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18 Commits

Author SHA1 Message Date
Kenny Zhang 4e0a10ecf3 ran unit tests locally 2025-02-27 16:44:50 -05:00
Kenny Zhang 950b135da6 formatting 2025-02-27 15:08:10 -05:00
Kenny Zhang b671345bb9 updated readme 2025-02-27 15:07:46 -05:00
Kenny Zhang d9a92f7f06 added file obj unit tests for rss and json 2025-02-27 15:05:29 -05:00
Kenny Zhang db0c8acbaf added file obj support to rss and plain text converters 2025-02-27 14:55:49 -05:00
Kenny Zhang 08330c2ac3 added core unit tests for file obj support 2025-02-27 11:27:05 -05:00
Kenny Zhang 4afc1fe886 added non-binary example to README 2025-02-21 13:31:37 -05:00
Kenny Zhang b0044720da updated docs 2025-02-20 16:56:47 -05:00
Kenny Zhang 07a28d4f00 black formatting 2025-02-20 16:49:37 -05:00
Kenny Zhang b8b3897952 modify ext guesser 2025-02-20 16:47:37 -05:00
Kenny Zhang 395ce2d301 close file object after using 2025-02-20 13:54:51 -05:00
Kenny Zhang 808401a331 added conversion path for file object in central class 2025-02-19 17:02:51 -05:00
Kenny Zhang e75f3f6f5b local path inputs to MarkitDown class adhere to new converterinput structure 2025-02-19 15:16:45 -05:00
Kenny Zhang 8e950325d2 refactored remaining converters 2025-02-19 14:01:43 -05:00
Kenny Zhang 096fef3d5f refactored more converters to support input class 2025-02-19 13:34:28 -05:00
Kenny Zhang 52cbff061a begin refactoring converter classes 2025-02-19 11:48:00 -05:00
Kenny Zhang 0027e6d425 added wrapper class for converter file input 2025-02-18 12:44:18 -05:00
Kenny Zhang 63a7bafadd removed redundant priority setting 2025-02-18 12:18:49 -05:00
142 changed files with 2128 additions and 14425 deletions
-1
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@@ -1,2 +1 @@
* *
!packages/
+1 -5
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@@ -1,5 +1 @@
packages/markitdown/tests/test_files/** linguist-vendored tests/test_files/** linguist-vendored
packages/markitdown-sample-plugin/tests/test_files/** linguist-vendored
# Treat PDF files as binary to prevent line ending conversion
*.pdf binary
+1 -1
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@@ -5,7 +5,7 @@ jobs:
pre-commit: pre-commit:
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- uses: actions/checkout@v5 - uses: actions/checkout@v4
- name: Set up Python - name: Set up Python
uses: actions/setup-python@v5 uses: actions/setup-python@v5
with: with:
+1 -1
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@@ -5,7 +5,7 @@ jobs:
tests: tests:
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- uses: actions/checkout@v5 - uses: actions/checkout@v4
- uses: actions/setup-python@v5 - uses: actions/setup-python@v5
with: with:
python-version: | python-version: |
-2
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@@ -52,7 +52,6 @@ coverage.xml
.hypothesis/ .hypothesis/
.pytest_cache/ .pytest_cache/
cover/ cover/
.test-logs/
# Translations # Translations
*.mo *.mo
@@ -165,4 +164,3 @@ cython_debug/
#.idea/ #.idea/
src/.DS_Store src/.DS_Store
.DS_Store .DS_Store
.cursorrules
+10 -20
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@@ -1,32 +1,22 @@
FROM python:3.13-slim-bullseye FROM python:3.13-slim-bullseye
ENV DEBIAN_FRONTEND=noninteractive USER root
ENV EXIFTOOL_PATH=/usr/bin/exiftool
ENV FFMPEG_PATH=/usr/bin/ffmpeg ARG INSTALL_GIT=false
RUN if [ "$INSTALL_GIT" = "true" ]; then \
apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*; \
fi
# Runtime dependency # Runtime dependency
RUN apt-get update && apt-get install -y --no-install-recommends \ RUN apt-get update && apt-get install -y --no-install-recommends \
ffmpeg \ ffmpeg \
exiftool && rm -rf /var/lib/apt/lists/*
ARG INSTALL_GIT=false RUN pip install markitdown
RUN if [ "$INSTALL_GIT" = "true" ]; then \
apt-get install -y --no-install-recommends \
git; \
fi
# Cleanup
RUN rm -rf /var/lib/apt/lists/*
WORKDIR /app
COPY . /app
RUN pip --no-cache-dir install \
/app/packages/markitdown[all] \
/app/packages/markitdown-sample-plugin
# Default USERID and GROUPID # Default USERID and GROUPID
ARG USERID=nobody ARG USERID=10000
ARG GROUPID=nogroup ARG GROUPID=10000
USER $USERID:$GROUPID USER $USERID:$GROUPID
+31 -113
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@@ -5,12 +5,10 @@
[![Built by AutoGen Team](https://img.shields.io/badge/Built%20by-AutoGen%20Team-blue)](https://github.com/microsoft/autogen) [![Built by AutoGen Team](https://img.shields.io/badge/Built%20by-AutoGen%20Team-blue)](https://github.com/microsoft/autogen)
> [!IMPORTANT] > [!IMPORTANT]
> MarkItDown performs I/O with the privileges of the current process. Like open() or requests.get(), it will access resources that the process itself can access. Sanitize your inputs in untrusted environments, and call the narrowest `convert_*` function needed for your use case (e.g., `convert_stream()`, or `convert_local()`). See the [Security Considerations](#security-considerations) section of the documentation for more information. > MarkItDown 0.0.2 alpha 1 (0.0.2a1) introduces a plugin-based architecture. As much as was possible, command-line and Python interfaces have remained the same as 0.0.1a3 to support backward compatibility. Please report any issues you encounter. Some interface changes may yet occur as we continue to refine MarkItDown to a first non-alpha release.
MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. To this end, it is most comparable to [textract](https://github.com/deanmalmgren/textract), but with a focus on preserving important document structure and content as Markdown (including: headings, lists, tables, links, etc.) While the output is often reasonably presentable and human-friendly, it is meant to be consumed by text analysis tools -- and may not be the best option for high-fidelity document conversions for human consumption.
MarkItDown currently supports the conversion from:
MarkItDown is a utility for converting various files to Markdown (e.g., for indexing, text analysis, etc).
It supports:
- PDF - PDF
- PowerPoint - PowerPoint
- Word - Word
@@ -20,52 +18,14 @@ MarkItDown currently supports the conversion from:
- HTML - HTML
- Text-based formats (CSV, JSON, XML) - Text-based formats (CSV, JSON, XML)
- ZIP files (iterates over contents) - ZIP files (iterates over contents)
- Youtube URLs
- EPubs
- ... and more! - ... and more!
## Why Markdown? To install MarkItDown, use pip: `pip install markitdown`. Alternatively, you can install it from the source:
Markdown is extremely close to plain text, with minimal markup or formatting, but still
provides a way to represent important document structure. Mainstream LLMs, such as
OpenAI's GPT-4o, natively "_speak_" Markdown, and often incorporate Markdown into their
responses unprompted. This suggests that they have been trained on vast amounts of
Markdown-formatted text, and understand it well. As a side benefit, Markdown conventions
are also highly token-efficient.
## Prerequisites
MarkItDown requires Python 3.10 or higher. It is recommended to use a virtual environment to avoid dependency conflicts.
With the standard Python installation, you can create and activate a virtual environment using the following commands:
```bash
python -m venv .venv
source .venv/bin/activate
```
If using `uv`, you can create a virtual environment with:
```bash
uv venv --python=3.12 .venv
source .venv/bin/activate
# NOTE: Be sure to use 'uv pip install' rather than just 'pip install' to install packages in this virtual environment
```
If you are using Anaconda, you can create a virtual environment with:
```bash
conda create -n markitdown python=3.12
conda activate markitdown
```
## Installation
To install MarkItDown, use pip: `pip install 'markitdown[all]'`. Alternatively, you can install it from the source:
```bash ```bash
git clone git@github.com:microsoft/markitdown.git git clone git@github.com:microsoft/markitdown.git
cd markitdown cd markitdown
pip install -e 'packages/markitdown[all]' pip install -e packages/markitdown
``` ```
## Usage ## Usage
@@ -88,28 +48,6 @@ You can also pipe content:
cat path-to-file.pdf | markitdown cat path-to-file.pdf | markitdown
``` ```
### Optional Dependencies
MarkItDown has optional dependencies for activating various file formats. Earlier in this document, we installed all optional dependencies with the `[all]` option. However, you can also install them individually for more control. For example:
```bash
pip install 'markitdown[pdf, docx, pptx]'
```
will install only the dependencies for PDF, DOCX, and PPTX files.
At the moment, the following optional dependencies are available:
* `[all]` Installs all optional dependencies
* `[pptx]` Installs dependencies for PowerPoint files
* `[docx]` Installs dependencies for Word files
* `[xlsx]` Installs dependencies for Excel files
* `[xls]` Installs dependencies for older Excel files
* `[pdf]` Installs dependencies for PDF files
* `[outlook]` Installs dependencies for Outlook messages
* `[az-doc-intel]` Installs dependencies for Azure Document Intelligence
* `[audio-transcription]` Installs dependencies for audio transcription of wav and mp3 files
* `[youtube-transcription]` Installs dependencies for fetching YouTube video transcription
### Plugins ### Plugins
MarkItDown also supports 3rd-party plugins. Plugins are disabled by default. To list installed plugins: MarkItDown also supports 3rd-party plugins. Plugins are disabled by default. To list installed plugins:
@@ -126,38 +64,6 @@ markitdown --use-plugins path-to-file.pdf
To find available plugins, search GitHub for the hashtag `#markitdown-plugin`. To develop a plugin, see `packages/markitdown-sample-plugin`. To find available plugins, search GitHub for the hashtag `#markitdown-plugin`. To develop a plugin, see `packages/markitdown-sample-plugin`.
#### markitdown-ocr Plugin
The `markitdown-ocr` plugin adds OCR support to PDF, DOCX, PPTX, and XLSX converters, extracting text from embedded images using LLM Vision — the same `llm_client` / `llm_model` pattern that MarkItDown already uses for image descriptions. No new ML libraries or binary dependencies required.
**Installation:**
```bash
pip install markitdown-ocr
pip install openai # or any OpenAI-compatible client
```
**Usage:**
Pass the same `llm_client` and `llm_model` you would use for image descriptions:
```python
from markitdown import MarkItDown
from openai import OpenAI
md = MarkItDown(
enable_plugins=True,
llm_client=OpenAI(),
llm_model="gpt-4o",
)
result = md.convert("document_with_images.pdf")
print(result.text_content)
```
If no `llm_client` is provided the plugin still loads, but OCR is silently skipped and the standard built-in converter is used instead.
See [`packages/markitdown-ocr/README.md`](packages/markitdown-ocr/README.md) for detailed documentation.
### Azure Document Intelligence ### Azure Document Intelligence
To use Microsoft Document Intelligence for conversion: To use Microsoft Document Intelligence for conversion:
@@ -168,6 +74,7 @@ markitdown path-to-file.pdf -o document.md -d -e "<document_intelligence_endpoin
More information about how to set up an Azure Document Intelligence Resource can be found [here](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/how-to-guides/create-document-intelligence-resource?view=doc-intel-4.0.0) More information about how to set up an Azure Document Intelligence Resource can be found [here](https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/how-to-guides/create-document-intelligence-resource?view=doc-intel-4.0.0)
### Python API ### Python API
Basic usage in Python: Basic usage in Python:
@@ -190,14 +97,33 @@ result = md.convert("test.pdf")
print(result.text_content) print(result.text_content)
``` ```
To use Large Language Models for image descriptions (currently only for pptx and image files), provide `llm_client` and `llm_model`: MarkItDown also supports converting file objects directly:
```python
from markitdown import MarkItDown
md = MarkItDown()
# Providing the file extension when converting via file objects is recommended for most consistent results
# Binary Mode
with open("test.docx", 'rb') as file:
result = md.convert(file, file_extension=".docx")
print(result.text_content)
# Non-Binary Mode
with open("sample.ipynb", 'rt', encoding="utf-8") as file:
result = md.convert(file, file_extension=".ipynb")
print(result.text_content)
```
To use Large Language Models for image descriptions, provide `llm_client` and `llm_model`:
```python ```python
from markitdown import MarkItDown from markitdown import MarkItDown
from openai import OpenAI from openai import OpenAI
client = OpenAI() client = OpenAI()
md = MarkItDown(llm_client=client, llm_model="gpt-4o", llm_prompt="optional custom prompt") md = MarkItDown(llm_client=client, llm_model="gpt-4o")
result = md.convert("example.jpg") result = md.convert("example.jpg")
print(result.text_content) print(result.text_content)
``` ```
@@ -225,12 +151,13 @@ contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additio
### How to Contribute ### How to Contribute
You can help by looking at issues or helping review PRs. Any issue or PR is welcome, but we have also marked some as 'open for contribution' and 'open for reviewing' to help facilitate community contributions. These are of course just suggestions and you are welcome to contribute in any way you like. You can help by looking at issues or helping review PRs. Any issue or PR is welcome, but we have also marked some as 'open for contribution' and 'open for reviewing' to help facilitate community contributions. These are ofcourse just suggestions and you are welcome to contribute in any way you like.
<div align="center"> <div align="center">
| | All | Especially Needs Help from Community | | | All | Especially Needs Help from Community |
| ---------- | ------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------- | |-----------------------|------------------------------------------|------------------------------------------------------------------------------------------|
| **Issues** | [All Issues](https://github.com/microsoft/markitdown/issues) | [Issues open for contribution](https://github.com/microsoft/markitdown/issues?q=is%3Aissue+is%3Aopen+label%3A%22open+for+contribution%22) | | **Issues** | [All Issues](https://github.com/microsoft/markitdown/issues) | [Issues open for contribution](https://github.com/microsoft/markitdown/issues?q=is%3Aissue+is%3Aopen+label%3A%22open+for+contribution%22) |
| **PRs** | [All PRs](https://github.com/microsoft/markitdown/pulls) | [PRs open for reviewing](https://github.com/microsoft/markitdown/pulls?q=is%3Apr+is%3Aopen+label%3A%22open+for+reviewing%22) | | **PRs** | [All PRs](https://github.com/microsoft/markitdown/pulls) | [PRs open for reviewing](https://github.com/microsoft/markitdown/pulls?q=is%3Apr+is%3Aopen+label%3A%22open+for+reviewing%22) |
@@ -245,7 +172,6 @@ You can help by looking at issues or helping review PRs. Any issue or PR is welc
``` ```
- Install `hatch` in your environment and run tests: - Install `hatch` in your environment and run tests:
```sh ```sh
pip install hatch # Other ways of installing hatch: https://hatch.pypa.io/dev/install/ pip install hatch # Other ways of installing hatch: https://hatch.pypa.io/dev/install/
hatch shell hatch shell
@@ -253,7 +179,6 @@ You can help by looking at issues or helping review PRs. Any issue or PR is welc
``` ```
(Alternative) Use the Devcontainer which has all the dependencies installed: (Alternative) Use the Devcontainer which has all the dependencies installed:
```sh ```sh
# Reopen the project in Devcontainer and run: # Reopen the project in Devcontainer and run:
hatch test hatch test
@@ -261,18 +186,11 @@ You can help by looking at issues or helping review PRs. Any issue or PR is welc
- Run pre-commit checks before submitting a PR: `pre-commit run --all-files` - Run pre-commit checks before submitting a PR: `pre-commit run --all-files`
### Security Considerations
MarkItDown performs I/O with the privileges of the current process. Like `open()` or `requests.get()`, it will access resources that the process itself can access.
**Sanitize your inputs:** Do not pass untrusted input directly to MarkItDown. If any part of the input may be controlled by an untrusted user or system, such as in hosted or server-side applications, it must be validated and restricted before calling MarkItDown. Depending on your environment, this may include restricting file paths, limiting URI schemes and network destinations, and blocking access to private, loopback, link-local, or metadata-service addresses.
**Call only the conversion method you need:** Prefer the narrowest conversion API that fits your use case. MarkItDown's `convert()` method is intentionally permissive and can handle local files, remote URIs, and byte streams. If your application only needs to read local files, call `convert_local()` instead. If you need more control over URI fetching, call `requests.get()` yourself and pass the response object to `convert_response()`. For maximum control, open a stream to the input you want converted and call `convert_stream()`.
### Contributing 3rd-party Plugins ### Contributing 3rd-party Plugins
You can also contribute by creating and sharing 3rd party plugins. See `packages/markitdown-sample-plugin` for more details. You can also contribute by creating and sharing 3rd party plugins. See `packages/markitdown-sample-plugin` for more details.
## Trademarks ## Trademarks
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft
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@@ -1,28 +0,0 @@
FROM python:3.13-slim-bullseye
ENV DEBIAN_FRONTEND=noninteractive
ENV EXIFTOOL_PATH=/usr/bin/exiftool
ENV FFMPEG_PATH=/usr/bin/ffmpeg
ENV MARKITDOWN_ENABLE_PLUGINS=True
# Runtime dependency
# NOTE: Add any additional MarkItDown plugins here
RUN apt-get update && apt-get install -y --no-install-recommends \
ffmpeg \
exiftool
# Cleanup
RUN rm -rf /var/lib/apt/lists/*
COPY . /app
RUN pip --no-cache-dir install /app
WORKDIR /workdir
# Default USERID and GROUPID
ARG USERID=nobody
ARG GROUPID=nogroup
USER $USERID:$GROUPID
ENTRYPOINT [ "markitdown-mcp" ]
-142
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@@ -1,142 +0,0 @@
# MarkItDown-MCP
> [!IMPORTANT]
> The MarkItDown-MCP package is meant for **local use**, with local trusted agents. In particular, when running the MCP server with Streamable HTTP or SSE, it binds to `localhost` by default, and is not exposed to other machines on the network or Internet. In this configuration, it is meant to be a direct alternative to the STDIO transport, which may be more convenient in some cases. DO NOT bind the server to other interfaces unless you understand the [security implications](#security-considerations) of doing so.
[![PyPI](https://img.shields.io/pypi/v/markitdown-mcp.svg)](https://pypi.org/project/markitdown-mcp/)
![PyPI - Downloads](https://img.shields.io/pypi/dd/markitdown-mcp)
[![Built by AutoGen Team](https://img.shields.io/badge/Built%20by-AutoGen%20Team-blue)](https://github.com/microsoft/autogen)
The `markitdown-mcp` package provides a lightweight STDIO, Streamable HTTP, and SSE MCP server for calling MarkItDown.
It exposes one tool: `convert_to_markdown(uri)`, where uri can be any `http:`, `https:`, `file:`, or `data:` URI.
## Installation
To install the package, use pip:
```bash
pip install markitdown-mcp
```
## Usage
To run the MCP server, using STDIO (default), use the following command:
```bash
markitdown-mcp
```
To run the MCP server, using Streamable HTTP and SSE, use the following command:
```bash
markitdown-mcp --http --host 127.0.0.1 --port 3001
```
## Running in Docker
To run `markitdown-mcp` in Docker, build the Docker image using the provided Dockerfile:
```bash
docker build -t markitdown-mcp:latest .
```
And run it using:
```bash
docker run -it --rm markitdown-mcp:latest
```
This will be sufficient for remote URIs. To access local files, you need to mount the local directory into the container. For example, if you want to access files in `/home/user/data`, you can run:
```bash
docker run -it --rm -v /home/user/data:/workdir markitdown-mcp:latest
```
Once mounted, all files under data will be accessible under `/workdir` in the container. For example, if you have a file `example.txt` in `/home/user/data`, it will be accessible in the container at `/workdir/example.txt`.
## Accessing from Claude Desktop
It is recommended to use the Docker image when running the MCP server for Claude Desktop.
Follow [these instructions](https://modelcontextprotocol.io/quickstart/user#for-claude-desktop-users) to access Claude's `claude_desktop_config.json` file.
Edit it to include the following JSON entry:
```json
{
"mcpServers": {
"markitdown": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"markitdown-mcp:latest"
]
}
}
}
```
If you want to mount a directory, adjust it accordingly:
```json
{
"mcpServers": {
"markitdown": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-v",
"/home/user/data:/workdir",
"markitdown-mcp:latest"
]
}
}
}
```
## Debugging
To debug the MCP server you can use the `MCP Inspector` tool.
```bash
npx @modelcontextprotocol/inspector
```
You can then connect to the inspector through the specified host and port (e.g., `http://localhost:5173/`).
If using STDIO:
* select `STDIO` as the transport type,
* input `markitdown-mcp` as the command, and
* click `Connect`
If using Streamable HTTP:
* select `Streamable HTTP` as the transport type,
* input `http://127.0.0.1:3001/mcp` as the URL, and
* click `Connect`
If using SSE:
* select `SSE` as the transport type,
* input `http://127.0.0.1:3001/sse` as the URL, and
* click `Connect`
Finally:
* click the `Tools` tab,
* click `List Tools`,
* click `convert_to_markdown`, and
* run the tool on any valid URI.
## Security Considerations
The server does not support authentication, and runs with the privileges of the user running it. For this reason, when running in SSE or Streamable HTTP mode, the server binds by default to `localhost`. Even still, it is important to recognize that the server can be accessed by any process or users on the same local machine, and that the `convert_to_markdown` tool can be used to read any file that the server's user has access to, or any data from the network. If you require additional security, consider running the server in a sandboxed environment, such as a virtual machine or container, and ensure that the user permissions are properly configured to limit access to sensitive files and network segments. Above all, DO NOT bind the server to other interfaces (non-localhost) unless you understand the security implications of doing so.
## 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.
-69
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@@ -1,69 +0,0 @@
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "markitdown-mcp"
dynamic = ["version"]
description = 'An MCP server 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 = [
"mcp~=1.8.0",
"markitdown[all]>=0.1.1,<0.2.0",
]
[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_mcp/__about__.py"
[project.scripts]
markitdown-mcp = "markitdown_mcp.__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_mcp tests}"
[tool.coverage.run]
source_pkgs = ["markitdown-mcp", "tests"]
branch = true
parallel = true
omit = [
"src/markitdown_mcp/__about__.py",
]
[tool.coverage.paths]
markitdown-mcp = ["src/markitdown_mcp", "*/markitdown-mcp/src/markitdown_mcp"]
tests = ["tests", "*/markitdown-mcp/tests"]
[tool.coverage.report]
exclude_lines = [
"no cov",
"if __name__ == .__main__.:",
"if TYPE_CHECKING:",
]
[tool.hatch.build.targets.sdist]
only-include = ["src/markitdown_mcp"]
@@ -1,4 +0,0 @@
# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
__version__ = "0.0.1a5"
@@ -1,9 +0,0 @@
# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
from .__about__ import __version__
__all__ = [
"__version__",
]
@@ -1,140 +0,0 @@
import contextlib
import sys
import os
from collections.abc import AsyncIterator
from mcp.server.fastmcp import FastMCP
from starlette.applications import Starlette
from mcp.server.sse import SseServerTransport
from starlette.requests import Request
from starlette.routing import Mount, Route
from starlette.types import Receive, Scope, Send
from mcp.server import Server
from mcp.server.streamable_http_manager import StreamableHTTPSessionManager
from markitdown import MarkItDown
import uvicorn
# Initialize FastMCP server for MarkItDown (SSE)
mcp = FastMCP("markitdown")
@mcp.tool()
async def convert_to_markdown(uri: str) -> str:
"""Convert a resource described by an http:, https:, file: or data: URI to markdown"""
return MarkItDown(enable_plugins=check_plugins_enabled()).convert_uri(uri).markdown
def check_plugins_enabled() -> bool:
return os.getenv("MARKITDOWN_ENABLE_PLUGINS", "false").strip().lower() in (
"true",
"1",
"yes",
)
def create_starlette_app(mcp_server: Server, *, debug: bool = False) -> Starlette:
sse = SseServerTransport("/messages/")
session_manager = StreamableHTTPSessionManager(
app=mcp_server,
event_store=None,
json_response=True,
stateless=True,
)
async def handle_sse(request: Request) -> None:
async with sse.connect_sse(
request.scope,
request.receive,
request._send,
) as (read_stream, write_stream):
await mcp_server.run(
read_stream,
write_stream,
mcp_server.create_initialization_options(),
)
async def handle_streamable_http(
scope: Scope, receive: Receive, send: Send
) -> None:
await session_manager.handle_request(scope, receive, send)
@contextlib.asynccontextmanager
async def lifespan(app: Starlette) -> AsyncIterator[None]:
"""Context manager for session manager."""
async with session_manager.run():
print("Application started with StreamableHTTP session manager!")
try:
yield
finally:
print("Application shutting down...")
return Starlette(
debug=debug,
routes=[
Route("/sse", endpoint=handle_sse),
Mount("/mcp", app=handle_streamable_http),
Mount("/messages/", app=sse.handle_post_message),
],
lifespan=lifespan,
)
# Main entry point
def main():
import argparse
mcp_server = mcp._mcp_server
parser = argparse.ArgumentParser(description="Run a MarkItDown MCP server")
parser.add_argument(
"--http",
action="store_true",
help="Run the server with Streamable HTTP and SSE transport rather than STDIO (default: False)",
)
parser.add_argument(
"--sse",
action="store_true",
help="(Deprecated) An alias for --http (default: False)",
)
parser.add_argument(
"--host", default=None, help="Host to bind to (default: 127.0.0.1)"
)
parser.add_argument(
"--port", type=int, default=None, help="Port to listen on (default: 3001)"
)
args = parser.parse_args()
use_http = args.http or args.sse
if not use_http and (args.host or args.port):
parser.error(
"Host and port arguments are only valid when using streamable HTTP or SSE transport (see: --http)."
)
sys.exit(1)
if use_http:
host = args.host if args.host else "127.0.0.1"
if args.host and args.host not in ("127.0.0.1", "localhost"):
print(
"\n"
"WARNING: The server is being bound to a non-localhost interface "
f"({host}).\n"
"This exposes the server to other machines on the network or Internet.\n"
"The server has NO authentication and runs with your user's privileges.\n"
"Any process or user that can reach this interface can read files and\n"
"fetch network resources accessible to this user.\n"
"Only proceed if you understand the security implications.\n",
file=sys.stderr,
)
starlette_app = create_starlette_app(mcp_server, debug=True)
uvicorn.run(
starlette_app,
host=host,
port=args.port if args.port else 3001,
)
else:
mcp.run()
if __name__ == "__main__":
main()
@@ -1,3 +0,0 @@
# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
#
# SPDX-License-Identifier: MIT
-21
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@@ -1,21 +0,0 @@
MIT License
Copyright (c) Microsoft Corporation.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE
-200
View File
@@ -1,200 +0,0 @@
# MarkItDown OCR Plugin
LLM Vision plugin for MarkItDown that extracts text from images embedded in PDF, DOCX, PPTX, and XLSX files.
Uses the same `llm_client` / `llm_model` pattern that MarkItDown already supports for image descriptions — no new ML libraries or binary dependencies required.
## Features
- **Enhanced PDF Converter**: Extracts text from images within PDFs, with full-page OCR fallback for scanned documents
- **Enhanced DOCX Converter**: OCR for images in Word documents
- **Enhanced PPTX Converter**: OCR for images in PowerPoint presentations
- **Enhanced XLSX Converter**: OCR for images in Excel spreadsheets
- **Context Preservation**: Maintains document structure and flow when inserting extracted text
## Installation
```bash
pip install markitdown-ocr
```
The plugin uses whatever OpenAI-compatible client you already have. Install one if you don't have it yet:
```bash
pip install openai
```
## Usage
### Command Line
```bash
markitdown document.pdf --use-plugins --llm-client openai --llm-model gpt-4o
```
### Python API
Pass `llm_client` and `llm_model` to `MarkItDown()` exactly as you would for image descriptions:
```python
from markitdown import MarkItDown
from openai import OpenAI
md = MarkItDown(
enable_plugins=True,
llm_client=OpenAI(),
llm_model="gpt-4o",
)
result = md.convert("document_with_images.pdf")
print(result.text_content)
```
If no `llm_client` is provided the plugin still loads, but OCR is silently skipped — falling back to the standard built-in converter.
### Custom Prompt
Override the default extraction prompt for specialized documents:
```python
md = MarkItDown(
enable_plugins=True,
llm_client=OpenAI(),
llm_model="gpt-4o",
llm_prompt="Extract all text from this image, preserving table structure.",
)
```
### Any OpenAI-Compatible Client
Works with any client that follows the OpenAI API:
```python
from openai import AzureOpenAI
md = MarkItDown(
enable_plugins=True,
llm_client=AzureOpenAI(
api_key="...",
azure_endpoint="https://your-resource.openai.azure.com/",
api_version="2024-02-01",
),
llm_model="gpt-4o",
)
```
## How It Works
When `MarkItDown(enable_plugins=True, llm_client=..., llm_model=...)` is called:
1. MarkItDown discovers the plugin via the `markitdown.plugin` entry point group
2. It calls `register_converters()`, forwarding all kwargs including `llm_client` and `llm_model`
3. The plugin creates an `LLMVisionOCRService` from those kwargs
4. Four OCR-enhanced converters are registered at **priority -1.0** — before the built-in converters at priority 0.0
When a file is converted:
1. The OCR converter accepts the file
2. It extracts embedded images from the document
3. Each image is sent to the LLM with an extraction prompt
4. The returned text is inserted inline, preserving document structure
5. If the LLM call fails, conversion continues without that image's text
## Supported File Formats
### PDF
- Embedded images are extracted by position (via `page.images` / page XObjects) and OCR'd inline, interleaved with the surrounding text in vertical reading order.
- **Scanned PDFs** (pages with no extractable text) are detected automatically: each page is rendered at 300 DPI and sent to the LLM as a full-page image.
- **Malformed PDFs** that pdfplumber/pdfminer cannot open (e.g. truncated EOF) are retried with PyMuPDF page rendering, so content is still recovered.
### DOCX
- Images are extracted via document part relationships (`doc.part.rels`).
- OCR is run before the DOCX→HTML→Markdown pipeline executes: placeholder tokens are injected into the HTML so that the markdown converter does not escape the OCR markers, and the final placeholders are replaced with the formatted `*[Image OCR]...[End OCR]*` blocks after conversion.
- Document flow (headings, paragraphs, tables) is fully preserved around the OCR blocks.
### PPTX
- Picture shapes, placeholder shapes with images, and images inside groups are all supported.
- Shapes are processed in top-to-left reading order per slide.
- If an `llm_client` is configured, the LLM is asked for a description first; OCR is used as the fallback when no description is returned.
### XLSX
- Images embedded in worksheets (`sheet._images`) are extracted per sheet.
- Cell position is calculated from the image anchor coordinates (column/row → Excel letter notation).
- Images are listed under a `### Images in this sheet:` section after the sheet's data table — they are not interleaved into the table rows.
### Output format
Every extracted OCR block is wrapped as:
```text
*[Image OCR]
<extracted text>
[End OCR]*
```
## Troubleshooting
### OCR text missing from output
The most likely cause is a missing `llm_client` or `llm_model`. Verify:
```python
from openai import OpenAI
from markitdown import MarkItDown
md = MarkItDown(
enable_plugins=True,
llm_client=OpenAI(), # required
llm_model="gpt-4o", # required
)
```
### Plugin not loading
Confirm the plugin is installed and discovered:
```bash
markitdown --list-plugins # should show: ocr
```
### API errors
The plugin propagates LLM API errors as warnings and continues conversion. Check your API key, quota, and that the chosen model supports vision inputs.
## Development
### Running Tests
```bash
cd packages/markitdown-ocr
pytest tests/ -v
```
### Building from Source
```bash
git clone https://github.com/microsoft/markitdown.git
cd markitdown/packages/markitdown-ocr
pip install -e .
```
## Contributing
Contributions are welcome! See the [MarkItDown repository](https://github.com/microsoft/markitdown) for guidelines.
## License
MIT — see [LICENSE](LICENSE).
## Changelog
### 0.1.0 (Initial Release)
- LLM Vision OCR for PDF, DOCX, PPTX, XLSX
- Full-page OCR fallback for scanned PDFs
- Context-aware inline text insertion
- Priority-based converter replacement (no code changes required)
-57
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@@ -1,57 +0,0 @@
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "markitdown-ocr"
dynamic = ["version"]
description = 'OCR plugin for MarkItDown - Extracts text from images in PDF, DOCX, PPTX, and XLSX via LLM Vision'
readme = "README.md"
requires-python = ">=3.10"
license = "MIT"
keywords = ["markitdown", "ocr", "pdf", "docx", "xlsx", "pptx", "llm", "vision"]
authors = [
{ name = "Contributors", email = "noreply@github.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",
]
# Core dependencies — matches the file-format libraries markitdown already uses
dependencies = [
"markitdown>=0.1.0",
"pdfminer.six>=20251230",
"pdfplumber>=0.11.9",
"PyMuPDF>=1.24.0",
"mammoth~=1.11.0",
"python-docx",
"python-pptx",
"pandas",
"openpyxl",
"Pillow>=9.0.0",
]
# llm_client is passed in by the user (same as for markitdown image descriptions);
# install openai or any OpenAI-compatible SDK separately.
[project.optional-dependencies]
llm = [
"openai>=1.0.0",
]
[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_ocr/__about__.py"
# CRITICAL: Plugin entry point - MarkItDown will discover this plugin through this entry point
[project.entry-points."markitdown.plugin"]
ocr = "markitdown_ocr"
@@ -1,4 +0,0 @@
# SPDX-FileCopyrightText: 2025-present Contributors
# SPDX-License-Identifier: MIT
__version__ = "0.1.0"
@@ -1,31 +0,0 @@
# SPDX-FileCopyrightText: 2025-present Contributors
# SPDX-License-Identifier: MIT
"""
markitdown-ocr: OCR plugin for MarkItDown
Adds LLM Vision-based text extraction from images embedded in PDF, DOCX, PPTX, and XLSX files.
"""
from ._plugin import __plugin_interface_version__, register_converters
from .__about__ import __version__
from ._ocr_service import (
OCRResult,
LLMVisionOCRService,
)
from ._pdf_converter_with_ocr import PdfConverterWithOCR
from ._docx_converter_with_ocr import DocxConverterWithOCR
from ._pptx_converter_with_ocr import PptxConverterWithOCR
from ._xlsx_converter_with_ocr import XlsxConverterWithOCR
__all__ = [
"__version__",
"__plugin_interface_version__",
"register_converters",
"OCRResult",
"LLMVisionOCRService",
"PdfConverterWithOCR",
"DocxConverterWithOCR",
"PptxConverterWithOCR",
"XlsxConverterWithOCR",
]
@@ -1,189 +0,0 @@
"""
Enhanced DOCX Converter with OCR support for embedded images.
Extracts images from Word documents and performs OCR while maintaining context.
"""
import io
import re
import sys
from typing import Any, BinaryIO, Optional
from markitdown.converters import HtmlConverter
from markitdown.converter_utils.docx.pre_process import pre_process_docx
from markitdown import DocumentConverterResult, StreamInfo
from markitdown._exceptions import (
MissingDependencyException,
MISSING_DEPENDENCY_MESSAGE,
)
from ._ocr_service import LLMVisionOCRService
# Try loading dependencies
_dependency_exc_info = None
try:
import mammoth
from docx import Document
except ImportError:
_dependency_exc_info = sys.exc_info()
# Placeholder injected into HTML so that mammoth never sees the OCR markers.
# Must be a single token with no special markdown characters.
_PLACEHOLDER = "MARKITDOWNOCRBLOCK{}"
class DocxConverterWithOCR(HtmlConverter):
"""
Enhanced DOCX Converter with OCR support for embedded images.
Maintains document flow while extracting text from images inline.
"""
def __init__(self, ocr_service: Optional[LLMVisionOCRService] = None):
super().__init__()
self._html_converter = HtmlConverter()
self.ocr_service = ocr_service
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension == ".docx":
return True
if mimetype.startswith(
"application/vnd.openxmlformats-officedocument.wordprocessingml"
):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> DocumentConverterResult:
if _dependency_exc_info is not None:
raise MissingDependencyException(
MISSING_DEPENDENCY_MESSAGE.format(
converter=type(self).__name__,
extension=".docx",
feature="docx",
)
) from _dependency_exc_info[1].with_traceback(
_dependency_exc_info[2]
) # type: ignore[union-attr]
# Get OCR service if available (from kwargs or instance)
ocr_service: Optional[LLMVisionOCRService] = (
kwargs.get("ocr_service") or self.ocr_service
)
if ocr_service:
# 1. Extract and OCR images — returns raw text per image
file_stream.seek(0)
image_ocr_map = self._extract_and_ocr_images(file_stream, ocr_service)
# 2. Convert DOCX → HTML via mammoth
file_stream.seek(0)
pre_process_stream = pre_process_docx(file_stream)
html_result = mammoth.convert_to_html(
pre_process_stream, style_map=kwargs.get("style_map")
).value
# 3. Replace <img> tags with plain placeholder tokens so that
# mammoth's HTML→markdown step never escapes our OCR markers.
html_with_placeholders, ocr_texts = self._inject_placeholders(
html_result, image_ocr_map
)
# 4. Convert HTML → markdown
md_result = self._html_converter.convert_string(
html_with_placeholders, **kwargs
)
md = md_result.markdown
# 5. Swap placeholders for the actual OCR blocks (post-conversion
# so * and _ are never escaped by the markdown converter).
for i, raw_text in enumerate(ocr_texts):
placeholder = _PLACEHOLDER.format(i)
ocr_block = f"*[Image OCR]\n{raw_text}\n[End OCR]*"
md = md.replace(placeholder, ocr_block)
return DocumentConverterResult(markdown=md)
else:
# Standard conversion without OCR
style_map = kwargs.get("style_map", None)
pre_process_stream = pre_process_docx(file_stream)
return self._html_converter.convert_string(
mammoth.convert_to_html(pre_process_stream, style_map=style_map).value,
**kwargs,
)
def _extract_and_ocr_images(
self, file_stream: BinaryIO, ocr_service: LLMVisionOCRService
) -> dict[str, str]:
"""
Extract images from DOCX and OCR them.
Returns:
Dict mapping image relationship IDs to raw OCR text (no markers).
"""
ocr_map = {}
try:
file_stream.seek(0)
doc = Document(file_stream)
for rel in doc.part.rels.values():
if "image" in rel.target_ref.lower():
try:
image_bytes = rel.target_part.blob
image_stream = io.BytesIO(image_bytes)
ocr_result = ocr_service.extract_text(image_stream)
if ocr_result.text.strip():
# Store raw text only — markers added later
ocr_map[rel.rId] = ocr_result.text.strip()
except Exception:
continue
except Exception:
pass
return ocr_map
def _inject_placeholders(
self, html: str, ocr_map: dict[str, str]
) -> tuple[str, list[str]]:
"""
Replace <img> tags with numbered placeholder tokens.
Returns:
(html_with_placeholders, ordered list of raw OCR texts)
"""
if not ocr_map:
return html, []
ocr_texts = list(ocr_map.values())
used: list[int] = []
def replace_img(match: re.Match) -> str: # type: ignore[type-arg]
for i in range(len(ocr_texts)):
if i not in used:
used.append(i)
return f"<p>{_PLACEHOLDER.format(i)}</p>"
return "" # remove image if all OCR texts already used
result = re.sub(r"<img[^>]*>", replace_img, html)
# Any OCR texts that had no matching <img> tag go at the end
for i in range(len(ocr_texts)):
if i not in used:
result += f"<p>{_PLACEHOLDER.format(i)}</p>"
return result, ocr_texts
@@ -1,110 +0,0 @@
"""
OCR Service Layer for MarkItDown
Provides LLM Vision-based image text extraction.
"""
import base64
from typing import Any, BinaryIO
from dataclasses import dataclass
from markitdown import StreamInfo
@dataclass
class OCRResult:
"""Result from OCR extraction."""
text: str
confidence: float | None = None
backend_used: str | None = None
error: str | None = None
class LLMVisionOCRService:
"""OCR service using LLM vision models (OpenAI-compatible)."""
def __init__(
self,
client: Any,
model: str,
default_prompt: str | None = None,
) -> None:
"""
Initialize LLM Vision OCR service.
Args:
client: OpenAI-compatible client
model: Model name (e.g., 'gpt-4o', 'gemini-2.0-flash')
default_prompt: Default prompt for OCR extraction
"""
self.client = client
self.model = model
self.default_prompt = default_prompt or (
"Extract all text from this image. "
"Return ONLY the extracted text, maintaining the original "
"layout and order. Do not add any commentary or description."
)
def extract_text(
self,
image_stream: BinaryIO,
prompt: str | None = None,
stream_info: StreamInfo | None = None,
**kwargs: Any,
) -> OCRResult:
"""Extract text using LLM vision."""
if self.client is None:
return OCRResult(
text="",
backend_used="llm_vision",
error="LLM client not configured",
)
try:
image_stream.seek(0)
content_type: str | None = None
if stream_info:
content_type = stream_info.mimetype
if not content_type:
try:
from PIL import Image
image_stream.seek(0)
img = Image.open(image_stream)
fmt = img.format.lower() if img.format else "png"
content_type = f"image/{fmt}"
except Exception:
content_type = "image/png"
image_stream.seek(0)
base64_image = base64.b64encode(image_stream.read()).decode("utf-8")
data_uri = f"data:{content_type};base64,{base64_image}"
actual_prompt = prompt or self.default_prompt
response = self.client.chat.completions.create(
model=self.model,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": actual_prompt},
{
"type": "image_url",
"image_url": {"url": data_uri},
},
],
}
],
)
text = response.choices[0].message.content
return OCRResult(
text=text.strip() if text else "",
backend_used="llm_vision",
)
except Exception as e:
return OCRResult(text="", backend_used="llm_vision", error=str(e))
finally:
image_stream.seek(0)
@@ -1,422 +0,0 @@
"""
Enhanced PDF Converter with OCR support for embedded images.
Extracts images from PDFs and performs OCR while maintaining document context.
"""
import io
import sys
from typing import Any, BinaryIO, Optional
from markitdown import DocumentConverter, DocumentConverterResult, StreamInfo
from markitdown._exceptions import (
MissingDependencyException,
MISSING_DEPENDENCY_MESSAGE,
)
from ._ocr_service import LLMVisionOCRService
# Import dependencies
_dependency_exc_info = None
try:
import pdfminer
import pdfminer.high_level
import pdfplumber
from PIL import Image
except ImportError:
_dependency_exc_info = sys.exc_info()
def _extract_images_from_page(page: Any) -> list[dict]:
"""
Extract images from a PDF page by rendering page regions.
Returns:
List of dicts with 'stream', 'bbox', 'name', 'y_pos' keys
"""
images_info = []
try:
# Try multiple methods to detect images
images = []
# Method 1: Use page.images (standard approach)
if hasattr(page, "images") and page.images:
images = page.images
# Method 2: If no images found, try underlying PDF objects
if not images and hasattr(page, "objects") and "image" in page.objects:
images = page.objects.get("image", [])
# Method 3: Try filtering all objects for image types
if not images and hasattr(page, "objects"):
all_objs = page.objects
for obj_type in all_objs.keys():
if "image" in obj_type.lower() or "xobject" in obj_type.lower():
potential_imgs = all_objs.get(obj_type, [])
if potential_imgs:
images = potential_imgs
break
for i, img_dict in enumerate(images):
try:
# Try to get the actual image stream from the PDF
img_stream = None
y_pos = 0
# Method A: If img_dict has 'stream' key, use it directly
if "stream" in img_dict and hasattr(img_dict["stream"], "get_data"):
try:
img_bytes = img_dict["stream"].get_data()
# Try to open as PIL Image to validate/decode
pil_img = Image.open(io.BytesIO(img_bytes))
# Convert to RGB if needed (handle CMYK, etc.)
if pil_img.mode not in ("RGB", "L"):
pil_img = pil_img.convert("RGB")
# Save to stream as PNG
img_stream = io.BytesIO()
pil_img.save(img_stream, format="PNG")
img_stream.seek(0)
y_pos = img_dict.get("top", 0)
except Exception:
pass
# Method B: Fallback to rendering page region
if img_stream is None:
x0 = img_dict.get("x0", 0)
y0 = img_dict.get("top", 0)
x1 = img_dict.get("x1", 0)
y1 = img_dict.get("bottom", 0)
y_pos = y0
# Check if dimensions are valid
if x1 <= x0 or y1 <= y0:
continue
# Use pdfplumber's within_bbox to crop, then render
# This preserves coordinate system correctly
bbox = (x0, y0, x1, y1)
cropped_page = page.within_bbox(bbox)
# Render at 150 DPI (balance between quality and size)
page_img = cropped_page.to_image(resolution=150)
# Save to stream
img_stream = io.BytesIO()
page_img.original.save(img_stream, format="PNG")
img_stream.seek(0)
if img_stream:
images_info.append(
{
"stream": img_stream,
"name": f"page_{page.page_number}_img_{i}",
"y_pos": y_pos,
}
)
except Exception:
continue
except Exception:
pass
return images_info
class PdfConverterWithOCR(DocumentConverter):
"""
Enhanced PDF Converter with OCR support for embedded images.
Maintains document structure while extracting text from images inline.
"""
def __init__(self, ocr_service: Optional[LLMVisionOCRService] = None):
super().__init__()
self.ocr_service = ocr_service
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension == ".pdf":
return True
if mimetype.startswith("application/pdf") or mimetype.startswith(
"application/x-pdf"
):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> DocumentConverterResult:
if _dependency_exc_info is not None:
raise MissingDependencyException(
MISSING_DEPENDENCY_MESSAGE.format(
converter=type(self).__name__,
extension=".pdf",
feature="pdf",
)
) from _dependency_exc_info[1].with_traceback(
_dependency_exc_info[2]
) # type: ignore[union-attr]
# Get OCR service if available (from kwargs or instance)
ocr_service: LLMVisionOCRService | None = (
kwargs.get("ocr_service") or self.ocr_service
)
# Read PDF into BytesIO
file_stream.seek(0)
pdf_bytes = io.BytesIO(file_stream.read())
markdown_content = []
try:
with pdfplumber.open(pdf_bytes) as pdf:
for page_num, page in enumerate(pdf.pages, 1):
markdown_content.append(f"\n## Page {page_num}\n")
# If OCR is enabled, interleave text and images by position
if ocr_service:
images_on_page = self._extract_page_images(pdf_bytes, page_num)
if images_on_page:
# Extract text lines with Y positions
chars = page.chars
if chars:
# Group chars into lines based on Y position
lines_with_y = []
current_line = []
current_y = None
for char in sorted(
chars, key=lambda c: (c["top"], c["x0"])
):
y = char["top"]
if current_y is None:
current_y = y
elif abs(y - current_y) > 2: # New line threshold
if current_line:
text = "".join(
[c["text"] for c in current_line]
)
lines_with_y.append(
{"y": current_y, "text": text.strip()}
)
current_line = []
current_y = y
current_line.append(char)
# Add last line
if current_line:
text = "".join([c["text"] for c in current_line])
lines_with_y.append(
{"y": current_y, "text": text.strip()}
)
else:
# Fallback: use simple text extraction
text_content = page.extract_text() or ""
lines_with_y = [
{"y": i * 10, "text": line}
for i, line in enumerate(text_content.split("\n"))
]
# OCR all images
image_data = []
for img_info in images_on_page:
ocr_result = ocr_service.extract_text(
img_info["stream"]
)
if ocr_result.text.strip():
image_data.append(
{
"y_pos": img_info["y_pos"],
"name": img_info["name"],
"ocr_text": ocr_result.text,
"backend": ocr_result.backend_used,
"type": "image",
}
)
# Add text items
content_items = [
{
"y_pos": item["y"],
"text": item["text"],
"type": "text",
}
for item in lines_with_y
if item["text"]
]
content_items.extend(image_data)
# Sort all items by Y position (top to bottom)
content_items.sort(key=lambda x: x["y_pos"])
# Build markdown by interleaving text and images
for item in content_items:
if item["type"] == "text":
markdown_content.append(item["text"])
else: # image
ocr_text = item["ocr_text"]
img_marker = (
f"\n\n*[Image OCR]\n{ocr_text}\n[End OCR]*\n"
)
markdown_content.append(img_marker)
else:
# No images detected - just extract regular text
text_content = page.extract_text() or ""
if text_content.strip():
markdown_content.append(text_content.strip())
else:
# No OCR, just extract text
text_content = page.extract_text() or ""
if text_content.strip():
markdown_content.append(text_content.strip())
# Build final markdown
markdown = "\n\n".join(markdown_content).strip()
# Fallback to pdfminer if empty
if not markdown:
pdf_bytes.seek(0)
markdown = pdfminer.high_level.extract_text(pdf_bytes)
except Exception:
# Fallback to pdfminer
try:
pdf_bytes.seek(0)
markdown = pdfminer.high_level.extract_text(pdf_bytes)
except Exception:
markdown = ""
# Final fallback: If still empty/whitespace and OCR is available,
# treat as scanned PDF and OCR full pages
if ocr_service and (not markdown or not markdown.strip()):
pdf_bytes.seek(0)
markdown = self._ocr_full_pages(pdf_bytes, ocr_service)
return DocumentConverterResult(markdown=markdown)
def _extract_page_images(self, pdf_bytes: io.BytesIO, page_num: int) -> list[dict]:
"""
Extract images from a PDF page using pdfplumber.
Args:
pdf_bytes: PDF file as BytesIO
page_num: Page number (1-indexed)
Returns:
List of image info dicts with 'stream', 'bbox', 'name', 'y_pos'
"""
images = []
try:
pdf_bytes.seek(0)
with pdfplumber.open(pdf_bytes) as pdf:
if page_num <= len(pdf.pages):
page = pdf.pages[page_num - 1] # 0-indexed
images = _extract_images_from_page(page)
except Exception:
pass
# Sort by vertical position (top to bottom)
images.sort(key=lambda x: x["y_pos"])
return images
def _ocr_full_pages(
self, pdf_bytes: io.BytesIO, ocr_service: LLMVisionOCRService
) -> str:
"""
Fallback for scanned PDFs: Convert entire pages to images and OCR them.
Used when text extraction returns empty/whitespace results.
Args:
pdf_bytes: PDF file as BytesIO
ocr_service: OCR service to use
Returns:
Markdown text extracted from OCR of full pages
"""
markdown_parts = []
try:
pdf_bytes.seek(0)
with pdfplumber.open(pdf_bytes) as pdf:
for page_num, page in enumerate(pdf.pages, 1):
try:
markdown_parts.append(f"\n## Page {page_num}\n")
# Render page to image
page_img = page.to_image(resolution=300)
img_stream = io.BytesIO()
page_img.original.save(img_stream, format="PNG")
img_stream.seek(0)
# Run OCR
ocr_result = ocr_service.extract_text(img_stream)
if ocr_result.text.strip():
text = ocr_result.text.strip()
markdown_parts.append(f"*[Image OCR]\n{text}\n[End OCR]*")
else:
markdown_parts.append(
"*[No text could be extracted from this page]*"
)
except Exception as e:
markdown_parts.append(
f"*[Error processing page {page_num}: {str(e)}]*"
)
continue
except Exception:
# pdfplumber failed (e.g. malformed EOF) — try PyMuPDF for rendering
markdown_parts = []
try:
import fitz # PyMuPDF
pdf_bytes.seek(0)
doc = fitz.open(stream=pdf_bytes.read(), filetype="pdf")
for page_num in range(1, doc.page_count + 1):
try:
markdown_parts.append(f"\n## Page {page_num}\n")
page = doc[page_num - 1]
mat = fitz.Matrix(300 / 72, 300 / 72) # 300 DPI
pix = page.get_pixmap(matrix=mat)
img_stream = io.BytesIO(pix.tobytes("png"))
img_stream.seek(0)
ocr_result = ocr_service.extract_text(img_stream)
if ocr_result.text.strip():
text = ocr_result.text.strip()
markdown_parts.append(f"*[Image OCR]\n{text}\n[End OCR]*")
else:
markdown_parts.append(
"*[No text could be extracted from this page]*"
)
except Exception as e:
markdown_parts.append(
f"*[Error processing page {page_num}: {str(e)}]*"
)
continue
doc.close()
except Exception:
return "*[Error: Could not process scanned PDF]*"
return "\n\n".join(markdown_parts).strip()
@@ -1,68 +0,0 @@
"""
Plugin registration for markitdown-ocr.
Registers OCR-enhanced converters with priority-based replacement strategy.
"""
from typing import Any
from markitdown import MarkItDown
from ._ocr_service import LLMVisionOCRService
from ._pdf_converter_with_ocr import PdfConverterWithOCR
from ._docx_converter_with_ocr import DocxConverterWithOCR
from ._pptx_converter_with_ocr import PptxConverterWithOCR
from ._xlsx_converter_with_ocr import XlsxConverterWithOCR
__plugin_interface_version__ = 1
def register_converters(markitdown: MarkItDown, **kwargs: Any) -> None:
"""
Register OCR-enhanced converters with MarkItDown.
This plugin provides OCR support for PDF, DOCX, PPTX, and XLSX files.
The converters are registered with priority -1.0 to run BEFORE built-in
converters (which have priority 0.0), effectively replacing them when
the plugin is enabled.
Args:
markitdown: MarkItDown instance to register converters with
**kwargs: Additional keyword arguments that may include:
- llm_client: OpenAI-compatible client for LLM-based OCR (required for OCR to work)
- llm_model: Model name (e.g., 'gpt-4o')
- llm_prompt: Custom prompt for text extraction
"""
# Create OCR service — reads the same llm_client/llm_model kwargs
# that MarkItDown itself already accepts for image descriptions
llm_client = kwargs.get("llm_client")
llm_model = kwargs.get("llm_model")
llm_prompt = kwargs.get("llm_prompt")
ocr_service: LLMVisionOCRService | None = None
if llm_client and llm_model:
ocr_service = LLMVisionOCRService(
client=llm_client,
model=llm_model,
default_prompt=llm_prompt,
)
# Register converters with priority -1.0 (before built-ins at 0.0)
# This effectively "replaces" the built-in converters when plugin is installed
# Pass the OCR service to each converter's constructor
PRIORITY_OCR_ENHANCED = -1.0
markitdown.register_converter(
PdfConverterWithOCR(ocr_service=ocr_service), priority=PRIORITY_OCR_ENHANCED
)
markitdown.register_converter(
DocxConverterWithOCR(ocr_service=ocr_service), priority=PRIORITY_OCR_ENHANCED
)
markitdown.register_converter(
PptxConverterWithOCR(ocr_service=ocr_service), priority=PRIORITY_OCR_ENHANCED
)
markitdown.register_converter(
XlsxConverterWithOCR(ocr_service=ocr_service), priority=PRIORITY_OCR_ENHANCED
)
@@ -1,249 +0,0 @@
"""
Enhanced PPTX Converter with improved OCR support.
Already has LLM-based image description, this enhances it with traditional OCR fallback.
"""
import io
import sys
from typing import Any, BinaryIO, Optional
from typing import BinaryIO, Any, Optional
from markitdown.converters import HtmlConverter
from markitdown import DocumentConverter, DocumentConverterResult, StreamInfo
from markitdown._exceptions import (
MissingDependencyException,
MISSING_DEPENDENCY_MESSAGE,
)
from ._ocr_service import LLMVisionOCRService
_dependency_exc_info = None
try:
import pptx
except ImportError:
_dependency_exc_info = sys.exc_info()
class PptxConverterWithOCR(DocumentConverter):
"""Enhanced PPTX Converter with OCR fallback."""
def __init__(self, ocr_service: Optional[LLMVisionOCRService] = None):
super().__init__()
self._html_converter = HtmlConverter()
self.ocr_service = ocr_service
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension == ".pptx":
return True
if mimetype.startswith(
"application/vnd.openxmlformats-officedocument.presentationml"
):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> DocumentConverterResult:
if _dependency_exc_info is not None:
raise MissingDependencyException(
MISSING_DEPENDENCY_MESSAGE.format(
converter=type(self).__name__,
extension=".pptx",
feature="pptx",
)
) from _dependency_exc_info[1].with_traceback(
_dependency_exc_info[2]
) # type: ignore[union-attr]
# Get OCR service (from kwargs or instance)
ocr_service: Optional[LLMVisionOCRService] = (
kwargs.get("ocr_service") or self.ocr_service
)
llm_client = kwargs.get("llm_client")
presentation = pptx.Presentation(file_stream)
md_content = ""
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
def get_shape_content(shape, **kwargs):
nonlocal md_content
# Pictures
if self._is_picture(shape):
# Get image data
image_stream = io.BytesIO(shape.image.blob)
# Try LLM description first if available
llm_description = ""
if llm_client and kwargs.get("llm_model"):
try:
from ._llm_caption import llm_caption
image_filename = shape.image.filename
image_extension = None
if image_filename:
import os
image_extension = os.path.splitext(image_filename)[1]
image_stream_info = StreamInfo(
mimetype=shape.image.content_type,
extension=image_extension,
filename=image_filename,
)
llm_description = llm_caption(
image_stream,
image_stream_info,
client=llm_client,
model=kwargs.get("llm_model"),
prompt=kwargs.get("llm_prompt"),
)
except Exception:
pass
# Try OCR if LLM failed or not available
ocr_text = ""
if not llm_description and ocr_service:
try:
image_stream.seek(0)
ocr_result = ocr_service.extract_text(image_stream)
if ocr_result.text.strip():
ocr_text = ocr_result.text.strip()
except Exception:
pass
# Format extracted content using unified OCR block format
content = (llm_description or ocr_text or "").strip()
if content:
md_content += f"\n*[Image OCR]\n{content}\n[End OCR]*\n"
# Tables
if self._is_table(shape):
md_content += self._convert_table_to_markdown(shape.table, **kwargs)
# 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"
# Group Shapes
if shape.shape_type == pptx.enum.shapes.MSO_SHAPE_TYPE.GROUP:
sorted_shapes = sorted(
shape.shapes,
key=lambda x: (
float("-inf") if not x.top else x.top,
float("-inf") if not x.left else x.left,
),
)
for subshape in sorted_shapes:
get_shape_content(subshape, **kwargs)
sorted_shapes = sorted(
slide.shapes,
key=lambda x: (
float("-inf") if not x.top else x.top,
float("-inf") if not x.left else x.left,
),
)
for shape in sorted_shapes:
get_shape_content(shape, **kwargs)
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(markdown=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_table_to_markdown(self, table, **kwargs):
import html
html_table = "<html><body><table>"
first_row = True
for row in 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>"
return (
self._html_converter.convert_string(html_table, **kwargs).markdown.strip()
+ "\\n"
)
def _convert_chart_to_markdown(self, chart):
try:
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:])
except ValueError as e:
if "unsupported plot type" in str(e):
return "\\n\\n[unsupported chart]\\n\\n"
except Exception:
return "\\n\\n[unsupported chart]\\n\\n"
@@ -1,225 +0,0 @@
"""
Enhanced XLSX Converter with OCR support for embedded images.
Extracts images from Excel spreadsheets and performs OCR while maintaining cell context.
"""
import io
import sys
from typing import Any, BinaryIO, Optional
from markitdown.converters import HtmlConverter
from markitdown import DocumentConverter, DocumentConverterResult, StreamInfo
from markitdown._exceptions import (
MissingDependencyException,
MISSING_DEPENDENCY_MESSAGE,
)
from ._ocr_service import LLMVisionOCRService
# Try loading dependencies
_xlsx_dependency_exc_info = None
try:
import pandas as pd
from openpyxl import load_workbook
except ImportError:
_xlsx_dependency_exc_info = sys.exc_info()
class XlsxConverterWithOCR(DocumentConverter):
"""
Enhanced XLSX Converter with OCR support for embedded images.
Extracts images with their cell positions and performs OCR.
"""
def __init__(self, ocr_service: Optional[LLMVisionOCRService] = None):
super().__init__()
self._html_converter = HtmlConverter()
self.ocr_service = ocr_service
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension == ".xlsx":
return True
if mimetype.startswith(
"application/vnd.openxmlformats-officedocument.spreadsheetml"
):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> DocumentConverterResult:
if _xlsx_dependency_exc_info is not None:
raise MissingDependencyException(
MISSING_DEPENDENCY_MESSAGE.format(
converter=type(self).__name__,
extension=".xlsx",
feature="xlsx",
)
) from _xlsx_dependency_exc_info[1].with_traceback(
_xlsx_dependency_exc_info[2]
) # type: ignore[union-attr]
# Get OCR service if available (from kwargs or instance)
ocr_service: Optional[LLMVisionOCRService] = (
kwargs.get("ocr_service") or self.ocr_service
)
if ocr_service:
# Remove ocr_service from kwargs to avoid duplicate argument error
kwargs_without_ocr = {k: v for k, v in kwargs.items() if k != "ocr_service"}
return self._convert_with_ocr(
file_stream, ocr_service, **kwargs_without_ocr
)
else:
return self._convert_standard(file_stream, **kwargs)
def _convert_standard(
self, file_stream: BinaryIO, **kwargs: Any
) -> DocumentConverterResult:
"""Standard conversion without OCR."""
file_stream.seek(0)
sheets = pd.read_excel(file_stream, sheet_name=None, engine="openpyxl")
md_content = ""
for sheet_name in sheets:
md_content += f"## {sheet_name}\n"
html_content = sheets[sheet_name].to_html(index=False)
md_content += (
self._html_converter.convert_string(
html_content, **kwargs
).markdown.strip()
+ "\n\n"
)
return DocumentConverterResult(markdown=md_content.strip())
def _convert_with_ocr(
self, file_stream: BinaryIO, ocr_service: LLMVisionOCRService, **kwargs: Any
) -> DocumentConverterResult:
"""Convert XLSX with image OCR."""
file_stream.seek(0)
wb = load_workbook(file_stream)
md_content = ""
for sheet_name in wb.sheetnames:
sheet = wb[sheet_name]
md_content += f"## {sheet_name}\n\n"
# Convert sheet data to markdown table
file_stream.seek(0)
try:
df = pd.read_excel(
file_stream, sheet_name=sheet_name, engine="openpyxl"
)
html_content = df.to_html(index=False)
md_content += (
self._html_converter.convert_string(
html_content, **kwargs
).markdown.strip()
+ "\n\n"
)
except Exception:
# If pandas fails, just skip the table
pass
# Extract and OCR images in this sheet
images_with_ocr = self._extract_and_ocr_sheet_images(sheet, ocr_service)
if images_with_ocr:
md_content += "### Images in this sheet:\n\n"
for img_info in images_with_ocr:
ocr_text = img_info["ocr_text"]
md_content += f"*[Image OCR]\n{ocr_text}\n[End OCR]*\n\n"
return DocumentConverterResult(markdown=md_content.strip())
def _extract_and_ocr_sheet_images(
self, sheet: Any, ocr_service: LLMVisionOCRService
) -> list[dict]:
"""
Extract and OCR images from an Excel sheet.
Args:
sheet: openpyxl worksheet
ocr_service: OCR service
Returns:
List of dicts with 'cell_ref' and 'ocr_text'
"""
results = []
try:
# Check if sheet has images
if hasattr(sheet, "_images"):
for img in sheet._images:
try:
# Get image data
if hasattr(img, "_data"):
image_data = img._data()
elif hasattr(img, "image"):
# Some versions store it differently
image_data = img.image
else:
continue
# Create image stream
image_stream = io.BytesIO(image_data)
# Get cell reference
cell_ref = "unknown"
if hasattr(img, "anchor"):
anchor = img.anchor
if hasattr(anchor, "_from"):
from_cell = anchor._from
if hasattr(from_cell, "col") and hasattr(
from_cell, "row"
):
# Convert column number to letter
col_letter = self._column_number_to_letter(
from_cell.col
)
cell_ref = f"{col_letter}{from_cell.row + 1}"
# Perform OCR
ocr_result = ocr_service.extract_text(image_stream)
if ocr_result.text.strip():
results.append(
{
"cell_ref": cell_ref,
"ocr_text": ocr_result.text.strip(),
"backend": ocr_result.backend_used,
}
)
except Exception:
continue
except Exception:
pass
return results
@staticmethod
def _column_number_to_letter(n: int) -> str:
"""Convert column number to Excel column letter (0-indexed)."""
result = ""
n = n + 1 # Make 1-indexed
while n > 0:
n -= 1
result = chr(65 + (n % 26)) + result
n //= 26
return result
@@ -1,79 +0,0 @@
%PDF-1.3
%“Œ‹ž ReportLab Generated PDF document http://www.reportlab.com
1 0 obj
<<
/F1 2 0 R
>>
endobj
2 0 obj
<<
/BaseFont /Helvetica /Encoding /WinAnsiEncoding /Name /F1 /Subtype /Type1 /Type /Font
>>
endobj
3 0 obj
<<
/BitsPerComponent 8 /ColorSpace /DeviceRGB /Filter [ /ASCII85Decode /FlateDecode ] /Height 80 /Length 4282 /Subtype /Image
/Type /XObject /Width 400
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@@ -1,223 +0,0 @@
"""
Unit tests for DocxConverterWithOCR.
For each DOCX test file: convert with a mock OCR service then compare the
full output string against the expected snapshot.
OCR block format used by the converter:
*[Image OCR]
MOCK_OCR_TEXT_12345
[End OCR]*
"""
import sys
from pathlib import Path
from typing import Any
import pytest
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from markitdown_ocr._ocr_service import OCRResult # noqa: E402
from markitdown_ocr._docx_converter_with_ocr import ( # noqa: E402
DocxConverterWithOCR,
)
from markitdown import StreamInfo # noqa: E402
TEST_DATA_DIR = Path(__file__).parent / "ocr_test_data"
_MOCK_TEXT = "MOCK_OCR_TEXT_12345"
class MockOCRService:
def extract_text( # noqa: ANN101
self, image_stream: Any, **kwargs: Any
) -> OCRResult:
return OCRResult(text=_MOCK_TEXT, backend_used="mock")
@pytest.fixture(scope="module")
def svc() -> MockOCRService:
return MockOCRService()
def _convert(filename: str, ocr_service: MockOCRService) -> str:
path = TEST_DATA_DIR / filename
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = DocxConverterWithOCR()
with open(path, "rb") as f:
return converter.convert(
f, StreamInfo(extension=".docx"), ocr_service=ocr_service
).text_content
# ---------------------------------------------------------------------------
# docx_image_start.docx
# ---------------------------------------------------------------------------
def test_docx_image_start(svc: MockOCRService) -> None:
expected = (
"Document with Image at Start\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"This is the main content after the header image.\n\n"
"More text content here."
)
assert _convert("docx_image_start.docx", svc) == expected
# ---------------------------------------------------------------------------
# docx_image_middle.docx
# ---------------------------------------------------------------------------
def test_docx_image_middle(svc: MockOCRService) -> None:
expected = (
"# Introduction\n\n"
"This is the introduction section.\n\n"
"We will see an image below.\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"# Analysis\n\n"
"This section comes after the image."
)
assert _convert("docx_image_middle.docx", svc) == expected
# ---------------------------------------------------------------------------
# docx_image_end.docx
# ---------------------------------------------------------------------------
def test_docx_image_end(svc: MockOCRService) -> None:
expected = (
"Report\n\n"
"Main findings of the report.\n\n"
"Details and analysis.\n\n"
"Recommendations.\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("docx_image_end.docx", svc) == expected
# ---------------------------------------------------------------------------
# docx_multiple_images.docx
# ---------------------------------------------------------------------------
def test_docx_multiple_images(svc: MockOCRService) -> None:
expected = (
"Multi-Image Document\n\n"
"First section\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"Second section with another image\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"Conclusion"
)
assert _convert("docx_multiple_images.docx", svc) == expected
# ---------------------------------------------------------------------------
# docx_multipage.docx
# ---------------------------------------------------------------------------
def test_docx_multipage(svc: MockOCRService) -> None:
expected = (
"# Page 1 - Mixed Content\n\n"
"This is the first paragraph on page 1.\n\n"
"BEFORE IMAGE: Important content appears here.\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"AFTER IMAGE: This content follows the image.\n\n"
"More text on page 1.\n\n"
"# Page 2 - Image at End\n\n"
"Content on page 2.\n\n"
"Multiple paragraphs of text.\n\n"
"Building up to the image...\n\n"
"Final paragraph before image.\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"# Page 3 - Image at Start\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"Content that follows the header image.\n\n"
"AFTER IMAGE: This text is after the image."
)
assert _convert("docx_multipage.docx", svc) == expected
# ---------------------------------------------------------------------------
# docx_complex_layout.docx
# ---------------------------------------------------------------------------
def test_docx_complex_layout(svc: MockOCRService) -> None:
expected = (
"Complex Document\n\n"
"| | |\n"
"| --- | --- |\n"
"| Feature | Status |\n"
"| Authentication | Active |\n"
"| Encryption | Enabled |\n\n"
"Security notice:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("docx_complex_layout.docx", svc) == expected
# ---------------------------------------------------------------------------
# _inject_placeholders — internal unit tests (no file I/O)
# ---------------------------------------------------------------------------
def test_inject_placeholders_single_image() -> None:
converter = DocxConverterWithOCR()
html = "<p>Before</p><img src='x.png'/><p>After</p>"
result_html, texts = converter._inject_placeholders(html, {"rId1": "TEXT"})
assert "<img" not in result_html
assert "MARKITDOWNOCRBLOCK0" in result_html
assert texts == ["TEXT"]
def test_inject_placeholders_two_images_sequential_tokens() -> None:
converter = DocxConverterWithOCR()
html = "<img src='a.png'/><p>Mid</p><img src='b.png'/>"
result_html, texts = converter._inject_placeholders(
html, {"rId1": "FIRST", "rId2": "SECOND"}
)
assert "MARKITDOWNOCRBLOCK0" in result_html
assert "MARKITDOWNOCRBLOCK1" in result_html
assert result_html.index("MARKITDOWNOCRBLOCK0") < result_html.index(
"MARKITDOWNOCRBLOCK1"
)
assert len(texts) == 2
def test_inject_placeholders_no_img_tag_appends_at_end() -> None:
converter = DocxConverterWithOCR()
html = "<p>No images</p>"
result_html, texts = converter._inject_placeholders(html, {"rId1": "ORPHAN"})
assert "MARKITDOWNOCRBLOCK0" in result_html
assert texts == ["ORPHAN"]
def test_inject_placeholders_empty_map_leaves_html_unchanged() -> None:
converter = DocxConverterWithOCR()
html = "<p>Content</p><img src='pic.jpg'/>"
result_html, texts = converter._inject_placeholders(html, {})
assert result_html == html
assert texts == []
# ---------------------------------------------------------------------------
# No OCR service — no OCR tags emitted
# ---------------------------------------------------------------------------
def test_docx_no_ocr_service_no_tags() -> None:
path = TEST_DATA_DIR / "docx_image_middle.docx"
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = DocxConverterWithOCR()
with open(path, "rb") as f:
md = converter.convert(f, StreamInfo(extension=".docx")).text_content
assert "*[Image OCR]" not in md
assert "[End OCR]*" not in md
@@ -1,234 +0,0 @@
"""
Unit tests for PdfConverterWithOCR.
For each PDF test file: convert with a mock OCR service then compare the
full output string against the expected snapshot.
OCR block format used by the converter:
*[Image OCR]
MOCK_OCR_TEXT_12345
[End OCR]*
"""
import io
import sys
from pathlib import Path
from typing import Any
from unittest.mock import MagicMock, patch
import pytest
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from markitdown_ocr._ocr_service import OCRResult # noqa: E402
from markitdown_ocr._pdf_converter_with_ocr import ( # noqa: E402
PdfConverterWithOCR,
)
from markitdown import StreamInfo # noqa: E402
TEST_DATA_DIR = Path(__file__).parent / "ocr_test_data"
_MOCK_TEXT = "MOCK_OCR_TEXT_12345"
_OCR_BLOCK = f"*[Image OCR]\n{_MOCK_TEXT}\n[End OCR]*"
_PAGE_1_SCANNED = f"## Page 1\n\n\n\n\n{_OCR_BLOCK}"
class MockOCRService:
def extract_text(
self, # noqa: ANN101
image_stream: Any,
**kwargs: Any,
) -> OCRResult:
return OCRResult(text=_MOCK_TEXT, backend_used="mock")
@pytest.fixture(scope="module")
def svc() -> MockOCRService:
return MockOCRService()
def _convert(filename: str, ocr_service: MockOCRService) -> str:
path = TEST_DATA_DIR / filename
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = PdfConverterWithOCR()
with open(path, "rb") as f:
return converter.convert(
f, StreamInfo(extension=".pdf"), ocr_service=ocr_service
).text_content
# ---------------------------------------------------------------------------
# pdf_image_start.pdf
# ---------------------------------------------------------------------------
def test_pdf_image_start(svc: MockOCRService) -> None:
expected = (
"## Page 1\n\n\n\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n\n"
"This is text BEFORE the image.\n\n"
"The image should appear above this text.\n\n"
"This is more content after the image."
)
assert _convert("pdf_image_start.pdf", svc) == expected
# ---------------------------------------------------------------------------
# pdf_image_middle.pdf
# ---------------------------------------------------------------------------
def test_pdf_image_middle(svc: MockOCRService) -> None:
expected = (
"## Page 1\n\n\n"
"Section 1: Introduction\n\n"
"This document contains an image in the middle.\n\n"
"Here is some introductory text.\n\n\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n\n"
"Section 2: Details\n\n"
"This text appears AFTER the image."
)
assert _convert("pdf_image_middle.pdf", svc) == expected
# ---------------------------------------------------------------------------
# pdf_image_end.pdf
# ---------------------------------------------------------------------------
def test_pdf_image_end(svc: MockOCRService) -> None:
expected = (
"## Page 1\n\n\n"
"Main Content\n\n"
"This is the main text content.\n\n"
"The image will appear at the end.\n\n"
"Keep reading...\n\n\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("pdf_image_end.pdf", svc) == expected
# ---------------------------------------------------------------------------
# pdf_multiple_images.pdf
# ---------------------------------------------------------------------------
def test_pdf_multiple_images(svc: MockOCRService) -> None:
expected = (
"## Page 1\n\n\n"
"Document with Multiple Images\n\n\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n\n"
"Text between first and second image.\n\n\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n\n"
"Final text after all images."
)
assert _convert("pdf_multiple_images.pdf", svc) == expected
# ---------------------------------------------------------------------------
# pdf_complex_layout.pdf
# ---------------------------------------------------------------------------
def test_pdf_complex_layout(svc: MockOCRService) -> None:
expected = (
"## Page 1\n\n\n"
"Complex Layout Document\n\n"
"Table:\n\n"
"ItemQuantity\n\n\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n\n"
"Widget A5"
)
assert _convert("pdf_complex_layout.pdf", svc) == expected
# ---------------------------------------------------------------------------
# pdf_multipage.pdf — pdfplumber/pdfminer fail (EOF); PyMuPDF fallback used
# ---------------------------------------------------------------------------
def test_pdf_multipage(svc: MockOCRService) -> None:
# pdfplumber cannot open this file (Unexpected EOF), so _ocr_full_pages
# falls back to PyMuPDF for page rendering. Each page becomes one OCR block.
expected = (
f"## Page 1\n\n\n{_OCR_BLOCK}\n\n\n"
f"## Page 2\n\n\n{_OCR_BLOCK}\n\n\n"
f"## Page 3\n\n\n{_OCR_BLOCK}"
)
assert _convert("pdf_multipage.pdf", svc) == expected
# ---------------------------------------------------------------------------
# pdf_scanned_*.pdf — raster-only pages → full-page OCR
# ---------------------------------------------------------------------------
def test_pdf_scanned_invoice(svc: MockOCRService) -> None:
assert _convert("pdf_scanned_invoice.pdf", svc) == _PAGE_1_SCANNED
def test_pdf_scanned_meeting_minutes(svc: MockOCRService) -> None:
assert _convert("pdf_scanned_meeting_minutes.pdf", svc) == _PAGE_1_SCANNED
def test_pdf_scanned_minimal(svc: MockOCRService) -> None:
assert _convert("pdf_scanned_minimal.pdf", svc) == _PAGE_1_SCANNED
def test_pdf_scanned_sales_report(svc: MockOCRService) -> None:
assert _convert("pdf_scanned_sales_report.pdf", svc) == _PAGE_1_SCANNED
def test_pdf_scanned_report(svc: MockOCRService) -> None:
expected = (
f"{_PAGE_1_SCANNED}\n\n\n\n"
f"## Page 2\n\n\n\n\n{_OCR_BLOCK}\n\n\n\n"
f"## Page 3\n\n\n\n\n{_OCR_BLOCK}"
)
assert _convert("pdf_scanned_report.pdf", svc) == expected
# ---------------------------------------------------------------------------
# Scanned PDF fallback path (pdfplumber finds no text → full-page OCR)
# ---------------------------------------------------------------------------
def test_pdf_scanned_fallback_format(svc: MockOCRService) -> None:
"""_ocr_full_pages emits *[Image OCR]...[End OCR]* for each page."""
path = TEST_DATA_DIR / "pdf_image_start.pdf"
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = PdfConverterWithOCR()
with patch("pdfplumber.open") as mock_plumber:
mock_pdf = MagicMock()
mock_page = MagicMock()
mock_page.page_number = 1
mock_pdf.pages = [mock_page]
mock_pdf.__enter__.return_value = mock_pdf
mock_plumber.return_value = mock_pdf
with open(path, "rb") as f:
md = converter._ocr_full_pages(io.BytesIO(f.read()), svc)
expected = "## Page 1\n\n\n" "*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
assert (
md == expected
), f"_ocr_full_pages must produce:\n{expected!r}\nActual:\n{md!r}"
# ---------------------------------------------------------------------------
# No OCR service — no OCR tags emitted
# ---------------------------------------------------------------------------
def test_pdf_no_ocr_service_no_tags() -> None:
path = TEST_DATA_DIR / "pdf_image_middle.pdf"
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = PdfConverterWithOCR()
with open(path, "rb") as f:
md = converter.convert(f, StreamInfo(extension=".pdf")).text_content
assert "*[Image OCR]" not in md
assert "[End OCR]*" not in md
@@ -1,148 +0,0 @@
"""
Unit tests for PptxConverterWithOCR.
For each PPTX test file: convert with a mock OCR service then compare the
full output string against the expected snapshot.
OCR block format used by the converter:
*[Image OCR]
MOCK_OCR_TEXT_12345
[End OCR]*
Note: PPTX slide text uses literal backslash-n (\\n) sequences from the
underlying PPTX converter template; OCR blocks use real newlines.
"""
import sys
from pathlib import Path
from typing import Any
import pytest
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from markitdown_ocr._ocr_service import OCRResult # noqa: E402
from markitdown_ocr._pptx_converter_with_ocr import ( # noqa: E402
PptxConverterWithOCR,
)
from markitdown import StreamInfo # noqa: E402
TEST_DATA_DIR = Path(__file__).parent / "ocr_test_data"
_MOCK_TEXT = "MOCK_OCR_TEXT_12345"
_OCR_BLOCK = f"*[Image OCR]\n{_MOCK_TEXT}\n[End OCR]*"
class MockOCRService:
def extract_text(
self, # noqa: ANN101
image_stream: Any,
**kwargs: Any,
) -> OCRResult:
return OCRResult(text=_MOCK_TEXT, backend_used="mock")
@pytest.fixture(scope="module")
def svc() -> MockOCRService:
return MockOCRService()
def _convert(filename: str, ocr_service: MockOCRService) -> str:
path = TEST_DATA_DIR / filename
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = PptxConverterWithOCR()
with open(path, "rb") as f:
return converter.convert(
f, StreamInfo(extension=".pptx"), ocr_service=ocr_service
).text_content
# ---------------------------------------------------------------------------
# pptx_image_start.pptx
# ---------------------------------------------------------------------------
def test_pptx_image_start(svc: MockOCRService) -> None:
# Slide 1: title "Welcome" followed by an image
expected = (
"\\n\\n<!-- Slide number: 1 -->\\n# Welcome\\n\\n"
"\n*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("pptx_image_start.pptx", svc) == expected
# ---------------------------------------------------------------------------
# pptx_image_middle.pptx
# ---------------------------------------------------------------------------
def test_pptx_image_middle(svc: MockOCRService) -> None:
# Slide 1: Introduction | Slide 2: Architecture + image | Slide 3: Conclusion # noqa: E501
expected = (
"\\n\\n<!-- Slide number: 1 -->\\n# Introduction"
"\\n\\n\\n\\n<!-- Slide number: 2 -->\\n# Architecture\\n\\n"
"\n*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
"\\n\\n<!-- Slide number: 3 -->\\n# Conclusion\\n\\n"
)
assert _convert("pptx_image_middle.pptx", svc) == expected
# ---------------------------------------------------------------------------
# pptx_image_end.pptx
# ---------------------------------------------------------------------------
def test_pptx_image_end(svc: MockOCRService) -> None:
# Slide 1: Presentation | Slide 2: Thank You + image
expected = (
"\\n\\n<!-- Slide number: 1 -->\\n# Presentation"
"\\n\\n\\n\\n<!-- Slide number: 2 -->\\n# Thank You\\n\\n"
"\n*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("pptx_image_end.pptx", svc) == expected
# ---------------------------------------------------------------------------
# pptx_multiple_images.pptx
# ---------------------------------------------------------------------------
def test_pptx_multiple_images(svc: MockOCRService) -> None:
# Slide 1: two images, no title text
expected = (
"\\n\\n<!-- Slide number: 1 -->\\n# \\n"
"\n*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
"\n\n*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("pptx_multiple_images.pptx", svc) == expected
# ---------------------------------------------------------------------------
# pptx_complex_layout.pptx
# ---------------------------------------------------------------------------
def test_pptx_complex_layout(svc: MockOCRService) -> None:
expected = (
"\\n\\n<!-- Slide number: 1 -->\\n# Product Comparison"
"\\n\\nOur products lead the market\\n"
"\n*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("pptx_complex_layout.pptx", svc) == expected
# ---------------------------------------------------------------------------
# No OCR service — no OCR tags emitted
# ---------------------------------------------------------------------------
def test_pptx_no_ocr_service_no_tags() -> None:
path = TEST_DATA_DIR / "pptx_image_middle.pptx"
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = PptxConverterWithOCR()
with open(path, "rb") as f:
md = converter.convert(f, StreamInfo(extension=".pptx")).text_content
assert "*[Image OCR]" not in md
assert "[End OCR]*" not in md
@@ -1,249 +0,0 @@
"""
Unit tests for XlsxConverterWithOCR.
For each XLSX test file: convert with a mock OCR service then compare the
full output string against the expected snapshot.
OCR block format used by the converter:
*[Image OCR]
MOCK_OCR_TEXT_12345
[End OCR]*
Images are grouped at the end of each sheet under:
### Images in this sheet:
"""
import sys
from pathlib import Path
from typing import Any
import pytest
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from markitdown_ocr._ocr_service import OCRResult # noqa: E402
from markitdown_ocr._xlsx_converter_with_ocr import ( # noqa: E402
XlsxConverterWithOCR,
)
from markitdown import StreamInfo # noqa: E402
TEST_DATA_DIR = Path(__file__).parent / "ocr_test_data"
_MOCK_TEXT = "MOCK_OCR_TEXT_12345"
_OCR_BLOCK = f"*[Image OCR]\n{_MOCK_TEXT}\n[End OCR]*"
_IMG_SECTION = "### Images in this sheet:"
class MockOCRService:
def extract_text(
self, # noqa: ANN101
image_stream: Any,
**kwargs: Any,
) -> OCRResult:
return OCRResult(text=_MOCK_TEXT, backend_used="mock")
@pytest.fixture(scope="module")
def svc() -> MockOCRService:
return MockOCRService()
def _convert(filename: str, ocr_service: MockOCRService) -> str:
path = TEST_DATA_DIR / filename
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = XlsxConverterWithOCR()
with open(path, "rb") as f:
return converter.convert(
f, StreamInfo(extension=".xlsx"), ocr_service=ocr_service
).text_content
# ---------------------------------------------------------------------------
# xlsx_image_start.xlsx
# ---------------------------------------------------------------------------
def test_xlsx_image_start(svc: MockOCRService) -> None:
expected = (
"## Sales Q1\n\n"
"| Product | Sales |\n"
"| --- | --- |\n"
"| Widget A | 100 |\n"
"| Widget B | 150 |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"## Forecast Q2\n\n"
"| Projected Sales | Unnamed: 1 |\n"
"| --- | --- |\n"
"| Widget A | 120 |\n"
"| Widget B | 180 |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("xlsx_image_start.xlsx", svc) == expected
# ---------------------------------------------------------------------------
# xlsx_image_middle.xlsx
# ---------------------------------------------------------------------------
def test_xlsx_image_middle(svc: MockOCRService) -> None:
expected = (
"## Revenue\n\n"
"| Q1 Report | Unnamed: 1 |\n"
"| --- | --- |\n"
"| NaN | NaN |\n"
"| Revenue | $50,000 |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| Profit Margin | 40% |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"## Expenses\n\n"
"| Expense Breakdown | Unnamed: 1 |\n"
"| --- | --- |\n"
"| NaN | NaN |\n"
"| Expenses | $30,000 |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| Savings | $5,000 |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("xlsx_image_middle.xlsx", svc) == expected
# ---------------------------------------------------------------------------
# xlsx_image_end.xlsx
# ---------------------------------------------------------------------------
def test_xlsx_image_end(svc: MockOCRService) -> None:
expected = (
"## Sheet\n\n"
"| Financial Summary | Unnamed: 1 |\n"
"| --- | --- |\n"
"| Total Revenue | $500,000 |\n"
"| Total Expenses | $300,000 |\n"
"| Net Profit | $200,000 |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| Signature: | NaN |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"## Budget\n\n"
"| Budget Allocation | Unnamed: 1 |\n"
"| --- | --- |\n"
"| Marketing | $100,000 |\n"
"| R&D | $150,000 |\n"
"| Operations | $50,000 |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| NaN | NaN |\n"
"| Approved: | NaN |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("xlsx_image_end.xlsx", svc) == expected
# ---------------------------------------------------------------------------
# xlsx_multiple_images.xlsx
# ---------------------------------------------------------------------------
def test_xlsx_multiple_images(svc: MockOCRService) -> None:
expected = (
"## Overview\n\n"
"| Dashboard |\n"
"| --- |\n"
"| Status: Active |\n"
"| NaN |\n"
"| NaN |\n"
"| NaN |\n"
"| NaN |\n"
"| Performance Summary |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"## Details\n\n"
"| Detailed Metrics |\n"
"| --- |\n"
"| System Health |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"## Summary\n\n"
"| Quarter Summary |\n"
"| --- |\n"
"| Overall Performance |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("xlsx_multiple_images.xlsx", svc) == expected
# ---------------------------------------------------------------------------
# xlsx_complex_layout.xlsx
# ---------------------------------------------------------------------------
def test_xlsx_complex_layout(svc: MockOCRService) -> None:
expected = (
"## Complex Report\n\n"
"| Annual Report 2024 | Unnamed: 1 |\n"
"| --- | --- |\n"
"| NaN | NaN |\n"
"| Month | Sales |\n"
"| Jan | 1000 |\n"
"| Feb | 1200 |\n"
"| NaN | NaN |\n"
"| Total | 2200 |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"## Customers\n\n"
"| Customer Metrics | Unnamed: 1 |\n"
"| --- | --- |\n"
"| NaN | NaN |\n"
"| New Customers | 250 |\n"
"| Retention Rate | 92% |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*\n\n"
"## Regions\n\n"
"| Regional Breakdown | Unnamed: 1 |\n"
"| --- | --- |\n"
"| NaN | NaN |\n"
"| Region | Revenue |\n"
"| North | $800K |\n"
"| South | $600K |\n\n"
"### Images in this sheet:\n\n"
"*[Image OCR]\nMOCK_OCR_TEXT_12345\n[End OCR]*"
)
assert _convert("xlsx_complex_layout.xlsx", svc) == expected
# ---------------------------------------------------------------------------
# No OCR service — no OCR tags emitted
# ---------------------------------------------------------------------------
def test_xlsx_no_ocr_service_no_tags() -> None:
path = TEST_DATA_DIR / "xlsx_image_middle.xlsx"
if not path.exists():
pytest.skip(f"Test file not found: {path}")
converter = XlsxConverterWithOCR()
with open(path, "rb") as f:
md = converter.convert(f, StreamInfo(extension=".xlsx")).text_content
assert "*[Image OCR]" not in md
assert "[End OCR]*" not in md
+18 -33
View File
@@ -1,7 +1,7 @@
# MarkItDown Sample Plugin # MarkItDown Sample Plugin
[![PyPI](https://img.shields.io/pypi/v/markitdown-sample-plugin.svg)](https://pypi.org/project/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-sample-plugin) ![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) [![Built by AutoGen Team](https://img.shields.io/badge/Built%20by-AutoGen%20Team-blue)](https://github.com/microsoft/autogen)
@@ -10,38 +10,23 @@ This project shows how to create a sample plugin for MarkItDown. The most import
Next, implement your custom DocumentConverter: Next, implement your custom DocumentConverter:
```python ```python
from typing import BinaryIO, Any from typing import Union
from markitdown import MarkItDown, DocumentConverter, DocumentConverterResult, StreamInfo from markitdown import DocumentConverter, DocumentConverterResult
class RtfConverter(DocumentConverter): 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
def __init__( # Implement the conversion logic here ...
self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
):
super().__init__(priority=priority)
def accepts( # Return the result
self, return DocumentConverterResult(
file_stream: BinaryIO, title=title,
stream_info: StreamInfo, text_content=text_content,
**kwargs: Any, )
) -> bool:
# Implement logic to check if the file stream is an RTF file
# ...
raise NotImplementedError()
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> DocumentConverterResult:
# Implement logic to convert the file stream to Markdown
# ...
raise NotImplementedError()
``` ```
Next, make sure your package implements and exports the following: Next, make sure your package implements and exports the following:
@@ -86,10 +71,10 @@ Once the plugin package is installed, verify that it is available to MarkItDown
markitdown --list-plugins markitdown --list-plugins
``` ```
To use the plugin for a conversion use the `--use-plugins` flag. For example, to convert an RTF file: To use the plugin for a conversion use the `--use-plugins` flag. For example, to convert a PDF:
```bash ```bash
markitdown --use-plugins path-to-file.rtf markitdown --use-plugins path-to-file.pdf
``` ```
In Python, plugins can be enabled as follows: In Python, plugins can be enabled as follows:
@@ -98,7 +83,7 @@ In Python, plugins can be enabled as follows:
from markitdown import MarkItDown from markitdown import MarkItDown
md = MarkItDown(enable_plugins=True) md = MarkItDown(enable_plugins=True)
result = md.convert("path-to-file.rtf") result = md.convert("path-to-file.pdf")
print(result.text_content) print(result.text_content)
``` ```
@@ -24,7 +24,7 @@ classifiers = [
"Programming Language :: Python :: Implementation :: PyPy", "Programming Language :: Python :: Implementation :: PyPy",
] ]
dependencies = [ dependencies = [
"markitdown>=0.1.0a1", "markitdown",
"striprtf", "striprtf",
] ]
@@ -1,4 +1,4 @@
# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com> # SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
# #
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
__version__ = "0.1.0a1" __version__ = "0.0.1a2"
@@ -1,26 +1,12 @@
import locale from typing import Union
from typing import BinaryIO, Any
from striprtf.striprtf import rtf_to_text from striprtf.striprtf import rtf_to_text
from markitdown import ( from markitdown import MarkItDown, DocumentConverter, DocumentConverterResult
MarkItDown,
DocumentConverter,
DocumentConverterResult,
StreamInfo,
)
__plugin_interface_version__ = ( __plugin_interface_version__ = (
1 # The version of the plugin interface that this plugin uses 1 # The version of the plugin interface that this plugin uses
) )
ACCEPTED_MIME_TYPE_PREFIXES = [
"text/rtf",
"application/rtf",
]
ACCEPTED_FILE_EXTENSIONS = [".rtf"]
def register_converters(markitdown: MarkItDown, **kwargs): def register_converters(markitdown: MarkItDown, **kwargs):
""" """
@@ -36,36 +22,18 @@ class RtfConverter(DocumentConverter):
Converts an RTF file to in the simplest possible way. Converts an RTF file to in the simplest possible way.
""" """
def accepts( def convert(self, local_path, **kwargs) -> Union[None, DocumentConverterResult]:
self, # Bail if not a RTF
file_stream: BinaryIO, extension = kwargs.get("file_extension", "")
stream_info: StreamInfo, if extension.lower() != ".rtf":
**kwargs: Any, return None
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS: # Read the RTF file
return True with open(local_path, "r") as f:
rtf = f.read()
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any,
) -> DocumentConverterResult:
# Read the file stream into an str using hte provided charset encoding, or using the system default
encoding = stream_info.charset or locale.getpreferredencoding()
stream_data = file_stream.read().decode(encoding)
# Return the result # Return the result
return DocumentConverterResult( return DocumentConverterResult(
title=None, title=None,
markdown=rtf_to_text(stream_data), text_content=rtf_to_text(rtf),
) )
@@ -1,7 +1,8 @@
#!/usr/bin/env python3 -m pytest #!/usr/bin/env python3 -m pytest
import os import os
import pytest
from markitdown import MarkItDown, StreamInfo from markitdown import MarkItDown
from markitdown_sample_plugin import RtfConverter from markitdown_sample_plugin import RtfConverter
TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files") TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
@@ -14,13 +15,9 @@ RTF_TEST_STRINGS = {
def test_converter() -> None: def test_converter() -> None:
"""Tests the RTF converter dirctly.""" """Tests the RTF converter dirctly."""
with open(os.path.join(TEST_FILES_DIR, "test.rtf"), "rb") as file_stream:
converter = RtfConverter() converter = RtfConverter()
result = converter.convert( result = converter.convert(
file_stream=file_stream, os.path.join(TEST_FILES_DIR, "test.rtf"), file_extension=".rtf"
stream_info=StreamInfo(
mimetype="text/rtf", extension=".rtf", filename="test.rtf"
),
) )
for test_string in RTF_TEST_STRINGS: for test_string in RTF_TEST_STRINGS:
@@ -29,7 +26,7 @@ def test_converter() -> None:
def test_markitdown() -> None: def test_markitdown() -> None:
"""Tests that MarkItDown correctly loads the plugin.""" """Tests that MarkItDown correctly loads the plugin."""
md = MarkItDown(enable_plugins=True) md = MarkItDown()
result = md.convert(os.path.join(TEST_FILES_DIR, "test.rtf")) result = md.convert(os.path.join(TEST_FILES_DIR, "test.rtf"))
for test_string in RTF_TEST_STRINGS: for test_string in RTF_TEST_STRINGS:
+3 -6
View File
@@ -1,19 +1,16 @@
# MarkItDown # MarkItDown
> [!TIP] > [!IMPORTANT]
> MarkItDown is a Python package and command-line utility for converting various files to Markdown (e.g., for indexing, text analysis, etc). > 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. > For more information, and full documentation, see the project [README.md](https://github.com/microsoft/markitdown) on GitHub.
> [!IMPORTANT]
> MarkItDown performs I/O with the privileges of the current process. Like open() or requests.get(), it will access resources that the process itself can access. Sanitize your inputs in untrusted environments, and call the narrowest `convert_*` function needed for your use case (e.g., `convert_stream()`, or `convert_local()`). See the [Security Considerations](https://github.com/microsoft/markitdown#security-considerations) section of the documentation for more information.
## Installation ## Installation
From PyPI: From PyPI:
```bash ```bash
pip install markitdown[all] pip install markitdown
``` ```
From source: From source:
@@ -21,7 +18,7 @@ From source:
```bash ```bash
git clone git@github.com:microsoft/markitdown.git git clone git@github.com:microsoft/markitdown.git
cd markitdown cd markitdown
pip install -e packages/markitdown[all] pip install -e packages/markitdown
``` ```
## Usage ## Usage
-232
View File
@@ -1,232 +0,0 @@
# THIRD-PARTY SOFTWARE NOTICES AND INFORMATION
**Do Not Translate or Localize**
This project incorporates components from the projects listed below. The original copyright notices and the licenses
under which MarkItDown received such components are set forth below. MarkItDown reserves all rights not expressly
granted herein, whether by implication, estoppel or otherwise.
1.dwml (https://github.com/xiilei/dwml)
dwml NOTICES AND INFORMATION BEGIN HERE
-----------------------------------------
NOTE 1: What follows is a verbatim copy of dwml's LICENSE file, as it appeared on March 28th, 2025 - including
placeholders for the copyright owner and year.
NOTE 2: The Apache License, Version 2.0, requires that modifications to the dwml source code be documented.
The following section summarizes these changes. The full details are available in the MarkItDown source code
repository under PR #1160 (https://github.com/microsoft/markitdown/pull/1160)
This project incorporates `dwml/latex_dict.py` and `dwml/omml.py` files without any additional logic modifications (which
lives in `packages/markitdown/src/markitdown/converter_utils/docx/math` location). However, we have reformatted the code
according to `black` code formatter. From `tests/docx.py` file, we have used `DOCXML_ROOT` XML namespaces and the rest of
the file is not used.
-----------------------------------------
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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-----------------------------------------
END OF dwml NOTICES AND INFORMATION
+11 -36
View File
@@ -26,38 +26,25 @@ classifiers = [
dependencies = [ dependencies = [
"beautifulsoup4", "beautifulsoup4",
"requests", "requests",
"mammoth",
"markdownify", "markdownify",
"magika~=0.6.1", "numpy",
"charset-normalizer",
"defusedxml",
]
[project.optional-dependencies]
all = [
"python-pptx", "python-pptx",
"mammoth~=1.11.0",
"pandas", "pandas",
"openpyxl", "openpyxl",
"xlrd", "xlrd",
"lxml", "pdfminer.six",
"pdfminer.six>=20251230", "puremagic",
"pdfplumber>=0.11.9",
"olefile",
"pydub", "pydub",
"olefile",
"youtube-transcript-api",
"SpeechRecognition", "SpeechRecognition",
"youtube-transcript-api~=1.0.0", "pathvalidate",
"charset-normalizer",
"openai",
"azure-ai-documentintelligence", "azure-ai-documentintelligence",
"azure-identity", "azure-identity"
] ]
pptx = ["python-pptx"]
docx = ["mammoth~=1.11.0", "lxml"]
xlsx = ["pandas", "openpyxl"]
xls = ["pandas", "xlrd"]
pdf = ["pdfminer.six>=20251230", "pdfplumber>=0.11.9"]
outlook = ["olefile"]
audio-transcription = ["pydub", "SpeechRecognition"]
youtube-transcription = ["youtube-transcript-api"]
az-doc-intel = ["azure-ai-documentintelligence", "azure-identity"]
[project.urls] [project.urls]
Documentation = "https://github.com/microsoft/markitdown#readme" Documentation = "https://github.com/microsoft/markitdown#readme"
@@ -70,24 +57,12 @@ path = "src/markitdown/__about__.py"
[project.scripts] [project.scripts]
markitdown = "markitdown.__main__:main" markitdown = "markitdown.__main__:main"
[tool.hatch.envs.default]
features = ["all"]
[tool.hatch.envs.hatch-test]
features = ["all"]
extra-dependencies = [
"openai",
]
[tool.hatch.envs.types] [tool.hatch.envs.types]
features = ["all"]
extra-dependencies = [ extra-dependencies = [
"openai",
"mypy>=1.0.0", "mypy>=1.0.0",
] ]
[tool.hatch.envs.types.scripts] [tool.hatch.envs.types.scripts]
check = "mypy --install-types --non-interactive --ignore-missing-imports {args:src/markitdown tests}" check = "mypy --install-types --non-interactive {args:src/markitdown tests}"
[tool.coverage.run] [tool.coverage.run]
source_pkgs = ["markitdown", "tests"] source_pkgs = ["markitdown", "tests"]
@@ -1,4 +1,4 @@
# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com> # SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
# #
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
__version__ = "0.1.6b2" __version__ = "0.0.2a1"
+4 -14
View File
@@ -3,20 +3,14 @@
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
from .__about__ import __version__ from .__about__ import __version__
from ._markitdown import ( from ._markitdown import MarkItDown
MarkItDown,
PRIORITY_SPECIFIC_FILE_FORMAT,
PRIORITY_GENERIC_FILE_FORMAT,
)
from ._base_converter import DocumentConverterResult, DocumentConverter
from ._stream_info import StreamInfo
from ._exceptions import ( from ._exceptions import (
MarkItDownException, MarkItDownException,
MissingDependencyException, ConverterPrerequisiteException,
FailedConversionAttempt,
FileConversionException, FileConversionException,
UnsupportedFormatException, UnsupportedFormatException,
) )
from .converters import DocumentConverter, DocumentConverterResult
__all__ = [ __all__ = [
"__version__", "__version__",
@@ -24,11 +18,7 @@ __all__ = [
"DocumentConverter", "DocumentConverter",
"DocumentConverterResult", "DocumentConverterResult",
"MarkItDownException", "MarkItDownException",
"MissingDependencyException", "ConverterPrerequisiteException",
"FailedConversionAttempt",
"FileConversionException", "FileConversionException",
"UnsupportedFormatException", "UnsupportedFormatException",
"StreamInfo",
"PRIORITY_SPECIFIC_FILE_FORMAT",
"PRIORITY_GENERIC_FILE_FORMAT",
] ]
+7 -91
View File
@@ -3,11 +3,10 @@
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
import argparse import argparse
import sys import sys
import codecs
from textwrap import dedent from textwrap import dedent
from importlib.metadata import entry_points from importlib.metadata import entry_points
from .__about__ import __version__ from .__about__ import __version__
from ._markitdown import MarkItDown, StreamInfo, DocumentConverterResult from ._markitdown import MarkItDown, DocumentConverterResult
def main(): def main():
@@ -59,24 +58,6 @@ def main():
help="Output file name. If not provided, output is written to stdout.", help="Output file name. If not provided, output is written to stdout.",
) )
parser.add_argument(
"-x",
"--extension",
help="Provide a hint about the file extension (e.g., when reading from stdin).",
)
parser.add_argument(
"-m",
"--mime-type",
help="Provide a hint about the file's MIME type.",
)
parser.add_argument(
"-c",
"--charset",
help="Provide a hint about the file's charset (e.g, UTF-8).",
)
parser.add_argument( parser.add_argument(
"-d", "-d",
"--use-docintel", "--use-docintel",
@@ -104,57 +85,9 @@ def main():
help="List installed 3rd-party plugins. Plugins are loaded when using the -p or --use-plugin option.", help="List installed 3rd-party plugins. Plugins are loaded when using the -p or --use-plugin option.",
) )
parser.add_argument(
"--keep-data-uris",
action="store_true",
help="Keep data URIs (like base64-encoded images) in the output. By default, data URIs are truncated.",
)
parser.add_argument("filename", nargs="?") parser.add_argument("filename", nargs="?")
args = parser.parse_args() args = parser.parse_args()
# Parse the extension hint
extension_hint = args.extension
if extension_hint is not None:
extension_hint = extension_hint.strip().lower()
if len(extension_hint) > 0:
if not extension_hint.startswith("."):
extension_hint = "." + extension_hint
else:
extension_hint = None
# Parse the mime type
mime_type_hint = args.mime_type
if mime_type_hint is not None:
mime_type_hint = mime_type_hint.strip()
if len(mime_type_hint) > 0:
if mime_type_hint.count("/") != 1:
_exit_with_error(f"Invalid MIME type: {mime_type_hint}")
else:
mime_type_hint = None
# Parse the charset
charset_hint = args.charset
if charset_hint is not None:
charset_hint = charset_hint.strip()
if len(charset_hint) > 0:
try:
charset_hint = codecs.lookup(charset_hint).name
except LookupError:
_exit_with_error(f"Invalid charset: {charset_hint}")
else:
charset_hint = None
stream_info = None
if (
extension_hint is not None
or mime_type_hint is not None
or charset_hint is not None
):
stream_info = StreamInfo(
extension=extension_hint, mimetype=mime_type_hint, charset=charset_hint
)
if args.list_plugins: if args.list_plugins:
# List installed plugins, then exit # List installed plugins, then exit
print("Installed MarkItDown 3rd-party Plugins:\n") print("Installed MarkItDown 3rd-party Plugins:\n")
@@ -174,12 +107,11 @@ def main():
if args.use_docintel: if args.use_docintel:
if args.endpoint is None: if args.endpoint is None:
_exit_with_error( raise ValueError(
"Document Intelligence Endpoint is required when using Document Intelligence." "Document Intelligence Endpoint is required when using Document Intelligence."
) )
elif args.filename is None: elif args.filename is None:
_exit_with_error("Filename is required when using Document Intelligence.") raise ValueError("Filename is required when using Document Intelligence.")
markitdown = MarkItDown( markitdown = MarkItDown(
enable_plugins=args.use_plugins, docintel_endpoint=args.endpoint enable_plugins=args.use_plugins, docintel_endpoint=args.endpoint
) )
@@ -187,15 +119,9 @@ def main():
markitdown = MarkItDown(enable_plugins=args.use_plugins) markitdown = MarkItDown(enable_plugins=args.use_plugins)
if args.filename is None: if args.filename is None:
result = markitdown.convert_stream( result = markitdown.convert_stream(sys.stdin.buffer)
sys.stdin.buffer,
stream_info=stream_info,
keep_data_uris=args.keep_data_uris,
)
else: else:
result = markitdown.convert( result = markitdown.convert(args.filename)
args.filename, stream_info=stream_info, keep_data_uris=args.keep_data_uris
)
_handle_output(args, result) _handle_output(args, result)
@@ -204,19 +130,9 @@ def _handle_output(args, result: DocumentConverterResult):
"""Handle output to stdout or file""" """Handle output to stdout or file"""
if args.output: if args.output:
with open(args.output, "w", encoding="utf-8") as f: with open(args.output, "w", encoding="utf-8") as f:
f.write(result.markdown) f.write(result.text_content)
else: else:
# Handle stdout encoding errors more gracefully print(result.text_content)
print(
result.markdown.encode(sys.stdout.encoding, errors="replace").decode(
sys.stdout.encoding
)
)
def _exit_with_error(message: str):
print(message)
sys.exit(1)
if __name__ == "__main__": if __name__ == "__main__":
@@ -1,105 +0,0 @@
from typing import Any, BinaryIO, Optional
from ._stream_info import StreamInfo
class DocumentConverterResult:
"""The result of converting a document to Markdown."""
def __init__(
self,
markdown: str,
*,
title: Optional[str] = None,
):
"""
Initialize the DocumentConverterResult.
The only required parameter is the converted Markdown text.
The title, and any other metadata that may be added in the future, are optional.
Parameters:
- markdown: The converted Markdown text.
- title: Optional title of the document.
"""
self.markdown = markdown
self.title = title
@property
def text_content(self) -> str:
"""Soft-deprecated alias for `markdown`. New code should migrate to using `markdown` or __str__."""
return self.markdown
@text_content.setter
def text_content(self, markdown: str):
"""Soft-deprecated alias for `markdown`. New code should migrate to using `markdown` or __str__."""
self.markdown = markdown
def __str__(self) -> str:
"""Return the converted Markdown text."""
return self.markdown
class DocumentConverter:
"""Abstract superclass of all DocumentConverters."""
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> bool:
"""
Return a quick determination on if the converter should attempt converting the document.
This is primarily based `stream_info` (typically, `stream_info.mimetype`, `stream_info.extension`).
In cases where the data is retrieved via HTTP, the `steam_info.url` might also be referenced to
make a determination (e.g., special converters for Wikipedia, YouTube etc).
Finally, it is conceivable that the `stream_info.filename` might be used to in cases
where the filename is well-known (e.g., `Dockerfile`, `Makefile`, etc)
NOTE: The method signature is designed to match that of the convert() method. This provides some
assurance that, if accepts() returns True, the convert() method will also be able to handle the document.
IMPORTANT: In rare cases, (e.g., OutlookMsgConverter) we need to read more from the stream to make a final
determination. Read operations inevitably advances the position in file_stream. In these case, the position
MUST be reset it MUST be reset before returning. This is because the convert() method may be called immediately
after accepts(), and will expect the file_stream to be at the original position.
E.g.,
cur_pos = file_stream.tell() # Save the current position
data = file_stream.read(100) # ... peek at the first 100 bytes, etc.
file_stream.seek(cur_pos) # Reset the position to the original position
Parameters:
- file_stream: The file-like object to convert. Must support seek(), tell(), and read() methods.
- stream_info: The StreamInfo object containing metadata about the file (mimetype, extension, charset, set)
- kwargs: Additional keyword arguments for the converter.
Returns:
- bool: True if the converter can handle the document, False otherwise.
"""
raise NotImplementedError(
f"The subclass, {type(self).__name__}, must implement the accepts() method to determine if they can handle the document."
)
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> DocumentConverterResult:
"""
Convert a document to Markdown text.
Parameters:
- file_stream: The file-like object to convert. Must support seek(), tell(), and read() methods.
- stream_info: The StreamInfo object containing metadata about the file (mimetype, extension, charset, set)
- kwargs: Additional keyword arguments for the converter.
Returns:
- DocumentConverterResult: The result of the conversion, which includes the title and markdown content.
Raises:
- FileConversionException: If the mimetype is recognized, but the conversion fails for some other reason.
- MissingDependencyException: If the converter requires a dependency that is not installed.
"""
raise NotImplementedError("Subclasses must implement this method")
@@ -1,14 +1,4 @@
from typing import Optional, List, Any class MarkItDownException(BaseException):
MISSING_DEPENDENCY_MESSAGE = """{converter} recognized the input as a potential {extension} file, but the dependencies needed to read {extension} files have not been installed. To resolve this error, include the optional dependency [{feature}] or [all] when installing MarkItDown. For example:
* pip install markitdown[{feature}]
* pip install markitdown[all]
* pip install markitdown[{feature}, ...]
* etc."""
class MarkItDownException(Exception):
""" """
Base exception class for MarkItDown. Base exception class for MarkItDown.
""" """
@@ -16,16 +6,24 @@ class MarkItDownException(Exception):
pass pass
class MissingDependencyException(MarkItDownException): class ConverterPrerequisiteException(MarkItDownException):
""" """
Converters shipped with MarkItDown may depend on optional Thrown when instantiating a DocumentConverter in cases where
dependencies. This exception is thrown when a converter's a required library or dependency is not installed, an API key
convert() method is called, but the required dependency is not is not set, or some other prerequisite is not met.
installed. This is not necessarily a fatal error, as the converter
will simply be skipped (an error will bubble up only if no other
suitable converter is found).
Error messages should clearly indicate which dependency is missing. 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 pass
@@ -37,40 +35,3 @@ class UnsupportedFormatException(MarkItDownException):
""" """
pass pass
class FailedConversionAttempt(object):
"""
Represents an a single attempt to convert a file.
"""
def __init__(self, converter: Any, exc_info: Optional[tuple] = None):
self.converter = converter
self.exc_info = exc_info
class FileConversionException(MarkItDownException):
"""
Thrown when a suitable converter was found, but the conversion
process fails for any reason.
"""
def __init__(
self,
message: Optional[str] = None,
attempts: Optional[List[FailedConversionAttempt]] = None,
):
self.attempts = attempts
if message is None:
if attempts is None:
message = "File conversion failed."
else:
message = f"File conversion failed after {len(attempts)} attempts:\n"
for attempt in attempts:
if attempt.exc_info is None:
message += f" - {type(attempt.converter).__name__} provided no execution info."
else:
message += f" - {type(attempt.converter).__name__} threw {attempt.exc_info[0].__name__} with message: {attempt.exc_info[1]}\n"
super().__init__(message)
+261 -565
View File
@@ -1,25 +1,24 @@
import copy
import mimetypes import mimetypes
import os import os
import re import re
import sys import tempfile
import shutil import warnings
import traceback import traceback
import io
from dataclasses import dataclass
from importlib.metadata import entry_points from importlib.metadata import entry_points
from typing import Any, List, Dict, Optional, Union, BinaryIO from typing import Any, List, Optional, Union
from pathlib import Path from pathlib import Path
from urllib.parse import urlparse from urllib.parse import urlparse
from warnings import warn from warnings import warn
import requests from io import BufferedIOBase, TextIOBase, BytesIO
import magika
import charset_normalizer
import codecs
from ._stream_info import StreamInfo # File-format detection
from ._uri_utils import parse_data_uri, file_uri_to_path import puremagic
import requests
from .converters import ( from .converters import (
DocumentConverter,
DocumentConverterResult,
PlainTextConverter, PlainTextConverter,
HtmlConverter, HtmlConverter,
RssConverter, RssConverter,
@@ -33,36 +32,27 @@ from .converters import (
XlsConverter, XlsConverter,
PptxConverter, PptxConverter,
ImageConverter, ImageConverter,
AudioConverter, WavConverter,
Mp3Converter,
OutlookMsgConverter, OutlookMsgConverter,
ZipConverter, ZipConverter,
EpubConverter,
DocumentIntelligenceConverter, DocumentIntelligenceConverter,
CsvConverter, ConverterInput,
) )
from ._base_converter import DocumentConverter, DocumentConverterResult
from ._exceptions import ( from ._exceptions import (
FileConversionException, FileConversionException,
UnsupportedFormatException, UnsupportedFormatException,
FailedConversionAttempt, ConverterPrerequisiteException,
) )
# Override mimetype for csv to fix issue on windows
mimetypes.add_type("text/csv", ".csv")
# Lower priority values are tried first. _plugins: Union[None | List[Any]] = None
PRIORITY_SPECIFIC_FILE_FORMAT = (
0.0 # e.g., .docx, .pdf, .xlsx, Or specific pages, e.g., wikipedia
)
PRIORITY_GENERIC_FILE_FORMAT = (
10.0 # Near catch-all converters for mimetypes like text/*, etc.
)
_plugins: Union[None, List[Any]] = None # If None, plugins have not been loaded yet. def _load_plugins() -> Union[None | List[Any]]:
def _load_plugins() -> Union[None, List[Any]]:
"""Lazy load plugins, exiting early if already loaded.""" """Lazy load plugins, exiting early if already loaded."""
global _plugins global _plugins
@@ -82,14 +72,6 @@ def _load_plugins() -> Union[None, List[Any]]:
return _plugins return _plugins
@dataclass(kw_only=True, frozen=True)
class ConverterRegistration:
"""A registration of a converter with its priority and other metadata."""
converter: DocumentConverter
priority: float
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.
This reader will convert common file-types or webpages to Markdown.""" This reader will convert common file-types or webpages to Markdown."""
@@ -107,27 +89,17 @@ class MarkItDown:
requests_session = kwargs.get("requests_session") requests_session = kwargs.get("requests_session")
if requests_session is None: if requests_session is None:
self._requests_session = requests.Session() self._requests_session = requests.Session()
# Signal that we prefer markdown over HTML, etc. if the server supports it.
# e.g., https://blog.cloudflare.com/markdown-for-agents/
self._requests_session.headers.update(
{
"Accept": "text/markdown, text/html;q=0.9, text/plain;q=0.8, */*;q=0.1"
}
)
else: else:
self._requests_session = requests_session self._requests_session = requests_session
self._magika = magika.Magika()
# TODO - remove these (see enable_builtins) # TODO - remove these (see enable_builtins)
self._llm_client: Any = None self._llm_client = None
self._llm_model: Union[str | None] = None self._llm_model = None
self._llm_prompt: Union[str | None] = None self._exiftool_path = None
self._exiftool_path: Union[str | None] = None self._style_map = None
self._style_map: Union[str | None] = None
# Register the converters # Register the converters
self._converters: List[ConverterRegistration] = [] self._page_converters: List[DocumentConverter] = []
if ( if (
enable_builtins is None or enable_builtins enable_builtins is None or enable_builtins
@@ -147,46 +119,17 @@ class MarkItDown:
# TODO: Move these into converter constructors # TODO: Move these into converter constructors
self._llm_client = kwargs.get("llm_client") self._llm_client = kwargs.get("llm_client")
self._llm_model = kwargs.get("llm_model") self._llm_model = kwargs.get("llm_model")
self._llm_prompt = kwargs.get("llm_prompt")
self._exiftool_path = kwargs.get("exiftool_path") self._exiftool_path = kwargs.get("exiftool_path")
self._style_map = kwargs.get("style_map") self._style_map = kwargs.get("style_map")
if self._exiftool_path is None: if self._exiftool_path is None:
self._exiftool_path = os.getenv("EXIFTOOL_PATH") self._exiftool_path = os.getenv("EXIFTOOL_PATH")
# Still none? Check well-known paths
if self._exiftool_path is None:
candidate = shutil.which("exiftool")
if candidate:
candidate = os.path.abspath(candidate)
if any(
d == os.path.dirname(candidate)
for d in [
"/usr/bin",
"/usr/local/bin",
"/opt",
"/opt/bin",
"/opt/local/bin",
"/opt/homebrew/bin",
"C:\\Windows\\System32",
"C:\\Program Files",
"C:\\Program Files (x86)",
]
):
self._exiftool_path = candidate
# Register converters for successful browsing operations # Register converters for successful browsing operations
# Later registrations are tried first / take higher priority than earlier registrations # 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 # To this end, the most specific converters should appear below the most generic converters
self.register_converter( self.register_converter(PlainTextConverter())
PlainTextConverter(), priority=PRIORITY_GENERIC_FILE_FORMAT self.register_converter(ZipConverter())
) self.register_converter(HtmlConverter())
self.register_converter(
ZipConverter(markitdown=self), priority=PRIORITY_GENERIC_FILE_FORMAT
)
self.register_converter(
HtmlConverter(), priority=PRIORITY_GENERIC_FILE_FORMAT
)
self.register_converter(RssConverter()) self.register_converter(RssConverter())
self.register_converter(WikipediaConverter()) self.register_converter(WikipediaConverter())
self.register_converter(YouTubeConverter()) self.register_converter(YouTubeConverter())
@@ -195,34 +138,18 @@ class MarkItDown:
self.register_converter(XlsxConverter()) self.register_converter(XlsxConverter())
self.register_converter(XlsConverter()) self.register_converter(XlsConverter())
self.register_converter(PptxConverter()) self.register_converter(PptxConverter())
self.register_converter(AudioConverter()) self.register_converter(WavConverter())
self.register_converter(Mp3Converter())
self.register_converter(ImageConverter()) self.register_converter(ImageConverter())
self.register_converter(IpynbConverter()) self.register_converter(IpynbConverter())
self.register_converter(PdfConverter()) self.register_converter(PdfConverter())
self.register_converter(OutlookMsgConverter()) self.register_converter(OutlookMsgConverter())
self.register_converter(EpubConverter())
self.register_converter(CsvConverter())
# Register Document Intelligence converter at the top of the stack if endpoint is provided # Register Document Intelligence converter at the top of the stack if endpoint is provided
docintel_endpoint = kwargs.get("docintel_endpoint") docintel_endpoint = kwargs.get("docintel_endpoint")
if docintel_endpoint is not None: if docintel_endpoint is not None:
docintel_args: Dict[str, Any] = {}
docintel_args["endpoint"] = docintel_endpoint
docintel_credential = kwargs.get("docintel_credential")
if docintel_credential is not None:
docintel_args["credential"] = docintel_credential
docintel_types = kwargs.get("docintel_file_types")
if docintel_types is not None:
docintel_args["file_types"] = docintel_types
docintel_version = kwargs.get("docintel_api_version")
if docintel_version is not None:
docintel_args["api_version"] = docintel_version
self.register_converter( self.register_converter(
DocumentIntelligenceConverter(**docintel_args), DocumentIntelligenceConverter(endpoint=docintel_endpoint)
) )
self._builtins_enabled = True self._builtins_enabled = True
@@ -237,9 +164,7 @@ class MarkItDown:
""" """
if not self._plugins_enabled: if not self._plugins_enabled:
# Load plugins # Load plugins
plugins = _load_plugins() for plugin in _load_plugins():
assert plugins is not None
for plugin in plugins:
try: try:
plugin.register_converters(self, **kwargs) plugin.register_converters(self, **kwargs)
except Exception: except Exception:
@@ -251,315 +176,192 @@ class MarkItDown:
def convert( def convert(
self, self,
source: Union[str, requests.Response, Path, BinaryIO], source: Union[str, requests.Response, Path, BufferedIOBase, TextIOBase],
*,
stream_info: Optional[StreamInfo] = None,
**kwargs: Any, **kwargs: Any,
) -> DocumentConverterResult: # TODO: deal with kwargs ) -> DocumentConverterResult: # TODO: deal with kwargs
""" """
Args: Args:
- source: can be a path (str or Path), url, or a requests.response object - source: can be a string representing a path either as string pathlib path object or url, a requests.response object, or a file object (TextIO or BinaryIO)
- stream_info: optional stream info to use for the conversion. If None, infer from source - extension: specifies the file extension to use when interpreting the file. If None, infer from source (path, uri, content-type, etc.)
- kwargs: additional arguments to pass to the converter
""" """
# Local path or url # Local path or url
if isinstance(source, str): if isinstance(source, str):
if ( if (
source.startswith("http:") source.startswith("http://")
or source.startswith("https:") or source.startswith("https://")
or source.startswith("file:") or source.startswith("file://")
or source.startswith("data:")
): ):
# Rename the url argument to mock_url return self.convert_url(source, **kwargs)
# (Deprecated -- use stream_info)
_kwargs = {k: v for k, v in kwargs.items()}
if "url" in _kwargs:
_kwargs["mock_url"] = _kwargs["url"]
del _kwargs["url"]
return self.convert_uri(source, stream_info=stream_info, **_kwargs)
else: else:
return self.convert_local(source, stream_info=stream_info, **kwargs) return self.convert_local(source, **kwargs)
# Path object
elif isinstance(source, Path):
return self.convert_local(source, stream_info=stream_info, **kwargs)
# Request response # Request response
elif isinstance(source, requests.Response): elif isinstance(source, requests.Response):
return self.convert_response(source, stream_info=stream_info, **kwargs) return self.convert_response(source, **kwargs)
# Binary stream elif isinstance(source, Path):
elif ( return self.convert_local(source, **kwargs)
hasattr(source, "read") # File object
and callable(source.read) elif isinstance(source, BufferedIOBase) or isinstance(source, TextIOBase):
and not isinstance(source, io.TextIOBase) return self.convert_file_object(source, **kwargs)
):
return self.convert_stream(source, stream_info=stream_info, **kwargs)
else:
raise TypeError(
f"Invalid source type: {type(source)}. Expected str, requests.Response, BinaryIO."
)
def convert_local( def convert_local(
self, self, path: Union[str, Path], **kwargs: Any
path: Union[str, Path], ) -> DocumentConverterResult: # TODO: deal with kwargs
*,
stream_info: Optional[StreamInfo] = None,
file_extension: Optional[str] = None, # Deprecated -- use stream_info
url: Optional[str] = None, # Deprecated -- use stream_info
**kwargs: Any,
) -> DocumentConverterResult:
if isinstance(path, Path): if isinstance(path, Path):
path = str(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 []
# Build a base StreamInfo object from which to start guesses # Get extension alternatives from the path and puremagic
base_guess = StreamInfo( base, ext = os.path.splitext(path)
local_path=path, self._append_ext(extensions, ext)
extension=os.path.splitext(path)[1],
filename=os.path.basename(path),
)
# Extend the base_guess with any additional info from the arguments for g in self._guess_ext_magic(source=path):
if stream_info is not None: self._append_ext(extensions, g)
base_guess = base_guess.copy_and_update(stream_info)
if file_extension is not None: # Create the ConverterInput object
# Deprecated -- use stream_info input = ConverterInput(input_type="filepath", filepath=path)
base_guess = base_guess.copy_and_update(extension=file_extension)
if url is not None:
# Deprecated -- use stream_info
base_guess = base_guess.copy_and_update(url=url)
with open(path, "rb") as fh:
guesses = self._get_stream_info_guesses(
file_stream=fh, base_guess=base_guess
)
return self._convert(file_stream=fh, stream_info_guesses=guesses, **kwargs)
def convert_stream(
self,
stream: BinaryIO,
*,
stream_info: Optional[StreamInfo] = None,
file_extension: Optional[str] = None, # Deprecated -- use stream_info
url: Optional[str] = None, # Deprecated -- use stream_info
**kwargs: Any,
) -> DocumentConverterResult:
guesses: List[StreamInfo] = []
# Do we have anything on which to base a guess?
base_guess = None
if stream_info is not None or file_extension is not None or url is not None:
# Start with a non-Null base guess
if stream_info is None:
base_guess = StreamInfo()
else:
base_guess = stream_info
if file_extension is not None:
# Deprecated -- use stream_info
assert base_guess is not None # for mypy
base_guess = base_guess.copy_and_update(extension=file_extension)
if url is not None:
# Deprecated -- use stream_info
assert base_guess is not None # for mypy
base_guess = base_guess.copy_and_update(url=url)
# Check if we have a seekable stream. If not, load the entire stream into memory.
if not stream.seekable():
buffer = io.BytesIO()
while True:
chunk = stream.read(4096)
if not chunk:
break
buffer.write(chunk)
buffer.seek(0)
stream = buffer
# Add guesses based on stream content
guesses = self._get_stream_info_guesses(
file_stream=stream, base_guess=base_guess or StreamInfo()
)
return self._convert(file_stream=stream, stream_info_guesses=guesses, **kwargs)
def convert_url(
self,
url: str,
*,
stream_info: Optional[StreamInfo] = None,
file_extension: Optional[str] = None,
mock_url: Optional[str] = None,
**kwargs: Any,
) -> DocumentConverterResult:
"""Alias for convert_uri()"""
# convert_url will likely be deprecated in the future in favor of convert_uri
return self.convert_uri(
url,
stream_info=stream_info,
file_extension=file_extension,
mock_url=mock_url,
**kwargs,
)
def convert_uri(
self,
uri: str,
*,
stream_info: Optional[StreamInfo] = None,
file_extension: Optional[str] = None, # Deprecated -- use stream_info
mock_url: Optional[
str
] = None, # Mock the request as if it came from a different URL
**kwargs: Any,
) -> DocumentConverterResult:
uri = uri.strip()
# File URIs
if uri.startswith("file:"):
netloc, path = file_uri_to_path(uri)
if netloc and netloc != "localhost":
raise ValueError(
f"Unsupported file URI: {uri}. Netloc must be empty or localhost."
)
return self.convert_local(
path,
stream_info=stream_info,
file_extension=file_extension,
url=mock_url,
**kwargs,
)
# Data URIs
elif uri.startswith("data:"):
mimetype, attributes, data = parse_data_uri(uri)
base_guess = StreamInfo(
mimetype=mimetype,
charset=attributes.get("charset"),
)
if stream_info is not None:
base_guess = base_guess.copy_and_update(stream_info)
return self.convert_stream(
io.BytesIO(data),
stream_info=base_guess,
file_extension=file_extension,
url=mock_url,
**kwargs,
)
# HTTP/HTTPS URIs
elif uri.startswith("http:") or uri.startswith("https:"):
response = self._requests_session.get(uri, stream=True)
response.raise_for_status()
return self.convert_response(
response,
stream_info=stream_info,
file_extension=file_extension,
url=mock_url,
**kwargs,
)
else:
raise ValueError(
f"Unsupported URI scheme: {uri.split(':')[0]}. Supported schemes are: file:, data:, http:, https:"
)
def convert_response(
self,
response: requests.Response,
*,
stream_info: Optional[StreamInfo] = None,
file_extension: Optional[str] = None, # Deprecated -- use stream_info
url: Optional[str] = None, # Deprecated -- use stream_info
**kwargs: Any,
) -> DocumentConverterResult:
# If there is a content-type header, get the mimetype and charset (if present)
mimetype: Optional[str] = None
charset: Optional[str] = None
if "content-type" in response.headers:
parts = response.headers["content-type"].split(";")
mimetype = parts.pop(0).strip()
for part in parts:
if part.strip().startswith("charset="):
_charset = part.split("=")[1].strip()
if len(_charset) > 0:
charset = _charset
# If there is a content-disposition header, get the filename and possibly the extension
filename: Optional[str] = None
extension: Optional[str] = None
if "content-disposition" in response.headers:
m = re.search(r"filename=([^;]+)", response.headers["content-disposition"])
if m:
filename = m.group(1).strip("\"'")
_, _extension = os.path.splitext(filename)
if len(_extension) > 0:
extension = _extension
# If there is still no filename, try to read it from the url
if filename is None:
parsed_url = urlparse(response.url)
_, _extension = os.path.splitext(parsed_url.path)
if len(_extension) > 0: # Looks like this might be a file!
filename = os.path.basename(parsed_url.path)
extension = _extension
# Create an initial guess from all this information
base_guess = StreamInfo(
mimetype=mimetype,
charset=charset,
filename=filename,
extension=extension,
url=response.url,
)
# Update with any additional info from the arguments
if stream_info is not None:
base_guess = base_guess.copy_and_update(stream_info)
if file_extension is not None:
# Deprecated -- use stream_info
base_guess = base_guess.copy_and_update(extension=file_extension)
if url is not None:
# Deprecated -- use stream_info
base_guess = base_guess.copy_and_update(url=url)
# Read into BytesIO
buffer = io.BytesIO()
for chunk in response.iter_content(chunk_size=512):
buffer.write(chunk)
buffer.seek(0)
# Convert # Convert
guesses = self._get_stream_info_guesses( return self._convert(input, extensions, **kwargs)
file_stream=buffer, base_guess=base_guess
) def convert_file_object(
return self._convert(file_stream=buffer, stream_info_guesses=guesses, **kwargs) self, file_object: Union[BufferedIOBase, TextIOBase], **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 []
# TODO: Curently, there are some ongoing issues with passing direct file objects to puremagic (incorrect guesses, unsupported file type errors, etc.)
# Only use puremagic as a last resort if no extensions were provided
if extensions == []:
for g in self._guess_ext_magic(source=file_object):
self._append_ext(extensions, g)
# Create the ConverterInput object
input = ConverterInput(input_type="object", file_object=file_object)
# Convert
return self._convert(input, 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(source=temp_path):
self._append_ext(extensions, g)
# Create the ConverterInput object
input = ConverterInput(input_type="filepath", filepath=temp_path)
# Convert
result = self._convert(input, 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(source=temp_path):
self._append_ext(extensions, g)
# Create the ConverterInput object
input = ConverterInput(input_type="filepath", filepath=temp_path)
# Convert
result = self._convert(input, extensions, url=response.url, **kwargs)
# Clean up
finally:
try:
fh.close()
except Exception:
pass
os.unlink(temp_path)
return result
def _convert( def _convert(
self, *, file_stream: BinaryIO, stream_info_guesses: List[StreamInfo], **kwargs self, input: ConverterInput, extensions: List[Union[str, None]], **kwargs
) -> DocumentConverterResult: ) -> DocumentConverterResult:
res: Union[None, DocumentConverterResult] = None error_trace = ""
# Keep track of which converters throw exceptions
failed_attempts: List[FailedConversionAttempt] = []
# Create a copy of the page_converters list, sorted by priority. # 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. # 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. # The sort is guaranteed to be stable, so converters with the same priority will remain in the same order.
sorted_registrations = sorted(self._converters, key=lambda x: x.priority) sorted_converters = sorted(self._page_converters, key=lambda x: x.priority)
# Remember the initial stream position so that we can return to it for ext in extensions + [None]: # Try last with no extension
cur_pos = file_stream.tell() for converter in sorted_converters:
_kwargs = copy.deepcopy(kwargs)
for stream_info in stream_info_guesses + [StreamInfo()]: # Overwrite file_extension appropriately
for converter_registration in sorted_registrations: if ext is None:
converter = converter_registration.converter if "file_extension" in _kwargs:
# Sanity check -- make sure the cur_pos is still the same del _kwargs["file_extension"]
assert ( else:
cur_pos == file_stream.tell() _kwargs.update({"file_extension": ext})
), "File stream position should NOT change between guess iterations"
_kwargs = {k: v for k, v in kwargs.items()}
# Copy any additional global options # Copy any additional global options
if "llm_client" not in _kwargs and self._llm_client is not None: if "llm_client" not in _kwargs and self._llm_client is not None:
@@ -568,9 +370,6 @@ class MarkItDown:
if "llm_model" not in _kwargs and self._llm_model is not None: if "llm_model" not in _kwargs and self._llm_model is not None:
_kwargs["llm_model"] = self._llm_model _kwargs["llm_model"] = self._llm_model
if "llm_prompt" not in _kwargs and self._llm_prompt is not None:
_kwargs["llm_prompt"] = self._llm_prompt
if "style_map" not in _kwargs and self._style_map is not None: if "style_map" not in _kwargs and self._style_map is not None:
_kwargs["style_map"] = self._style_map _kwargs["style_map"] = self._style_map
@@ -578,40 +377,13 @@ class MarkItDown:
_kwargs["exiftool_path"] = self._exiftool_path _kwargs["exiftool_path"] = self._exiftool_path
# Add the list of converters for nested processing # Add the list of converters for nested processing
_kwargs["_parent_converters"] = self._converters _kwargs["_parent_converters"] = self._page_converters
# Add legaxy kwargs # If we hit an error log it and keep trying
if stream_info is not None:
if stream_info.extension is not None:
_kwargs["file_extension"] = stream_info.extension
if stream_info.url is not None:
_kwargs["url"] = stream_info.url
# Check if the converter will accept the file, and if so, try to convert it
_accepts = False
try: try:
_accepts = converter.accepts(file_stream, stream_info, **_kwargs) res = converter.convert(input, **_kwargs)
except NotImplementedError:
pass
# accept() should not have changed the file stream position
assert (
cur_pos == file_stream.tell()
), f"{type(converter).__name__}.accept() should NOT change the file_stream position"
# Attempt the conversion
if _accepts:
try:
res = converter.convert(file_stream, stream_info, **_kwargs)
except Exception: except Exception:
failed_attempts.append( error_trace = ("\n\n" + traceback.format_exc()).strip()
FailedConversionAttempt(
converter=converter, exc_info=sys.exc_info()
)
)
finally:
file_stream.seek(cur_pos)
if res is not None: if res is not None:
# Normalize the content # Normalize the content
@@ -619,17 +391,81 @@ class MarkItDown:
[line.rstrip() for line in re.split(r"\r?\n", res.text_content)] [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) res.text_content = re.sub(r"\n{3,}", "\n\n", res.text_content)
# Todo
return res return res
# If we got this far without success, report any exceptions # If we got this far without success, report any exceptions
if len(failed_attempts) > 0: if len(error_trace) > 0:
raise FileConversionException(attempts=failed_attempts) raise FileConversionException(
f"Could not convert '{input.filepath}' 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! # Nothing can handle it!
raise UnsupportedFormatException( raise UnsupportedFormatException(
"Could not convert stream to Markdown. No converter attempted a conversion, suggesting that the filetype is simply not supported." f"Could not convert '{input.filepath}' 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, source):
"""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 = []
# Guess extensions for filepaths
if isinstance(source, str):
guesses = puremagic.magic_file(source)
# 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(source, "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
# Guess extensions for file objects. Note that the puremagic's magic_stream function requires a BytesIO-like file source
# TODO: Figure out how to guess extensions for TextIO-like file sources (manually converting to BytesIO does not work)
elif isinstance(source, BufferedIOBase):
guesses = puremagic.magic_stream(source)
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: def register_page_converter(self, converter: DocumentConverter) -> None:
"""DEPRECATED: User register_converter instead.""" """DEPRECATED: User register_converter instead."""
warn( warn(
@@ -638,146 +474,6 @@ class MarkItDown:
) )
self.register_converter(converter) self.register_converter(converter)
def register_converter( def register_converter(self, converter: DocumentConverter) -> None:
self, """Register a page text converter."""
converter: DocumentConverter, self._page_converters.insert(0, converter)
*,
priority: float = PRIORITY_SPECIFIC_FILE_FORMAT,
) -> None:
"""
Register a DocumentConverter with a given priority.
Priorities work as follows: By default, most converters get priority
DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT (== 0). The exception
is the PlainTextConverter, HtmlConverter, and ZipConverter, which get
priority PRIORITY_SPECIFIC_FILE_FORMAT (== 10), with lower values
being tried first (i.e., higher priority).
Just prior to conversion, the converters are sorted by priority, using
a stable sort. This means that converters with the same priority will
remain in the same order, with the most recently registered converters
appearing first.
We have tight control over the order of built-in converters, but
plugins can register converters in any order. The registration's priority
field reasserts some control over the order of converters.
Plugins can register converters with any priority, to appear before or
after the built-ins. For example, a plugin with priority 9 will run
before the PlainTextConverter, but after the built-in converters.
"""
self._converters.insert(
0, ConverterRegistration(converter=converter, priority=priority)
)
def _get_stream_info_guesses(
self, file_stream: BinaryIO, base_guess: StreamInfo
) -> List[StreamInfo]:
"""
Given a base guess, attempt to guess or expand on the stream info using the stream content (via magika).
"""
guesses: List[StreamInfo] = []
# Enhance the base guess with information based on the extension or mimetype
enhanced_guess = base_guess.copy_and_update()
# If there's an extension and no mimetype, try to guess the mimetype
if base_guess.mimetype is None and base_guess.extension is not None:
_m, _ = mimetypes.guess_type(
"placeholder" + base_guess.extension, strict=False
)
if _m is not None:
enhanced_guess = enhanced_guess.copy_and_update(mimetype=_m)
# If there's a mimetype and no extension, try to guess the extension
if base_guess.mimetype is not None and base_guess.extension is None:
_e = mimetypes.guess_all_extensions(base_guess.mimetype, strict=False)
if len(_e) > 0:
enhanced_guess = enhanced_guess.copy_and_update(extension=_e[0])
# Call magika to guess from the stream
cur_pos = file_stream.tell()
try:
result = self._magika.identify_stream(file_stream)
if result.status == "ok" and result.prediction.output.label != "unknown":
# If it's text, also guess the charset
charset = None
if result.prediction.output.is_text:
# Read the first 4k to guess the charset
file_stream.seek(cur_pos)
stream_page = file_stream.read(4096)
charset_result = charset_normalizer.from_bytes(stream_page).best()
if charset_result is not None:
charset = self._normalize_charset(charset_result.encoding)
# Normalize the first extension listed
guessed_extension = None
if len(result.prediction.output.extensions) > 0:
guessed_extension = "." + result.prediction.output.extensions[0]
# Determine if the guess is compatible with the base guess
compatible = True
if (
base_guess.mimetype is not None
and base_guess.mimetype != result.prediction.output.mime_type
):
compatible = False
if (
base_guess.extension is not None
and base_guess.extension.lstrip(".")
not in result.prediction.output.extensions
):
compatible = False
if (
base_guess.charset is not None
and self._normalize_charset(base_guess.charset) != charset
):
compatible = False
if compatible:
# Add the compatible base guess
guesses.append(
StreamInfo(
mimetype=base_guess.mimetype
or result.prediction.output.mime_type,
extension=base_guess.extension or guessed_extension,
charset=base_guess.charset or charset,
filename=base_guess.filename,
local_path=base_guess.local_path,
url=base_guess.url,
)
)
else:
# The magika guess was incompatible with the base guess, so add both guesses
guesses.append(enhanced_guess)
guesses.append(
StreamInfo(
mimetype=result.prediction.output.mime_type,
extension=guessed_extension,
charset=charset,
filename=base_guess.filename,
local_path=base_guess.local_path,
url=base_guess.url,
)
)
else:
# There were no other guesses, so just add the base guess
guesses.append(enhanced_guess)
finally:
file_stream.seek(cur_pos)
return guesses
def _normalize_charset(self, charset: str | None) -> str | None:
"""
Normalize a charset string to a canonical form.
"""
if charset is None:
return None
try:
return codecs.lookup(charset).name
except LookupError:
return charset
@@ -1,32 +0,0 @@
from dataclasses import dataclass, asdict
from typing import Optional
@dataclass(kw_only=True, frozen=True)
class StreamInfo:
"""The StreamInfo class is used to store information about a file stream.
All fields can be None, and will depend on how the stream was opened.
"""
mimetype: Optional[str] = None
extension: Optional[str] = None
charset: Optional[str] = None
filename: Optional[
str
] = None # From local path, url, or Content-Disposition header
local_path: Optional[str] = None # If read from disk
url: Optional[str] = None # If read from url
def copy_and_update(self, *args, **kwargs):
"""Copy the StreamInfo object and update it with the given StreamInfo
instance and/or other keyword arguments."""
new_info = asdict(self)
for si in args:
assert isinstance(si, StreamInfo)
new_info.update({k: v for k, v in asdict(si).items() if v is not None})
if len(kwargs) > 0:
new_info.update(kwargs)
return StreamInfo(**new_info)
@@ -1,52 +0,0 @@
import base64
import os
from typing import Tuple, Dict
from urllib.request import url2pathname
from urllib.parse import urlparse, unquote_to_bytes
def file_uri_to_path(file_uri: str) -> Tuple[str | None, str]:
"""Convert a file URI to a local file path"""
parsed = urlparse(file_uri)
if parsed.scheme != "file":
raise ValueError(f"Not a file URL: {file_uri}")
netloc = parsed.netloc if parsed.netloc else None
path = os.path.abspath(url2pathname(parsed.path))
return netloc, path
def parse_data_uri(uri: str) -> Tuple[str | None, Dict[str, str], bytes]:
if not uri.startswith("data:"):
raise ValueError("Not a data URI")
header, _, data = uri.partition(",")
if not _:
raise ValueError("Malformed data URI, missing ',' separator")
meta = header[5:] # Strip 'data:'
parts = meta.split(";")
is_base64 = False
# Ends with base64?
if parts[-1] == "base64":
parts.pop()
is_base64 = True
mime_type = None # Normally this would default to text/plain but we won't assume
if len(parts) and len(parts[0]) > 0:
# First part is the mime type
mime_type = parts.pop(0)
attributes: Dict[str, str] = {}
for part in parts:
# Handle key=value pairs in the middle
if "=" in part:
key, value = part.split("=", 1)
attributes[key] = value
elif len(part) > 0:
attributes[part] = ""
content = base64.b64decode(data) if is_base64 else unquote_to_bytes(data)
return mime_type, attributes, content
@@ -1,273 +0,0 @@
# -*- coding: utf-8 -*-
"""
Adapted from https://github.com/xiilei/dwml/blob/master/dwml/latex_dict.py
On 25/03/2025
"""
from __future__ import unicode_literals
CHARS = ("{", "}", "_", "^", "#", "&", "$", "%", "~")
BLANK = ""
BACKSLASH = "\\"
ALN = "&"
CHR = {
# Unicode : Latex Math Symbols
# Top accents
"\u0300": "\\grave{{{0}}}",
"\u0301": "\\acute{{{0}}}",
"\u0302": "\\hat{{{0}}}",
"\u0303": "\\tilde{{{0}}}",
"\u0304": "\\bar{{{0}}}",
"\u0305": "\\overbar{{{0}}}",
"\u0306": "\\breve{{{0}}}",
"\u0307": "\\dot{{{0}}}",
"\u0308": "\\ddot{{{0}}}",
"\u0309": "\\ovhook{{{0}}}",
"\u030a": "\\ocirc{{{0}}}}",
"\u030c": "\\check{{{0}}}}",
"\u0310": "\\candra{{{0}}}",
"\u0312": "\\oturnedcomma{{{0}}}",
"\u0315": "\\ocommatopright{{{0}}}",
"\u031a": "\\droang{{{0}}}",
"\u0338": "\\not{{{0}}}",
"\u20d0": "\\leftharpoonaccent{{{0}}}",
"\u20d1": "\\rightharpoonaccent{{{0}}}",
"\u20d2": "\\vertoverlay{{{0}}}",
"\u20d6": "\\overleftarrow{{{0}}}",
"\u20d7": "\\vec{{{0}}}",
"\u20db": "\\dddot{{{0}}}",
"\u20dc": "\\ddddot{{{0}}}",
"\u20e1": "\\overleftrightarrow{{{0}}}",
"\u20e7": "\\annuity{{{0}}}",
"\u20e9": "\\widebridgeabove{{{0}}}",
"\u20f0": "\\asteraccent{{{0}}}",
# Bottom accents
"\u0330": "\\wideutilde{{{0}}}",
"\u0331": "\\underbar{{{0}}}",
"\u20e8": "\\threeunderdot{{{0}}}",
"\u20ec": "\\underrightharpoondown{{{0}}}",
"\u20ed": "\\underleftharpoondown{{{0}}}",
"\u20ee": "\\underledtarrow{{{0}}}",
"\u20ef": "\\underrightarrow{{{0}}}",
# Over | group
"\u23b4": "\\overbracket{{{0}}}",
"\u23dc": "\\overparen{{{0}}}",
"\u23de": "\\overbrace{{{0}}}",
# Under| group
"\u23b5": "\\underbracket{{{0}}}",
"\u23dd": "\\underparen{{{0}}}",
"\u23df": "\\underbrace{{{0}}}",
}
CHR_BO = {
# Big operators,
"\u2140": "\\Bbbsum",
"\u220f": "\\prod",
"\u2210": "\\coprod",
"\u2211": "\\sum",
"\u222b": "\\int",
"\u22c0": "\\bigwedge",
"\u22c1": "\\bigvee",
"\u22c2": "\\bigcap",
"\u22c3": "\\bigcup",
"\u2a00": "\\bigodot",
"\u2a01": "\\bigoplus",
"\u2a02": "\\bigotimes",
}
T = {
"\u2192": "\\rightarrow ",
# Greek letters
"\U0001d6fc": "\\alpha ",
"\U0001d6fd": "\\beta ",
"\U0001d6fe": "\\gamma ",
"\U0001d6ff": "\\theta ",
"\U0001d700": "\\epsilon ",
"\U0001d701": "\\zeta ",
"\U0001d702": "\\eta ",
"\U0001d703": "\\theta ",
"\U0001d704": "\\iota ",
"\U0001d705": "\\kappa ",
"\U0001d706": "\\lambda ",
"\U0001d707": "\\m ",
"\U0001d708": "\\n ",
"\U0001d709": "\\xi ",
"\U0001d70a": "\\omicron ",
"\U0001d70b": "\\pi ",
"\U0001d70c": "\\rho ",
"\U0001d70d": "\\varsigma ",
"\U0001d70e": "\\sigma ",
"\U0001d70f": "\\ta ",
"\U0001d710": "\\upsilon ",
"\U0001d711": "\\phi ",
"\U0001d712": "\\chi ",
"\U0001d713": "\\psi ",
"\U0001d714": "\\omega ",
"\U0001d715": "\\partial ",
"\U0001d716": "\\varepsilon ",
"\U0001d717": "\\vartheta ",
"\U0001d718": "\\varkappa ",
"\U0001d719": "\\varphi ",
"\U0001d71a": "\\varrho ",
"\U0001d71b": "\\varpi ",
# Relation symbols
"\u2190": "\\leftarrow ",
"\u2191": "\\uparrow ",
"\u2192": "\\rightarrow ",
"\u2193": "\\downright ",
"\u2194": "\\leftrightarrow ",
"\u2195": "\\updownarrow ",
"\u2196": "\\nwarrow ",
"\u2197": "\\nearrow ",
"\u2198": "\\searrow ",
"\u2199": "\\swarrow ",
"\u22ee": "\\vdots ",
"\u22ef": "\\cdots ",
"\u22f0": "\\adots ",
"\u22f1": "\\ddots ",
"\u2260": "\\ne ",
"\u2264": "\\leq ",
"\u2265": "\\geq ",
"\u2266": "\\leqq ",
"\u2267": "\\geqq ",
"\u2268": "\\lneqq ",
"\u2269": "\\gneqq ",
"\u226a": "\\ll ",
"\u226b": "\\gg ",
"\u2208": "\\in ",
"\u2209": "\\notin ",
"\u220b": "\\ni ",
"\u220c": "\\nni ",
# Ordinary symbols
"\u221e": "\\infty ",
# Binary relations
"\u00b1": "\\pm ",
"\u2213": "\\mp ",
# Italic, Latin, uppercase
"\U0001d434": "A",
"\U0001d435": "B",
"\U0001d436": "C",
"\U0001d437": "D",
"\U0001d438": "E",
"\U0001d439": "F",
"\U0001d43a": "G",
"\U0001d43b": "H",
"\U0001d43c": "I",
"\U0001d43d": "J",
"\U0001d43e": "K",
"\U0001d43f": "L",
"\U0001d440": "M",
"\U0001d441": "N",
"\U0001d442": "O",
"\U0001d443": "P",
"\U0001d444": "Q",
"\U0001d445": "R",
"\U0001d446": "S",
"\U0001d447": "T",
"\U0001d448": "U",
"\U0001d449": "V",
"\U0001d44a": "W",
"\U0001d44b": "X",
"\U0001d44c": "Y",
"\U0001d44d": "Z",
# Italic, Latin, lowercase
"\U0001d44e": "a",
"\U0001d44f": "b",
"\U0001d450": "c",
"\U0001d451": "d",
"\U0001d452": "e",
"\U0001d453": "f",
"\U0001d454": "g",
"\U0001d456": "i",
"\U0001d457": "j",
"\U0001d458": "k",
"\U0001d459": "l",
"\U0001d45a": "m",
"\U0001d45b": "n",
"\U0001d45c": "o",
"\U0001d45d": "p",
"\U0001d45e": "q",
"\U0001d45f": "r",
"\U0001d460": "s",
"\U0001d461": "t",
"\U0001d462": "u",
"\U0001d463": "v",
"\U0001d464": "w",
"\U0001d465": "x",
"\U0001d466": "y",
"\U0001d467": "z",
}
FUNC = {
"sin": "\\sin({fe})",
"cos": "\\cos({fe})",
"tan": "\\tan({fe})",
"arcsin": "\\arcsin({fe})",
"arccos": "\\arccos({fe})",
"arctan": "\\arctan({fe})",
"arccot": "\\arccot({fe})",
"sinh": "\\sinh({fe})",
"cosh": "\\cosh({fe})",
"tanh": "\\tanh({fe})",
"coth": "\\coth({fe})",
"sec": "\\sec({fe})",
"csc": "\\csc({fe})",
}
FUNC_PLACE = "{fe}"
BRK = "\\\\"
CHR_DEFAULT = {
"ACC_VAL": "\\hat{{{0}}}",
}
POS = {
"top": "\\overline{{{0}}}", # not sure
"bot": "\\underline{{{0}}}",
}
POS_DEFAULT = {
"BAR_VAL": "\\overline{{{0}}}",
}
SUB = "_{{{0}}}"
SUP = "^{{{0}}}"
F = {
"bar": "\\frac{{{num}}}{{{den}}}",
"skw": r"^{{{num}}}/_{{{den}}}",
"noBar": "\\genfrac{{}}{{}}{{0pt}}{{}}{{{num}}}{{{den}}}",
"lin": "{{{num}}}/{{{den}}}",
}
F_DEFAULT = "\\frac{{{num}}}{{{den}}}"
D = "\\left{left}{text}\\right{right}"
D_DEFAULT = {
"left": "(",
"right": ")",
"null": ".",
}
RAD = "\\sqrt[{deg}]{{{text}}}"
RAD_DEFAULT = "\\sqrt{{{text}}}"
ARR = "\\begin{{array}}{{c}}{text}\\end{{array}}"
LIM_FUNC = {
"lim": "\\lim_{{{lim}}}",
"max": "\\max_{{{lim}}}",
"min": "\\min_{{{lim}}}",
}
LIM_TO = ("\\rightarrow", "\\to")
LIM_UPP = "\\overset{{{lim}}}{{{text}}}"
M = "\\begin{{matrix}}{text}\\end{{matrix}}"
@@ -1,400 +0,0 @@
# -*- coding: utf-8 -*-
"""
Office Math Markup Language (OMML)
Adapted from https://github.com/xiilei/dwml/blob/master/dwml/omml.py
On 25/03/2025
"""
from defusedxml import ElementTree as ET
from .latex_dict import (
CHARS,
CHR,
CHR_BO,
CHR_DEFAULT,
POS,
POS_DEFAULT,
SUB,
SUP,
F,
F_DEFAULT,
T,
FUNC,
D,
D_DEFAULT,
RAD,
RAD_DEFAULT,
ARR,
LIM_FUNC,
LIM_TO,
LIM_UPP,
M,
BRK,
BLANK,
BACKSLASH,
ALN,
FUNC_PLACE,
)
OMML_NS = "{http://schemas.openxmlformats.org/officeDocument/2006/math}"
def load(stream):
tree = ET.parse(stream)
for omath in tree.findall(OMML_NS + "oMath"):
yield oMath2Latex(omath)
def load_string(string):
root = ET.fromstring(string)
for omath in root.findall(OMML_NS + "oMath"):
yield oMath2Latex(omath)
def escape_latex(strs):
last = None
new_chr = []
strs = strs.replace(r"\\", "\\")
for c in strs:
if (c in CHARS) and (last != BACKSLASH):
new_chr.append(BACKSLASH + c)
else:
new_chr.append(c)
last = c
return BLANK.join(new_chr)
def get_val(key, default=None, store=CHR):
if key is not None:
return key if not store else store.get(key, key)
else:
return default
class Tag2Method(object):
def call_method(self, elm, stag=None):
getmethod = self.tag2meth.get
if stag is None:
stag = elm.tag.replace(OMML_NS, "")
method = getmethod(stag)
if method:
return method(self, elm)
else:
return None
def process_children_list(self, elm, include=None):
"""
process children of the elm,return iterable
"""
for _e in list(elm):
if OMML_NS not in _e.tag:
continue
stag = _e.tag.replace(OMML_NS, "")
if include and (stag not in include):
continue
t = self.call_method(_e, stag=stag)
if t is None:
t = self.process_unknow(_e, stag)
if t is None:
continue
yield (stag, t, _e)
def process_children_dict(self, elm, include=None):
"""
process children of the elm,return dict
"""
latex_chars = dict()
for stag, t, e in self.process_children_list(elm, include):
latex_chars[stag] = t
return latex_chars
def process_children(self, elm, include=None):
"""
process children of the elm,return string
"""
return BLANK.join(
(
t if not isinstance(t, Tag2Method) else str(t)
for stag, t, e in self.process_children_list(elm, include)
)
)
def process_unknow(self, elm, stag):
return None
class Pr(Tag2Method):
text = ""
__val_tags = ("chr", "pos", "begChr", "endChr", "type")
__innerdict = None # can't use the __dict__
""" common properties of element"""
def __init__(self, elm):
self.__innerdict = {}
self.text = self.process_children(elm)
def __str__(self):
return self.text
def __unicode__(self):
return self.__str__(self)
def __getattr__(self, name):
return self.__innerdict.get(name, None)
def do_brk(self, elm):
self.__innerdict["brk"] = BRK
return BRK
def do_common(self, elm):
stag = elm.tag.replace(OMML_NS, "")
if stag in self.__val_tags:
t = elm.get("{0}val".format(OMML_NS))
self.__innerdict[stag] = t
return None
tag2meth = {
"brk": do_brk,
"chr": do_common,
"pos": do_common,
"begChr": do_common,
"endChr": do_common,
"type": do_common,
}
class oMath2Latex(Tag2Method):
"""
Convert oMath element of omml to latex
"""
_t_dict = T
__direct_tags = ("box", "sSub", "sSup", "sSubSup", "num", "den", "deg", "e")
def __init__(self, element):
self._latex = self.process_children(element)
def __str__(self):
return self.latex
def __unicode__(self):
return self.__str__(self)
def process_unknow(self, elm, stag):
if stag in self.__direct_tags:
return self.process_children(elm)
elif stag[-2:] == "Pr":
return Pr(elm)
else:
return None
@property
def latex(self):
return self._latex
def do_acc(self, elm):
"""
the accent function
"""
c_dict = self.process_children_dict(elm)
latex_s = get_val(
c_dict["accPr"].chr, default=CHR_DEFAULT.get("ACC_VAL"), store=CHR
)
return latex_s.format(c_dict["e"])
def do_bar(self, elm):
"""
the bar function
"""
c_dict = self.process_children_dict(elm)
pr = c_dict["barPr"]
latex_s = get_val(pr.pos, default=POS_DEFAULT.get("BAR_VAL"), store=POS)
return pr.text + latex_s.format(c_dict["e"])
def do_d(self, elm):
"""
the delimiter object
"""
c_dict = self.process_children_dict(elm)
pr = c_dict["dPr"]
null = D_DEFAULT.get("null")
s_val = get_val(pr.begChr, default=D_DEFAULT.get("left"), store=T)
e_val = get_val(pr.endChr, default=D_DEFAULT.get("right"), store=T)
return pr.text + D.format(
left=null if not s_val else escape_latex(s_val),
text=c_dict["e"],
right=null if not e_val else escape_latex(e_val),
)
def do_spre(self, elm):
"""
the Pre-Sub-Superscript object -- Not support yet
"""
pass
def do_sub(self, elm):
text = self.process_children(elm)
return SUB.format(text)
def do_sup(self, elm):
text = self.process_children(elm)
return SUP.format(text)
def do_f(self, elm):
"""
the fraction object
"""
c_dict = self.process_children_dict(elm)
pr = c_dict["fPr"]
latex_s = get_val(pr.type, default=F_DEFAULT, store=F)
return pr.text + latex_s.format(num=c_dict.get("num"), den=c_dict.get("den"))
def do_func(self, elm):
"""
the Function-Apply object (Examples:sin cos)
"""
c_dict = self.process_children_dict(elm)
func_name = c_dict.get("fName")
return func_name.replace(FUNC_PLACE, c_dict.get("e"))
def do_fname(self, elm):
"""
the func name
"""
latex_chars = []
for stag, t, e in self.process_children_list(elm):
if stag == "r":
if FUNC.get(t):
latex_chars.append(FUNC[t])
else:
raise NotImplementedError("Not support func %s" % t)
else:
latex_chars.append(t)
t = BLANK.join(latex_chars)
return t if FUNC_PLACE in t else t + FUNC_PLACE # do_func will replace this
def do_groupchr(self, elm):
"""
the Group-Character object
"""
c_dict = self.process_children_dict(elm)
pr = c_dict["groupChrPr"]
latex_s = get_val(pr.chr)
return pr.text + latex_s.format(c_dict["e"])
def do_rad(self, elm):
"""
the radical object
"""
c_dict = self.process_children_dict(elm)
text = c_dict.get("e")
deg_text = c_dict.get("deg")
if deg_text:
return RAD.format(deg=deg_text, text=text)
else:
return RAD_DEFAULT.format(text=text)
def do_eqarr(self, elm):
"""
the Array object
"""
return ARR.format(
text=BRK.join(
[t for stag, t, e in self.process_children_list(elm, include=("e",))]
)
)
def do_limlow(self, elm):
"""
the Lower-Limit object
"""
t_dict = self.process_children_dict(elm, include=("e", "lim"))
latex_s = LIM_FUNC.get(t_dict["e"])
if not latex_s:
raise NotImplementedError("Not support lim %s" % t_dict["e"])
else:
return latex_s.format(lim=t_dict.get("lim"))
def do_limupp(self, elm):
"""
the Upper-Limit object
"""
t_dict = self.process_children_dict(elm, include=("e", "lim"))
return LIM_UPP.format(lim=t_dict.get("lim"), text=t_dict.get("e"))
def do_lim(self, elm):
"""
the lower limit of the limLow object and the upper limit of the limUpp function
"""
return self.process_children(elm).replace(LIM_TO[0], LIM_TO[1])
def do_m(self, elm):
"""
the Matrix object
"""
rows = []
for stag, t, e in self.process_children_list(elm):
if stag == "mPr":
pass
elif stag == "mr":
rows.append(t)
return M.format(text=BRK.join(rows))
def do_mr(self, elm):
"""
a single row of the matrix m
"""
return ALN.join(
[t for stag, t, e in self.process_children_list(elm, include=("e",))]
)
def do_nary(self, elm):
"""
the n-ary object
"""
res = []
bo = ""
for stag, t, e in self.process_children_list(elm):
if stag == "naryPr":
bo = get_val(t.chr, store=CHR_BO)
else:
res.append(t)
return bo + BLANK.join(res)
def do_r(self, elm):
"""
Get text from 'r' element,And try convert them to latex symbols
@todo text style support , (sty)
@todo \text (latex pure text support)
"""
_str = []
for s in elm.findtext("./{0}t".format(OMML_NS)):
# s = s if isinstance(s,unicode) else unicode(s,'utf-8')
_str.append(self._t_dict.get(s, s))
return escape_latex(BLANK.join(_str))
tag2meth = {
"acc": do_acc,
"r": do_r,
"bar": do_bar,
"sub": do_sub,
"sup": do_sup,
"f": do_f,
"func": do_func,
"fName": do_fname,
"groupChr": do_groupchr,
"d": do_d,
"rad": do_rad,
"eqArr": do_eqarr,
"limLow": do_limlow,
"limUpp": do_limupp,
"lim": do_lim,
"m": do_m,
"mr": do_mr,
"nary": do_nary,
}
@@ -1,156 +0,0 @@
import zipfile
from io import BytesIO
from typing import BinaryIO
from xml.etree import ElementTree as ET
from bs4 import BeautifulSoup, Tag
from .math.omml import OMML_NS, oMath2Latex
MATH_ROOT_TEMPLATE = "".join(
(
"<w:document ",
'xmlns:wpc="http://schemas.microsoft.com/office/word/2010/wordprocessingCanvas" ',
'xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006" ',
'xmlns:o="urn:schemas-microsoft-com:office:office" ',
'xmlns:r="http://schemas.openxmlformats.org/officeDocument/2006/relationships" ',
'xmlns:m="http://schemas.openxmlformats.org/officeDocument/2006/math" ',
'xmlns:v="urn:schemas-microsoft-com:vml" ',
'xmlns:wp14="http://schemas.microsoft.com/office/word/2010/wordprocessingDrawing" ',
'xmlns:wp="http://schemas.openxmlformats.org/drawingml/2006/wordprocessingDrawing" ',
'xmlns:w10="urn:schemas-microsoft-com:office:word" ',
'xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main" ',
'xmlns:w14="http://schemas.microsoft.com/office/word/2010/wordml" ',
'xmlns:wpg="http://schemas.microsoft.com/office/word/2010/wordprocessingGroup" ',
'xmlns:wpi="http://schemas.microsoft.com/office/word/2010/wordprocessingInk" ',
'xmlns:wne="http://schemas.microsoft.com/office/word/2006/wordml" ',
'xmlns:wps="http://schemas.microsoft.com/office/word/2010/wordprocessingShape" mc:Ignorable="w14 wp14">',
"{0}</w:document>",
)
)
def _convert_omath_to_latex(tag: Tag) -> str:
"""
Converts an OMML (Office Math Markup Language) tag to LaTeX format.
Args:
tag (Tag): A BeautifulSoup Tag object representing the OMML element.
Returns:
str: The LaTeX representation of the OMML element.
"""
# Format the tag into a complete XML document string
math_root = ET.fromstring(MATH_ROOT_TEMPLATE.format(str(tag)))
# Find the 'oMath' element within the XML document
math_element = math_root.find(OMML_NS + "oMath")
# Convert the 'oMath' element to LaTeX using the oMath2Latex function
latex = oMath2Latex(math_element).latex
return latex
def _get_omath_tag_replacement(tag: Tag, block: bool = False) -> Tag:
"""
Creates a replacement tag for an OMML (Office Math Markup Language) element.
Args:
tag (Tag): A BeautifulSoup Tag object representing the "oMath" element.
block (bool, optional): If True, the LaTeX will be wrapped in double dollar signs for block mode. Defaults to False.
Returns:
Tag: A BeautifulSoup Tag object representing the replacement element.
"""
t_tag = Tag(name="w:t")
t_tag.string = (
f"$${_convert_omath_to_latex(tag)}$$"
if block
else f"${_convert_omath_to_latex(tag)}$"
)
r_tag = Tag(name="w:r")
r_tag.append(t_tag)
return r_tag
def _replace_equations(tag: Tag):
"""
Replaces OMML (Office Math Markup Language) elements with their LaTeX equivalents.
Args:
tag (Tag): A BeautifulSoup Tag object representing the OMML element. Could be either "oMathPara" or "oMath".
Raises:
ValueError: If the tag is not supported.
"""
if tag.name == "oMathPara":
# Create a new paragraph tag
p_tag = Tag(name="w:p")
# Replace each 'oMath' child tag with its LaTeX equivalent as block equations
for child_tag in tag.find_all("oMath"):
p_tag.append(_get_omath_tag_replacement(child_tag, block=True))
# Replace the original 'oMathPara' tag with the new paragraph tag
tag.replace_with(p_tag)
elif tag.name == "oMath":
# Replace the 'oMath' tag with its LaTeX equivalent as inline equation
tag.replace_with(_get_omath_tag_replacement(tag, block=False))
else:
raise ValueError(f"Not supported tag: {tag.name}")
def _pre_process_math(content: bytes) -> bytes:
"""
Pre-processes the math content in a DOCX -> XML file by converting OMML (Office Math Markup Language) elements to LaTeX.
This preprocessed content can be directly replaced in the DOCX file -> XMLs.
Args:
content (bytes): The XML content of the DOCX file as bytes.
Returns:
bytes: The processed content with OMML elements replaced by their LaTeX equivalents, encoded as bytes.
"""
soup = BeautifulSoup(content.decode(), features="xml")
for tag in soup.find_all("oMathPara"):
_replace_equations(tag)
for tag in soup.find_all("oMath"):
_replace_equations(tag)
return str(soup).encode()
def pre_process_docx(input_docx: BinaryIO) -> BinaryIO:
"""
Pre-processes a DOCX file with provided steps.
The process works by unzipping the DOCX file in memory, transforming specific XML files
(such as converting OMML elements to LaTeX), and then zipping everything back into a
DOCX file without writing to disk.
Args:
input_docx (BinaryIO): A binary input stream representing the DOCX file.
Returns:
BinaryIO: A binary output stream representing the processed DOCX file.
"""
output_docx = BytesIO()
# The files that need to be pre-processed from .docx
pre_process_enable_files = [
"word/document.xml",
"word/footnotes.xml",
"word/endnotes.xml",
]
with zipfile.ZipFile(input_docx, mode="r") as zip_input:
files = {name: zip_input.read(name) for name in zip_input.namelist()}
with zipfile.ZipFile(output_docx, mode="w") as zip_output:
zip_output.comment = zip_input.comment
for name, content in files.items():
if name in pre_process_enable_files:
try:
# Pre-process the content
updated_content = _pre_process_math(content)
# In the future, if there are more pre-processing steps, they can be added here
zip_output.writestr(name, updated_content)
except Exception:
# If there is an error in processing the content, write the original content
zip_output.writestr(name, content)
else:
zip_output.writestr(name, content)
output_docx.seek(0)
return output_docx
@@ -2,6 +2,7 @@
# #
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
from ._base import DocumentConverter, DocumentConverterResult
from ._plain_text_converter import PlainTextConverter from ._plain_text_converter import PlainTextConverter
from ._html_converter import HtmlConverter from ._html_converter import HtmlConverter
from ._rss_converter import RssConverter from ._rss_converter import RssConverter
@@ -14,17 +15,16 @@ 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 ._audio_converter import AudioConverter from ._wav_converter import WavConverter
from ._mp3_converter import Mp3Converter
from ._outlook_msg_converter import OutlookMsgConverter from ._outlook_msg_converter import OutlookMsgConverter
from ._zip_converter import ZipConverter from ._zip_converter import ZipConverter
from ._doc_intel_converter import ( from ._doc_intel_converter import DocumentIntelligenceConverter
DocumentIntelligenceConverter, from ._converter_input import ConverterInput
DocumentIntelligenceFileType,
)
from ._epub_converter import EpubConverter
from ._csv_converter import CsvConverter
__all__ = [ __all__ = [
"DocumentConverter",
"DocumentConverterResult",
"PlainTextConverter", "PlainTextConverter",
"HtmlConverter", "HtmlConverter",
"RssConverter", "RssConverter",
@@ -38,11 +38,10 @@ __all__ = [
"XlsConverter", "XlsConverter",
"PptxConverter", "PptxConverter",
"ImageConverter", "ImageConverter",
"AudioConverter", "WavConverter",
"Mp3Converter",
"OutlookMsgConverter", "OutlookMsgConverter",
"ZipConverter", "ZipConverter",
"DocumentIntelligenceConverter", "DocumentIntelligenceConverter",
"DocumentIntelligenceFileType", "ConverterInput",
"EpubConverter",
"CsvConverter",
] ]
@@ -1,101 +0,0 @@
from typing import Any, BinaryIO
from ._exiftool import exiftool_metadata
from ._transcribe_audio import transcribe_audio
from .._base_converter import DocumentConverter, DocumentConverterResult
from .._stream_info import StreamInfo
from .._exceptions import MissingDependencyException
ACCEPTED_MIME_TYPE_PREFIXES = [
"audio/x-wav",
"audio/mpeg",
"video/mp4",
]
ACCEPTED_FILE_EXTENSIONS = [
".wav",
".mp3",
".m4a",
".mp4",
]
class AudioConverter(DocumentConverter):
"""
Converts audio files to markdown via extraction of metadata (if `exiftool` is installed), and speech transcription (if `speech_recognition` is installed).
"""
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> DocumentConverterResult:
md_content = ""
# Add metadata
metadata = exiftool_metadata(
file_stream, exiftool_path=kwargs.get("exiftool_path")
)
if metadata:
for f in [
"Title",
"Artist",
"Author",
"Band",
"Album",
"Genre",
"Track",
"DateTimeOriginal",
"CreateDate",
# "Duration", -- Wrong values when read from memory
"NumChannels",
"SampleRate",
"AvgBytesPerSec",
"BitsPerSample",
]:
if f in metadata:
md_content += f"{f}: {metadata[f]}\n"
# Figure out the audio format for transcription
if stream_info.extension == ".wav" or stream_info.mimetype == "audio/x-wav":
audio_format = "wav"
elif stream_info.extension == ".mp3" or stream_info.mimetype == "audio/mpeg":
audio_format = "mp3"
elif (
stream_info.extension in [".mp4", ".m4a"]
or stream_info.mimetype == "video/mp4"
):
audio_format = "mp4"
else:
audio_format = None
# Transcribe
if audio_format:
try:
transcript = transcribe_audio(file_stream, audio_format=audio_format)
if transcript:
md_content += "\n\n### Audio Transcript:\n" + transcript
except MissingDependencyException:
pass
# Return the result
return DocumentConverterResult(markdown=md_content.strip())
@@ -0,0 +1,63 @@
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."""
# Lower priority values are tried first.
PRIORITY_SPECIFIC_FILE_FORMAT = (
0.0 # e.g., .docx, .pdf, .xlsx, Or specific pages, e.g., wikipedia
)
PRIORITY_GENERIC_FILE_FORMAT = (
10.0 # Near catch-all converters for mimetypes like text/*, etc.
)
def __init__(self, priority: float = PRIORITY_SPECIFIC_FILE_FORMAT):
"""
Initialize the DocumentConverter with a given priority.
Priorities work as follows: By default, most converters get priority
DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT (== 0). The exception
is the PlainTextConverter, which gets priority PRIORITY_SPECIFIC_FILE_FORMAT (== 10),
with lower values being tried first (i.e., higher priority).
Just prior to conversion, the converters are sorted by priority, using
a stable sort. This means that converters with the same priority will
remain in the same order, with the most recently registered converters
appearing first.
We have tight control over the order of built-in converters, but
plugins can register converters in any order. A converter's priority
field reasserts some control over the order of converters.
Plugins can register converters with any priority, to appear before or
after the built-ins. For example, a plugin with priority 9 will run
before the PlainTextConverter, but after the built-in converters.
"""
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")
@@ -1,23 +1,14 @@
import re # type: ignore
import base64 import base64
import binascii import re
from typing import Union
from urllib.parse import parse_qs, urlparse from urllib.parse import parse_qs, urlparse
from typing import Any, BinaryIO
from bs4 import BeautifulSoup from bs4 import BeautifulSoup
from .._base_converter import DocumentConverter, DocumentConverterResult from ._base import DocumentConverter, DocumentConverterResult
from .._stream_info import StreamInfo
from ._markdownify import _CustomMarkdownify from ._markdownify import _CustomMarkdownify
from ._converter_input import ConverterInput
ACCEPTED_MIME_TYPE_PREFIXES = [
"text/html",
"application/xhtml",
]
ACCEPTED_FILE_EXTENSIONS = [
".html",
".htm",
]
class BingSerpConverter(DocumentConverter): class BingSerpConverter(DocumentConverter):
@@ -26,49 +17,31 @@ class BingSerpConverter(DocumentConverter):
NOTE: It is better to use the Bing API NOTE: It is better to use the Bing API
""" """
def accepts( def __init__(
self, self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
file_stream: BinaryIO, ):
stream_info: StreamInfo, super().__init__(priority=priority)
**kwargs: Any, # Options to pass to the converter
) -> bool:
"""
Make sure we're dealing with HTML content *from* Bing.
"""
url = stream_info.url or ""
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if not re.search(r"^https://www\.bing\.com/search\?q=", url):
# Not a Bing SERP URL
return False
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
# Not HTML content
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if not a Bing SERP
**kwargs: Any, # Options to pass to the converter extension = kwargs.get("file_extension", "")
) -> DocumentConverterResult: if extension.lower() not in [".html", ".htm"]:
assert stream_info.url is not None return None
url = kwargs.get("url", "")
if not re.search(r"^https://www\.bing\.com/search\?q=", url):
return None
# Parse the query parameters # Parse the query parameters
parsed_params = parse_qs(urlparse(stream_info.url).query) parsed_params = parse_qs(urlparse(url).query)
query = parsed_params.get("q", [""])[0] query = parsed_params.get("q", [""])[0]
# Parse the stream # Parse the file
encoding = "utf-8" if stream_info.charset is None else stream_info.charset soup = None
soup = BeautifulSoup(file_stream, "html.parser", from_encoding=encoding) file_obj = input.read_file(mode="rt", encoding="utf-8")
soup = BeautifulSoup(file_obj.read(), "html.parser")
file_obj.close()
# Clean up some formatting # Clean up some formatting
for tptt in soup.find_all(class_="tptt"): for tptt in soup.find_all(class_="tptt"):
@@ -78,12 +51,9 @@ class BingSerpConverter(DocumentConverter):
slug.extract() slug.extract()
# Parse the algorithmic results # Parse the algorithmic results
_markdownify = _CustomMarkdownify(**kwargs) _markdownify = _CustomMarkdownify()
results = list() results = list()
for result in soup.find_all(class_="b_algo"): for result in soup.find_all(class_="b_algo"):
if not hasattr(result, "find_all"):
continue
# Rewrite redirect urls # Rewrite redirect urls
for a in result.find_all("a", href=True): for a in result.find_all("a", href=True):
parsed_href = urlparse(a["href"]) parsed_href = urlparse(a["href"])
@@ -115,6 +85,6 @@ class BingSerpConverter(DocumentConverter):
) )
return DocumentConverterResult( return DocumentConverterResult(
markdown=webpage_text,
title=None if soup.title is None else soup.title.string, title=None if soup.title is None else soup.title.string,
text_content=webpage_text,
) )
@@ -0,0 +1,30 @@
from typing import Any, Union
class ConverterInput:
"""
Wrapper for inputs to converter functions.
"""
def __init__(
self,
input_type: str = "filepath",
filepath: Union[str, None] = None,
file_object: Union[Any, None] = None,
):
if input_type not in ["filepath", "object"]:
raise ValueError(f"Invalid converter input type: {input_type}")
self.input_type = input_type
self.filepath = filepath
self.file_object = file_object
def read_file(
self,
mode: str = "rb",
encoding: Union[str, None] = None,
) -> Any:
if self.input_type == "object":
return self.file_object
return open(self.filepath, mode=mode, encoding=encoding)
@@ -1,77 +0,0 @@
import csv
import io
from typing import BinaryIO, Any
from charset_normalizer import from_bytes
from .._base_converter import DocumentConverter, DocumentConverterResult
from .._stream_info import StreamInfo
ACCEPTED_MIME_TYPE_PREFIXES = [
"text/csv",
"application/csv",
]
ACCEPTED_FILE_EXTENSIONS = [".csv"]
class CsvConverter(DocumentConverter):
"""
Converts CSV files to Markdown tables.
"""
def __init__(self):
super().__init__()
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> DocumentConverterResult:
# Read the file content
if stream_info.charset:
content = file_stream.read().decode(stream_info.charset)
else:
content = str(from_bytes(file_stream.read()).best())
# Parse CSV content
reader = csv.reader(io.StringIO(content))
rows = list(reader)
if not rows:
return DocumentConverterResult(markdown="")
# Create markdown table
markdown_table = []
# Add header row
markdown_table.append("| " + " | ".join(rows[0]) + " |")
# Add separator row
markdown_table.append("| " + " | ".join(["---"] * len(rows[0])) + " |")
# Add data rows
for row in rows[1:]:
# Make sure row has the same number of columns as header
while len(row) < len(rows[0]):
row.append("")
# Truncate if row has more columns than header
row = row[: len(rows[0])]
markdown_table.append("| " + " | ".join(row) + " |")
result = "\n".join(markdown_table)
return DocumentConverterResult(markdown=result)
@@ -1,50 +1,17 @@
import sys from typing import Any, Union
import re import re
import os
from typing import BinaryIO, Any, List
from enum import Enum
from .._base_converter import DocumentConverter, DocumentConverterResult # Azure imports
from .._stream_info import StreamInfo from azure.ai.documentintelligence import DocumentIntelligenceClient
from .._exceptions import MissingDependencyException from azure.ai.documentintelligence.models import (
# Try loading optional (but in this case, required) dependencies
# Save reporting of any exceptions for later
_dependency_exc_info = None
try:
from azure.ai.documentintelligence import DocumentIntelligenceClient
from azure.ai.documentintelligence.models import (
AnalyzeDocumentRequest, AnalyzeDocumentRequest,
AnalyzeResult, AnalyzeResult,
DocumentAnalysisFeature, DocumentAnalysisFeature,
) )
from azure.core.credentials import AzureKeyCredential, TokenCredential from azure.identity import DefaultAzureCredential
from azure.identity import DefaultAzureCredential
except ImportError:
# Preserve the error and stack trace for later
_dependency_exc_info = sys.exc_info()
# Define these types for type hinting when the package is not available from ._base import DocumentConverter, DocumentConverterResult
class AzureKeyCredential: from ._converter_input import ConverterInput
pass
class TokenCredential:
pass
class DocumentIntelligenceClient:
pass
class AnalyzeDocumentRequest:
pass
class AnalyzeResult:
pass
class DocumentAnalysisFeature:
pass
class DefaultAzureCredential:
pass
# TODO: currently, there is a bug in the document intelligence SDK with importing the "ContentFormat" enum. # TODO: currently, there is a bug in the document intelligence SDK with importing the "ContentFormat" enum.
@@ -52,203 +19,74 @@ except ImportError:
CONTENT_FORMAT = "markdown" CONTENT_FORMAT = "markdown"
class DocumentIntelligenceFileType(str, Enum):
"""Enum of file types supported by the Document Intelligence Converter."""
# No OCR
DOCX = "docx"
PPTX = "pptx"
XLSX = "xlsx"
HTML = "html"
# OCR
PDF = "pdf"
JPEG = "jpeg"
PNG = "png"
BMP = "bmp"
TIFF = "tiff"
def _get_mime_type_prefixes(types: List[DocumentIntelligenceFileType]) -> List[str]:
"""Get the MIME type prefixes for the given file types."""
prefixes: List[str] = []
for type_ in types:
if type_ == DocumentIntelligenceFileType.DOCX:
prefixes.append(
"application/vnd.openxmlformats-officedocument.wordprocessingml.document"
)
elif type_ == DocumentIntelligenceFileType.PPTX:
prefixes.append(
"application/vnd.openxmlformats-officedocument.presentationml"
)
elif type_ == DocumentIntelligenceFileType.XLSX:
prefixes.append(
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
)
elif type_ == DocumentIntelligenceFileType.HTML:
prefixes.append("text/html")
prefixes.append("application/xhtml+xml")
elif type_ == DocumentIntelligenceFileType.PDF:
prefixes.append("application/pdf")
prefixes.append("application/x-pdf")
elif type_ == DocumentIntelligenceFileType.JPEG:
prefixes.append("image/jpeg")
elif type_ == DocumentIntelligenceFileType.PNG:
prefixes.append("image/png")
elif type_ == DocumentIntelligenceFileType.BMP:
prefixes.append("image/bmp")
elif type_ == DocumentIntelligenceFileType.TIFF:
prefixes.append("image/tiff")
return prefixes
def _get_file_extensions(types: List[DocumentIntelligenceFileType]) -> List[str]:
"""Get the file extensions for the given file types."""
extensions: List[str] = []
for type_ in types:
if type_ == DocumentIntelligenceFileType.DOCX:
extensions.append(".docx")
elif type_ == DocumentIntelligenceFileType.PPTX:
extensions.append(".pptx")
elif type_ == DocumentIntelligenceFileType.XLSX:
extensions.append(".xlsx")
elif type_ == DocumentIntelligenceFileType.PDF:
extensions.append(".pdf")
elif type_ == DocumentIntelligenceFileType.JPEG:
extensions.append(".jpg")
extensions.append(".jpeg")
elif type_ == DocumentIntelligenceFileType.PNG:
extensions.append(".png")
elif type_ == DocumentIntelligenceFileType.BMP:
extensions.append(".bmp")
elif type_ == DocumentIntelligenceFileType.TIFF:
extensions.append(".tiff")
elif type_ == DocumentIntelligenceFileType.HTML:
extensions.append(".html")
return extensions
class DocumentIntelligenceConverter(DocumentConverter): class DocumentIntelligenceConverter(DocumentConverter):
"""Specialized DocumentConverter that uses Document Intelligence to extract text from documents.""" """Specialized DocumentConverter that uses Document Intelligence to extract text from documents."""
def __init__( def __init__(
self, self,
*, *,
priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT,
endpoint: str, endpoint: str,
api_version: str = "2024-07-31-preview", api_version: str = "2024-07-31-preview",
credential: AzureKeyCredential | TokenCredential | None = None,
file_types: List[DocumentIntelligenceFileType] = [
DocumentIntelligenceFileType.DOCX,
DocumentIntelligenceFileType.PPTX,
DocumentIntelligenceFileType.XLSX,
DocumentIntelligenceFileType.PDF,
DocumentIntelligenceFileType.JPEG,
DocumentIntelligenceFileType.PNG,
DocumentIntelligenceFileType.BMP,
DocumentIntelligenceFileType.TIFF,
],
): ):
""" super().__init__(priority=priority)
Initialize the DocumentIntelligenceConverter.
Args:
endpoint (str): The endpoint for the Document Intelligence service.
api_version (str): The API version to use. Defaults to "2024-07-31-preview".
credential (AzureKeyCredential | TokenCredential | None): The credential to use for authentication.
file_types (List[DocumentIntelligenceFileType]): The file types to accept. Defaults to all supported file types.
"""
super().__init__()
self._file_types = file_types
# Raise an error if the dependencies are not available.
# This is different than other converters since this one isn't even instantiated
# unless explicitly requested.
if _dependency_exc_info is not None:
raise MissingDependencyException(
"DocumentIntelligenceConverter requires the optional dependency [az-doc-intel] (or [all]) to be installed. E.g., `pip install markitdown[az-doc-intel]`"
) from _dependency_exc_info[
1
].with_traceback( # type: ignore[union-attr]
_dependency_exc_info[2]
)
if credential is None:
if os.environ.get("AZURE_API_KEY") is None:
credential = DefaultAzureCredential()
else:
credential = AzureKeyCredential(os.environ["AZURE_API_KEY"])
self.endpoint = endpoint self.endpoint = endpoint
self.api_version = api_version self.api_version = api_version
self.doc_intel_client = DocumentIntelligenceClient( self.doc_intel_client = DocumentIntelligenceClient(
endpoint=self.endpoint, endpoint=self.endpoint,
api_version=self.api_version, api_version=self.api_version,
credential=credential, credential=DefaultAzureCredential(),
) )
def accepts( def convert(
self, self, input: ConverterInput, **kwargs: Any
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if extension is not supported by Document Intelligence
**kwargs: Any, # Options to pass to the converter extension = kwargs.get("file_extension", "")
) -> bool: docintel_extensions = [
mimetype = (stream_info.mimetype or "").lower() ".pdf",
extension = (stream_info.extension or "").lower() ".docx",
".xlsx",
if extension in _get_file_extensions(self._file_types): ".pptx",
return True ".html",
".jpeg",
for prefix in _get_mime_type_prefixes(self._file_types): ".jpg",
if mimetype.startswith(prefix): ".png",
return True ".bmp",
".tiff",
return False ".heif",
def _analysis_features(self, stream_info: StreamInfo) -> List[str]:
"""
Helper needed to determine which analysis features to use.
Certain document analysis features are not availiable for
office filetypes (.xlsx, .pptx, .html, .docx)
"""
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
# Types that don't support ocr
no_ocr_types = [
DocumentIntelligenceFileType.DOCX,
DocumentIntelligenceFileType.PPTX,
DocumentIntelligenceFileType.XLSX,
DocumentIntelligenceFileType.HTML,
] ]
if extension.lower() not in docintel_extensions:
return None
if extension in _get_file_extensions(no_ocr_types): # Get the bytestring from the converter input
return [] file_obj = input.read_file(mode="rb")
file_bytes = file_obj.read()
file_obj.close()
for prefix in _get_mime_type_prefixes(no_ocr_types): # Certain document analysis features are not availiable for office filetypes (.xlsx, .pptx, .html, .docx)
if mimetype.startswith(prefix): if extension.lower() in [".xlsx", ".pptx", ".html", ".docx"]:
return [] analysis_features = []
else:
return [ analysis_features = [
DocumentAnalysisFeature.FORMULAS, # enable formula extraction DocumentAnalysisFeature.FORMULAS, # enable formula extraction
DocumentAnalysisFeature.OCR_HIGH_RESOLUTION, # enable high resolution OCR DocumentAnalysisFeature.OCR_HIGH_RESOLUTION, # enable high resolution OCR
DocumentAnalysisFeature.STYLE_FONT, # enable font style extraction DocumentAnalysisFeature.STYLE_FONT, # enable font style extraction
] ]
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> DocumentConverterResult:
# Extract the text using Azure Document Intelligence # Extract the text using Azure Document Intelligence
poller = self.doc_intel_client.begin_analyze_document( poller = self.doc_intel_client.begin_analyze_document(
model_id="prebuilt-layout", model_id="prebuilt-layout",
body=AnalyzeDocumentRequest(bytes_source=file_stream.read()), body=AnalyzeDocumentRequest(bytes_source=file_bytes),
features=self._analysis_features(stream_info), features=analysis_features,
output_content_format=CONTENT_FORMAT, # TODO: replace with "ContentFormat.MARKDOWN" when the bug is fixed output_content_format=CONTENT_FORMAT, # TODO: replace with "ContentFormat.MARKDOWN" when the bug is fixed
) )
result: AnalyzeResult = poller.result() result: AnalyzeResult = poller.result()
# remove comments from the markdown content generated by Doc Intelligence and append to markdown string # 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) markdown_text = re.sub(r"<!--.*?-->", "", result.content, flags=re.DOTALL)
return DocumentConverterResult(markdown=markdown_text) return DocumentConverterResult(
title=None,
text_content=markdown_text,
)
@@ -1,31 +1,14 @@
import sys from typing import Union
import io
from warnings import warn
from typing import BinaryIO, Any import mammoth
from ._base import (
DocumentConverterResult,
)
from ._base import DocumentConverter
from ._html_converter import HtmlConverter from ._html_converter import HtmlConverter
from ..converter_utils.docx.pre_process import pre_process_docx from ._converter_input import ConverterInput
from .._base_converter import DocumentConverterResult
from .._stream_info import StreamInfo
from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
# Try loading optional (but in this case, required) dependencies
# Save reporting of any exceptions for later
_dependency_exc_info = None
try:
import mammoth
except ImportError:
# Preserve the error and stack trace for later
_dependency_exc_info = sys.exc_info()
ACCEPTED_MIME_TYPE_PREFIXES = [
"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
]
ACCEPTED_FILE_EXTENSIONS = [".docx"]
class DocxConverter(HtmlConverter): class DocxConverter(HtmlConverter):
@@ -33,51 +16,25 @@ class DocxConverter(HtmlConverter):
Converts DOCX files to Markdown. Style information (e.g.m headings) and tables are preserved where possible. Converts DOCX files to Markdown. Style information (e.g.m headings) and tables are preserved where possible.
""" """
def __init__(self): def __init__(
super().__init__() self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
self._html_converter = HtmlConverter() ):
super().__init__(priority=priority)
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if not a DOCX
**kwargs: Any, # Options to pass to the converter extension = kwargs.get("file_extension", "")
) -> DocumentConverterResult: if extension.lower() != ".docx":
# Check: the dependencies return None
if _dependency_exc_info is not None:
raise MissingDependencyException(
MISSING_DEPENDENCY_MESSAGE.format(
converter=type(self).__name__,
extension=".docx",
feature="docx",
)
) from _dependency_exc_info[
1
].with_traceback( # type: ignore[union-attr]
_dependency_exc_info[2]
)
result = None
style_map = kwargs.get("style_map", None) style_map = kwargs.get("style_map", None)
pre_process_stream = pre_process_docx(file_stream) file_obj = input.read_file(mode="rb")
return self._html_converter.convert_string( result = mammoth.convert_to_html(file_obj, style_map=style_map)
mammoth.convert_to_html(pre_process_stream, style_map=style_map).value, file_obj.close()
**kwargs, html_content = result.value
) result = self._convert(html_content)
return result
@@ -1,146 +0,0 @@
import os
import zipfile
from defusedxml import minidom
from xml.dom.minidom import Document
from typing import BinaryIO, Any, Dict, List
from ._html_converter import HtmlConverter
from .._base_converter import DocumentConverterResult
from .._stream_info import StreamInfo
ACCEPTED_MIME_TYPE_PREFIXES = [
"application/epub",
"application/epub+zip",
"application/x-epub+zip",
]
ACCEPTED_FILE_EXTENSIONS = [".epub"]
MIME_TYPE_MAPPING = {
".html": "text/html",
".xhtml": "application/xhtml+xml",
}
class EpubConverter(HtmlConverter):
"""
Converts EPUB files to Markdown. Style information (e.g.m headings) and tables are preserved where possible.
"""
def __init__(self):
super().__init__()
self._html_converter = HtmlConverter()
def accepts(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert(
self,
file_stream: BinaryIO,
stream_info: StreamInfo,
**kwargs: Any, # Options to pass to the converter
) -> DocumentConverterResult:
with zipfile.ZipFile(file_stream, "r") as z:
# Extracts metadata (title, authors, language, publisher, date, description, cover) from an EPUB file."""
# Locate content.opf
container_dom = minidom.parse(z.open("META-INF/container.xml"))
opf_path = container_dom.getElementsByTagName("rootfile")[0].getAttribute(
"full-path"
)
# Parse content.opf
opf_dom = minidom.parse(z.open(opf_path))
metadata: Dict[str, Any] = {
"title": self._get_text_from_node(opf_dom, "dc:title"),
"authors": self._get_all_texts_from_nodes(opf_dom, "dc:creator"),
"language": self._get_text_from_node(opf_dom, "dc:language"),
"publisher": self._get_text_from_node(opf_dom, "dc:publisher"),
"date": self._get_text_from_node(opf_dom, "dc:date"),
"description": self._get_text_from_node(opf_dom, "dc:description"),
"identifier": self._get_text_from_node(opf_dom, "dc:identifier"),
}
# Extract manifest items (ID → href mapping)
manifest = {
item.getAttribute("id"): item.getAttribute("href")
for item in opf_dom.getElementsByTagName("item")
}
# Extract spine order (ID refs)
spine_items = opf_dom.getElementsByTagName("itemref")
spine_order = [item.getAttribute("idref") for item in spine_items]
# Convert spine order to actual file paths
base_path = "/".join(
opf_path.split("/")[:-1]
) # Get base directory of content.opf
spine = [
f"{base_path}/{manifest[item_id]}" if base_path else manifest[item_id]
for item_id in spine_order
if item_id in manifest
]
# Extract and convert the content
markdown_content: List[str] = []
for file in spine:
if file in z.namelist():
with z.open(file) as f:
filename = os.path.basename(file)
extension = os.path.splitext(filename)[1].lower()
mimetype = MIME_TYPE_MAPPING.get(extension)
converted_content = self._html_converter.convert(
f,
StreamInfo(
mimetype=mimetype,
extension=extension,
filename=filename,
),
)
markdown_content.append(converted_content.markdown.strip())
# Format and add the metadata
metadata_markdown = []
for key, value in metadata.items():
if isinstance(value, list):
value = ", ".join(value)
if value:
metadata_markdown.append(f"**{key.capitalize()}:** {value}")
markdown_content.insert(0, "\n".join(metadata_markdown))
return DocumentConverterResult(
markdown="\n\n".join(markdown_content), title=metadata["title"]
)
def _get_text_from_node(self, dom: Document, tag_name: str) -> str | None:
"""Convenience function to extract a single occurrence of a tag (e.g., title)."""
texts = self._get_all_texts_from_nodes(dom, tag_name)
if len(texts) > 0:
return texts[0]
else:
return None
def _get_all_texts_from_nodes(self, dom: Document, tag_name: str) -> List[str]:
"""Helper function to extract all occurrences of a tag (e.g., multiple authors)."""
texts: List[str] = []
for node in dom.getElementsByTagName(tag_name):
if node.firstChild and hasattr(node.firstChild, "nodeValue"):
texts.append(node.firstChild.nodeValue.strip())
return texts
@@ -1,52 +0,0 @@
import json
import locale
import subprocess
from typing import Any, BinaryIO, Union
def _parse_version(version: str) -> tuple:
return tuple(map(int, (version.split("."))))
def exiftool_metadata(
file_stream: BinaryIO,
*,
exiftool_path: Union[str, None],
) -> Any: # Need a better type for json data
# Nothing to do
if not exiftool_path:
return {}
# Verify exiftool version
try:
version_output = subprocess.run(
[exiftool_path, "-ver"],
capture_output=True,
text=True,
check=True,
).stdout.strip()
version = _parse_version(version_output)
min_version = (12, 24)
if version < min_version:
raise RuntimeError(
f"ExifTool version {version_output} is vulnerable to CVE-2021-22204. "
"Please upgrade to version 12.24 or later."
)
except (subprocess.CalledProcessError, ValueError) as e:
raise RuntimeError("Failed to verify ExifTool version.") from e
# Run exiftool
cur_pos = file_stream.tell()
try:
output = subprocess.run(
[exiftool_path, "-json", "-"],
input=file_stream.read(),
capture_output=True,
text=False,
).stdout
return json.loads(
output.decode(locale.getpreferredencoding(False)),
)[0]
finally:
file_stream.seek(cur_pos)
@@ -1,57 +1,39 @@
import io from typing import Any, Union
import warnings
from typing import Any, BinaryIO, Optional
from bs4 import BeautifulSoup from bs4 import BeautifulSoup
from .._base_converter import DocumentConverter, DocumentConverterResult from ._base import DocumentConverter, DocumentConverterResult
from .._stream_info import StreamInfo
from ._markdownify import _CustomMarkdownify from ._markdownify import _CustomMarkdownify
from ._converter_input import ConverterInput
ACCEPTED_MIME_TYPE_PREFIXES = [
"text/html",
"application/xhtml",
]
ACCEPTED_FILE_EXTENSIONS = [
".html",
".htm",
]
class HtmlConverter(DocumentConverter): class HtmlConverter(DocumentConverter):
"""Anything with content type text/html""" """Anything with content type text/html"""
def accepts( def __init__(
self, self, priority: float = DocumentConverter.PRIORITY_GENERIC_FILE_FORMAT
file_stream: BinaryIO, ):
stream_info: StreamInfo, super().__init__(priority=priority)
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs: Any
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if not html
**kwargs: Any, # Options to pass to the converter extension = kwargs.get("file_extension", "")
) -> DocumentConverterResult: if extension.lower() not in [".html", ".htm"]:
# Pop our own keyword before forwarding the rest to markdownify. return None
# strict=True raises RecursionError instead of falling back to plain text.
strict: bool = kwargs.pop("strict", False)
# Parse the stream result = None
encoding = "utf-8" if stream_info.charset is None else stream_info.charset file_obj = input.read_file(mode="rt", encoding="utf-8")
soup = BeautifulSoup(file_stream, "html.parser", from_encoding=encoding) result = self._convert(file_obj.read())
file_obj.close()
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 # Remove javascript and style blocks
for script in soup(["script", "style"]): for script in soup(["script", "style"]):
@@ -60,25 +42,10 @@ class HtmlConverter(DocumentConverter):
# Print only the main content # Print only the main content
body_elm = soup.find("body") body_elm = soup.find("body")
webpage_text = "" webpage_text = ""
try:
if body_elm: if body_elm:
webpage_text = _CustomMarkdownify(**kwargs).convert_soup(body_elm) webpage_text = _CustomMarkdownify().convert_soup(body_elm)
else: else:
webpage_text = _CustomMarkdownify(**kwargs).convert_soup(soup) webpage_text = _CustomMarkdownify().convert_soup(soup)
except RecursionError:
if strict:
raise
# Large or deeply-nested HTML can exceed Python's recursion limit
# during markdownify's recursive DOM traversal. Fall back to
# BeautifulSoup's iterative get_text() so the caller still gets
# usable plain-text content instead of raw HTML.
warnings.warn(
"HTML document is too deeply nested for markdown conversion "
"(RecursionError). Falling back to plain-text extraction.",
stacklevel=2,
)
target = body_elm if body_elm else soup
webpage_text = target.get_text("\n", strip=True)
assert isinstance(webpage_text, str) assert isinstance(webpage_text, str)
@@ -86,25 +53,6 @@ class HtmlConverter(DocumentConverter):
webpage_text = webpage_text.strip() webpage_text = webpage_text.strip()
return DocumentConverterResult( return DocumentConverterResult(
markdown=webpage_text,
title=None if soup.title is None else soup.title.string, title=None if soup.title is None else soup.title.string,
) text_content=webpage_text,
def convert_string(
self, html_content: str, *, url: Optional[str] = None, **kwargs
) -> DocumentConverterResult:
"""
Non-standard convenience method to convert a string to markdown.
Given that many converters produce HTML as intermediate output, this
allows for easy conversion of HTML to markdown.
"""
return self.convert(
file_stream=io.BytesIO(html_content.encode("utf-8")),
stream_info=StreamInfo(
mimetype="text/html",
extension=".html",
charset="utf-8",
url=url,
),
**kwargs,
) )
@@ -1,53 +1,32 @@
from typing import BinaryIO, Any, Union from typing import Union
import base64 from ._base import DocumentConverter, DocumentConverterResult
import mimetypes from ._media_converter import MediaConverter
from ._exiftool import exiftool_metadata from ._converter_input import ConverterInput
from .._base_converter import DocumentConverter, DocumentConverterResult
from .._stream_info import StreamInfo
ACCEPTED_MIME_TYPE_PREFIXES = [
"image/jpeg",
"image/png",
]
ACCEPTED_FILE_EXTENSIONS = [".jpg", ".jpeg", ".png"]
class ImageConverter(DocumentConverter): class ImageConverter(MediaConverter):
""" """
Converts images to markdown via extraction of metadata (if `exiftool` is installed), and description via a multimodal LLM (if an llm_client is configured). 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 accepts( def __init__(
self, self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
file_stream: BinaryIO, ):
stream_info: StreamInfo, super().__init__(priority=priority)
**kwargs: Any,
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if not an image
**kwargs: Any, # Options to pass to the converter extension = kwargs.get("file_extension", "")
) -> DocumentConverterResult: if extension.lower() not in [".jpg", ".jpeg", ".png"]:
return None
md_content = "" md_content = ""
# Add metadata # Add metadata if a local path is provided
metadata = exiftool_metadata( if input.input_type == "filepath":
file_stream, exiftool_path=kwargs.get("exiftool_path") metadata = self._get_metadata(input.filepath, kwargs.get("exiftool_path"))
)
if metadata: if metadata:
for f in [ for f in [
@@ -65,59 +44,42 @@ class ImageConverter(DocumentConverter):
if f in metadata: if f in metadata:
md_content += f"{f}: {metadata[f]}\n" md_content += f"{f}: {metadata[f]}\n"
# Try describing the image with GPT # Try describing the image with GPTV
llm_client = kwargs.get("llm_client") llm_client = kwargs.get("llm_client")
llm_model = kwargs.get("llm_model") llm_model = kwargs.get("llm_model")
if llm_client is not None and llm_model is not None: if llm_client is not None and llm_model is not None:
llm_description = self._get_llm_description( md_content += (
file_stream, "\n# Description:\n"
stream_info, + self._get_llm_description(
client=llm_client, input,
model=llm_model, extension,
llm_client,
llm_model,
prompt=kwargs.get("llm_prompt"), prompt=kwargs.get("llm_prompt"),
).strip()
+ "\n"
) )
if llm_description is not None:
md_content += "\n# Description:\n" + llm_description.strip() + "\n"
return DocumentConverterResult( return DocumentConverterResult(
markdown=md_content, title=None,
text_content=md_content,
) )
def _get_llm_description( def _get_llm_description(
self, self, input: ConverterInput, extension, client, model, prompt=None
file_stream: BinaryIO, ):
stream_info: StreamInfo,
*,
client,
model,
prompt=None,
) -> Union[None, str]:
if prompt is None or prompt.strip() == "": if prompt is None or prompt.strip() == "":
prompt = "Write a detailed caption for this image." prompt = "Write a detailed caption for this image."
# Get the content type data_uri = ""
content_type = stream_info.mimetype content_type, encoding = mimetypes.guess_type("_dummy" + extension)
if not content_type: if content_type is None:
content_type, _ = mimetypes.guess_type( content_type = "image/jpeg"
"_dummy" + (stream_info.extension or "") image_file = input.read_file(mode="rb")
) image_base64 = base64.b64encode(image_file.read()).decode("utf-8")
if not content_type: image_file.close()
content_type = "application/octet-stream" data_uri = f"data:{content_type};base64,{image_base64}"
# Convert to base64
cur_pos = file_stream.tell()
try:
base64_image = base64.b64encode(file_stream.read()).decode("utf-8")
except Exception as e:
return None
finally:
file_stream.seek(cur_pos)
# Prepare the data-uri
data_uri = f"data:{content_type};base64,{base64_image}"
# Prepare the OpenAI API request
messages = [ messages = [
{ {
"role": "user", "role": "user",
@@ -133,6 +95,5 @@ class ImageConverter(DocumentConverter):
} }
] ]
# Call the OpenAI API
response = client.chat.completions.create(model=model, messages=messages) response = client.chat.completions.create(model=model, messages=messages)
return response.choices[0].message.content return response.choices[0].message.content
@@ -1,60 +1,41 @@
from typing import BinaryIO, Any
import json import json
from typing import Any, Union
from ._base import (
DocumentConverter,
DocumentConverterResult,
)
from .._base_converter import DocumentConverter, DocumentConverterResult
from .._exceptions import FileConversionException from .._exceptions import FileConversionException
from .._stream_info import StreamInfo from ._converter_input import ConverterInput
CANDIDATE_MIME_TYPE_PREFIXES = [
"application/json",
]
ACCEPTED_FILE_EXTENSIONS = [".ipynb"]
class IpynbConverter(DocumentConverter): class IpynbConverter(DocumentConverter):
"""Converts Jupyter Notebook (.ipynb) files to Markdown.""" """Converts Jupyter Notebook (.ipynb) files to Markdown."""
def accepts( def __init__(
self, self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
file_stream: BinaryIO, ):
stream_info: StreamInfo, super().__init__(priority=priority)
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in CANDIDATE_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
# Read further to see if it's a notebook
cur_pos = file_stream.tell()
try:
encoding = stream_info.charset or "utf-8"
notebook_content = file_stream.read().decode(encoding)
return (
"nbformat" in notebook_content
and "nbformat_minor" in notebook_content
)
finally:
file_stream.seek(cur_pos)
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs: Any
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if not ipynb
**kwargs: Any, # Options to pass to the converter extension = kwargs.get("file_extension", "")
) -> DocumentConverterResult: if extension.lower() != ".ipynb":
# Parse and convert the notebook return None
encoding = stream_info.charset or "utf-8"
notebook_content = file_stream.read().decode(encoding=encoding)
return self._convert(json.loads(notebook_content))
def _convert(self, notebook_content: dict) -> DocumentConverterResult: # Parse and convert the notebook
result = None
file_obj = input.read_file(mode="rt", encoding="utf-8")
notebook_content = json.load(file_obj)
file_obj.close()
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.""" """Helper function that converts notebook JSON content to Markdown."""
try: try:
md_output = [] md_output = []
@@ -86,8 +67,8 @@ class IpynbConverter(DocumentConverter):
title = notebook_content.get("metadata", {}).get("title", title) title = notebook_content.get("metadata", {}).get("title", title)
return DocumentConverterResult( return DocumentConverterResult(
markdown=md_text,
title=title, title=title,
text_content=md_text,
) )
except Exception as e: except Exception as e:
@@ -1,50 +0,0 @@
from typing import BinaryIO, Union
import base64
import mimetypes
from .._stream_info import StreamInfo
def llm_caption(
file_stream: BinaryIO, stream_info: StreamInfo, *, client, model, prompt=None
) -> Union[None, str]:
if prompt is None or prompt.strip() == "":
prompt = "Write a detailed caption for this image."
# Get the content type
content_type = stream_info.mimetype
if not content_type:
content_type, _ = mimetypes.guess_type("_dummy" + (stream_info.extension or ""))
if not content_type:
content_type = "application/octet-stream"
# Convert to base64
cur_pos = file_stream.tell()
try:
base64_image = base64.b64encode(file_stream.read()).decode("utf-8")
except Exception as e:
return None
finally:
file_stream.seek(cur_pos)
# Prepare the data-uri
data_uri = f"data:{content_type};base64,{base64_image}"
# Prepare the OpenAI API request
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": prompt},
{
"type": "image_url",
"image_url": {
"url": data_uri,
},
},
],
}
]
# Call the OpenAI API
response = client.chat.completions.create(model=model, messages=messages)
return response.choices[0].message.content
@@ -1,7 +1,7 @@
import re import re
import markdownify import markdownify
from typing import Any, Optional from typing import Any
from urllib.parse import quote, unquote, urlparse, urlunparse from urllib.parse import quote, unquote, urlparse, urlunparse
@@ -17,18 +17,10 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
def __init__(self, **options: Any): def __init__(self, **options: Any):
options["heading_style"] = options.get("heading_style", markdownify.ATX) options["heading_style"] = options.get("heading_style", markdownify.ATX)
options["keep_data_uris"] = options.get("keep_data_uris", False)
# Explicitly cast options to the expected type if necessary # Explicitly cast options to the expected type if necessary
super().__init__(**options) super().__init__(**options)
def convert_hn( def convert_hn(self, n: int, el: Any, text: str, convert_as_inline: bool) -> str:
self,
n: int,
el: Any,
text: str,
convert_as_inline: Optional[bool] = False,
**kwargs,
) -> str:
"""Same as usual, but be sure to start with a new line""" """Same as usual, but be sure to start with a new line"""
if not convert_as_inline: if not convert_as_inline:
if not re.search(r"^\n", text): if not re.search(r"^\n", text):
@@ -36,13 +28,7 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
return 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( def convert_a(self, el: Any, text: str, convert_as_inline: bool):
self,
el: Any,
text: str,
convert_as_inline: Optional[bool] = False,
**kwargs,
):
"""Same as usual converter, but removes Javascript links and escapes URIs.""" """Same as usual converter, but removes Javascript links and escapes URIs."""
prefix, suffix, text = markdownify.chomp(text) # type: ignore prefix, suffix, text = markdownify.chomp(text) # type: ignore
if not text: if not text:
@@ -82,21 +68,13 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
else text else text
) )
def convert_img( def convert_img(self, el: Any, text: str, convert_as_inline: bool) -> str:
self,
el: Any,
text: str,
convert_as_inline: Optional[bool] = False,
**kwargs,
) -> str:
"""Same as usual converter, but removes data URIs""" """Same as usual converter, but removes data URIs"""
alt = el.attrs.get("alt", None) or "" alt = el.attrs.get("alt", None) or ""
src = el.attrs.get("src", None) or el.attrs.get("data-src", None) or "" src = el.attrs.get("src", None) or ""
title = el.attrs.get("title", None) or "" title = el.attrs.get("title", None) or ""
title_part = ' "%s"' % title.replace('"', r"\"") if title else "" title_part = ' "%s"' % title.replace('"', r"\"") if title else ""
# Remove all line breaks from alt
alt = alt.replace("\n", " ")
if ( if (
convert_as_inline convert_as_inline
and el.parent.name not in self.options["keep_inline_images_in"] and el.parent.name not in self.options["keep_inline_images_in"]
@@ -104,23 +82,10 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
return alt return alt
# Remove dataURIs # Remove dataURIs
if src.startswith("data:") and not self.options["keep_data_uris"]: if src.startswith("data:"):
src = src.split(",")[0] + "..." src = src.split(",")[0] + "..."
return "![%s](%s%s)" % (alt, src, title_part) return "![%s](%s%s)" % (alt, src, title_part)
def convert_input(
self,
el: Any,
text: str,
convert_as_inline: Optional[bool] = False,
**kwargs,
) -> str:
"""Convert checkboxes to Markdown [x]/[ ] syntax."""
if el.get("type") == "checkbox":
return "[x] " if el.has_attr("checked") else "[ ] "
return ""
def convert_soup(self, soup: Any) -> str: def convert_soup(self, soup: Any) -> str:
return super().convert_soup(soup) # type: ignore return super().convert_soup(soup) # type: ignore
@@ -0,0 +1,41 @@
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 __init__(
self, priority: float = DocumentConverter.PRIORITY_GENERIC_FILE_FORMAT
):
super().__init__(priority=priority)
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:
if True:
result = subprocess.run(
[exiftool_path, "-json", local_path], capture_output=True, text=True
).stdout
return json.loads(result)[0]
# except Exception:
# return None
@@ -0,0 +1,98 @@
import tempfile
import os
from typing import Union
from ._base import DocumentConverter, DocumentConverterResult
from ._wav_converter import WavConverter
from warnings import resetwarnings, catch_warnings
from ._converter_input import ConverterInput
# 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 __init__(
self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
):
super().__init__(priority=priority)
def convert(
self, input: ConverterInput, **kwargs
) -> Union[None, DocumentConverterResult]:
# Bail if not a MP3
extension = kwargs.get("file_extension", "")
if extension.lower() != ".mp3":
return None
# Bail if a local path was not provided
if input.input_type != "filepath":
return None
local_path = input.filepath
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(),
)
@@ -1,24 +1,7 @@
import sys import olefile
from typing import Any, Union, BinaryIO from typing import Any, Union
from .._stream_info import StreamInfo from ._base import DocumentConverter, DocumentConverterResult
from .._base_converter import DocumentConverter, DocumentConverterResult from ._converter_input import ConverterInput
from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
# Try loading optional (but in this case, required) dependencies
# Save reporting of any exceptions for later
_dependency_exc_info = None
olefile = None
try:
import olefile # type: ignore[no-redef]
except ImportError:
# Preserve the error and stack trace for later
_dependency_exc_info = sys.exc_info()
ACCEPTED_MIME_TYPE_PREFIXES = [
"application/vnd.ms-outlook",
]
ACCEPTED_FILE_EXTENSIONS = [".msg"]
class OutlookMsgConverter(DocumentConverter): class OutlookMsgConverter(DocumentConverter):
@@ -29,71 +12,22 @@ class OutlookMsgConverter(DocumentConverter):
- Email body content - Email body content
""" """
def accepts( def __init__(
self, self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
file_stream: BinaryIO, ):
stream_info: StreamInfo, super().__init__(priority=priority)
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
# Check the extension and mimetype
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
# Brute force, check if we have an OLE file
cur_pos = file_stream.tell()
try:
if olefile and not olefile.isOleFile(file_stream):
return False
finally:
file_stream.seek(cur_pos)
# Brue force, check if it's an Outlook file
try:
if olefile is not None:
msg = olefile.OleFileIO(file_stream)
toc = "\n".join([str(stream) for stream in msg.listdir()])
return (
"__properties_version1.0" in toc
and "__recip_version1.0_#00000000" in toc
)
except Exception as e:
pass
finally:
file_stream.seek(cur_pos)
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs: Any
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if not a MSG file
**kwargs: Any, # Options to pass to the converter extension = kwargs.get("file_extension", "")
) -> DocumentConverterResult: if extension.lower() != ".msg":
# Check: the dependencies return None
if _dependency_exc_info is not None:
raise MissingDependencyException(
MISSING_DEPENDENCY_MESSAGE.format(
converter=type(self).__name__,
extension=".msg",
feature="outlook",
)
) from _dependency_exc_info[
1
].with_traceback( # type: ignore[union-attr]
_dependency_exc_info[2]
)
assert ( try:
olefile is not None file_obj = input.read_file(mode="rb")
) # If we made it this far, olefile should be available msg = olefile.OleFileIO(file_obj)
msg = olefile.OleFileIO(file_stream)
# Extract email metadata # Extract email metadata
md_content = "# Email Message\n\n" md_content = "# Email Message\n\n"
@@ -118,19 +52,21 @@ class OutlookMsgConverter(DocumentConverter):
md_content += body md_content += body
msg.close() msg.close()
file_obj.close()
return DocumentConverterResult( return DocumentConverterResult(
markdown=md_content.strip(), title=headers.get("Subject"), text_content=md_content.strip()
title=headers.get("Subject"),
) )
def _get_stream_data(self, msg: Any, stream_path: str) -> Union[str, None]: except Exception as e:
"""Helper to safely extract and decode stream data from the MSG file.""" raise FileConversionException(
assert olefile is not None f"Could not convert MSG file '{input.filepath}': {str(e)}"
assert isinstance( )
msg, olefile.OleFileIO
) # Ensure msg is of the correct type (type hinting is not possible with the optional olefile package)
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: try:
if msg.exists(stream_path): if msg.exists(stream_path):
data = msg.openstream(stream_path).read() data = msg.openstream(stream_path).read()
@@ -1,589 +1,35 @@
import sys import pdfminer
import io import pdfminer.high_level
import re from typing import Union
from typing import BinaryIO, Any from io import StringIO
from ._base import DocumentConverter, DocumentConverterResult
from .._base_converter import DocumentConverter, DocumentConverterResult from ._converter_input import ConverterInput
from .._stream_info import StreamInfo
from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
# Pattern for MasterFormat-style partial numbering (e.g., ".1", ".2", ".10")
PARTIAL_NUMBERING_PATTERN = re.compile(r"^\.\d+$")
def _merge_partial_numbering_lines(text: str) -> str:
"""
Post-process extracted text to merge MasterFormat-style partial numbering
with the following text line.
MasterFormat documents use partial numbering like:
.1 The intent of this Request for Proposal...
.2 Available information relative to...
Some PDF extractors split these into separate lines:
.1
The intent of this Request for Proposal...
This function merges them back together.
"""
lines = text.split("\n")
result_lines: list[str] = []
i = 0
while i < len(lines):
line = lines[i]
stripped = line.strip()
# Check if this line is ONLY a partial numbering
if PARTIAL_NUMBERING_PATTERN.match(stripped):
# Look for the next non-empty line to merge with
j = i + 1
while j < len(lines) and not lines[j].strip():
j += 1
if j < len(lines):
# Merge the partial numbering with the next line
next_line = lines[j].strip()
result_lines.append(f"{stripped} {next_line}")
i = j + 1 # Skip past the merged line
else:
# No next line to merge with, keep as is
result_lines.append(line)
i += 1
else:
result_lines.append(line)
i += 1
return "\n".join(result_lines)
# Load dependencies
_dependency_exc_info = None
try:
import pdfminer
import pdfminer.high_level
import pdfplumber
except ImportError:
_dependency_exc_info = sys.exc_info()
ACCEPTED_MIME_TYPE_PREFIXES = [
"application/pdf",
"application/x-pdf",
]
ACCEPTED_FILE_EXTENSIONS = [".pdf"]
def _to_markdown_table(table: list[list[str]], include_separator: bool = True) -> str:
"""Convert a 2D list (rows/columns) into a nicely aligned Markdown table.
Args:
table: 2D list of cell values
include_separator: If True, include header separator row (standard markdown).
If False, output simple pipe-separated rows.
"""
if not table:
return ""
# Normalize None → ""
table = [[cell if cell is not None else "" for cell in row] for row in table]
# Filter out empty rows
table = [row for row in table if any(cell.strip() for cell in row)]
if not table:
return ""
# Column widths
col_widths = [max(len(str(cell)) for cell in col) for col in zip(*table)]
def fmt_row(row: list[str]) -> str:
return (
"|"
+ "|".join(str(cell).ljust(width) for cell, width in zip(row, col_widths))
+ "|"
)
if include_separator:
header, *rows = table
md = [fmt_row(header)]
md.append("|" + "|".join("-" * w for w in col_widths) + "|")
for row in rows:
md.append(fmt_row(row))
else:
md = [fmt_row(row) for row in table]
return "\n".join(md)
def _extract_form_content_from_words(page: Any) -> str | None:
"""
Extract form-style content from a PDF page by analyzing word positions.
This handles borderless forms/tables where words are aligned in columns.
Returns markdown with proper table formatting:
- Tables have pipe-separated columns with header separator rows
- Non-table content is rendered as plain text
Returns None if the page doesn't appear to be a form-style document,
indicating that pdfminer should be used instead for better text spacing.
"""
words = page.extract_words(keep_blank_chars=True, x_tolerance=3, y_tolerance=3)
if not words:
return None
# Group words by their Y position (rows)
y_tolerance = 5
rows_by_y: dict[float, list[dict]] = {}
for word in words:
y_key = round(word["top"] / y_tolerance) * y_tolerance
if y_key not in rows_by_y:
rows_by_y[y_key] = []
rows_by_y[y_key].append(word)
# Sort rows by Y position
sorted_y_keys = sorted(rows_by_y.keys())
page_width = page.width if hasattr(page, "width") else 612
# First pass: analyze each row
row_info: list[dict] = []
for y_key in sorted_y_keys:
row_words = sorted(rows_by_y[y_key], key=lambda w: w["x0"])
if not row_words:
continue
first_x0 = row_words[0]["x0"]
last_x1 = row_words[-1]["x1"]
line_width = last_x1 - first_x0
combined_text = " ".join(w["text"] for w in row_words)
# Count distinct x-position groups (columns)
x_positions = [w["x0"] for w in row_words]
x_groups: list[float] = []
for x in sorted(x_positions):
if not x_groups or x - x_groups[-1] > 50:
x_groups.append(x)
# Determine row type
is_paragraph = line_width > page_width * 0.55 and len(combined_text) > 60
# Check for MasterFormat-style partial numbering (e.g., ".1", ".2")
# These should be treated as list items, not table rows
has_partial_numbering = False
if row_words:
first_word = row_words[0]["text"].strip()
if PARTIAL_NUMBERING_PATTERN.match(first_word):
has_partial_numbering = True
row_info.append(
{
"y_key": y_key,
"words": row_words,
"text": combined_text,
"x_groups": x_groups,
"is_paragraph": is_paragraph,
"num_columns": len(x_groups),
"has_partial_numbering": has_partial_numbering,
}
)
# Collect ALL x-positions from rows with 3+ columns (table-like rows)
# This gives us the global column structure
all_table_x_positions: list[float] = []
for info in row_info:
if info["num_columns"] >= 3 and not info["is_paragraph"]:
all_table_x_positions.extend(info["x_groups"])
if not all_table_x_positions:
return None
# Compute adaptive column clustering tolerance based on gap analysis
all_table_x_positions.sort()
# Calculate gaps between consecutive x-positions
gaps = []
for i in range(len(all_table_x_positions) - 1):
gap = all_table_x_positions[i + 1] - all_table_x_positions[i]
if gap > 5: # Only significant gaps
gaps.append(gap)
# Determine optimal tolerance using statistical analysis
if gaps and len(gaps) >= 3:
# Use 70th percentile of gaps as threshold (balances precision/recall)
sorted_gaps = sorted(gaps)
percentile_70_idx = int(len(sorted_gaps) * 0.70)
adaptive_tolerance = sorted_gaps[percentile_70_idx]
# Clamp tolerance to reasonable range [25, 50]
adaptive_tolerance = max(25, min(50, adaptive_tolerance))
else:
# Fallback to conservative value
adaptive_tolerance = 35
# Compute global column boundaries using adaptive tolerance
global_columns: list[float] = []
for x in all_table_x_positions:
if not global_columns or x - global_columns[-1] > adaptive_tolerance:
global_columns.append(x)
# Adaptive max column check based on page characteristics
# Calculate average column width
if len(global_columns) > 1:
content_width = global_columns[-1] - global_columns[0]
avg_col_width = content_width / len(global_columns)
# Forms with very narrow columns (< 30px) are likely dense text
if avg_col_width < 30:
return None
# Compute adaptive max based on columns per inch
# Typical forms have 3-8 columns per inch
columns_per_inch = len(global_columns) / (content_width / 72)
# If density is too high (> 10 cols/inch), likely not a form
if columns_per_inch > 10:
return None
# Adaptive max: allow more columns for wider pages
# Standard letter is 612pt wide, so scale accordingly
adaptive_max_columns = int(20 * (page_width / 612))
adaptive_max_columns = max(15, adaptive_max_columns) # At least 15
if len(global_columns) > adaptive_max_columns:
return None
else:
# Single column, not a form
return None
# Now classify each row as table row or not
# A row is a table row if it has words that align with 2+ of the global columns
for info in row_info:
if info["is_paragraph"]:
info["is_table_row"] = False
continue
# Rows with partial numbering (e.g., ".1", ".2") are list items, not table rows
if info["has_partial_numbering"]:
info["is_table_row"] = False
continue
# Count how many global columns this row's words align with
aligned_columns: set[int] = set()
for word in info["words"]:
word_x = word["x0"]
for col_idx, col_x in enumerate(global_columns):
if abs(word_x - col_x) < 40:
aligned_columns.add(col_idx)
break
# If row uses 2+ of the established columns, it's a table row
info["is_table_row"] = len(aligned_columns) >= 2
# Find table regions (consecutive table rows)
table_regions: list[tuple[int, int]] = [] # (start_idx, end_idx)
i = 0
while i < len(row_info):
if row_info[i]["is_table_row"]:
start_idx = i
while i < len(row_info) and row_info[i]["is_table_row"]:
i += 1
end_idx = i
table_regions.append((start_idx, end_idx))
else:
i += 1
# Check if enough rows are table rows (at least 20%)
total_table_rows = sum(end - start for start, end in table_regions)
if len(row_info) > 0 and total_table_rows / len(row_info) < 0.2:
return None
# Build output - collect table data first, then format with proper column widths
result_lines: list[str] = []
num_cols = len(global_columns)
# Helper function to extract cells from a row
def extract_cells(info: dict) -> list[str]:
cells: list[str] = ["" for _ in range(num_cols)]
for word in info["words"]:
word_x = word["x0"]
# Find the correct column using boundary ranges
assigned_col = num_cols - 1 # Default to last column
for col_idx in range(num_cols - 1):
col_end = global_columns[col_idx + 1]
if word_x < col_end - 20:
assigned_col = col_idx
break
if cells[assigned_col]:
cells[assigned_col] += " " + word["text"]
else:
cells[assigned_col] = word["text"]
return cells
# Process rows, collecting table data for proper formatting
idx = 0
while idx < len(row_info):
info = row_info[idx]
# Check if this row starts a table region
table_region = None
for start, end in table_regions:
if idx == start:
table_region = (start, end)
break
if table_region:
start, end = table_region
# Collect all rows in this table
table_data: list[list[str]] = []
for table_idx in range(start, end):
cells = extract_cells(row_info[table_idx])
table_data.append(cells)
# Calculate column widths for this table
if table_data:
col_widths = [
max(len(row[col]) for row in table_data) for col in range(num_cols)
]
# Ensure minimum width of 3 for separator dashes
col_widths = [max(w, 3) for w in col_widths]
# Format header row
header = table_data[0]
header_str = (
"| "
+ " | ".join(
cell.ljust(col_widths[i]) for i, cell in enumerate(header)
)
+ " |"
)
result_lines.append(header_str)
# Format separator row
separator = (
"| "
+ " | ".join("-" * col_widths[i] for i in range(num_cols))
+ " |"
)
result_lines.append(separator)
# Format data rows
for row in table_data[1:]:
row_str = (
"| "
+ " | ".join(
cell.ljust(col_widths[i]) for i, cell in enumerate(row)
)
+ " |"
)
result_lines.append(row_str)
idx = end # Skip to end of table region
else:
# Check if we're inside a table region (not at start)
in_table = False
for start, end in table_regions:
if start < idx < end:
in_table = True
break
if not in_table:
# Non-table content
result_lines.append(info["text"])
idx += 1
return "\n".join(result_lines)
def _extract_tables_from_words(page: Any) -> list[list[list[str]]]:
"""
Extract tables from a PDF page by analyzing word positions.
This handles borderless tables where words are aligned in columns.
This function is designed for structured tabular data (like invoices),
not for multi-column text layouts in scientific documents.
"""
words = page.extract_words(keep_blank_chars=True, x_tolerance=3, y_tolerance=3)
if not words:
return []
# Group words by their Y position (rows)
y_tolerance = 5
rows_by_y: dict[float, list[dict]] = {}
for word in words:
y_key = round(word["top"] / y_tolerance) * y_tolerance
if y_key not in rows_by_y:
rows_by_y[y_key] = []
rows_by_y[y_key].append(word)
# Sort rows by Y position
sorted_y_keys = sorted(rows_by_y.keys())
# Find potential column boundaries by analyzing x positions across all rows
all_x_positions = []
for words_in_row in rows_by_y.values():
for word in words_in_row:
all_x_positions.append(word["x0"])
if not all_x_positions:
return []
# Cluster x positions to find column starts
all_x_positions.sort()
x_tolerance_col = 20
column_starts: list[float] = []
for x in all_x_positions:
if not column_starts or x - column_starts[-1] > x_tolerance_col:
column_starts.append(x)
# Need at least 3 columns but not too many (likely text layout, not table)
if len(column_starts) < 3 or len(column_starts) > 10:
return []
# Find rows that span multiple columns (potential table rows)
table_rows = []
for y_key in sorted_y_keys:
words_in_row = sorted(rows_by_y[y_key], key=lambda w: w["x0"])
# Assign words to columns
row_data = [""] * len(column_starts)
for word in words_in_row:
# Find the closest column
best_col = 0
min_dist = float("inf")
for i, col_x in enumerate(column_starts):
dist = abs(word["x0"] - col_x)
if dist < min_dist:
min_dist = dist
best_col = i
if row_data[best_col]:
row_data[best_col] += " " + word["text"]
else:
row_data[best_col] = word["text"]
# Only include rows that have content in multiple columns
non_empty = sum(1 for cell in row_data if cell.strip())
if non_empty >= 2:
table_rows.append(row_data)
# Validate table quality - tables should have:
# 1. Enough rows (at least 3 including header)
# 2. Short cell content (tables have concise data, not paragraphs)
# 3. Consistent structure across rows
if len(table_rows) < 3:
return []
# Check if cells contain short, structured data (not long text)
long_cell_count = 0
total_cell_count = 0
for row in table_rows:
for cell in row:
if cell.strip():
total_cell_count += 1
# If cell has more than 30 chars, it's likely prose text
if len(cell.strip()) > 30:
long_cell_count += 1
# If more than 30% of cells are long, this is probably not a table
if total_cell_count > 0 and long_cell_count / total_cell_count > 0.3:
return []
return [table_rows]
class PdfConverter(DocumentConverter): class PdfConverter(DocumentConverter):
""" """
Converts PDFs to Markdown. Converts PDFs to Markdown. Most style information is ignored, so the results are essentially plain-text.
Supports extracting tables into aligned Markdown format (via pdfplumber).
Falls back to pdfminer if pdfplumber is missing or fails.
""" """
def accepts( def __init__(
self, self, priority: float = DocumentConverter.PRIORITY_SPECIFIC_FILE_FORMAT
file_stream: BinaryIO, ):
stream_info: StreamInfo, super().__init__(priority=priority)
**kwargs: Any,
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Bail if not a PDF
**kwargs: Any, extension = kwargs.get("file_extension", "")
) -> DocumentConverterResult: if extension.lower() != ".pdf":
if _dependency_exc_info is not None: return None
raise MissingDependencyException(
MISSING_DEPENDENCY_MESSAGE.format( output = StringIO()
converter=type(self).__name__, file_obj = input.read_file(mode="rb")
extension=".pdf", pdfminer.high_level.extract_text_to_fp(file_obj, output)
feature="pdf", file_obj.close()
return DocumentConverterResult(
title=None,
text_content=output.getvalue(),
) )
) from _dependency_exc_info[1].with_traceback(
_dependency_exc_info[2]
) # type: ignore[union-attr]
assert isinstance(file_stream, io.IOBase)
# Read file stream into BytesIO for compatibility with pdfplumber
pdf_bytes = io.BytesIO(file_stream.read())
try:
# Single pass: check every page for form-style content.
# Pages with tables/forms get rich extraction; plain-text
# pages are collected separately. page.close() is called
# after each page to free pdfplumber's cached objects and
# keep memory usage constant regardless of page count.
markdown_chunks: list[str] = []
form_page_count = 0
plain_page_indices: list[int] = []
with pdfplumber.open(pdf_bytes) as pdf:
for page_idx, page in enumerate(pdf.pages):
page_content = _extract_form_content_from_words(page)
if page_content is not None:
form_page_count += 1
if page_content.strip():
markdown_chunks.append(page_content)
else:
plain_page_indices.append(page_idx)
text = page.extract_text()
if text and text.strip():
markdown_chunks.append(text.strip())
page.close() # Free cached page data immediately
# If no pages had form-style content, use pdfminer for
# the whole document (better text spacing for prose).
if form_page_count == 0:
pdf_bytes.seek(0)
markdown = pdfminer.high_level.extract_text(pdf_bytes)
else:
markdown = "\n\n".join(markdown_chunks).strip()
except Exception:
# Fallback if pdfplumber fails
pdf_bytes.seek(0)
markdown = pdfminer.high_level.extract_text(pdf_bytes)
# Fallback if still empty
if not markdown:
pdf_bytes.seek(0)
markdown = pdfminer.high_level.extract_text(pdf_bytes)
# Post-process to merge MasterFormat-style partial numbering with following text
markdown = _merge_partial_numbering_lines(markdown)
return DocumentConverterResult(markdown=markdown)
@@ -1,71 +1,43 @@
import sys import mimetypes
from typing import BinaryIO, Any from charset_normalizer import from_path, from_bytes
from charset_normalizer import from_bytes from typing import Any, Union
from .._base_converter import DocumentConverter, DocumentConverterResult
from .._stream_info import StreamInfo
# Try loading optional (but in this case, required) dependencies from ._base import DocumentConverter, DocumentConverterResult
# Save reporting of any exceptions for later from ._converter_input import ConverterInput
_dependency_exc_info = None
try:
import mammoth # noqa: F401
except ImportError:
# Preserve the error and stack trace for later
_dependency_exc_info = sys.exc_info()
ACCEPTED_MIME_TYPE_PREFIXES = [
"text/",
"application/json",
"application/markdown",
]
ACCEPTED_FILE_EXTENSIONS = [
".txt",
".text",
".md",
".markdown",
".json",
".jsonl",
]
class PlainTextConverter(DocumentConverter): class PlainTextConverter(DocumentConverter):
"""Anything with content type text/plain""" """Anything with content type text/plain"""
def accepts( def __init__(
self, self, priority: float = DocumentConverter.PRIORITY_GENERIC_FILE_FORMAT
file_stream: BinaryIO, ):
stream_info: StreamInfo, super().__init__(priority=priority)
**kwargs: Any, # Options to pass to the converter
) -> bool:
mimetype = (stream_info.mimetype or "").lower()
extension = (stream_info.extension or "").lower()
# If we have a charset, we can safely assume it's text
# With Magika in the earlier stages, this handles most cases
if stream_info.charset is not None:
return True
# Otherwise, check the mimetype and extension
if extension in ACCEPTED_FILE_EXTENSIONS:
return True
for prefix in ACCEPTED_MIME_TYPE_PREFIXES:
if mimetype.startswith(prefix):
return True
return False
def convert( def convert(
self, self, input: ConverterInput, **kwargs: Any
file_stream: BinaryIO, ) -> Union[None, DocumentConverterResult]:
stream_info: StreamInfo, # Read file object from input
**kwargs: Any, # Options to pass to the converter file_obj = input.read_file(mode="rb")
) -> DocumentConverterResult:
if stream_info.charset:
text_content = file_stream.read().decode(stream_info.charset)
else:
text_content = str(from_bytes(file_stream.read()).best())
return DocumentConverterResult(markdown=text_content) # 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_bytes(file_obj.read()).best())
file_obj.close()
return DocumentConverterResult(
title=None,
text_content=text_content,
)

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