import base64
import contextlib
import logging

from bs4 import BeautifulSoup

from configs import dify_config
from core.rag.extractor.extractor_base import BaseExtractor
from core.rag.models.document import Document

logger = logging.getLogger(__name__)


class UnstructuredEmailExtractor(BaseExtractor):
    """Load eml files.
    Args:
        file_path: Path to the file to load.
    """

    def __init__(self, file_path: str, api_url: str | None = None, api_key: str = ""):
        """Initialize with file path."""
        self._file_path = file_path
        self._api_url = api_url
        self._api_key = api_key

    def extract(self) -> list[Document]:
        if self._api_url:
            from unstructured.partition.api import partition_via_api

            elements = partition_via_api(filename=self._file_path, api_url=self._api_url, api_key=self._api_key)
        else:
            from unstructured.partition.email import partition_email

            elements = partition_email(filename=self._file_path)

        # noinspection PyBroadException
        with contextlib.suppress(Exception):
            for element in elements:
                element_text = element.text.strip()

                padding_needed = 4 - len(element_text) % 4
                element_text += "=" * padding_needed

                element_decode = base64.b64decode(element_text)
                soup = BeautifulSoup(element_decode.decode("utf-8"), "html.parser")
                element.text = soup.get_text()

        from unstructured.chunking.title import chunk_by_title

        max_characters = dify_config.INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH
        chunks = chunk_by_title(elements, max_characters=max_characters, combine_text_under_n_chars=max_characters)
        documents = []
        for chunk in chunks:
            text = chunk.text.strip()
            documents.append(Document(page_content=text))
        return documents