from typing import Callable, Dict, List, Optional

from pathlib import Path
import re
import logging
import string 
import streamlit as st
logger = logging.getLogger(__name__)

import os
os.environ["TOKENIZERS_PARALLELISM"] = "false"

from haystack.utils import convert_files_to_docs, fetch_archive_from_http
from haystack.nodes.file_converter import BaseConverter, DocxToTextConverter 
from haystack.nodes.file_converter import PDFToTextConverter, TextConverter
from haystack.schema import Document
import pdfplumber

import pandas as pd

import tempfile
import sqlite3



def load_document(
    file_path: str,
    file_name,
    encoding: Optional[str] = None,
    id_hash_keys: Optional[List[str]] = None,
) -> List[Document]:
    
    """
    takes docx, txt and pdf files as input and \
    extracts text as well as the filename as metadata. \
    Since haystack does not take care of all pdf files, \
    pdfplumber is attached to the pipeline in case the pdf \ 
    extraction fails via Haystack.

    Returns a list of type haystack.schema.Document
    """

    if file_name.endswith('.pdf'):
        converter = PDFToTextConverter(remove_numeric_tables=True)
    if file_name.endswith('.txt'):
        converter = TextConverter()
    if file_name.endswith('.docx'):
        converter = DocxToTextConverter()


    documents = []
    logger.info("Converting {}".format(file_name))
    # PDFToTextConverter, TextConverter, and DocxToTextConverter 
    # return a list containing a single Document
    document = converter.convert(
                file_path=file_path, meta=None, 
                encoding=encoding, id_hash_keys=id_hash_keys
                )[0]
    text = document.content
    documents.append(Document(content=text, 
                              meta={"name": file_name}, 
                              id_hash_keys=id_hash_keys))
    
    '''check if text is empty and apply different pdf processor. \
    This can happen whith certain pdf types.'''
    for i in documents: 
        if i.content == "":
            st.write("using pdfplumber")
            text = []
            with pdfplumber.open(file_path) as pdf:
                for page in pdf.pages:
                    text.append(page.extract_text())
            i.content = ' '.join([page for page in text])
    
    return documents