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Cleanup and refactor, in preparation for plugin support. (#318)

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* Work started moving converters to individual files.
* Significant cleanup and refactor.
* Moved everything to a packages subfolder.
* Added sample plugin.
* Added instructions to the README.md
* Bumped version, and added a note about compatibility.
This commit is contained in:
afourney
2025-02-10 15:21:44 -08:00
committed by GitHub
parent 73ba69d8cd
commit c73afcffea
60 changed files with 2755 additions and 1901 deletions
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# MarkItDown Sample Plugin
[![PyPI](https://img.shields.io/pypi/v/markitdown.svg)](https://pypi.org/project/markitdown/)
![PyPI - Downloads](https://img.shields.io/pypi/dd/markitdown)
[![Built by AutoGen Team](https://img.shields.io/badge/Built%20by-AutoGen%20Team-blue)](https://github.com/microsoft/autogen)
This project shows how to create a sample plugin for MarkItDown. The most important parts are as follows:
FNext, implement your custom DocumentConverter:
```python
from typing import Union
from markitdown import DocumentConverter, DocumentConverterResult
class RtfConverter(DocumentConverter):
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not an RTF file
extension = kwargs.get("file_extension", "")
if extension.lower() != ".rtf":
return None
# Implement the conversion logic here ...
# Return the result
return DocumentConverterResult(
title=title,
text_content=text_content,
)
```
Next, make sure your package implements and exports the following:
```python
# The version of the plugin interface that this plugin uses.
# The only supported version is 1 for now.
__plugin_interface_version__ = 1
# The main entrypoint for the plugin. This is called each time MarkItDown instances are created.
def register_converters(markitdown: MarkItDown, **kwargs):
"""
Called during construction of MarkItDown instances to register converters provided by plugins.
"""
# Simply create and attach an RtfConverter instance
markitdown.register_converter(RtfConverter())
```
Finally, create an entrypoint in the `pyproject.toml` file:
```toml
[project.entry-points."markitdown.plugin"]
sample_plugin = "markitdown_sample_plugin"
```
Here, the value of `sample_plugin` can be any key, but should ideally be the name of the plugin. The value is the fully qualified name of the package implementing the plugin.
## Installation
To use the plugin with MarkItDown, it must be installed. To install the plugin from the current directory use:
```bash
pip install -e .
```
Once the plugin package is installed, verify that it is available to MarkItDown by running:
```bash
markitdown --list-plugins
```
To use the plugin for a conversion use the `--use-plugins` flag. For example, to convert a PDF:
```bash
markitdown --use-plugins path-to-file.pdf
```
In Python, plugins can be enabled as follows:
```python
from markitdown import MarkItDown
md = MarkItDown(enable_plugins=True)
result = md.convert("path-to-file.pdf")
print(result.text_content)
```
## Trademarks
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft
trademarks or logos is subject to and must follow
[Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).
Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
Any use of third-party trademarks or logos are subject to those third-party's policies.

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[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "markitdown-sample-plugin"
dynamic = ["version"]
description = 'A sample plugin for the "markitdown" library.'
readme = "README.md"
requires-python = ">=3.10"
license = "MIT"
keywords = []
authors = [
{ name = "Adam Fourney", email = "adamfo@microsoft.com" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Programming Language :: Python",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: Implementation :: CPython",
"Programming Language :: Python :: Implementation :: PyPy",
]
dependencies = [
"markitdown",
"striprtf",
]
[project.urls]
Documentation = "https://github.com/microsoft/markitdown#readme"
Issues = "https://github.com/microsoft/markitdown/issues"
Source = "https://github.com/microsoft/markitdown"
[tool.hatch.version]
path = "src/markitdown_sample_plugin/__about__.py"
# IMPORTANT: MarkItDown will look for this entry point to find the plugin.
[project.entry-points."markitdown.plugin"]
sample_plugin = "markitdown_sample_plugin"
[tool.hatch.envs.types]
extra-dependencies = [
"mypy>=1.0.0",
]
[tool.hatch.envs.types.scripts]
check = "mypy --install-types --non-interactive {args:src/markitdown_sample_plugin tests}"
[tool.coverage.run]
source_pkgs = ["markitdown-sample-plugin", "tests"]
branch = true
parallel = true
omit = [
"src/markitdown_sample_plugin/__about__.py",
]
[tool.coverage.paths]
markitdown-sample-plugin = ["src/markitdown_sample_plugin", "*/markitdown-sample-plugin/src/markitdown_sample_plugin"]
tests = ["tests", "*/markitdown-sample-plugin/tests"]
[tool.coverage.report]
exclude_lines = [
"no cov",
"if __name__ == .__main__.:",
"if TYPE_CHECKING:",
]
[tool.hatch.build.targets.sdist]
only-include = ["src/markitdown_sample_plugin"]

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
__version__ = "0.0.1a2"

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
from ._plugin import __plugin_interface_version__, register_converters, RtfConverter
from .__about__ import __version__
__all__ = [
"__version__",
"__plugin_interface_version__",
"register_converters",
"RtfConverter",
]

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from typing import Union
from striprtf.striprtf import rtf_to_text
from markitdown import MarkItDown, DocumentConverter, DocumentConverterResult
__plugin_interface_version__ = (
1 # The version of the plugin interface that this plugin uses
)
def register_converters(markitdown: MarkItDown, **kwargs):
"""
Called during construction of MarkItDown instances to register converters provided by plugins.
"""
# Simply create and attach an RtfConverter instance
markitdown.register_converter(RtfConverter())
class RtfConverter(DocumentConverter):
"""
Converts an RTF file to in the simplest possible way.
"""
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not a DOCX
extension = kwargs.get("file_extension", "")
if extension.lower() != ".rtf":
return None
# Read the RTF file
with open(local_path, "r") as f:
rtf = f.read()
# Return the result
return DocumentConverterResult(
title=None,
text_content=rtf_to_text(rtf),
)

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT

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40
packages/markitdown-sample-plugin/tests/test_sample_plugin.py Normal file
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#!/usr/bin/env python3 -m pytest
import os
import pytest
from markitdown import MarkItDown
from markitdown_sample_plugin import RtfConverter
TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
RTF_TEST_STRINGS = {
"This is a Sample RTF File",
"It is included to test if the MarkItDown sample plugin can correctly convert RTF files.",
}
def test_converter() -> None:
"""Tests the RTF converter dirctly."""
converter = RtfConverter()
result = converter.convert(
os.path.join(TEST_FILES_DIR, "test.rtf"), file_extension=".rtf"
)
for test_string in RTF_TEST_STRINGS:
assert test_string in result.text_content
def test_markitdown() -> None:
"""Tests that MarkItDown correctly loads the plugin."""
md = MarkItDown()
result = md.convert(os.path.join(TEST_FILES_DIR, "test.rtf"))
for test_string in RTF_TEST_STRINGS:
assert test_string in result.text_content
if __name__ == "__main__":
"""Runs this file's tests from the command line."""
test_converter()
test_markitdown()
print("All tests passed.")

52
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# MarkItDown
> [!IMPORTANT]
> MarkItDown is a Python package and command-line utility for converting various files to Markdown (e.g., for indexing, text analysis, etc).
>
> For more information, and full documentation, see the project [README.md](https://github.com/microsoft/markitdown) on GitHub.
## Installation
From PyPI:
```bash
pip install markitdown
```
From source:
```bash
git clone git@github.com:microsoft/markitdown.git
cd markitdown
pip install -e packages/markitdown
```
## Usage
### Command-Line
```bash
markitdown path-to-file.pdf > document.md
```
### Python API
```python
from markitdown import MarkItDown
md = MarkItDown()
result = md.convert("test.xlsx")
print(result.text_content)
```
### More Information
For more information, and full documentation, see the project [README.md](https://github.com/microsoft/markitdown) on GitHub.
## Trademarks
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft
trademarks or logos is subject to and must follow
[Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).
Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
Any use of third-party trademarks or logos are subject to those third-party's policies.

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[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "markitdown"
dynamic = ["version"]
description = 'Utility tool for converting various files to Markdown'
readme = "README.md"
requires-python = ">=3.10"
license = "MIT"
keywords = []
authors = [
{ name = "Adam Fourney", email = "adamfo@microsoft.com" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Programming Language :: Python",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: Implementation :: CPython",
"Programming Language :: Python :: Implementation :: PyPy",
]
dependencies = [
"beautifulsoup4",
"requests",
"mammoth",
"markdownify",
"numpy",
"python-pptx",
"pandas",
"openpyxl",
"xlrd",
"pdfminer.six",
"puremagic",
"pydub",
"olefile",
"youtube-transcript-api",
"SpeechRecognition",
"pathvalidate",
"charset-normalizer",
"openai",
"azure-ai-documentintelligence",
"azure-identity"
]
[project.urls]
Documentation = "https://github.com/microsoft/markitdown#readme"
Issues = "https://github.com/microsoft/markitdown/issues"
Source = "https://github.com/microsoft/markitdown"
[tool.hatch.version]
path = "src/markitdown/__about__.py"
[project.scripts]
markitdown = "markitdown.__main__:main"
[tool.hatch.envs.types]
extra-dependencies = [
"mypy>=1.0.0",
]
[tool.hatch.envs.types.scripts]
check = "mypy --install-types --non-interactive {args:src/markitdown tests}"
[tool.coverage.run]
source_pkgs = ["markitdown", "tests"]
branch = true
parallel = true
omit = [
"src/markitdown/__about__.py",
]
[tool.coverage.paths]
markitdown = ["src/markitdown", "*/markitdown/src/markitdown"]
tests = ["tests", "*/markitdown/tests"]
[tool.coverage.report]
exclude_lines = [
"no cov",
"if __name__ == .__main__.:",
"if TYPE_CHECKING:",
]
[tool.hatch.build.targets.sdist]
only-include = ["src/markitdown"]

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
__version__ = "0.0.2a1"

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
from ._markitdown import MarkItDown
from ._exceptions import (
MarkItDownException,
ConverterPrerequisiteException,
FileConversionException,
UnsupportedFormatException,
)
from .converters import DocumentConverter, DocumentConverterResult
__all__ = [
"MarkItDown",
"DocumentConverter",
"DocumentConverterResult",
"MarkItDownException",
"ConverterPrerequisiteException",
"FileConversionException",
"UnsupportedFormatException",
]

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
import argparse
import sys
from textwrap import dedent
from importlib.metadata import entry_points
from .__about__ import __version__
from ._markitdown import MarkItDown, DocumentConverterResult
def main():
parser = argparse.ArgumentParser(
description="Convert various file formats to markdown.",
prog="markitdown",
formatter_class=argparse.RawDescriptionHelpFormatter,
usage=dedent(
"""
SYNTAX:
markitdown <OPTIONAL: FILENAME>
If FILENAME is empty, markitdown reads from stdin.
EXAMPLE:
markitdown example.pdf
OR
cat example.pdf | markitdown
OR
markitdown < example.pdf
OR to save to a file use
markitdown example.pdf -o example.md
OR
markitdown example.pdf > example.md
"""
).strip(),
)
parser.add_argument(
"-v",
"--version",
action="version",
version=f"%(prog)s {__version__}",
help="show the version number and exit",
)
parser.add_argument(
"-o",
"--output",
help="Output file name. If not provided, output is written to stdout.",
)
parser.add_argument(
"-d",
"--use-docintel",
action="store_true",
help="Use Document Intelligence to extract text instead of offline conversion. Requires a valid Document Intelligence Endpoint.",
)
parser.add_argument(
"-e",
"--endpoint",
type=str,
help="Document Intelligence Endpoint. Required if using Document Intelligence.",
)
parser.add_argument(
"-p",
"--use-plugins",
action="store_true",
help="Use 3rd-party plugins to convert files. Use --list-plugins to see installed plugins.",
)
parser.add_argument(
"--list-plugins",
action="store_true",
help="List installed 3rd-party plugins. Plugins are loaded when using the -p or --use-plugin option.",
)
parser.add_argument("filename", nargs="?")
args = parser.parse_args()
if args.list_plugins:
# List installed plugins, then exit
print("Installed MarkItDown 3rd-party Plugins:\n")
plugin_entry_points = list(entry_points(group="markitdown.plugin"))
if len(plugin_entry_points) == 0:
print(" * No 3rd-party plugins installed.")
print(
"\nFind plugins by searching for the hashtag #markitdown-plugin on GitHub.\n"
)
else:
for entry_point in plugin_entry_points:
print(f" * {entry_point.name:<16}\t(package: {entry_point.value})")
print(
"\nUse the -p (or --use-plugins) option to enable 3rd-party plugins.\n"
)
sys.exit(0)
if args.use_docintel:
if args.endpoint is None:
raise ValueError(
"Document Intelligence Endpoint is required when using Document Intelligence."
)
elif args.filename is None:
raise ValueError("Filename is required when using Document Intelligence.")
markitdown = MarkItDown(
enable_plugins=args.use_plugins, docintel_endpoint=args.endpoint
)
else:
markitdown = MarkItDown(enable_plugins=args.use_plugins)
if args.filename is None:
result = markitdown.convert_stream(sys.stdin.buffer)
else:
result = markitdown.convert(args.filename)
_handle_output(args, result)
def _handle_output(args, result: DocumentConverterResult):
"""Handle output to stdout or file"""
if args.output:
with open(args.output, "w", encoding="utf-8") as f:
f.write(result.text_content)
else:
print(result.text_content)
if __name__ == "__main__":
main()

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class MarkItDownException(BaseException):
"""
Base exception class for MarkItDown.
"""
pass
class ConverterPrerequisiteException(MarkItDownException):
"""
Thrown when instantiating a DocumentConverter in cases where
a required library or dependency is not installed, an API key
is not set, or some other prerequisite is not met.
This is not necessarily a fatal error. If thrown during
MarkItDown's plugin loading phase, the converter will simply be
skipped, and a warning will be issued.
"""
pass
class FileConversionException(MarkItDownException):
"""
Thrown when a suitable converter was found, but the conversion
process fails for any reason.
"""
pass
class UnsupportedFormatException(MarkItDownException):
"""
Thrown when no suitable converter was found for the given file.
"""
pass

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import copy
import mimetypes
import os
import re
import tempfile
import warnings
import traceback
from importlib.metadata import entry_points
from typing import Any, List, Optional, Union
from pathlib import Path
from urllib.parse import urlparse
from warnings import warn
# File-format detection
import puremagic
import requests
from .converters import (
DocumentConverter,
DocumentConverterResult,
PlainTextConverter,
HtmlConverter,
RssConverter,
WikipediaConverter,
YouTubeConverter,
IpynbConverter,
BingSerpConverter,
PdfConverter,
DocxConverter,
XlsxConverter,
XlsConverter,
PptxConverter,
ImageConverter,
WavConverter,
Mp3Converter,
OutlookMsgConverter,
ZipConverter,
DocumentIntelligenceConverter,
)
from ._exceptions import (
FileConversionException,
UnsupportedFormatException,
ConverterPrerequisiteException,
)
# Override mimetype for csv to fix issue on windows
mimetypes.add_type("text/csv", ".csv")
PRIORITY_SPECIFIC_FILE_FORMAT = 0.0
PRIORITY_GENERIC_FILE_FORMAT = 10.0
_plugins: Union[None | List[Any]] = None
def _load_plugins() -> Union[None | List[Any]]:
"""Lazy load plugins, exiting early if already loaded."""
global _plugins
# Skip if we've already loaded plugins
if _plugins is not None:
return _plugins
# Load plugins
_plugins = []
for entry_point in entry_points(group="markitdown.plugin"):
try:
_plugins.append(entry_point.load())
except Exception:
tb = traceback.format_exc()
warn(f"Plugin '{entry_point.name}' failed to load ... skipping:\n{tb}")
return _plugins
class MarkItDown:
"""(In preview) An extremely simple text-based document reader, suitable for LLM use.
This reader will convert common file-types or webpages to Markdown."""
def __init__(
self,
*,
enable_builtins: Union[None, bool] = None,
enable_plugins: Union[None, bool] = None,
**kwargs,
):
self._builtins_enabled = False
self._plugins_enabled = False
requests_session = kwargs.get("requests_session")
if requests_session is None:
self._requests_session = requests.Session()
else:
self._requests_session = requests_session
# TODO - remove these (see enable_builtins)
self._llm_client = None
self._llm_model = None
self._exiftool_path = None
self._style_map = None
# Register the converters
self._page_converters: List[DocumentConverter] = []
if (
enable_builtins is None or enable_builtins
): # Default to True when not specified
self.enable_builtins(**kwargs)
if enable_plugins:
self.enable_plugins(**kwargs)
def enable_builtins(self, **kwargs) -> None:
"""
Enable and register built-in converters.
Built-in converters are enabled by default.
This method should only be called once, if built-ins were initially disabled.
"""
if not self._builtins_enabled:
# TODO: Move these into converter constructors
self._llm_client = kwargs.get("llm_client")
self._llm_model = kwargs.get("llm_model")
self._exiftool_path = kwargs.get("exiftool_path")
self._style_map = kwargs.get("style_map")
# Register converters for successful browsing operations
# Later registrations are tried first / take higher priority than earlier registrations
# To this end, the most specific converters should appear below the most generic converters
self.register_converter(PlainTextConverter())
self.register_converter(ZipConverter())
self.register_converter(HtmlConverter())
self.register_converter(RssConverter())
self.register_converter(WikipediaConverter())
self.register_converter(YouTubeConverter())
self.register_converter(BingSerpConverter())
self.register_converter(DocxConverter())
self.register_converter(XlsxConverter())
self.register_converter(XlsConverter())
self.register_converter(PptxConverter())
self.register_converter(WavConverter())
self.register_converter(Mp3Converter())
self.register_converter(ImageConverter())
self.register_converter(IpynbConverter())
self.register_converter(PdfConverter())
self.register_converter(OutlookMsgConverter())
# Register Document Intelligence converter at the top of the stack if endpoint is provided
docintel_endpoint = kwargs.get("docintel_endpoint")
if docintel_endpoint is not None:
self.register_converter(
DocumentIntelligenceConverter(endpoint=docintel_endpoint)
)
self._builtins_enabled = True
else:
warn("Built-in converters are already enabled.", RuntimeWarning)
def enable_plugins(self, **kwargs) -> None:
"""
Enable and register converters provided by plugins.
Plugins are disabled by default.
This method should only be called once, if plugins were initially disabled.
"""
if not self._plugins_enabled:
# Load plugins
for plugin in _load_plugins():
try:
plugin.register_converters(self, **kwargs)
except Exception:
tb = traceback.format_exc()
warn(f"Plugin '{plugin}' failed to register converters:\n{tb}")
self._plugins_enabled = True
else:
warn("Plugins converters are already enabled.", RuntimeWarning)
def convert(
self, source: Union[str, requests.Response, Path], **kwargs: Any
) -> DocumentConverterResult: # TODO: deal with kwargs
"""
Args:
- source: can be a string representing a path either as string pathlib path object or url, or a requests.response object
- extension: specifies the file extension to use when interpreting the file. If None, infer from source (path, uri, content-type, etc.)
"""
# Local path or url
if isinstance(source, str):
if (
source.startswith("http://")
or source.startswith("https://")
or source.startswith("file://")
):
return self.convert_url(source, **kwargs)
else:
return self.convert_local(source, **kwargs)
# Request response
elif isinstance(source, requests.Response):
return self.convert_response(source, **kwargs)
elif isinstance(source, Path):
return self.convert_local(source, **kwargs)
def convert_local(
self, path: Union[str, Path], **kwargs: Any
) -> DocumentConverterResult: # TODO: deal with kwargs
if isinstance(path, Path):
path = str(path)
# Prepare a list of extensions to try (in order of priority)
ext = kwargs.get("file_extension")
extensions = [ext] if ext is not None else []
# Get extension alternatives from the path and puremagic
base, ext = os.path.splitext(path)
self._append_ext(extensions, ext)
for g in self._guess_ext_magic(path):
self._append_ext(extensions, g)
# Convert
return self._convert(path, extensions, **kwargs)
# TODO what should stream's type be?
def convert_stream(
self, stream: Any, **kwargs: Any
) -> DocumentConverterResult: # TODO: deal with kwargs
# Prepare a list of extensions to try (in order of priority)
ext = kwargs.get("file_extension")
extensions = [ext] if ext is not None else []
# Save the file locally to a temporary file. It will be deleted before this method exits
handle, temp_path = tempfile.mkstemp()
fh = os.fdopen(handle, "wb")
result = None
try:
# Write to the temporary file
content = stream.read()
if isinstance(content, str):
fh.write(content.encode("utf-8"))
else:
fh.write(content)
fh.close()
# Use puremagic to check for more extension options
for g in self._guess_ext_magic(temp_path):
self._append_ext(extensions, g)
# Convert
result = self._convert(temp_path, extensions, **kwargs)
# Clean up
finally:
try:
fh.close()
except Exception:
pass
os.unlink(temp_path)
return result
def convert_url(
self, url: str, **kwargs: Any
) -> DocumentConverterResult: # TODO: fix kwargs type
# Send a HTTP request to the URL
response = self._requests_session.get(url, stream=True)
response.raise_for_status()
return self.convert_response(response, **kwargs)
def convert_response(
self, response: requests.Response, **kwargs: Any
) -> DocumentConverterResult: # TODO fix kwargs type
# Prepare a list of extensions to try (in order of priority)
ext = kwargs.get("file_extension")
extensions = [ext] if ext is not None else []
# Guess from the mimetype
content_type = response.headers.get("content-type", "").split(";")[0]
self._append_ext(extensions, mimetypes.guess_extension(content_type))
# Read the content disposition if there is one
content_disposition = response.headers.get("content-disposition", "")
m = re.search(r"filename=([^;]+)", content_disposition)
if m:
base, ext = os.path.splitext(m.group(1).strip("\"'"))
self._append_ext(extensions, ext)
# Read from the extension from the path
base, ext = os.path.splitext(urlparse(response.url).path)
self._append_ext(extensions, ext)
# Save the file locally to a temporary file. It will be deleted before this method exits
handle, temp_path = tempfile.mkstemp()
fh = os.fdopen(handle, "wb")
result = None
try:
# Download the file
for chunk in response.iter_content(chunk_size=512):
fh.write(chunk)
fh.close()
# Use puremagic to check for more extension options
for g in self._guess_ext_magic(temp_path):
self._append_ext(extensions, g)
# Convert
result = self._convert(temp_path, extensions, url=response.url, **kwargs)
# Clean up
finally:
try:
fh.close()
except Exception:
pass
os.unlink(temp_path)
return result
def _convert(
self, local_path: str, extensions: List[Union[str, None]], **kwargs
) -> DocumentConverterResult:
error_trace = ""
# Create a copy of the page_converters list, sorted by priority.
# We do this with each call to _convert because the priority of converters may change between calls.
# The sort is guaranteed to be stable, so converters with the same priority will remain in the same order.
sorted_converters = sorted(self._page_converters, key=lambda x: x.priority)
for ext in extensions + [None]: # Try last with no extension
for converter in sorted_converters:
_kwargs = copy.deepcopy(kwargs)
# Overwrite file_extension appropriately
if ext is None:
if "file_extension" in _kwargs:
del _kwargs["file_extension"]
else:
_kwargs.update({"file_extension": ext})
# Copy any additional global options
if "llm_client" not in _kwargs and self._llm_client is not None:
_kwargs["llm_client"] = self._llm_client
if "llm_model" not in _kwargs and self._llm_model is not None:
_kwargs["llm_model"] = self._llm_model
if "style_map" not in _kwargs and self._style_map is not None:
_kwargs["style_map"] = self._style_map
if "exiftool_path" not in _kwargs and self._exiftool_path is not None:
_kwargs["exiftool_path"] = self._exiftool_path
# Add the list of converters for nested processing
_kwargs["_parent_converters"] = self._page_converters
# If we hit an error log it and keep trying
# try:
if True:
res = converter.convert(local_path, **_kwargs)
# except Exception:
# error_trace = ("\n\n" + traceback.format_exc()).strip()
if res is not None:
# Normalize the content
res.text_content = "\n".join(
[line.rstrip() for line in re.split(r"\r?\n", res.text_content)]
)
res.text_content = re.sub(r"\n{3,}", "\n\n", res.text_content)
# Todo
return res
# If we got this far without success, report any exceptions
if len(error_trace) > 0:
raise FileConversionException(
f"Could not convert '{local_path}' to Markdown. File type was recognized as {extensions}. While converting the file, the following error was encountered:\n\n{error_trace}"
)
# Nothing can handle it!
raise UnsupportedFormatException(
f"Could not convert '{local_path}' to Markdown. The formats {extensions} are not supported."
)
def _append_ext(self, extensions, ext):
"""Append a unique non-None, non-empty extension to a list of extensions."""
if ext is None:
return
ext = ext.strip()
if ext == "":
return
# if ext not in extensions:
extensions.append(ext)
def _guess_ext_magic(self, path):
"""Use puremagic (a Python implementation of libmagic) to guess a file's extension based on the first few bytes."""
# Use puremagic to guess
try:
guesses = puremagic.magic_file(path)
# Fix for: https://github.com/microsoft/markitdown/issues/222
# If there are no guesses, then try again after trimming leading ASCII whitespaces.
# ASCII whitespace characters are those byte values in the sequence b' \t\n\r\x0b\f'
# (space, tab, newline, carriage return, vertical tab, form feed).
if len(guesses) == 0:
with open(path, "rb") as file:
while True:
char = file.read(1)
if not char: # End of file
break
if not char.isspace():
file.seek(file.tell() - 1)
break
try:
guesses = puremagic.magic_stream(file)
except puremagic.main.PureError:
pass
extensions = list()
for g in guesses:
ext = g.extension.strip()
if len(ext) > 0:
if not ext.startswith("."):
ext = "." + ext
if ext not in extensions:
extensions.append(ext)
return extensions
except FileNotFoundError:
pass
except IsADirectoryError:
pass
except PermissionError:
pass
return []
def register_page_converter(self, converter: DocumentConverter) -> None:
"""DEPRECATED: User register_converter instead."""
warn(
"register_page_converter is deprecated. Use register_converter instead.",
DeprecationWarning,
)
self.register_converter(converter)
def register_converter(self, converter: DocumentConverter) -> None:
"""Register a page text converter."""
self._page_converters.insert(0, converter)

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
from ._base import DocumentConverter, DocumentConverterResult
from ._plain_text_converter import PlainTextConverter
from ._html_converter import HtmlConverter
from ._rss_converter import RssConverter
from ._wikipedia_converter import WikipediaConverter
from ._youtube_converter import YouTubeConverter
from ._ipynb_converter import IpynbConverter
from ._bing_serp_converter import BingSerpConverter
from ._pdf_converter import PdfConverter
from ._docx_converter import DocxConverter
from ._xlsx_converter import XlsxConverter, XlsConverter
from ._pptx_converter import PptxConverter
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__ = [
"DocumentConverter",
"DocumentConverterResult",
"PlainTextConverter",
"HtmlConverter",
"RssConverter",
"WikipediaConverter",
"YouTubeConverter",
"IpynbConverter",
"BingSerpConverter",
"PdfConverter",
"DocxConverter",
"XlsxConverter",
"XlsConverter",
"PptxConverter",
"ImageConverter",
"WavConverter",
"Mp3Converter",
"OutlookMsgConverter",
"ZipConverter",
"DocumentIntelligenceConverter",
]

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from typing import Any, Union
class DocumentConverterResult:
"""The result of converting a document to text."""
def __init__(self, title: Union[str, None] = None, text_content: str = ""):
self.title: Union[str, None] = title
self.text_content: str = text_content
class DocumentConverter:
"""Abstract superclass of all DocumentConverters."""
def __init__(self, priority: float = 0.0):
self._priority = priority
def convert(
self, local_path: str, **kwargs: Any
) -> Union[None, DocumentConverterResult]:
raise NotImplementedError("Subclasses must implement this method")
@property
def priority(self) -> float:
"""Priority of the converter in markitdown's converter list. Higher priority values are tried first."""
return self._priority
@priority.setter
def radius(self, value: float):
self._priority = value
@priority.deleter
def radius(self):
raise AttributeError("Cannot delete the priority attribute")

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# type: ignore
import base64
import re
from typing import Union
from urllib.parse import parse_qs, urlparse
from bs4 import BeautifulSoup
from ._base import DocumentConverter, DocumentConverterResult
from ._markdownify import _CustomMarkdownify
class BingSerpConverter(DocumentConverter):
"""
Handle Bing results pages (only the organic search results).
NOTE: It is better to use the Bing API
"""
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not a Bing SERP
extension = kwargs.get("file_extension", "")
if extension.lower() not in [".html", ".htm"]:
return None
url = kwargs.get("url", "")
if not re.search(r"^https://www\.bing\.com/search\?q=", url):
return None
# Parse the query parameters
parsed_params = parse_qs(urlparse(url).query)
query = parsed_params.get("q", [""])[0]
# Parse the file
soup = None
with open(local_path, "rt", encoding="utf-8") as fh:
soup = BeautifulSoup(fh.read(), "html.parser")
# Clean up some formatting
for tptt in soup.find_all(class_="tptt"):
if hasattr(tptt, "string") and tptt.string:
tptt.string += " "
for slug in soup.find_all(class_="algoSlug_icon"):
slug.extract()
# Parse the algorithmic results
_markdownify = _CustomMarkdownify()
results = list()
for result in soup.find_all(class_="b_algo"):
# Rewrite redirect urls
for a in result.find_all("a", href=True):
parsed_href = urlparse(a["href"])
qs = parse_qs(parsed_href.query)
# The destination is contained in the u parameter,
# but appears to be base64 encoded, with some prefix
if "u" in qs:
u = (
qs["u"][0][2:].strip() + "=="
) # Python 3 doesn't care about extra padding
try:
# RFC 4648 / Base64URL" variant, which uses "-" and "_"
a["href"] = base64.b64decode(u, altchars="-_").decode("utf-8")
except UnicodeDecodeError:
pass
except binascii.Error:
pass
# Convert to markdown
md_result = _markdownify.convert_soup(result).strip()
lines = [line.strip() for line in re.split(r"\n+", md_result)]
results.append("\n".join([line for line in lines if len(line) > 0]))
webpage_text = (
f"## A Bing search for '{query}' found the following results:\n\n"
+ "\n\n".join(results)
)
return DocumentConverterResult(
title=None if soup.title is None else soup.title.string,
text_content=webpage_text,
)

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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
# 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,
)

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from typing import Union
import mammoth
from ._base import (
DocumentConverterResult,
)
from ._html_converter import HtmlConverter
class DocxConverter(HtmlConverter):
"""
Converts DOCX files to Markdown. Style information (e.g.m headings) and tables are preserved where possible.
"""
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not a DOCX
extension = kwargs.get("file_extension", "")
if extension.lower() != ".docx":
return None
result = None
with open(local_path, "rb") as docx_file:
style_map = kwargs.get("style_map", None)
result = mammoth.convert_to_html(docx_file, style_map=style_map)
html_content = result.value
result = self._convert(html_content)
return result

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from typing import Any, Union
from bs4 import BeautifulSoup
from ._base import DocumentConverter, DocumentConverterResult
from ._markdownify import _CustomMarkdownify
class HtmlConverter(DocumentConverter):
"""Anything with content type text/html"""
def convert(
self, local_path: str, **kwargs: Any
) -> Union[None, DocumentConverterResult]:
# Bail if not html
extension = kwargs.get("file_extension", "")
if extension.lower() not in [".html", ".htm"]:
return None
result = None
with open(local_path, "rt", encoding="utf-8") as fh:
result = self._convert(fh.read())
return result
def _convert(self, html_content: str) -> Union[None, DocumentConverterResult]:
"""Helper function that converts an HTML string."""
# Parse the string
soup = BeautifulSoup(html_content, "html.parser")
# Remove javascript and style blocks
for script in soup(["script", "style"]):
script.extract()
# Print only the main content
body_elm = soup.find("body")
webpage_text = ""
if body_elm:
webpage_text = _CustomMarkdownify().convert_soup(body_elm)
else:
webpage_text = _CustomMarkdownify().convert_soup(soup)
assert isinstance(webpage_text, str)
# remove leading and trailing \n
webpage_text = webpage_text.strip()
return DocumentConverterResult(
title=None if soup.title is None else soup.title.string,
text_content=webpage_text,
)

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from typing import Union
from ._base import DocumentConverterResult
from ._media_converter import MediaConverter
class ImageConverter(MediaConverter):
"""
Converts images to markdown via extraction of metadata (if `exiftool` is installed), OCR (if `easyocr` is installed), and description via a multimodal LLM (if an llm_client is configured).
"""
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not an image
extension = kwargs.get("file_extension", "")
if extension.lower() not in [".jpg", ".jpeg", ".png"]:
return None
md_content = ""
# Add metadata
metadata = self._get_metadata(local_path, kwargs.get("exiftool_path"))
if metadata:
for f in [
"ImageSize",
"Title",
"Caption",
"Description",
"Keywords",
"Artist",
"Author",
"DateTimeOriginal",
"CreateDate",
"GPSPosition",
]:
if f in metadata:
md_content += f"{f}: {metadata[f]}\n"
# Try describing the image with GPTV
llm_client = kwargs.get("llm_client")
llm_model = kwargs.get("llm_model")
if llm_client is not None and llm_model is not None:
md_content += (
"\n# Description:\n"
+ self._get_llm_description(
local_path,
extension,
llm_client,
llm_model,
prompt=kwargs.get("llm_prompt"),
).strip()
+ "\n"
)
return DocumentConverterResult(
title=None,
text_content=md_content,
)
def _get_llm_description(self, local_path, extension, client, model, prompt=None):
if prompt is None or prompt.strip() == "":
prompt = "Write a detailed caption for this image."
data_uri = ""
with open(local_path, "rb") as image_file:
content_type, encoding = mimetypes.guess_type("_dummy" + extension)
if content_type is None:
content_type = "image/jpeg"
image_base64 = base64.b64encode(image_file.read()).decode("utf-8")
data_uri = f"data:{content_type};base64,{image_base64}"
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": prompt},
{
"type": "image_url",
"image_url": {
"url": data_uri,
},
},
],
}
]
response = client.chat.completions.create(model=model, messages=messages)
return response.choices[0].message.content

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import json
from typing import Any, Union
from ._base import (
DocumentConverter,
DocumentConverterResult,
)
from .._exceptions import FileConversionException
class IpynbConverter(DocumentConverter):
"""Converts Jupyter Notebook (.ipynb) files to Markdown."""
def convert(
self, local_path: str, **kwargs: Any
) -> Union[None, DocumentConverterResult]:
# Bail if not ipynb
extension = kwargs.get("file_extension", "")
if extension.lower() != ".ipynb":
return None
# Parse and convert the notebook
result = None
with open(local_path, "rt", encoding="utf-8") as fh:
notebook_content = json.load(fh)
result = self._convert(notebook_content)
return result
def _convert(self, notebook_content: dict) -> Union[None, DocumentConverterResult]:
"""Helper function that converts notebook JSON content to Markdown."""
try:
md_output = []
title = None
for cell in notebook_content.get("cells", []):
cell_type = cell.get("cell_type", "")
source_lines = cell.get("source", [])
if cell_type == "markdown":
md_output.append("".join(source_lines))
# Extract the first # heading as title if not already found
if title is None:
for line in source_lines:
if line.startswith("# "):
title = line.lstrip("# ").strip()
break
elif cell_type == "code":
# Code cells are wrapped in Markdown code blocks
md_output.append(f"```python\n{''.join(source_lines)}\n```")
elif cell_type == "raw":
md_output.append(f"```\n{''.join(source_lines)}\n```")
md_text = "\n\n".join(md_output)
# Check for title in notebook metadata
title = notebook_content.get("metadata", {}).get("title", title)
return DocumentConverterResult(
title=title,
text_content=md_text,
)
except Exception as e:
raise FileConversionException(
f"Error converting .ipynb file: {str(e)}"
) from e

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import re
import markdownify
from typing import Any
from urllib.parse import quote, unquote, urlparse, urlunparse
class _CustomMarkdownify(markdownify.MarkdownConverter):
"""
A custom version of markdownify's MarkdownConverter. Changes include:
- Altering the default heading style to use '#', '##', etc.
- Removing javascript hyperlinks.
- Truncating images with large data:uri sources.
- Ensuring URIs are properly escaped, and do not conflict with Markdown syntax
"""
def __init__(self, **options: Any):
options["heading_style"] = options.get("heading_style", markdownify.ATX)
# Explicitly cast options to the expected type if necessary
super().__init__(**options)
def convert_hn(self, n: int, el: Any, text: str, convert_as_inline: bool) -> str:
"""Same as usual, but be sure to start with a new line"""
if not convert_as_inline:
if not re.search(r"^\n", text):
return "\n" + super().convert_hn(n, el, text, convert_as_inline) # type: ignore
return super().convert_hn(n, el, text, convert_as_inline) # type: ignore
def convert_a(self, el: Any, text: str, convert_as_inline: bool):
"""Same as usual converter, but removes Javascript links and escapes URIs."""
prefix, suffix, text = markdownify.chomp(text) # type: ignore
if not text:
return ""
href = el.get("href")
title = el.get("title")
# Escape URIs and skip non-http or file schemes
if href:
try:
parsed_url = urlparse(href) # type: ignore
if parsed_url.scheme and parsed_url.scheme.lower() not in ["http", "https", "file"]: # type: ignore
return "%s%s%s" % (prefix, text, suffix)
href = urlunparse(parsed_url._replace(path=quote(unquote(parsed_url.path)))) # type: ignore
except ValueError: # It's not clear if this ever gets thrown
return "%s%s%s" % (prefix, text, suffix)
# For the replacement see #29: text nodes underscores are escaped
if (
self.options["autolinks"]
and text.replace(r"\_", "_") == href
and not title
and not self.options["default_title"]
):
# Shortcut syntax
return "<%s>" % href
if self.options["default_title"] and not title:
title = href
title_part = ' "%s"' % title.replace('"', r"\"") if title else ""
return (
"%s[%s](%s%s)%s" % (prefix, text, href, title_part, suffix)
if href
else text
)
def convert_img(self, el: Any, text: str, convert_as_inline: bool) -> str:
"""Same as usual converter, but removes data URIs"""
alt = el.attrs.get("alt", None) or ""
src = el.attrs.get("src", None) or ""
title = el.attrs.get("title", None) or ""
title_part = ' "%s"' % title.replace('"', r"\"") if title else ""
if (
convert_as_inline
and el.parent.name not in self.options["keep_inline_images_in"]
):
return alt
# Remove dataURIs
if src.startswith("data:"):
src = src.split(",")[0] + "..."
return "![%s](%s%s)" % (alt, src, title_part)
def convert_soup(self, soup: Any) -> str:
return super().convert_soup(soup) # type: ignore

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import subprocess
import shutil
import json
from warnings import warn
from ._base import DocumentConverter
class MediaConverter(DocumentConverter):
"""
Abstract class for multi-modal media (e.g., images and audio)
"""
def _get_metadata(self, local_path, exiftool_path=None):
if not exiftool_path:
which_exiftool = shutil.which("exiftool")
if which_exiftool:
warn(
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.,
md = MarkItDown(exiftool_path="{which_exiftool}")
This warning will be removed in future releases.
""",
DeprecationWarning,
)
return None
else:
try:
result = subprocess.run(
[exiftool_path, "-json", local_path], capture_output=True, text=True
).stdout
return json.loads(result)[0]
except Exception:
return None

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import tempfile
from typing import Union
from ._base import DocumentConverterResult
from ._wav_converter import WavConverter
from warnings import 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(),
)

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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

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import pdfminer
import pdfminer.high_level
from typing import Union
from ._base import DocumentConverter, DocumentConverterResult
class PdfConverter(DocumentConverter):
"""
Converts PDFs to Markdown. Most style information is ignored, so the results are essentially plain-text.
"""
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not a PDF
extension = kwargs.get("file_extension", "")
if extension.lower() != ".pdf":
return None
return DocumentConverterResult(
title=None,
text_content=pdfminer.high_level.extract_text(local_path),
)

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import mimetypes
from charset_normalizer import from_path
from typing import Any, Union
from ._base import DocumentConverter, DocumentConverterResult
class PlainTextConverter(DocumentConverter):
"""Anything with content type text/plain"""
def convert(
self, local_path: str, **kwargs: Any
) -> Union[None, DocumentConverterResult]:
# Guess the content type from any file extension that might be around
content_type, _ = mimetypes.guess_type(
"__placeholder" + kwargs.get("file_extension", "")
)
# Only accept text files
if content_type is None:
return None
elif all(
not content_type.lower().startswith(type_prefix)
for type_prefix in ["text/", "application/json"]
):
return None
text_content = str(from_path(local_path).best())
return DocumentConverterResult(
title=None,
text_content=text_content,
)

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import base64
import pptx
import re
import html
from typing import Union
from ._base import DocumentConverterResult, DocumentConverter
from ._html_converter import HtmlConverter
class PptxConverter(HtmlConverter):
"""
Converts PPTX files to Markdown. Supports heading, tables and images with alt text.
"""
def _get_llm_description(
self, llm_client, llm_model, image_blob, content_type, prompt=None
):
if prompt is None or prompt.strip() == "":
prompt = "Write a detailed alt text for this image with less than 50 words."
image_base64 = base64.b64encode(image_blob).decode("utf-8")
data_uri = f"data:{content_type};base64,{image_base64}"
messages = [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": data_uri,
},
},
{"type": "text", "text": prompt},
],
}
]
response = llm_client.chat.completions.create(
model=llm_model, messages=messages
)
return response.choices[0].message.content
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not a PPTX
extension = kwargs.get("file_extension", "")
if extension.lower() != ".pptx":
return None
md_content = ""
presentation = pptx.Presentation(local_path)
slide_num = 0
for slide in presentation.slides:
slide_num += 1
md_content += f"\n\n<!-- Slide number: {slide_num} -->\n"
title = slide.shapes.title
for shape in slide.shapes:
# Pictures
if self._is_picture(shape):
# https://github.com/scanny/python-pptx/pull/512#issuecomment-1713100069
llm_description = None
alt_text = None
llm_client = kwargs.get("llm_client")
llm_model = kwargs.get("llm_model")
if llm_client is not None and llm_model is not None:
try:
llm_description = self._get_llm_description(
llm_client,
llm_model,
shape.image.blob,
shape.image.content_type,
)
except Exception:
# Unable to describe with LLM
pass
if not llm_description:
try:
alt_text = shape._element._nvXxPr.cNvPr.attrib.get(
"descr", ""
)
except Exception:
# Unable to get alt text
pass
# A placeholder name
filename = re.sub(r"\W", "", shape.name) + ".jpg"
md_content += (
"\n!["
+ (llm_description or alt_text or shape.name)
+ "]("
+ filename
+ ")\n"
)
# Tables
if self._is_table(shape):
html_table = "<html><body><table>"
first_row = True
for row in shape.table.rows:
html_table += "<tr>"
for cell in row.cells:
if first_row:
html_table += "<th>" + html.escape(cell.text) + "</th>"
else:
html_table += "<td>" + html.escape(cell.text) + "</td>"
html_table += "</tr>"
first_row = False
html_table += "</table></body></html>"
md_content += (
"\n" + self._convert(html_table).text_content.strip() + "\n"
)
# Charts
if shape.has_chart:
md_content += self._convert_chart_to_markdown(shape.chart)
# Text areas
elif shape.has_text_frame:
if shape == title:
md_content += "# " + shape.text.lstrip() + "\n"
else:
md_content += shape.text + "\n"
md_content = md_content.strip()
if slide.has_notes_slide:
md_content += "\n\n### Notes:\n"
notes_frame = slide.notes_slide.notes_text_frame
if notes_frame is not None:
md_content += notes_frame.text
md_content = md_content.strip()
return DocumentConverterResult(
title=None,
text_content=md_content.strip(),
)
def _is_picture(self, shape):
if shape.shape_type == pptx.enum.shapes.MSO_SHAPE_TYPE.PICTURE:
return True
if shape.shape_type == pptx.enum.shapes.MSO_SHAPE_TYPE.PLACEHOLDER:
if hasattr(shape, "image"):
return True
return False
def _is_table(self, shape):
if shape.shape_type == pptx.enum.shapes.MSO_SHAPE_TYPE.TABLE:
return True
return False
def _convert_chart_to_markdown(self, chart):
md = "\n\n### Chart"
if chart.has_title:
md += f": {chart.chart_title.text_frame.text}"
md += "\n\n"
data = []
category_names = [c.label for c in chart.plots[0].categories]
series_names = [s.name for s in chart.series]
data.append(["Category"] + series_names)
for idx, category in enumerate(category_names):
row = [category]
for series in chart.series:
row.append(series.values[idx])
data.append(row)
markdown_table = []
for row in data:
markdown_table.append("| " + " | ".join(map(str, row)) + " |")
header = markdown_table[0]
separator = "|" + "|".join(["---"] * len(data[0])) + "|"
return md + "\n".join([header, separator] + markdown_table[1:])

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from xml.dom import minidom
from typing import Union
from bs4 import BeautifulSoup
from ._markdownify import _CustomMarkdownify
from ._base import DocumentConverter, DocumentConverterResult
class RssConverter(DocumentConverter):
"""Convert RSS / Atom type to markdown"""
def convert(
self, local_path: str, **kwargs
) -> Union[None, DocumentConverterResult]:
# Bail if not RSS type
extension = kwargs.get("file_extension", "")
if extension.lower() not in [".xml", ".rss", ".atom"]:
return None
try:
doc = minidom.parse(local_path)
except BaseException as _:
return None
result = None
if doc.getElementsByTagName("rss"):
# A RSS feed must have a root element of <rss>
result = self._parse_rss_type(doc)
elif doc.getElementsByTagName("feed"):
root = doc.getElementsByTagName("feed")[0]
if root.getElementsByTagName("entry"):
# An Atom feed must have a root element of <feed> and at least one <entry>
result = self._parse_atom_type(doc)
else:
return None
else:
# not rss or atom
return None
return result
def _parse_atom_type(
self, doc: minidom.Document
) -> Union[None, DocumentConverterResult]:
"""Parse the type of an Atom feed.
Returns None if the feed type is not recognized or something goes wrong.
"""
try:
root = doc.getElementsByTagName("feed")[0]
title = self._get_data_by_tag_name(root, "title")
subtitle = self._get_data_by_tag_name(root, "subtitle")
entries = root.getElementsByTagName("entry")
md_text = f"# {title}\n"
if subtitle:
md_text += f"{subtitle}\n"
for entry in entries:
entry_title = self._get_data_by_tag_name(entry, "title")
entry_summary = self._get_data_by_tag_name(entry, "summary")
entry_updated = self._get_data_by_tag_name(entry, "updated")
entry_content = self._get_data_by_tag_name(entry, "content")
if entry_title:
md_text += f"\n## {entry_title}\n"
if entry_updated:
md_text += f"Updated on: {entry_updated}\n"
if entry_summary:
md_text += self._parse_content(entry_summary)
if entry_content:
md_text += self._parse_content(entry_content)
return DocumentConverterResult(
title=title,
text_content=md_text,
)
except BaseException as _:
return None
def _parse_rss_type(
self, doc: minidom.Document
) -> Union[None, DocumentConverterResult]:
"""Parse the type of an RSS feed.
Returns None if the feed type is not recognized or something goes wrong.
"""
try:
root = doc.getElementsByTagName("rss")[0]
channel = root.getElementsByTagName("channel")
if not channel:
return None
channel = channel[0]
channel_title = self._get_data_by_tag_name(channel, "title")
channel_description = self._get_data_by_tag_name(channel, "description")
items = channel.getElementsByTagName("item")
if channel_title:
md_text = f"# {channel_title}\n"
if channel_description:
md_text += f"{channel_description}\n"
if not items:
items = []
for item in items:
title = self._get_data_by_tag_name(item, "title")
description = self._get_data_by_tag_name(item, "description")
pubDate = self._get_data_by_tag_name(item, "pubDate")
content = self._get_data_by_tag_name(item, "content:encoded")
if title:
md_text += f"\n## {title}\n"
if pubDate:
md_text += f"Published on: {pubDate}\n"
if description:
md_text += self._parse_content(description)
if content:
md_text += self._parse_content(content)
return DocumentConverterResult(
title=channel_title,
text_content=md_text,
)
except BaseException as _:
print(traceback.format_exc())
return None
def _parse_content(self, content: str) -> str:
"""Parse the content of an RSS feed item"""
try:
# using bs4 because many RSS feeds have HTML-styled content
soup = BeautifulSoup(content, "html.parser")
return _CustomMarkdownify().convert_soup(soup)
except BaseException as _:
return content
def _get_data_by_tag_name(
self, element: minidom.Element, tag_name: str
) -> Union[str, None]:
"""Get data from first child element with the given tag name.
Returns None when no such element is found.
"""
nodes = element.getElementsByTagName(tag_name)
if not nodes:
return None
fc = nodes[0].firstChild
if fc:
return fc.data
return None

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from typing import Union
from ._base import DocumentConverterResult
from ._media_converter import MediaConverter
# Optional Transcription support
IS_AUDIO_TRANSCRIPTION_CAPABLE = False
try:
import speech_recognition as sr
IS_AUDIO_TRANSCRIPTION_CAPABLE = True
except ModuleNotFoundError:
pass
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()

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import re
from typing import Any, Union
from bs4 import BeautifulSoup
from ._base import DocumentConverter, DocumentConverterResult
from ._markdownify import _CustomMarkdownify
class WikipediaConverter(DocumentConverter):
"""Handle Wikipedia pages separately, focusing only on the main document content."""
def convert(
self, local_path: str, **kwargs: Any
) -> Union[None, DocumentConverterResult]:
# Bail if not Wikipedia
extension = kwargs.get("file_extension", "")
if extension.lower() not in [".html", ".htm"]:
return None
url = kwargs.get("url", "")
if not re.search(r"^https?:\/\/[a-zA-Z]{2,3}\.wikipedia.org\/", url):
return None
# Parse the file
soup = None
with open(local_path, "rt", encoding="utf-8") as fh:
soup = BeautifulSoup(fh.read(), "html.parser")
# Remove javascript and style blocks
for script in soup(["script", "style"]):
script.extract()
# Print only the main content
body_elm = soup.find("div", {"id": "mw-content-text"})
title_elm = soup.find("span", {"class": "mw-page-title-main"})
webpage_text = ""
main_title = None if soup.title is None else soup.title.string
if body_elm:
# What's the title
if title_elm and len(title_elm) > 0:
main_title = title_elm.string # type: ignore
assert isinstance(main_title, str)
# Convert the page
webpage_text = f"# {main_title}\n\n" + _CustomMarkdownify().convert_soup(
body_elm
)
else:
webpage_text = _CustomMarkdownify().convert_soup(soup)
return DocumentConverterResult(
title=main_title,
text_content=webpage_text,
)

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from typing import Union
import pandas as pd
from ._base import DocumentConverterResult
from ._html_converter import HtmlConverter
class XlsxConverter(HtmlConverter):
"""
Converts XLSX files to Markdown, with each sheet presented as a separate Markdown table.
"""
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not a XLSX
extension = kwargs.get("file_extension", "")
if extension.lower() != ".xlsx":
return None
sheets = pd.read_excel(local_path, sheet_name=None, engine="openpyxl")
md_content = ""
for s in sheets:
md_content += f"## {s}\n"
html_content = sheets[s].to_html(index=False)
md_content += self._convert(html_content).text_content.strip() + "\n\n"
return DocumentConverterResult(
title=None,
text_content=md_content.strip(),
)
class XlsConverter(HtmlConverter):
"""
Converts XLS files to Markdown, with each sheet presented as a separate Markdown table.
"""
def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
# Bail if not a XLS
extension = kwargs.get("file_extension", "")
if extension.lower() != ".xls":
return None
sheets = pd.read_excel(local_path, sheet_name=None, engine="xlrd")
md_content = ""
for s in sheets:
md_content += f"## {s}\n"
html_content = sheets[s].to_html(index=False)
md_content += self._convert(html_content).text_content.strip() + "\n\n"
return DocumentConverterResult(
title=None,
text_content=md_content.strip(),
)

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import re
from typing import Any, Union, Dict, List
from urllib.parse import parse_qs, urlparse
from bs4 import BeautifulSoup
from ._base import DocumentConverter, DocumentConverterResult
# Optional YouTube transcription support
try:
from youtube_transcript_api import YouTubeTranscriptApi
IS_YOUTUBE_TRANSCRIPT_CAPABLE = True
except ModuleNotFoundError:
pass
class YouTubeConverter(DocumentConverter):
"""Handle YouTube specially, focusing on the video title, description, and transcript."""
def convert(
self, local_path: str, **kwargs: Any
) -> Union[None, DocumentConverterResult]:
# Bail if not YouTube
extension = kwargs.get("file_extension", "")
if extension.lower() not in [".html", ".htm"]:
return None
url = kwargs.get("url", "")
if not url.startswith("https://www.youtube.com/watch?"):
return None
# Parse the file
soup = None
with open(local_path, "rt", encoding="utf-8") as fh:
soup = BeautifulSoup(fh.read(), "html.parser")
# Read the meta tags
assert soup.title is not None and soup.title.string is not None
metadata: Dict[str, str] = {"title": soup.title.string}
for meta in soup(["meta"]):
for a in meta.attrs:
if a in ["itemprop", "property", "name"]:
metadata[meta[a]] = meta.get("content", "")
break
# We can also try to read the full description. This is more prone to breaking, since it reaches into the page implementation
try:
for script in soup(["script"]):
content = script.text
if "ytInitialData" in content:
lines = re.split(r"\r?\n", content)
obj_start = lines[0].find("{")
obj_end = lines[0].rfind("}")
if obj_start >= 0 and obj_end >= 0:
data = json.loads(lines[0][obj_start : obj_end + 1])
attrdesc = self._findKey(data, "attributedDescriptionBodyText") # type: ignore
if attrdesc:
metadata["description"] = str(attrdesc["content"])
break
except Exception:
pass
# Start preparing the page
webpage_text = "# YouTube\n"
title = self._get(metadata, ["title", "og:title", "name"]) # type: ignore
assert isinstance(title, str)
if title:
webpage_text += f"\n## {title}\n"
stats = ""
views = self._get(metadata, ["interactionCount"]) # type: ignore
if views:
stats += f"- **Views:** {views}\n"
keywords = self._get(metadata, ["keywords"]) # type: ignore
if keywords:
stats += f"- **Keywords:** {keywords}\n"
runtime = self._get(metadata, ["duration"]) # type: ignore
if runtime:
stats += f"- **Runtime:** {runtime}\n"
if len(stats) > 0:
webpage_text += f"\n### Video Metadata\n{stats}\n"
description = self._get(metadata, ["description", "og:description"]) # type: ignore
if description:
webpage_text += f"\n### Description\n{description}\n"
if IS_YOUTUBE_TRANSCRIPT_CAPABLE:
transcript_text = ""
parsed_url = urlparse(url) # type: ignore
params = parse_qs(parsed_url.query) # type: ignore
if "v" in params:
assert isinstance(params["v"][0], str)
video_id = str(params["v"][0])
try:
youtube_transcript_languages = kwargs.get(
"youtube_transcript_languages", ("en",)
)
# Must be a single transcript.
transcript = YouTubeTranscriptApi.get_transcript(video_id, languages=youtube_transcript_languages) # type: ignore
transcript_text = " ".join([part["text"] for part in transcript]) # type: ignore
# Alternative formatting:
# formatter = TextFormatter()
# formatter.format_transcript(transcript)
except Exception:
pass
if transcript_text:
webpage_text += f"\n### Transcript\n{transcript_text}\n"
title = title if title else soup.title.string
assert isinstance(title, str)
return DocumentConverterResult(
title=title,
text_content=webpage_text,
)
def _get(
self,
metadata: Dict[str, str],
keys: List[str],
default: Union[str, None] = None,
) -> Union[str, None]:
for k in keys:
if k in metadata:
return metadata[k]
return default
def _findKey(self, json: Any, key: str) -> Union[str, None]: # TODO: Fix json type
if isinstance(json, list):
for elm in json:
ret = self._findKey(elm, key)
if ret is not None:
return ret
elif isinstance(json, dict):
for k in json:
if k == key:
return json[k]
else:
ret = self._findKey(json[k], key)
if ret is not None:
return ret
return None

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import os
import zipfile
import shutil
from typing import Any, Union
from ._base import DocumentConverter, DocumentConverterResult
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)}",
)

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# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT

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{
"key1": "string_value",
"key2": 1234,
"key3": [
"list_value1",
"list_value2"
],
"5b64c88c-b3c3-4510-bcb8-da0b200602d8": "uuid_key",
"uuid_value": "9700dc99-6685-40b4-9a3a-5e406dcb37f3"
}

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<EFBFBD><EFBFBD><EFBFBD>O,<EFBFBD>N<EFBFBD><EFBFBD>,<EFBFBD>Z<EFBFBD><EFBFBD>
<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Y,30,<EFBFBD><EFBFBD><EFBFBD><EFBFBD>
<EFBFBD>O<EFBFBD>؉p<EFBFBD>q,25,<EFBFBD><EFBFBD><EFBFBD><EFBFBD>
<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>~,35,<EFBFBD><EFBFBD><EFBFBD>É<EFBFBD>
1 –¼‘O ”N—î �Z�Š
2 �²“¡‘¾˜Y 30 “Œ‹ž
3 ŽO–؉pŽq 25 ‘å�ã
4 îà‹´�~ 35 –¼ŒÃ‰®

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{
"cells": [
{
"cell_type": "markdown",
"id": "0f61db80",
"metadata": {},
"source": [
"# Test Notebook"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "3f2a5bbd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"markitdown\n"
]
}
],
"source": [
"print('markitdown')"
]
},
{
"cell_type": "markdown",
"id": "9b9c0468",
"metadata": {},
"source": [
"## Code Cell Below"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "37d8088a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"42\n"
]
}
],
"source": [
"# comment in code\n",
"print(42)"
]
},
{
"cell_type": "markdown",
"id": "2e3177bd",
"metadata": {},
"source": [
"End\n",
"\n",
"---"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.8"
},
"title": "Test Notebook Title"
},
"nbformat": 4,
"nbformat_minor": 5
}

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#!/usr/bin/env python3 -m pytest
import io
import os
import shutil
import pytest
import requests
from warnings import catch_warnings, resetwarnings
from markitdown import MarkItDown
skip_remote = (
True if os.environ.get("GITHUB_ACTIONS") else False
) # Don't run these tests in CI
# Don't run the llm tests without a key and the client library
skip_llm = False if os.environ.get("OPENAI_API_KEY") else True
try:
import openai
except ModuleNotFoundError:
skip_llm = True
# Skip exiftool tests if not installed
skip_exiftool = shutil.which("exiftool") is None
TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
JPG_TEST_EXIFTOOL = {
"Author": "AutoGen Authors",
"Title": "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
"Description": "AutoGen enables diverse LLM-based applications",
"ImageSize": "1615x1967",
"DateTimeOriginal": "2024:03:14 22:10:00",
}
PDF_TEST_URL = "https://arxiv.org/pdf/2308.08155v2.pdf"
PDF_TEST_STRINGS = [
"While there is contemporaneous exploration of multi-agent approaches"
]
YOUTUBE_TEST_URL = "https://www.youtube.com/watch?v=V2qZ_lgxTzg"
YOUTUBE_TEST_STRINGS = [
"## AutoGen FULL Tutorial with Python (Step-By-Step)",
"This is an intermediate tutorial for installing and using AutoGen locally",
"PT15M4S",
"the model we're going to be using today is GPT 3.5 turbo", # From the transcript
]
XLSX_TEST_STRINGS = [
"## 09060124-b5e7-4717-9d07-3c046eb",
"6ff4173b-42a5-4784-9b19-f49caff4d93d",
"affc7dad-52dc-4b98-9b5d-51e65d8a8ad0",
]
XLS_TEST_STRINGS = [
"## 09060124-b5e7-4717-9d07-3c046eb",
"6ff4173b-42a5-4784-9b19-f49caff4d93d",
"affc7dad-52dc-4b98-9b5d-51e65d8a8ad0",
]
DOCX_TEST_STRINGS = [
"314b0a30-5b04-470b-b9f7-eed2c2bec74a",
"49e168b7-d2ae-407f-a055-2167576f39a1",
"## d666f1f7-46cb-42bd-9a39-9a39cf2a509f",
"# Abstract",
"# Introduction",
"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
]
MSG_TEST_STRINGS = [
"# Email Message",
"**From:** test.sender@example.com",
"**To:** test.recipient@example.com",
"**Subject:** Test Email Message",
"## Content",
"This is the body of the test email message",
]
DOCX_COMMENT_TEST_STRINGS = [
"314b0a30-5b04-470b-b9f7-eed2c2bec74a",
"49e168b7-d2ae-407f-a055-2167576f39a1",
"## d666f1f7-46cb-42bd-9a39-9a39cf2a509f",
"# Abstract",
"# Introduction",
"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
"This is a test comment. 12df-321a",
"Yet another comment in the doc. 55yiyi-asd09",
]
PPTX_TEST_STRINGS = [
"2cdda5c8-e50e-4db4-b5f0-9722a649f455",
"04191ea8-5c73-4215-a1d3-1cfb43aaaf12",
"44bf7d06-5e7a-4a40-a2e1-a2e42ef28c8a",
"1b92870d-e3b5-4e65-8153-919f4ff45592",
"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
"a3f6004b-6f4f-4ea8-bee3-3741f4dc385f", # chart title
"2003", # chart value
]
BLOG_TEST_URL = "https://microsoft.github.io/autogen/blog/2023/04/21/LLM-tuning-math"
BLOG_TEST_STRINGS = [
"Large language models (LLMs) are powerful tools that can generate natural language texts for various applications, such as chatbots, summarization, translation, and more. GPT-4 is currently the state of the art LLM in the world. Is model selection irrelevant? What about inference parameters?",
"an example where high cost can easily prevent a generic complex",
]
RSS_TEST_STRINGS = [
"The Official Microsoft Blog",
"In the case of AI, it is absolutely true that the industry is moving incredibly fast",
]
WIKIPEDIA_TEST_URL = "https://en.wikipedia.org/wiki/Microsoft"
WIKIPEDIA_TEST_STRINGS = [
"Microsoft entered the operating system (OS) business in 1980 with its own version of [Unix]",
'Microsoft was founded by [Bill Gates](/wiki/Bill_Gates "Bill Gates")',
]
WIKIPEDIA_TEST_EXCLUDES = [
"You are encouraged to create an account and log in",
"154 languages",
"move to sidebar",
]
SERP_TEST_URL = "https://www.bing.com/search?q=microsoft+wikipedia"
SERP_TEST_STRINGS = [
"](https://en.wikipedia.org/wiki/Microsoft",
"Microsoft Corporation is **an American multinational corporation and technology company headquartered** in Redmond",
"1995–2007: Foray into the Web, Windows 95, Windows XP, and Xbox",
]
SERP_TEST_EXCLUDES = [
"https://www.bing.com/ck/a?!&&p=",
"data:image/svg+xml,%3Csvg%20width%3D",
]
CSV_CP932_TEST_STRINGS = [
"名前,年齢,住所",
"佐藤太郎,30,東京",
"三木英子,25,大阪",
"髙橋淳,35,名古屋",
]
LLM_TEST_STRINGS = [
"5bda1dd6",
]
JSON_TEST_STRINGS = [
"5b64c88c-b3c3-4510-bcb8-da0b200602d8",
"9700dc99-6685-40b4-9a3a-5e406dcb37f3",
]
# --- Helper Functions ---
def validate_strings(result, expected_strings, exclude_strings=None):
"""Validate presence or absence of specific strings."""
text_content = result.text_content.replace("\\", "")
for string in expected_strings:
assert string in text_content
if exclude_strings:
for string in exclude_strings:
assert string not in text_content
@pytest.mark.skipif(
skip_remote,
reason="do not run tests that query external urls",
)
def test_markitdown_remote() -> None:
markitdown = MarkItDown()
# By URL
result = markitdown.convert(PDF_TEST_URL)
for test_string in PDF_TEST_STRINGS:
assert test_string in result.text_content
# By stream
response = requests.get(PDF_TEST_URL)
result = markitdown.convert_stream(
io.BytesIO(response.content), file_extension=".pdf", url=PDF_TEST_URL
)
for test_string in PDF_TEST_STRINGS:
assert test_string in result.text_content
# Youtube
# TODO: This test randomly fails for some reason. Haven't been able to repro it yet. Disabling until I can debug the issue
# result = markitdown.convert(YOUTUBE_TEST_URL)
# for test_string in YOUTUBE_TEST_STRINGS:
# assert test_string in result.text_content
def test_markitdown_local() -> None:
markitdown = MarkItDown()
# Test XLSX processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.xlsx"))
validate_strings(result, XLSX_TEST_STRINGS)
# Test XLS processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.xls"))
for test_string in XLS_TEST_STRINGS:
text_content = result.text_content.replace("\\", "")
assert test_string in text_content
# Test DOCX processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.docx"))
validate_strings(result, DOCX_TEST_STRINGS)
# Test DOCX processing, with comments
result = markitdown.convert(
os.path.join(TEST_FILES_DIR, "test_with_comment.docx"),
style_map="comment-reference => ",
)
validate_strings(result, DOCX_COMMENT_TEST_STRINGS)
# Test DOCX processing, with comments and setting style_map on init
markitdown_with_style_map = MarkItDown(style_map="comment-reference => ")
result = markitdown_with_style_map.convert(
os.path.join(TEST_FILES_DIR, "test_with_comment.docx")
)
validate_strings(result, DOCX_COMMENT_TEST_STRINGS)
# Test PPTX processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.pptx"))
validate_strings(result, PPTX_TEST_STRINGS)
# Test HTML processing
result = markitdown.convert(
os.path.join(TEST_FILES_DIR, "test_blog.html"), url=BLOG_TEST_URL
)
validate_strings(result, BLOG_TEST_STRINGS)
# Test ZIP file processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_files.zip"))
validate_strings(result, XLSX_TEST_STRINGS)
# Test Wikipedia processing
result = markitdown.convert(
os.path.join(TEST_FILES_DIR, "test_wikipedia.html"), url=WIKIPEDIA_TEST_URL
)
text_content = result.text_content.replace("\\", "")
validate_strings(result, WIKIPEDIA_TEST_STRINGS, WIKIPEDIA_TEST_EXCLUDES)
# Test Bing processing
result = markitdown.convert(
os.path.join(TEST_FILES_DIR, "test_serp.html"), url=SERP_TEST_URL
)
text_content = result.text_content.replace("\\", "")
validate_strings(result, SERP_TEST_STRINGS, SERP_TEST_EXCLUDES)
# Test RSS processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_rss.xml"))
text_content = result.text_content.replace("\\", "")
for test_string in RSS_TEST_STRINGS:
assert test_string in text_content
## Test non-UTF-8 encoding
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_mskanji.csv"))
validate_strings(result, CSV_CP932_TEST_STRINGS)
# Test MSG (Outlook email) processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_outlook_msg.msg"))
validate_strings(result, MSG_TEST_STRINGS)
# Test JSON processing
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.json"))
validate_strings(result, JSON_TEST_STRINGS)
# Test input with leading blank characters
input_data = b" \n\n\n<html><body><h1>Test</h1></body></html>"
result = markitdown.convert_stream(io.BytesIO(input_data))
assert "# Test" in result.text_content
@pytest.mark.skipif(
skip_exiftool,
reason="do not run if exiftool is not installed",
)
def test_markitdown_exiftool() -> None:
# Test the automatic discovery of exiftool throws a warning
# and is disabled
try:
with catch_warnings(record=True) as w:
markitdown = MarkItDown()
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.jpg"))
assert len(w) == 1
assert w[0].category is DeprecationWarning
assert result.text_content.strip() == ""
finally:
resetwarnings()
# Test explicitly setting the location of exiftool
which_exiftool = shutil.which("exiftool")
markitdown = MarkItDown(exiftool_path=which_exiftool)
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.jpg"))
for key in JPG_TEST_EXIFTOOL:
target = f"{key}: {JPG_TEST_EXIFTOOL[key]}"
assert target in result.text_content
# Test setting the exiftool path through an environment variable
os.environ["EXIFTOOL_PATH"] = which_exiftool
markitdown = MarkItDown()
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.jpg"))
for key in JPG_TEST_EXIFTOOL:
target = f"{key}: {JPG_TEST_EXIFTOOL[key]}"
assert target in result.text_content
@pytest.mark.skipif(
skip_llm,
reason="do not run llm tests without a key",
)
def test_markitdown_llm() -> None:
client = openai.OpenAI()
markitdown = MarkItDown(llm_client=client, llm_model="gpt-4o")
result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_llm.jpg"))
for test_string in LLM_TEST_STRINGS:
assert test_string in result.text_content
# This is not super precise. It would also accept "red square", "blue circle",
# "the square is not blue", etc. But it's sufficient for this test.
for test_string in ["red", "circle", "blue", "square"]:
assert test_string in result.text_content.lower()
if __name__ == "__main__":
"""Runs this file's tests from the command line."""
# test_markitdown_remote()
# test_markitdown_local()
test_markitdown_exiftool()
# test_markitdown_deprecation()
# test_markitdown_llm()