main.py

import streamlit as st
import pandas as pd
from pipeline import process_text_to_embeddings

st.set_page_config(page_title="📄 RAG Chatbot", layout="wide")

# init state
if "mode" not in st.session_state:
    st.session_state.mode = "upload"
if "embed_text" not in st.session_state:
    st.session_state.embed_text = None

if st.session_state.mode == "upload":
    st.markdown(
    """
    Upload your PDF and let our **Retrieval-Augmented Generation (RAG)** model  
    build an intelligent chatbot that can answer your questions directly from the document.  

    🔹 No more scrolling through pages  
    🔹 Just ask, and get answers in seconds  
    """
    )

    store_pdf = st.file_uploader("Upload PDF", type="pdf")

    if store_pdf is not None:
        with st.spinner("Processing the PDF......... Hang in there!"):
            embed_text = process_text_to_embeddings(store_pdf)
        st.success("PDF processed successfully!")
    
        if st.button("➡️ Setup ChatBot"):
            st.session_state.mode = "app"
    
elif st.session_state.mode == "app":
    st.title("🤖 Chatbot Mode")