app.py

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

def stress_level_to_string(stress_level):
    """Convert numerical stress level (0, 1, 2) to a string representation."""
    if stress_level == 0:
        return "Low"
    elif stress_level == 1:
        return "Moderate"
    else:
        return "High"

# Chatbot interface for conversation-like experience
def chatbot_interface():
    st.title("🎓 Student Well-being Chatbot")
    st.write("Hello! I’m here to assist you with well-being advice based on your responses.")

    # Initialize session state
    if 'messages' not in st.session_state:
        st.session_state.messages = [
            {"role": "bot", "content": "Hi there! I'm here to help with your well-being. Let's start! 😊"}
        ]
    
    def next_step(user_input=None):
        # Save the user's message to the chat history
        if user_input:
            st.session_state.messages.append({"role": "user", "content": user_input})
        
        # Proceed to next step in the conversation
        if len(st.session_state.messages) == 1:
            st.session_state.messages.append({"role": "bot", "content": "On a scale of 1 to 10, how would you rate your anxiety level?"})
        elif len(st.session_state.messages) == 2:
            anxiety_level = int(user_input)
            st.session_state.user_data = {'anxiety_level': anxiety_level}
            st.session_state.messages.append({"role": "bot", "content": f"Got it! Your anxiety level is {anxiety_level}. Now, on a scale of 1 to 10, how would you rate your self-esteem?"})
        elif len(st.session_state.messages) == 3:
            self_esteem = int(user_input)
            st.session_state.user_data['self_esteem'] = self_esteem
            st.session_state.messages.append({"role": "bot", "content": f"Got it! Your self-esteem level is {self_esteem}. How would you describe your mental health history?"})
        elif len(st.session_state.messages) == 4:
            st.session_state.user_data['mental_health_history'] = user_input
            st.session_state.messages.append({"role": "bot", "content": "Thanks! Now, on a scale of 0 to 2, how would you rate your stress level?"})
        elif len(st.session_state.messages) == 5:
            stress_level = int(user_input)
            st.session_state.user_data['stress_level'] = stress_level
            st.session_state.messages.append({"role": "bot", "content": "Thank you for providing the information! Let me get your personalized advice..."})
            # Get the advice from Groq API
            advice = get_personalized_advice(st.session_state.user_data)
            st.session_state.messages.append({"role": "bot", "content": advice or "I couldn't retrieve specific advice right now, but please check back later."})
        elif len(st.session_state.messages) == 6:
            st.session_state.messages.append({"role": "bot", "content": "Would you like to start over?"})

    # Display conversation history
    for message in st.session_state.messages:
        if message['role'] == 'bot':
            st.markdown(f"**Bot**: {message['content']}")
        else:
            st.markdown(f"**You**: {message['content']}")

    # User input field for chat interaction
    user_input = st.text_input("Your message:", "")
    if user_input:
        next_step(user_input)

    # Option to restart the conversation
    if len(st.session_state.messages) >= 6:
        restart_button = st.button("Start Over")
        if restart_button:
            st.session_state.messages = [{"role": "bot", "content": "Hi there! I'm here to help with your well-being. Let's start! 😊"}]

# Main function to run the chatbot
def main():
    chatbot_interface()

if __name__ == "__main__":
    main()