your self-esteem?")
self_esteem = st.slider("Your Self-Esteem Level:", min_value=1, max_value=10, value=5, step=1, help="Rate your self-esteem from 1 (low) to 10 (high).")
st.session_state.user_data['self_esteem'] = self_esteem
next_step()
# Step 3: Ask for mental health history
elif st.session_state.step == 3:
st.write("Bot: How would you describe your mental health history?")
mental_health_history = st.selectbox(
"Select your mental health history:",
["None", "Minor Issues", "Moderate Issues", "Severe Issues"],
help="Choose an option that best describes your mental health background."
)
st.session_state.user_data['mental_health_history'] = mental_health_history
next_step()
# Step 4: Ask for stress level with slider
elif st.session_state.step == 4:
st.write("Bot: On a scale of 0 to 2, how would you rate your stress level?")
stress_level = st.slider("Your Stress Level:", min_value=0, max_value=2, value=1, step=1, help="Rate your stress from 0 (low) to 2 (high).")
st.session_state.user_data['stress_level'] = stress_level
next_step()
# Step 5: Show advice based on user input
elif st.session_state.step == 5:
st.write("Bot: Thank you for providing the information! Hereβs your personalized advice:")
user_data = st.session_state.user_data
st.write(f"Your Data: {user_data}")
# Fetch personalized advice from Groq
st.subheader("π Here's Your Personalized Well-being Advice:")
advice = get_personalized_advice(user_data)
if advice:
st.write(advice)
else:
st.write("I couldn't retrieve specific advice right now, but please check back later.")
# Option to restart the chat
st.markdown("<hr>", unsafe_allow_html=True)
restart_button = st.button("Start Over", key="restart_button", help="Click to restart the questionnaire.")
if restart_button:
st.session_state.step = 0
st.session_state.user_data = {}
# Main function to run the chatbot
def main():
chatbot_interface()
if __name__ == "__main__":
main()
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