import os
import streamlit as st
from knowledge_manager import KnowledgeManager

st.set_page_config(
    page_title="Sirraya xBrain - LangChain QA Assistant",
    layout="centered",
    page_icon="🧠",
    initial_sidebar_state="expanded",
)

st.title("🧠 Sirraya xBrain — Intelligent QA Assistant")

if "km" not in st.session_state:
    with st.spinner("Initializing knowledge base and LLM..."):
        try:
            st.session_state.km = KnowledgeManager()
            st.success("✅ Knowledge engine initialized successfully!")
            st.info(st.session_state.km.get_knowledge_summary())
        except Exception as e:
            st.error(f"❌ Failed to initialize system: {e}")
            st.session_state.km = None

if st.session_state.km is None:
    st.warning("Knowledge base not loaded or failed to initialize.")
    st.stop()

question = st.text_input("Ask a question about the knowledge base:", "")

if question:
    with st.spinner("Generating answer..."):
        answer, sources = st.session_state.km.query(question)

        st.markdown("### Answer:")
        st.write(answer)

        if sources:
            with st.expander("📚 Source documents"):
                for i, src in enumerate(sources, 1):
                    st.write(f"Source {i}:")
                    st.write(src)