app.py

import streamlit as st
import pandas as pd
import tempfile

from core.ingestion.docling_loader import load_and_convert_cv
from core.parsing.extractor import extract_resume
from core.processing.dataframe import resume_to_df, resume_to_dfs

st.title("📊 Resume Details Extractor")

# ---- session state init ----
if "processed" not in st.session_state:
    st.session_state.processed = False
if "dfs" not in st.session_state:
    st.session_state.dfs = None

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


if not uploaded_file:
    st.session_state.processed = False
    st.session_state.dfs = None


# ---- process only once ----
if uploaded_file and not st.session_state.processed:
    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp:
        tmp.write(uploaded_file.read())
        pdf_path = tmp.name

    text = load_and_convert_cv(pdf_path)
    data = extract_resume(text)
    dfs = resume_to_dfs(data)

    st.session_state.data = data
    st.session_state.dfs = dfs
    st.session_state.processed = True

# ---- display from session (no recompute) ----
if st.session_state.processed and st.session_state.dfs is not None:
    dfs = st.session_state.dfs
    data = st.session_state.data # Ensure data is pulled from state


    # Display other tables (Experience, Education, etc.)
    for label, df in dfs.items(): 
        st.subheader(label.replace("_", " ").title())
        st.dataframe(df, use_container_width=True)
        csv = df.to_csv(index=False).encode("utf-8")
        st.download_button(
            "Download CSV",
            data=csv,
            file_name=f"{label}.csv",
            mime="text/csv"
        )