import os
import pandas as pd
import logging
from PyPDF2 import PdfReader
from lingtrain_aligner import preprocessor, splitter, aligner, resolver, reader, vis_helper

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def pdf_to_text(pdf_path):
    text = ""
    with open(pdf_path, "rb") as file:
        reader = PdfReader(file)
        for page_num in range(len(reader.pages)):
            page = reader.pages[page_num]
            text += page.extract_text() + "\n"
    return text

def align_text(txt1: str, txt2: str, lang1: str, lang2: str) -> pd.DataFrame:
    db_path = "bilingualdata.db"
    models = ["sentence_transformer_multilingual", "sentence_transformer_multilingual_labse"]
    model_name = models[0]

    txt1 = txt1.split("\n")
    txt2 = txt2.split("\n")

    text1_prepared = preprocessor.mark_paragraphs(txt1)
    text2_prepared = preprocessor.mark_paragraphs(txt2)
    splitted_from = splitter.split_by_sentences_wrapper(text1_prepared, lang1)
    splitted_to = splitter.split_by_sentences_wrapper(text2_prepared, lang2)

    if os.path.isfile(db_path):
        os.unlink(db_path)

    aligner.fill_db(db_path, lang1, lang2, splitted_from, splitted_to)
    batch_ids = [0, 1]

    aligner.align_db(db_path,
                     model_name,
                     batch_size=100,
                     window=40,
                     batch_ids=batch_ids,
                     save_pic=False,
                     embed_batch_size=10,
                     normalize_embeddings=True,
                     show_progress_bar=True)

    conflicts_to_solve, rest = resolver.get_all_conflicts(db_path, min_chain_length=2, max_conflicts_len=6, batch_id=-1)
    resolver.get_statistics(conflicts_to_solve)
    resolver.get_statistics(rest)

    steps = 3
    batch_id = -1

    for i in range(steps):
        conflicts, rest = resolver.get_all_conflicts(db_path, min_chain_length=2 + i, max_conflicts_len=6 * (i + 1), batch_id=batch_id)
        resolver.resolve_all_conflicts(db_path, conflicts, model_name, show_logs=False)
        #vis_helper.visualize_alignment_by_db(db_path, output_path="img_test1.png", lang_name_from=lang1, lang_name_to=lang2, batch_size=400, size=(600, 600), plt_show=True)

        if len(rest) == 0:
            break

    paragraphs_dict, par_ids, meta_info, sent_counter_dict = reader.get_paragraphs(db_path)
    
    # Log the keys of paragraphs_dict
    logger.info(f"paragraphs_dict keys: {paragraphs_dict.keys()}")

    paragraphs_from = paragraphs_dict["from"]
    paragraphs_to = paragraphs_dict["to"]

    data = []
    for from_paragraph, to_paragraph in zip(paragraphs_from, paragraphs_to):
        if isinstance(from_paragraph, int) or isinstance(to_paragraph, int):
            logger.warning(f"from_paragraph: {from_paragraph}, to_paragraph: {to_paragraph}")
            continue
        for from_line, to_line in zip(from_paragraph, to_paragraph):
            data.append({"From": from_line, "To": to_line})

    df = pd.DataFrame(data)
    return df
    
def save_to_excel(df, file_name: str):
    df.to_excel(file_name, index=False)