pages/chatbot.py

import streamlit as st
import requests
import json

# Set up Gemini API key
GEMINI_API_KEY = "AIzaSyCbkm1DvOWXeQxrH2BYz3PrRbpdAseor20"
API_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={GEMINI_API_KEY}"

# Define addiction assessment questions
questions = [
    "How many hours do you spend on social media daily? (0-24)",
    "How often do you check social media? (Rarely, Sometimes, Often, Always)",
    "Does social media affect your productivity? (Yes/No)",
    "Do you feel anxious when not using social media? (Yes/No)",
    "Have you tried to reduce your usage but failed? (Yes/No)"
]

# Mapping responses to addiction scores
def calculate_addiction_score(responses):
    score = 0

    # Question 1: Hours spent on social media (0-10)
    score += int(responses[0]) if responses[0].isdigit() else 0

    # Question 2: Frequency of checking
    frequency_scores = {"Rarely": 2, "Sometimes": 4, "Often": 7, "Always": 10}
    score += frequency_scores.get(responses[1], 0)

    # Yes/No questions (Questions 3-5)
    for i in range(2, 5):
        if responses[i].strip().lower() == "yes":
            score += 2  # Add 2 points for each 'Yes'

    # Normalize score (Max possible is 30)
    return min(score, 10)  # Keep score between 0-10

def get_gemini_response(score):
    """Send addiction level to Gemini API and get a response."""
    headers = {"Content-Type": "application/json"}
    data = {
        "contents": [{"parts": [{"text": f"The user has a social media addiction score of {score}/10. Provide advice accordingly."}]}]
    }
    
    response = requests.post(API_URL, headers=headers, json=data)
    if response.status_code == 200:
        return response.json()["candidates"][0]["content"]["parts"][0]["text"]
    else:
        return "⚠️ Error: Unable to get response. Check API key and usage limits."

# Streamlit UI
st.title("📱 Social Media Addiction Test")

# Initialize session state
if "responses" not in st.session_state:
    st.session_state.responses = []
if "question_index" not in st.session_state:
    st.session_state.question_index = 0
if "addiction_score" not in st.session_state:
    st.session_state.addiction_score = None

# Ask Questions One by One
if st.session_state.question_index < len(questions):
    user_response = st.text_input(questions[st.session_state.question_index])

    if user_response:
        st.session_state.responses.append(user_response)
        st.session_state.question_index += 1
        st.rerun()

# Once all questions are answered, calculate addiction level
elif st.session_state.addiction_score is None:
    st.session_state.addiction_score = calculate_addiction_score(st.session_state.responses)
    addiction_level = st.session_state.addiction_score

    st.subheader(f"📊 Your Social Media Addiction Score: {addiction_level}/10")
    
    # Get advice from Gemini API
    advice = get_gemini_response(addiction_level)
    st.write(advice)

    # Reset session for next test
    if st.button("Retake Test"):
        st.session_state.responses = []
        st.session_state.question_index = 0
        st.session_state.addiction_score = None
        st.rerun()



# import streamlit as st
# import requests
# import json

# # Set up Gemini API key
# GEMINI_API_KEY = "AIzaSyCbkm1DvOWXeQxrH2BYz3PrRbpdAseor20"
# API_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={GEMINI_API_KEY}"

# def get_gemini_response(user_input):
#     """Send request to Gemini API and return the response."""
#     headers = {"Content-Type": "application/json"}
#     data = {
#         "contents": [{"parts": [{"text": user_input}]}]
#     }
    
#     response = requests.post(API_URL, headers=headers, json=data)
#     if response.status_code == 200:
#         return response.json()["candidates"][0]["content"]["parts"][0]["text"]
#     else:
#         return "⚠️ Error: Unable to get response. Check API key and usage limits."

# # Streamlit UI
# st.title("🤖 Gemini AI Chatbot")

# st.sidebar.header("Chatbot Settings")
# st.sidebar.write("This bot gives **concise & to-the-point** responses.")

# # Initialize chat history
# if "messages" not in st.session_state:
#     st.session_state.messages = []

# # Display chat history
# for msg in st.session_state.messages:
#     with st.chat_message(msg["role"]):
#         st.write(msg["content"])

# # User input
# user_input = st.chat_input("Ask me anything...")
# if user_input:
#     st.session_state.messages.append({"role": "user", "content": user_input})

#     # Get response from Gemini
#     bot_reply = get_gemini_response(user_input)
#     st.session_state.messages.append({"role": "assistant", "content": bot_reply})

#     # Display bot response
#     with st.chat_message("assistant"):
#         st.write(bot_reply)