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 following user's responses:
    - 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']}

    Please provide professional, personalized mental health advice tailored to these responses.
    """

    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 professional user experience
def chatbot_interface():
    st.title("🎓 Professional Student Well-being Chatbot")
    st.write("Welcome to the Student Well-being Chatbot. I’m here to assist you in improving your mental well-being based on your responses. Please answer the following questions.")

    # 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

    def clear_data():
        """Clear session data and reset to initial step."""
        st.session_state.step = 0
        st.session_state.user_data = {}

    # Step 0: Welcome message and initial question
    if st.session_state.step == 0:
        st.write("Bot: Thank you for choosing to take this well-being assessment. We will gather some insights to provide personalized advice.")
        st.write("Bot: Please answer the following questions as accurately as possible.")
        next_step_button = st.button("Start Assessment")
        clear_button = st.button("Clear All")
        if next_step_button:
            next_step()
        if clear_button:
            clear_data()

    # Step 1: Ask for anxiety level
    elif st.session_state.step == 1:
        st.write("Bot: On a scale from 1 to 10, how would you rate your current anxiety level?")
        anxiety_level = st.slider("Anxiety Level", 1, 10, 5)
        if anxiety_level:
            st.session_state.user_data['anxiety_level'] = anxiety_level
            next_step()

    # Step 2: Ask for self-esteem
    elif st.session_state.step == 2:
        st.write("Bot: On a scale from 1 to 10, how would you rate your current self-esteem?")
        self_esteem = st.slider("Self-esteem Level", 1, 10, 5)
        if self_esteem:
            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(
            "Please select the option that best represents your mental health history:",
            ["None", "Minor Issues", "Moderate Issues", "Severe Issues"]
        )
        st.session_state.user_data['mental_health_history'] = mental_health_history
        next_step()

    # Step 4: Ask for stress level
    elif st.session_state.step == 4:
        st.write("Bot: On a scale from 0 to 2, how would you rate your current stress level?")
        stress_level = st.radio("Stress Level (0 = Low, 1 = Moderate, 2 = High)", [0, 1, 2])
        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.")
        user_data = st.session_state.user_data
        st.write(f"Bot: Based on your inputs, here is a summary of your responses: {user_data}")

        # Show professional, personalized advice
        st.subheader("🔔 Professional Well-being Advice:")
        advice = get_personalized_advice(user_data)
        if advice:
            st.write(f"Bot: {advice}")
        else:
            st.write("Bot: Unfortunately, I couldn't retrieve specific advice at this moment, but feel free to try again later.")

        # Option to restart the chat
        restart_button = st.button("Start Over")
        clear_button = st.button("Clear All")
        if restart_button:
            clear_data()
        if clear_button:
            clear_data()

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

if __name__ == "__main__":
    main()