import streamlit as st
import google.generativeai as palm
from gradio_client import Client
import time
import threading

# Initialize the Gradio client with the API URL
client = Client("https://akdeniz27-llama-2-70b-chat-hf-with-easyllm.hf.space/")

# Information about obtaining a free API key
st.sidebar.info("🔑 Get your free palm2 API key at [makersuite.google.com/app/apikey](https://makersuite.google.com/app/apikey)")

# Ask the user for palm2 API key
api_key_palm2 = st.sidebar.text_input("🔒 Enter your palm2 API key for study notes:", type="password")
palm.configure(api_key=api_key_palm2)

# Styling for the title
st.title("🚀 Auto Study Notes Generator")
st.markdown("---")

# Sidebar for settings
st.sidebar.title("⚙️ Settings")

# User choice for mode selection
selected_mode = st.sidebar.radio("🔍 Select Mode:", ['Generate Study Notes (Palm2)', 'Use Llama 70b for Notes'])

# Initialize view count
view_count = 0

# Function to simulate live view count
def update_view_count():
    global view_count
    while True:
        time.sleep(5)  # Simulate updates every 5 seconds
        view_count += 1

# Start the thread to simulate live view count
thread = threading.Thread(target=update_view_count)
thread.start()

# Main content area
if selected_mode == 'Generate Study Notes (Palm2)':
    st.header("📚 Study Notes Generation (Palm2)")

    # User input for class and study topic
    user_class = st.sidebar.selectbox('👩‍🎓 Select your class:', ['Class 1', 'Class 2', 'Class 3', 'Class 4', 'Class 5', 'Class 6',
                                                                   'Class 7', 'Class 8', 'Class 9', 'Class 10', 'Class 11', 'Class 12'])
    user_input = st.text_input(f'✏️ Enter your study topic for {user_class}:', placeholder='e.g., History')

    if st.button('🚀 Generate Study Notes', key="generate_notes", help="Click to generate study notes"):
        if user_input.lower() in ['quit', 'exit', 'bye']:
            st.success("👋 Goodbye! Have a great day!")
        else:
            with st.spinner("⌛ Generating study notes. Please wait..."):
                prompt = f"Provide study notes for {user_class} on the topic: {user_input}."
                response = palm.generate_text(model='models/text-bison-001', prompt=prompt)
                study_notes = response.result

                # Display the generated study notes
                st.subheader(f"📚 Study Notes for {user_class} - {user_input}")
                st.write(study_notes)

elif selected_mode == 'Use Llama 70b for Notes':
    st.header("🦙 Llama 70b Mode")

    # User input for Llama 70b mode
    llama_input = st.text_input('💬 Enter a message for Llama 70b (type "exit" to quit):', placeholder='e.g., Tell me a joke')

    if st.button('🔍 Get Llama 70b Response', key="get_llama_response", help="Click to get Llama 70b response"):
        if llama_input.lower() == 'exit':
            st.success("👋 Exiting Llama 70b mode. Have a great day!")
        else:
            with st.spinner("⌛ Getting response from Llama 70b. Please wait..."):
                # Make a prediction using Llama 70b API
                llama_result = client.predict(
                    llama_input,
                    api_name="/chat"
                )

                # Check if the result is not None
                if llama_result is not None:
                    # Display the result
                    st.subheader("🦙 Llama 70b Response")
                    st.write(llama_result)
                else:
                    st.warning("⚠️ Llama 70b API response was None. Please try again later.")

# Show live view count
st.sidebar.markdown("---")
st.sidebar.subheader("👀 Live View Count:")
st.sidebar.write(view_count)

# Add a footer with updated text
st.sidebar.text("© 2023 HelpingAI")

# Hide Streamlit menu
st.markdown("""
    <style>
        #MainMenu {visibility: hidden;}
    </style>
""", unsafe_allow_html=True)