import streamlit as st
import pandas as pd
from src.services import BankStatementService
from src.utils import model_manager

import asyncio


st.set_page_config(page_title="Bank Statement Analyzer", layout="wide")
st.title("📄 Bank Statement Analyzer")


async def preload_models():
    await model_manager.ensure_models_loaded()


async def process_file(uploaded_file):
    async with BankStatementService() as service:
        return await service.process_bank_statement(uploaded_file)


# Pre-load models only once
if 'models_loaded' not in st.session_state:
    st.session_state.models_loaded = False
    asyncio.run(preload_models())
    st.session_state.models_loaded = True


uploaded_file = st.file_uploader("Upload Bank Statement PDF", type=["pdf"])

if uploaded_file:
    st.info("📥 Processing uploaded file...")

    with st.spinner("Extracting data..."):
        result = asyncio.run(process_file(uploaded_file))

    if result:
        # --- Account Summary ---
        account_df = pd.DataFrame(result.account_summary.items(), columns=["Account Summary", "Data"])
        st.dataframe(account_df, use_container_width=True, hide_index=True)

        # --- Tables Section ---
        st.subheader("📊 Extracted Tables")

        for name, df in result.transaction_tables.items():
            if df.empty:
                continue
            st.markdown(f"### {name.capitalize()} Table")
            st.dataframe(df, use_container_width=True, hide_index=True)
    else:
        st.error("⚠️ Unable to parse the statement correctly.")
else:
    st.warning("📤 Please upload a PDF file to begin.")