# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
#
# SPDX-License-Identifier: Apache-2.0

import os
from pathlib import Path
from typing import Any

from haystack import Document, component, logging
from haystack.components.converters.utils import get_bytestream_from_source, normalize_metadata
from haystack.dataclasses import ByteStream

logger = logging.getLogger(__name__)


@component
class TextFileToDocument:
    """
    Converts text files to documents your pipeline can query.

    By default, it uses UTF-8 encoding when converting files but
    you can also set custom encoding.
    It can attach metadata to the resulting documents.

    ### Usage example

    ```python
    from haystack.components.converters.txt import TextFileToDocument

    converter = TextFileToDocument()
    results = converter.run(sources=["sample.txt"])
    documents = results["documents"]
    print(documents[0].content)
    # 'This is the content from the txt file.'
    ```
    """

    def __init__(self, encoding: str = "utf-8", store_full_path: bool = False):
        """
        Creates a TextFileToDocument component.

        :param encoding:
            The encoding of the text files to convert.
            If the encoding is specified in the metadata of a source ByteStream,
            it overrides this value.
        :param store_full_path:
            If True, the full path of the file is stored in the metadata of the document.
            If False, only the file name is stored.
        """
        self.encoding = encoding
        self.store_full_path = store_full_path

    @component.output_types(documents=list[Document])
    def run(self, sources: list[str | Path | ByteStream], meta: dict[str, Any] | list[dict[str, Any]] | None = None):
        """
        Converts text files to documents.

        :param sources:
            List of text file paths or ByteStream objects to convert.
        :param meta:
            Optional metadata to attach to the documents.
            This value can be a list of dictionaries or a single dictionary.
            If it's a single dictionary, its content is added to the metadata of all produced documents.
            If it's a list, its length must match the number of sources as they're zipped together.
            For ByteStream objects, their `meta` is added to the output documents.

        :returns:
            A dictionary with the following keys:
            - `documents`: A list of converted documents.
        """
        documents = []

        meta_list = normalize_metadata(meta, sources_count=len(sources))

        for source, metadata in zip(sources, meta_list):
            try:
                bytestream = get_bytestream_from_source(source)
            except Exception as e:
                logger.warning("Could not read {source}. Skipping it. Error: {error}", source=source, error=e)
                continue
            try:
                encoding = bytestream.meta.get("encoding", self.encoding)
                text = bytestream.data.decode(encoding)
            except Exception as e:
                logger.warning(
                    "Could not convert file {source}. Skipping it. Error message: {error}", source=source, error=e
                )
                continue

            merged_metadata = {**bytestream.meta, **metadata}

            if not self.store_full_path and (file_path := bytestream.meta.get("file_path")):
                merged_metadata["file_path"] = os.path.basename(file_path)
            document = Document(content=text, meta=merged_metadata)
            documents.append(document)

        return {"documents": documents}
