import streamlit as st
from meta_ai_api import MetaAI

# Initialize Meta AI API
ai = MetaAI()

PAGE_CONFIG = {
    "page_title": "Meta AI Query Analysis - a Free SEO Tool by WordLift",
    "page_icon": "img/fav-ico.png",
    "layout": "centered"
}

def local_css(file_name):
    with open(file_name) as f:
        st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)


st.set_page_config(**PAGE_CONFIG)

local_css("style.css")


def fetch_response(query):
    response = ai.prompt(message=query)
    return response

def display_sources(sources):
    if sources:
        for source in sources:
            st.markdown(f"[{source['title']}]({source['link']})", unsafe_allow_html=True)
    else:
        st.write("No sources available.")

# ---------------------------------------------------------------------------- #
# Main Function
# ---------------------------------------------------------------------------- #


def main():
    st.title("Meta AI SEO Tool")

    # User input
    user_query = st.text_area("Enter your query:", height=150)
    submit_button = st.button("Analyze Query")

    if submit_button and user_query:
        # Fetching response from Meta AI
        response = fetch_response(user_query)

        st.write(response.get('message', 'No response message.'))
        
        # Display the AI response in a collapsible section
        with st.expander("Show Full Response"):
            display_sources(response.get('sources', []))
                    
if __name__ == "__main__":
    main()