All converters.
This commit is contained in:
Adam Fourney
parent
6793648d15
commit
a795a16ce0
9 changed files with 493 additions and 443 deletions
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@ -61,6 +61,11 @@ from .converters import (
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XlsConverter,
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XlsConverter,
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PptxConverter,
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PptxConverter,
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ImageConverter,
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ImageConverter,
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WavConverter,
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Mp3Converter,
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OutlookMsgConverter,
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ZipConverter,
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DocumentIntelligenceConverter,
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)
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)
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from .converters._markdownify import _CustomMarkdownify
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from .converters._markdownify import _CustomMarkdownify
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@ -71,450 +76,12 @@ from ._exceptions import (
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UnsupportedFormatException,
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UnsupportedFormatException,
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)
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)
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# TODO: currently, there is a bug in the document intelligence SDK with importing the "ContentFormat" enum.
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# This constant is a temporary fix until the bug is resolved.
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CONTENT_FORMAT = "markdown"
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# Override mimetype for csv to fix issue on windows
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# Override mimetype for csv to fix issue on windows
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mimetypes.add_type("text/csv", ".csv")
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mimetypes.add_type("text/csv", ".csv")
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PRIORITY_SPECIFIC_FILE_FORMAT = 0.0
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PRIORITY_SPECIFIC_FILE_FORMAT = 0.0
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PRIORITY_GENERIC_FILE_FORMAT = -10.0
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PRIORITY_GENERIC_FILE_FORMAT = -10.0
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# Optional Transcription support
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IS_AUDIO_TRANSCRIPTION_CAPABLE = False
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try:
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# Using warnings' catch_warnings to catch
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# pydub's warning of ffmpeg or avconv missing
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with catch_warnings(record=True) as w:
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import pydub
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if w:
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raise ModuleNotFoundError
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import speech_recognition as sr
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IS_AUDIO_TRANSCRIPTION_CAPABLE = True
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except ModuleNotFoundError:
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pass
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finally:
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resetwarnings()
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class MediaConverter(DocumentConverter):
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"""
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Abstract class for multi-modal media (e.g., images and audio)
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"""
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def _get_metadata(self, local_path, exiftool_path=None):
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if not exiftool_path:
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which_exiftool = shutil.which("exiftool")
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if which_exiftool:
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warn(
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f"""Implicit discovery of 'exiftool' is disabled. If you would like to continue to use exiftool in MarkItDown, please set the exiftool_path parameter in the MarkItDown consructor. E.g.,
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md = MarkItDown(exiftool_path="{which_exiftool}")
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This warning will be removed in future releases.
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""",
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DeprecationWarning,
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)
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return None
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else:
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try:
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result = subprocess.run(
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[exiftool_path, "-json", local_path], capture_output=True, text=True
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).stdout
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return json.loads(result)[0]
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except Exception:
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return None
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class WavConverter(MediaConverter):
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"""
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Converts WAV files to markdown via extraction of metadata (if `exiftool` is installed), and speech transcription (if `speech_recognition` is installed).
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"""
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def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
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# Bail if not a WAV
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extension = kwargs.get("file_extension", "")
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if extension.lower() != ".wav":
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return None
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md_content = ""
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# Add metadata
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metadata = self._get_metadata(local_path, kwargs.get("exiftool_path"))
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if metadata:
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for f in [
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"Title",
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"Artist",
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"Author",
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"Band",
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"Album",
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"Genre",
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"Track",
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"DateTimeOriginal",
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"CreateDate",
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"Duration",
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]:
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if f in metadata:
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md_content += f"{f}: {metadata[f]}\n"
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# Transcribe
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if IS_AUDIO_TRANSCRIPTION_CAPABLE:
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try:
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transcript = self._transcribe_audio(local_path)
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md_content += "\n\n### Audio Transcript:\n" + (
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"[No speech detected]" if transcript == "" else transcript
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)
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except Exception:
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md_content += (
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"\n\n### Audio Transcript:\nError. Could not transcribe this audio."
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)
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return DocumentConverterResult(
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title=None,
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text_content=md_content.strip(),
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)
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def _transcribe_audio(self, local_path) -> str:
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recognizer = sr.Recognizer()
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with sr.AudioFile(local_path) as source:
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audio = recognizer.record(source)
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return recognizer.recognize_google(audio).strip()
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class Mp3Converter(WavConverter):
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"""
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Converts MP3 files to markdown via extraction of metadata (if `exiftool` is installed), and speech transcription (if `speech_recognition` AND `pydub` are installed).
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"""
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def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
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# Bail if not a MP3
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extension = kwargs.get("file_extension", "")
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if extension.lower() != ".mp3":
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return None
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md_content = ""
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# Add metadata
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metadata = self._get_metadata(local_path, kwargs.get("exiftool_path"))
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if metadata:
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for f in [
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"Title",
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"Artist",
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"Author",
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"Band",
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"Album",
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"Genre",
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"Track",
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"DateTimeOriginal",
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"CreateDate",
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"Duration",
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]:
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if f in metadata:
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md_content += f"{f}: {metadata[f]}\n"
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# Transcribe
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if IS_AUDIO_TRANSCRIPTION_CAPABLE:
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handle, temp_path = tempfile.mkstemp(suffix=".wav")
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os.close(handle)
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try:
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sound = pydub.AudioSegment.from_mp3(local_path)
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sound.export(temp_path, format="wav")
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_args = dict()
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_args.update(kwargs)
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_args["file_extension"] = ".wav"
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try:
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transcript = super()._transcribe_audio(temp_path).strip()
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md_content += "\n\n### Audio Transcript:\n" + (
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"[No speech detected]" if transcript == "" else transcript
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)
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except Exception:
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md_content += "\n\n### Audio Transcript:\nError. Could not transcribe this audio."
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finally:
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os.unlink(temp_path)
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# Return the result
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return DocumentConverterResult(
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title=None,
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text_content=md_content.strip(),
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)
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class OutlookMsgConverter(DocumentConverter):
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"""Converts Outlook .msg files to markdown by extracting email metadata and content.
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Uses the olefile package to parse the .msg file structure and extract:
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- Email headers (From, To, Subject)
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- Email body content
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"""
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def convert(
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self, local_path: str, **kwargs: Any
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) -> Union[None, DocumentConverterResult]:
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# Bail if not a MSG file
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extension = kwargs.get("file_extension", "")
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if extension.lower() != ".msg":
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return None
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try:
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msg = olefile.OleFileIO(local_path)
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# Extract email metadata
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md_content = "# Email Message\n\n"
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# Get headers
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headers = {
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"From": self._get_stream_data(msg, "__substg1.0_0C1F001F"),
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"To": self._get_stream_data(msg, "__substg1.0_0E04001F"),
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"Subject": self._get_stream_data(msg, "__substg1.0_0037001F"),
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}
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# Add headers to markdown
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for key, value in headers.items():
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if value:
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md_content += f"**{key}:** {value}\n"
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md_content += "\n## Content\n\n"
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# Get email body
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body = self._get_stream_data(msg, "__substg1.0_1000001F")
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if body:
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md_content += body
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msg.close()
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return DocumentConverterResult(
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title=headers.get("Subject"), text_content=md_content.strip()
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)
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except Exception as e:
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raise FileConversionException(
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f"Could not convert MSG file '{local_path}': {str(e)}"
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)
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def _get_stream_data(
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self, msg: olefile.OleFileIO, stream_path: str
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) -> Union[str, None]:
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"""Helper to safely extract and decode stream data from the MSG file."""
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try:
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if msg.exists(stream_path):
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data = msg.openstream(stream_path).read()
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# Try UTF-16 first (common for .msg files)
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try:
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return data.decode("utf-16-le").strip()
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except UnicodeDecodeError:
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# Fall back to UTF-8
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try:
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return data.decode("utf-8").strip()
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except UnicodeDecodeError:
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# Last resort - ignore errors
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return data.decode("utf-8", errors="ignore").strip()
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except Exception:
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pass
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return None
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class ZipConverter(DocumentConverter):
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"""Converts ZIP files to markdown by extracting and converting all contained files.
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The converter extracts the ZIP contents to a temporary directory, processes each file
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using appropriate converters based on file extensions, and then combines the results
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into a single markdown document. The temporary directory is cleaned up after processing.
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Example output format:
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```markdown
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Content from the zip file `example.zip`:
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## File: docs/readme.txt
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This is the content of readme.txt
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Multiple lines are preserved
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## File: images/example.jpg
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ImageSize: 1920x1080
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DateTimeOriginal: 2024-02-15 14:30:00
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Description: A beautiful landscape photo
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## File: data/report.xlsx
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## Sheet1
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| Column1 | Column2 | Column3 |
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|---------|---------|---------|
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| data1 | data2 | data3 |
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| data4 | data5 | data6 |
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```
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Key features:
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- Maintains original file structure in headings
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- Processes nested files recursively
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- Uses appropriate converters for each file type
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- Preserves formatting of converted content
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- Cleans up temporary files after processing
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"""
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def convert(
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self, local_path: str, **kwargs: Any
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) -> Union[None, DocumentConverterResult]:
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# Bail if not a ZIP
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extension = kwargs.get("file_extension", "")
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if extension.lower() != ".zip":
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return None
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# Get parent converters list if available
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parent_converters = kwargs.get("_parent_converters", [])
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if not parent_converters:
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return DocumentConverterResult(
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title=None,
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text_content=f"[ERROR] No converters available to process zip contents from: {local_path}",
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)
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extracted_zip_folder_name = (
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f"extracted_{os.path.basename(local_path).replace('.zip', '_zip')}"
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)
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extraction_dir = os.path.normpath(
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os.path.join(os.path.dirname(local_path), extracted_zip_folder_name)
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)
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md_content = f"Content from the zip file `{os.path.basename(local_path)}`:\n\n"
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try:
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# Extract the zip file safely
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with zipfile.ZipFile(local_path, "r") as zipObj:
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# Safeguard against path traversal
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for member in zipObj.namelist():
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member_path = os.path.normpath(os.path.join(extraction_dir, member))
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if (
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not os.path.commonprefix([extraction_dir, member_path])
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== extraction_dir
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):
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raise ValueError(
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f"Path traversal detected in zip file: {member}"
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)
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# Extract all files safely
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zipObj.extractall(path=extraction_dir)
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# Process each extracted file
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for root, dirs, files in os.walk(extraction_dir):
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for name in files:
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file_path = os.path.join(root, name)
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relative_path = os.path.relpath(file_path, extraction_dir)
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# Get file extension
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_, file_extension = os.path.splitext(name)
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# Update kwargs for the file
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file_kwargs = kwargs.copy()
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file_kwargs["file_extension"] = file_extension
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file_kwargs["_parent_converters"] = parent_converters
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# Try converting the file using available converters
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for converter in parent_converters:
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# Skip the zip converter to avoid infinite recursion
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if isinstance(converter, ZipConverter):
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continue
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result = converter.convert(file_path, **file_kwargs)
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if result is not None:
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md_content += f"\n## File: {relative_path}\n\n"
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md_content += result.text_content + "\n\n"
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break
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# Clean up extracted files if specified
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if kwargs.get("cleanup_extracted", True):
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shutil.rmtree(extraction_dir)
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return DocumentConverterResult(title=None, text_content=md_content.strip())
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except zipfile.BadZipFile:
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return DocumentConverterResult(
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title=None,
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text_content=f"[ERROR] Invalid or corrupted zip file: {local_path}",
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)
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except ValueError as ve:
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return DocumentConverterResult(
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title=None,
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text_content=f"[ERROR] Security error in zip file {local_path}: {str(ve)}",
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)
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except Exception as e:
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return DocumentConverterResult(
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title=None,
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text_content=f"[ERROR] Failed to process zip file {local_path}: {str(e)}",
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)
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class DocumentIntelligenceConverter(DocumentConverter):
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"""Specialized DocumentConverter that uses Document Intelligence to extract text from documents."""
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def __init__(
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self,
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endpoint: str,
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api_version: str = "2024-07-31-preview",
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):
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self.endpoint = endpoint
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self.api_version = api_version
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self.doc_intel_client = DocumentIntelligenceClient(
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endpoint=self.endpoint,
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api_version=self.api_version,
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|
||||||
credential=DefaultAzureCredential(),
|
|
||||||
)
|
|
||||||
|
|
||||||
def convert(
|
|
||||||
self, local_path: str, **kwargs: Any
|
|
||||||
) -> Union[None, DocumentConverterResult]:
|
|
||||||
# Bail if extension is not supported by Document Intelligence
|
|
||||||
extension = kwargs.get("file_extension", "")
|
|
||||||
docintel_extensions = [
|
|
||||||
".pdf",
|
|
||||||
".docx",
|
|
||||||
".xlsx",
|
|
||||||
".pptx",
|
|
||||||
".html",
|
|
||||||
".jpeg",
|
|
||||||
".jpg",
|
|
||||||
".png",
|
|
||||||
".bmp",
|
|
||||||
".tiff",
|
|
||||||
".heif",
|
|
||||||
]
|
|
||||||
if extension.lower() not in docintel_extensions:
|
|
||||||
return None
|
|
||||||
|
|
||||||
# Get the bytestring for the local path
|
|
||||||
with open(local_path, "rb") as f:
|
|
||||||
file_bytes = f.read()
|
|
||||||
|
|
||||||
# Certain document analysis features are not availiable for filetypes (.xlsx, .pptx, .html)
|
|
||||||
if extension.lower() in [".xlsx", ".pptx", ".html"]:
|
|
||||||
analysis_features = []
|
|
||||||
else:
|
|
||||||
analysis_features = [
|
|
||||||
DocumentAnalysisFeature.FORMULAS, # enable formula extraction
|
|
||||||
DocumentAnalysisFeature.OCR_HIGH_RESOLUTION, # enable high resolution OCR
|
|
||||||
DocumentAnalysisFeature.STYLE_FONT, # enable font style extraction
|
|
||||||
]
|
|
||||||
|
|
||||||
# Extract the text using Azure Document Intelligence
|
|
||||||
poller = self.doc_intel_client.begin_analyze_document(
|
|
||||||
model_id="prebuilt-layout",
|
|
||||||
body=AnalyzeDocumentRequest(bytes_source=file_bytes),
|
|
||||||
features=analysis_features,
|
|
||||||
output_content_format=CONTENT_FORMAT, # TODO: replace with "ContentFormat.MARKDOWN" when the bug is fixed
|
|
||||||
)
|
|
||||||
result: AnalyzeResult = poller.result()
|
|
||||||
|
|
||||||
# remove comments from the markdown content generated by Doc Intelligence and append to markdown string
|
|
||||||
markdown_text = re.sub(r"<!--.*?-->", "", result.content, flags=re.DOTALL)
|
|
||||||
return DocumentConverterResult(
|
|
||||||
title=None,
|
|
||||||
text_content=markdown_text,
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
class MarkItDown:
|
class MarkItDown:
|
||||||
"""(In preview) An extremely simple text-based document reader, suitable for LLM use.
|
"""(In preview) An extremely simple text-based document reader, suitable for LLM use.
|
||||||
|
|
@ -800,10 +367,11 @@ class MarkItDown:
|
||||||
_kwargs["_parent_converters"] = self._page_converters
|
_kwargs["_parent_converters"] = self._page_converters
|
||||||
|
|
||||||
# If we hit an error log it and keep trying
|
# If we hit an error log it and keep trying
|
||||||
try:
|
# try:
|
||||||
|
if True:
|
||||||
res = converter.convert(local_path, **_kwargs)
|
res = converter.convert(local_path, **_kwargs)
|
||||||
except Exception:
|
# except Exception:
|
||||||
error_trace = ("\n\n" + traceback.format_exc()).strip()
|
# error_trace = ("\n\n" + traceback.format_exc()).strip()
|
||||||
|
|
||||||
if res is not None:
|
if res is not None:
|
||||||
# Normalize the content
|
# Normalize the content
|
||||||
|
|
|
||||||
|
|
@ -15,6 +15,11 @@ from ._docx_converter import DocxConverter
|
||||||
from ._xlsx_converter import XlsxConverter, XlsConverter
|
from ._xlsx_converter import XlsxConverter, XlsConverter
|
||||||
from ._pptx_converter import PptxConverter
|
from ._pptx_converter import PptxConverter
|
||||||
from ._image_converter import ImageConverter
|
from ._image_converter import ImageConverter
|
||||||
|
from ._wav_converter import WavConverter
|
||||||
|
from ._mp3_converter import Mp3Converter
|
||||||
|
from ._outlook_msg_converter import OutlookMsgConverter
|
||||||
|
from ._zip_converter import ZipConverter
|
||||||
|
from ._doc_intel_converter import DocumentIntelligenceConverter
|
||||||
|
|
||||||
__all__ = [
|
__all__ = [
|
||||||
"DocumentConverter",
|
"DocumentConverter",
|
||||||
|
|
@ -32,4 +37,9 @@ __all__ = [
|
||||||
"XlsConverter",
|
"XlsConverter",
|
||||||
"PptxConverter",
|
"PptxConverter",
|
||||||
"ImageConverter",
|
"ImageConverter",
|
||||||
|
"WavConverter",
|
||||||
|
"Mp3Converter",
|
||||||
|
"OutlookMsgConverter",
|
||||||
|
"ZipConverter",
|
||||||
|
"DocumentIntelligenceConverter",
|
||||||
]
|
]
|
||||||
|
|
|
||||||
91
src/markitdown/converters/_doc_intel_converter.py
Normal file
91
src/markitdown/converters/_doc_intel_converter.py
Normal file
|
|
@ -0,0 +1,91 @@
|
||||||
|
from typing import Any, Union
|
||||||
|
|
||||||
|
# Azure imports
|
||||||
|
from azure.ai.documentintelligence import DocumentIntelligenceClient
|
||||||
|
from azure.ai.documentintelligence.models import (
|
||||||
|
AnalyzeDocumentRequest,
|
||||||
|
AnalyzeResult,
|
||||||
|
DocumentAnalysisFeature,
|
||||||
|
)
|
||||||
|
from azure.identity import DefaultAzureCredential
|
||||||
|
|
||||||
|
from ._base import DocumentConverter, DocumentConverterResult
|
||||||
|
|
||||||
|
from .._exceptions import (
|
||||||
|
MarkItDownException,
|
||||||
|
ConverterPrerequisiteException,
|
||||||
|
FileConversionException,
|
||||||
|
UnsupportedFormatException,
|
||||||
|
)
|
||||||
|
|
||||||
|
# TODO: currently, there is a bug in the document intelligence SDK with importing the "ContentFormat" enum.
|
||||||
|
# This constant is a temporary fix until the bug is resolved.
|
||||||
|
CONTENT_FORMAT = "markdown"
|
||||||
|
|
||||||
|
|
||||||
|
class DocumentIntelligenceConverter(DocumentConverter):
|
||||||
|
"""Specialized DocumentConverter that uses Document Intelligence to extract text from documents."""
|
||||||
|
|
||||||
|
def __init__(
|
||||||
|
self,
|
||||||
|
endpoint: str,
|
||||||
|
api_version: str = "2024-07-31-preview",
|
||||||
|
):
|
||||||
|
self.endpoint = endpoint
|
||||||
|
self.api_version = api_version
|
||||||
|
self.doc_intel_client = DocumentIntelligenceClient(
|
||||||
|
endpoint=self.endpoint,
|
||||||
|
api_version=self.api_version,
|
||||||
|
credential=DefaultAzureCredential(),
|
||||||
|
)
|
||||||
|
|
||||||
|
def convert(
|
||||||
|
self, local_path: str, **kwargs: Any
|
||||||
|
) -> Union[None, DocumentConverterResult]:
|
||||||
|
# Bail if extension is not supported by Document Intelligence
|
||||||
|
extension = kwargs.get("file_extension", "")
|
||||||
|
docintel_extensions = [
|
||||||
|
".pdf",
|
||||||
|
".docx",
|
||||||
|
".xlsx",
|
||||||
|
".pptx",
|
||||||
|
".html",
|
||||||
|
".jpeg",
|
||||||
|
".jpg",
|
||||||
|
".png",
|
||||||
|
".bmp",
|
||||||
|
".tiff",
|
||||||
|
".heif",
|
||||||
|
]
|
||||||
|
if extension.lower() not in docintel_extensions:
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Get the bytestring for the local path
|
||||||
|
with open(local_path, "rb") as f:
|
||||||
|
file_bytes = f.read()
|
||||||
|
|
||||||
|
# Certain document analysis features are not availiable for filetypes (.xlsx, .pptx, .html)
|
||||||
|
if extension.lower() in [".xlsx", ".pptx", ".html"]:
|
||||||
|
analysis_features = []
|
||||||
|
else:
|
||||||
|
analysis_features = [
|
||||||
|
DocumentAnalysisFeature.FORMULAS, # enable formula extraction
|
||||||
|
DocumentAnalysisFeature.OCR_HIGH_RESOLUTION, # enable high resolution OCR
|
||||||
|
DocumentAnalysisFeature.STYLE_FONT, # enable font style extraction
|
||||||
|
]
|
||||||
|
|
||||||
|
# Extract the text using Azure Document Intelligence
|
||||||
|
poller = self.doc_intel_client.begin_analyze_document(
|
||||||
|
model_id="prebuilt-layout",
|
||||||
|
body=AnalyzeDocumentRequest(bytes_source=file_bytes),
|
||||||
|
features=analysis_features,
|
||||||
|
output_content_format=CONTENT_FORMAT, # TODO: replace with "ContentFormat.MARKDOWN" when the bug is fixed
|
||||||
|
)
|
||||||
|
result: AnalyzeResult = poller.result()
|
||||||
|
|
||||||
|
# remove comments from the markdown content generated by Doc Intelligence and append to markdown string
|
||||||
|
markdown_text = re.sub(r"<!--.*?-->", "", result.content, flags=re.DOTALL)
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=None,
|
||||||
|
text_content=markdown_text,
|
||||||
|
)
|
||||||
|
|
@ -6,6 +6,8 @@ from ._base import (
|
||||||
DocumentConverterResult,
|
DocumentConverterResult,
|
||||||
)
|
)
|
||||||
|
|
||||||
|
from .._exceptions import FileConversionException
|
||||||
|
|
||||||
|
|
||||||
class IpynbConverter(DocumentConverter):
|
class IpynbConverter(DocumentConverter):
|
||||||
"""Converts Jupyter Notebook (.ipynb) files to Markdown."""
|
"""Converts Jupyter Notebook (.ipynb) files to Markdown."""
|
||||||
|
|
|
||||||
84
src/markitdown/converters/_mp3_converter.py
Normal file
84
src/markitdown/converters/_mp3_converter.py
Normal file
|
|
@ -0,0 +1,84 @@
|
||||||
|
import tempfile
|
||||||
|
from typing import Any, Dict, List, Optional, Union
|
||||||
|
from ._base import DocumentConverter, DocumentConverterResult
|
||||||
|
from ._wav_converter import WavConverter
|
||||||
|
from warnings import warn, resetwarnings, catch_warnings
|
||||||
|
|
||||||
|
# Optional Transcription support
|
||||||
|
IS_AUDIO_TRANSCRIPTION_CAPABLE = False
|
||||||
|
try:
|
||||||
|
# Using warnings' catch_warnings to catch
|
||||||
|
# pydub's warning of ffmpeg or avconv missing
|
||||||
|
with catch_warnings(record=True) as w:
|
||||||
|
import pydub
|
||||||
|
|
||||||
|
if w:
|
||||||
|
raise ModuleNotFoundError
|
||||||
|
import speech_recognition as sr
|
||||||
|
|
||||||
|
IS_AUDIO_TRANSCRIPTION_CAPABLE = True
|
||||||
|
except ModuleNotFoundError:
|
||||||
|
pass
|
||||||
|
finally:
|
||||||
|
resetwarnings()
|
||||||
|
|
||||||
|
|
||||||
|
class Mp3Converter(WavConverter):
|
||||||
|
"""
|
||||||
|
Converts MP3 files to markdown via extraction of metadata (if `exiftool` is installed), and speech transcription (if `speech_recognition` AND `pydub` are installed).
|
||||||
|
"""
|
||||||
|
|
||||||
|
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
|
||||||
|
# Bail if not a MP3
|
||||||
|
extension = kwargs.get("file_extension", "")
|
||||||
|
if extension.lower() != ".mp3":
|
||||||
|
return None
|
||||||
|
|
||||||
|
md_content = ""
|
||||||
|
|
||||||
|
# Add metadata
|
||||||
|
metadata = self._get_metadata(local_path, kwargs.get("exiftool_path"))
|
||||||
|
if metadata:
|
||||||
|
for f in [
|
||||||
|
"Title",
|
||||||
|
"Artist",
|
||||||
|
"Author",
|
||||||
|
"Band",
|
||||||
|
"Album",
|
||||||
|
"Genre",
|
||||||
|
"Track",
|
||||||
|
"DateTimeOriginal",
|
||||||
|
"CreateDate",
|
||||||
|
"Duration",
|
||||||
|
]:
|
||||||
|
if f in metadata:
|
||||||
|
md_content += f"{f}: {metadata[f]}\n"
|
||||||
|
|
||||||
|
# Transcribe
|
||||||
|
if IS_AUDIO_TRANSCRIPTION_CAPABLE:
|
||||||
|
handle, temp_path = tempfile.mkstemp(suffix=".wav")
|
||||||
|
os.close(handle)
|
||||||
|
try:
|
||||||
|
sound = pydub.AudioSegment.from_mp3(local_path)
|
||||||
|
sound.export(temp_path, format="wav")
|
||||||
|
|
||||||
|
_args = dict()
|
||||||
|
_args.update(kwargs)
|
||||||
|
_args["file_extension"] = ".wav"
|
||||||
|
|
||||||
|
try:
|
||||||
|
transcript = super()._transcribe_audio(temp_path).strip()
|
||||||
|
md_content += "\n\n### Audio Transcript:\n" + (
|
||||||
|
"[No speech detected]" if transcript == "" else transcript
|
||||||
|
)
|
||||||
|
except Exception:
|
||||||
|
md_content += "\n\n### Audio Transcript:\nError. Could not transcribe this audio."
|
||||||
|
|
||||||
|
finally:
|
||||||
|
os.unlink(temp_path)
|
||||||
|
|
||||||
|
# Return the result
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=None,
|
||||||
|
text_content=md_content.strip(),
|
||||||
|
)
|
||||||
76
src/markitdown/converters/_outlook_msg_converter.py
Normal file
76
src/markitdown/converters/_outlook_msg_converter.py
Normal file
|
|
@ -0,0 +1,76 @@
|
||||||
|
import olefile
|
||||||
|
from typing import Any, Union
|
||||||
|
from ._base import DocumentConverter, DocumentConverterResult
|
||||||
|
|
||||||
|
|
||||||
|
class OutlookMsgConverter(DocumentConverter):
|
||||||
|
"""Converts Outlook .msg files to markdown by extracting email metadata and content.
|
||||||
|
|
||||||
|
Uses the olefile package to parse the .msg file structure and extract:
|
||||||
|
- Email headers (From, To, Subject)
|
||||||
|
- Email body content
|
||||||
|
"""
|
||||||
|
|
||||||
|
def convert(
|
||||||
|
self, local_path: str, **kwargs: Any
|
||||||
|
) -> Union[None, DocumentConverterResult]:
|
||||||
|
# Bail if not a MSG file
|
||||||
|
extension = kwargs.get("file_extension", "")
|
||||||
|
if extension.lower() != ".msg":
|
||||||
|
return None
|
||||||
|
|
||||||
|
try:
|
||||||
|
msg = olefile.OleFileIO(local_path)
|
||||||
|
# Extract email metadata
|
||||||
|
md_content = "# Email Message\n\n"
|
||||||
|
|
||||||
|
# Get headers
|
||||||
|
headers = {
|
||||||
|
"From": self._get_stream_data(msg, "__substg1.0_0C1F001F"),
|
||||||
|
"To": self._get_stream_data(msg, "__substg1.0_0E04001F"),
|
||||||
|
"Subject": self._get_stream_data(msg, "__substg1.0_0037001F"),
|
||||||
|
}
|
||||||
|
|
||||||
|
# Add headers to markdown
|
||||||
|
for key, value in headers.items():
|
||||||
|
if value:
|
||||||
|
md_content += f"**{key}:** {value}\n"
|
||||||
|
|
||||||
|
md_content += "\n## Content\n\n"
|
||||||
|
|
||||||
|
# Get email body
|
||||||
|
body = self._get_stream_data(msg, "__substg1.0_1000001F")
|
||||||
|
if body:
|
||||||
|
md_content += body
|
||||||
|
|
||||||
|
msg.close()
|
||||||
|
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=headers.get("Subject"), text_content=md_content.strip()
|
||||||
|
)
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
raise FileConversionException(
|
||||||
|
f"Could not convert MSG file '{local_path}': {str(e)}"
|
||||||
|
)
|
||||||
|
|
||||||
|
def _get_stream_data(
|
||||||
|
self, msg: olefile.OleFileIO, stream_path: str
|
||||||
|
) -> Union[str, None]:
|
||||||
|
"""Helper to safely extract and decode stream data from the MSG file."""
|
||||||
|
try:
|
||||||
|
if msg.exists(stream_path):
|
||||||
|
data = msg.openstream(stream_path).read()
|
||||||
|
# Try UTF-16 first (common for .msg files)
|
||||||
|
try:
|
||||||
|
return data.decode("utf-16-le").strip()
|
||||||
|
except UnicodeDecodeError:
|
||||||
|
# Fall back to UTF-8
|
||||||
|
try:
|
||||||
|
return data.decode("utf-8").strip()
|
||||||
|
except UnicodeDecodeError:
|
||||||
|
# Last resort - ignore errors
|
||||||
|
return data.decode("utf-8", errors="ignore").strip()
|
||||||
|
except Exception:
|
||||||
|
pass
|
||||||
|
return None
|
||||||
77
src/markitdown/converters/_wav_converter.py
Normal file
77
src/markitdown/converters/_wav_converter.py
Normal file
|
|
@ -0,0 +1,77 @@
|
||||||
|
from typing import Union
|
||||||
|
from ._base import DocumentConverter, DocumentConverterResult
|
||||||
|
from ._media_converter import MediaConverter
|
||||||
|
from warnings import warn, resetwarnings, catch_warnings
|
||||||
|
|
||||||
|
# Optional Transcription support
|
||||||
|
IS_AUDIO_TRANSCRIPTION_CAPABLE = False
|
||||||
|
try:
|
||||||
|
# Using warnings' catch_warnings to catch
|
||||||
|
# pydub's warning of ffmpeg or avconv missing
|
||||||
|
with catch_warnings(record=True) as w:
|
||||||
|
import pydub
|
||||||
|
|
||||||
|
if w:
|
||||||
|
raise ModuleNotFoundError
|
||||||
|
import speech_recognition as sr
|
||||||
|
|
||||||
|
IS_AUDIO_TRANSCRIPTION_CAPABLE = True
|
||||||
|
except ModuleNotFoundError:
|
||||||
|
pass
|
||||||
|
finally:
|
||||||
|
resetwarnings()
|
||||||
|
|
||||||
|
|
||||||
|
class WavConverter(MediaConverter):
|
||||||
|
"""
|
||||||
|
Converts WAV files to markdown via extraction of metadata (if `exiftool` is installed), and speech transcription (if `speech_recognition` is installed).
|
||||||
|
"""
|
||||||
|
|
||||||
|
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
|
||||||
|
# Bail if not a WAV
|
||||||
|
extension = kwargs.get("file_extension", "")
|
||||||
|
if extension.lower() != ".wav":
|
||||||
|
return None
|
||||||
|
|
||||||
|
md_content = ""
|
||||||
|
|
||||||
|
# Add metadata
|
||||||
|
metadata = self._get_metadata(local_path, kwargs.get("exiftool_path"))
|
||||||
|
if metadata:
|
||||||
|
for f in [
|
||||||
|
"Title",
|
||||||
|
"Artist",
|
||||||
|
"Author",
|
||||||
|
"Band",
|
||||||
|
"Album",
|
||||||
|
"Genre",
|
||||||
|
"Track",
|
||||||
|
"DateTimeOriginal",
|
||||||
|
"CreateDate",
|
||||||
|
"Duration",
|
||||||
|
]:
|
||||||
|
if f in metadata:
|
||||||
|
md_content += f"{f}: {metadata[f]}\n"
|
||||||
|
|
||||||
|
# Transcribe
|
||||||
|
if IS_AUDIO_TRANSCRIPTION_CAPABLE:
|
||||||
|
try:
|
||||||
|
transcript = self._transcribe_audio(local_path)
|
||||||
|
md_content += "\n\n### Audio Transcript:\n" + (
|
||||||
|
"[No speech detected]" if transcript == "" else transcript
|
||||||
|
)
|
||||||
|
except Exception:
|
||||||
|
md_content += (
|
||||||
|
"\n\n### Audio Transcript:\nError. Could not transcribe this audio."
|
||||||
|
)
|
||||||
|
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=None,
|
||||||
|
text_content=md_content.strip(),
|
||||||
|
)
|
||||||
|
|
||||||
|
def _transcribe_audio(self, local_path) -> str:
|
||||||
|
recognizer = sr.Recognizer()
|
||||||
|
with sr.AudioFile(local_path) as source:
|
||||||
|
audio = recognizer.record(source)
|
||||||
|
return recognizer.recognize_google(audio).strip()
|
||||||
|
|
@ -1,8 +1,8 @@
|
||||||
from typing import Any, Dict, List, Optional, Union
|
from typing import Union
|
||||||
|
|
||||||
import pandas as pd
|
import pandas as pd
|
||||||
|
|
||||||
from ._base import DocumentConverter, DocumentConverterResult
|
from ._base import DocumentConverterResult
|
||||||
from ._html_converter import HtmlConverter
|
from ._html_converter import HtmlConverter
|
||||||
|
|
||||||
|
|
||||||
|
|
|
||||||
142
src/markitdown/converters/_zip_converter.py
Normal file
142
src/markitdown/converters/_zip_converter.py
Normal file
|
|
@ -0,0 +1,142 @@
|
||||||
|
import os
|
||||||
|
import zipfile
|
||||||
|
import shutil
|
||||||
|
from typing import Any, Union
|
||||||
|
|
||||||
|
from ._base import DocumentConverter, DocumentConverterResult
|
||||||
|
|
||||||
|
from .._exceptions import (
|
||||||
|
MarkItDownException,
|
||||||
|
ConverterPrerequisiteException,
|
||||||
|
FileConversionException,
|
||||||
|
UnsupportedFormatException,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
class ZipConverter(DocumentConverter):
|
||||||
|
"""Converts ZIP files to markdown by extracting and converting all contained files.
|
||||||
|
|
||||||
|
The converter extracts the ZIP contents to a temporary directory, processes each file
|
||||||
|
using appropriate converters based on file extensions, and then combines the results
|
||||||
|
into a single markdown document. The temporary directory is cleaned up after processing.
|
||||||
|
|
||||||
|
Example output format:
|
||||||
|
```markdown
|
||||||
|
Content from the zip file `example.zip`:
|
||||||
|
|
||||||
|
## File: docs/readme.txt
|
||||||
|
|
||||||
|
This is the content of readme.txt
|
||||||
|
Multiple lines are preserved
|
||||||
|
|
||||||
|
## File: images/example.jpg
|
||||||
|
|
||||||
|
ImageSize: 1920x1080
|
||||||
|
DateTimeOriginal: 2024-02-15 14:30:00
|
||||||
|
Description: A beautiful landscape photo
|
||||||
|
|
||||||
|
## File: data/report.xlsx
|
||||||
|
|
||||||
|
## Sheet1
|
||||||
|
| Column1 | Column2 | Column3 |
|
||||||
|
|---------|---------|---------|
|
||||||
|
| data1 | data2 | data3 |
|
||||||
|
| data4 | data5 | data6 |
|
||||||
|
```
|
||||||
|
|
||||||
|
Key features:
|
||||||
|
- Maintains original file structure in headings
|
||||||
|
- Processes nested files recursively
|
||||||
|
- Uses appropriate converters for each file type
|
||||||
|
- Preserves formatting of converted content
|
||||||
|
- Cleans up temporary files after processing
|
||||||
|
"""
|
||||||
|
|
||||||
|
def convert(
|
||||||
|
self, local_path: str, **kwargs: Any
|
||||||
|
) -> Union[None, DocumentConverterResult]:
|
||||||
|
# Bail if not a ZIP
|
||||||
|
extension = kwargs.get("file_extension", "")
|
||||||
|
if extension.lower() != ".zip":
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Get parent converters list if available
|
||||||
|
parent_converters = kwargs.get("_parent_converters", [])
|
||||||
|
if not parent_converters:
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=None,
|
||||||
|
text_content=f"[ERROR] No converters available to process zip contents from: {local_path}",
|
||||||
|
)
|
||||||
|
|
||||||
|
extracted_zip_folder_name = (
|
||||||
|
f"extracted_{os.path.basename(local_path).replace('.zip', '_zip')}"
|
||||||
|
)
|
||||||
|
extraction_dir = os.path.normpath(
|
||||||
|
os.path.join(os.path.dirname(local_path), extracted_zip_folder_name)
|
||||||
|
)
|
||||||
|
md_content = f"Content from the zip file `{os.path.basename(local_path)}`:\n\n"
|
||||||
|
|
||||||
|
try:
|
||||||
|
# Extract the zip file safely
|
||||||
|
with zipfile.ZipFile(local_path, "r") as zipObj:
|
||||||
|
# Safeguard against path traversal
|
||||||
|
for member in zipObj.namelist():
|
||||||
|
member_path = os.path.normpath(os.path.join(extraction_dir, member))
|
||||||
|
if (
|
||||||
|
not os.path.commonprefix([extraction_dir, member_path])
|
||||||
|
== extraction_dir
|
||||||
|
):
|
||||||
|
raise ValueError(
|
||||||
|
f"Path traversal detected in zip file: {member}"
|
||||||
|
)
|
||||||
|
|
||||||
|
# Extract all files safely
|
||||||
|
zipObj.extractall(path=extraction_dir)
|
||||||
|
|
||||||
|
# Process each extracted file
|
||||||
|
for root, dirs, files in os.walk(extraction_dir):
|
||||||
|
for name in files:
|
||||||
|
file_path = os.path.join(root, name)
|
||||||
|
relative_path = os.path.relpath(file_path, extraction_dir)
|
||||||
|
|
||||||
|
# Get file extension
|
||||||
|
_, file_extension = os.path.splitext(name)
|
||||||
|
|
||||||
|
# Update kwargs for the file
|
||||||
|
file_kwargs = kwargs.copy()
|
||||||
|
file_kwargs["file_extension"] = file_extension
|
||||||
|
file_kwargs["_parent_converters"] = parent_converters
|
||||||
|
|
||||||
|
# Try converting the file using available converters
|
||||||
|
for converter in parent_converters:
|
||||||
|
# Skip the zip converter to avoid infinite recursion
|
||||||
|
if isinstance(converter, ZipConverter):
|
||||||
|
continue
|
||||||
|
|
||||||
|
result = converter.convert(file_path, **file_kwargs)
|
||||||
|
if result is not None:
|
||||||
|
md_content += f"\n## File: {relative_path}\n\n"
|
||||||
|
md_content += result.text_content + "\n\n"
|
||||||
|
break
|
||||||
|
|
||||||
|
# Clean up extracted files if specified
|
||||||
|
if kwargs.get("cleanup_extracted", True):
|
||||||
|
shutil.rmtree(extraction_dir)
|
||||||
|
|
||||||
|
return DocumentConverterResult(title=None, text_content=md_content.strip())
|
||||||
|
|
||||||
|
except zipfile.BadZipFile:
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=None,
|
||||||
|
text_content=f"[ERROR] Invalid or corrupted zip file: {local_path}",
|
||||||
|
)
|
||||||
|
except ValueError as ve:
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=None,
|
||||||
|
text_content=f"[ERROR] Security error in zip file {local_path}: {str(ve)}",
|
||||||
|
)
|
||||||
|
except Exception as e:
|
||||||
|
return DocumentConverterResult(
|
||||||
|
title=None,
|
||||||
|
text_content=f"[ERROR] Failed to process zip file {local_path}: {str(e)}",
|
||||||
|
)
|
||||||
Loading…
Reference in a new issue