import streamlit as st
from typing import Union, List
import pandas as pd
from io import BytesIO
import json
import os
from application.utils import logger

logger = logger.get_logger()

PAGE_TITLE = "PDF Extractor"
PAGE_LAYOUT = "wide"
# PAGE_ICON = "src/frontend/images/page_icon.jpg"
# GITHUB_LINK = "https://github.com/Vela-Test1993/yuvabe-care-companion-ai"
# ABOUT_US = "An AI-powered assistant for personalized healthcare guidance."


def config_homepage(page_title=PAGE_TITLE):
    """
    Configures the Streamlit homepage with essential settings.

    This function sets up the page title, icon, layout, and sidebar state.
    It also defines custom menu items for better navigation.

    Args:
        page_title (str): The title displayed on the browser tab (default is PAGE_TITLE).

    Key Features:
    - Ensures `st.set_page_config()` is called only once to avoid errors.
    - Uses constants for improved maintainability and consistency.
    - Provides links for help, bug reporting, and an 'About' section.

    Example:
        >>> config_homepage("My Custom App")
    """
    if "page_config_set" not in st.session_state:
        st.set_page_config(
            page_title=page_title,
            # page_icon=PAGE_ICON,
            layout=PAGE_LAYOUT,
            initial_sidebar_state="collapsed",
            # menu_items={
            #     "Get help": GITHUB_LINK,
            #     "Report a bug": GITHUB_LINK,
            #     "About": ABOUT_US
            # }
        )
        # st.session_state.page_config_set = True

def upload_file(
    file_types: Union[str, List[str]] = "pdf",
    label: str = "📤 Upload a file",
    help_text: str = "Upload your file for processing.",
    allow_multiple: bool = False,
):
    """
    Streamlit file uploader widget with options.

    Args:
        file_types (str or list): Allowed file type(s), e.g., "pdf" or ["pdf", "docx"].
        label (str): Label displayed above the uploader.
        help_text (str): Tooltip help text.
        allow_multiple (bool): Allow multiple file uploads.

    Returns:
        Uploaded file(s): A single file object or a list of file objects.
    """
    if isinstance(file_types, str):
        file_types = [file_types]

    uploaded_files = st.file_uploader(
        label=label,
        type=file_types,
        help=help_text,
        accept_multiple_files=allow_multiple
    )

    if st.button("Submit"):
        st.session_state.pdf_file = uploaded_files
        return uploaded_files

def export_results_to_excel(results: dict, sheet_name: str, filename: str = "output.xlsx") -> BytesIO:
    """
    Converts a dictionary result into a formatted Excel file.
    Appends to a file in the 'data/' folder if it already exists,
    and returns an in-memory Excel file for download.

    Args:
        results (dict): The data to export.
        sheet_name (str): The sheet name to write to.
        filename (str): The Excel file name (with or without '.xlsx').

    Returns:
        BytesIO: In-memory Excel file for Streamlit download.
    """
    try:
        df = pd.json_normalize(results, sep='_')
        df.replace({None: "", "NULL": ""}, inplace=True)
    except Exception as e:
        df = pd.DataFrame([{"error": f"Could not parse result: {str(e)}"}])

    # Ensure correct file extension and path
    filename = f"{filename}.xlsx" if not filename.endswith(".xlsx") else filename
    full_path = os.path.join("data", filename)

    os.makedirs("data", exist_ok=True)  # Ensure the folder exists

    # Save to physical file
    if os.path.exists(full_path):
        with pd.ExcelWriter(full_path, engine="openpyxl", mode="a", if_sheet_exists="overlay") as writer:
            book = writer.book
            if sheet_name in book.sheetnames:
                sheet = book[sheet_name]
                start_row = sheet.max_row
            else:
                start_row = 0
            df.to_excel(writer, sheet_name=sheet_name, index=False, header=start_row == 0, startrow=start_row)
    else:
        df.to_excel(full_path, index=False, engine="openpyxl", sheet_name=sheet_name)

    # Prepare in-memory Excel for download
    output_stream = BytesIO()
    with pd.ExcelWriter(output_stream, engine="openpyxl") as writer:
        df.to_excel(writer, index=False, sheet_name=sheet_name)
    output_stream.seek(0)

    return output_stream